mirror of
https://github.com/MervinPraison/PraisonAI.git
synced 2026-11-10 03:31:28 -10:00
Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Mervin Praison
|
2c4dd0e2d4 | ||
|
Mervin Praison
|
fd23d62841 | ||
|
Mervin Praison
|
5f3bcb78ac | ||
|
Mervin Praison
|
3c40c2278e | ||
|
Mervin Praison
|
1921b03aab | ||
|
Mervin Praison
|
f33bf57662 | ||
|
github-actions[bot]
|
df21c419ea | ||
|
Mervin Praison
|
fe997d525c | ||
|
Mervin Praison
|
ca26988774 | ||
|
Mervin Praison
|
3600594316 | ||
|
Mervin Praison
|
097cd42890 | ||
|
Mervin Praison
|
595add2991 | ||
|
Mervin Praison
|
03a3aa420b | ||
|
Mervin Praison
|
9533abd8a4 | ||
|
Mervin Praison
|
39c9e50875 |
No files matched your search
@@ -0,0 +1,57 @@
|
||||
name: Update API Reference
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [ "main" ]
|
||||
paths:
|
||||
- 'src/praisonai-agents/praisonaiagents/**/*.py'
|
||||
- 'src/praisonai/praisonai/**/*.py'
|
||||
- 'src/praisonai-ts/src/**/*.ts'
|
||||
- '.github/workflows/update-api-md.yml'
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
jobs:
|
||||
update-api-md:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: main
|
||||
persist-credentials: true
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Generate api.md
|
||||
run: |
|
||||
cd $GITHUB_WORKSPACE
|
||||
python3 src/praisonai/scripts/generate_api_md.py
|
||||
|
||||
- name: Check for changes
|
||||
id: check_changes
|
||||
run: |
|
||||
if git diff --quiet api.md; then
|
||||
echo "changes=false" >> $GITHUB_OUTPUT
|
||||
echo "No changes to api.md"
|
||||
else
|
||||
echo "changes=true" >> $GITHUB_OUTPUT
|
||||
echo "api.md has been updated"
|
||||
git diff api.md | head -50
|
||||
fi
|
||||
|
||||
- name: Commit and push changes
|
||||
if: steps.check_changes.outputs.changes == 'true'
|
||||
uses: stefanzweifel/git-auto-commit-action@v5
|
||||
with:
|
||||
commit_message: "docs: auto-update api.md [skip ci]"
|
||||
file_pattern: 'api.md'
|
||||
commit_user_name: "github-actions[bot]"
|
||||
commit_user_email: "41898282+github-actions[bot]@users.noreply.github.com"
|
||||
commit_author: "github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>"
|
||||
+2
-1
@@ -83,4 +83,5 @@ issue_details.json
|
||||
# MCP Registry tokens
|
||||
.mcpregistry_*
|
||||
|
||||
*.log
|
||||
*.log
|
||||
.internal
|
||||
@@ -0,0 +1,867 @@
|
||||
# PraisonAI API Reference
|
||||
|
||||
This file is auto-generated. Do not edit manually.
|
||||
Regenerate with: `praisonai docs api-md --write`
|
||||
|
||||
# Shared Types
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import ContextPolicy, GuardrailResult, HandoffConfig, HandoffCycleError, HandoffDepthError, HandoffError, HandoffInputData, HandoffResult, HandoffTimeoutError, ReflectionOutput, StepResult, TaskOutput, ToolResult, ToolValidationError, WorkflowContext
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class GuardrailResult">GuardrailResult.<a href="./src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py">from_tuple</a>(result: Tuple[bool, Any]) -> 'GuardrailResult'</code>
|
||||
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_dict</a>(data: Dict[str, Any]) -> 'HandoffConfig'</code>
|
||||
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">json</a>() -> Optional[str]</code>
|
||||
* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">to_dict</a>() -> dict</code>
|
||||
* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
|
||||
# Agents
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Agent, Agents, AutoAgents, AutoRagAgent, ContextAgent, DeepResearchAgent, ImageAgent, PraisonAIAgents, PromptExpanderAgent, QueryRewriterAgent, create_context_agent
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">achat</a>(prompt: str, temperature = 1.0, tools = None, output_json = None, output_pydantic = None, reasoning_steps = False, task_name = None, task_description = None, task_id = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">aexecute</a>(task, context = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">agent_id</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">analyze_prompt</a>(prompt: str) -> set</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">arun</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">astart</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat</a>(prompt, temperature = 1.0, tools = None, output_json = None, output_pydantic = None, reasoning_steps = False, stream = None, task_name = None, task_description = None, task_id = None, config = None, force_retrieval = False, skip_retrieval = False)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_with_context</a>(message: str, context: 'ContextPack', **kwargs) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">clean_json_output</a>(output: str) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">clear_history</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">console</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">context_manager</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">context_manager</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">display_generating</a>(content: str, start_time: float)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute</a>(task, context = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute_tool</a>(function_name, arguments)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute_tool_async</a>(function_name: str, arguments: Dict[str, Any]) -> Any</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">from_template</a>(uri: str, config: Optional[Dict[str, Any]] = None, offline: bool = False, **kwargs) -> 'Agent'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">generate_task</a>() -> 'Task'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_available_tools</a>() -> List[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_memory_context</a>(query: Optional[str] = None) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_recommended_stage</a>(prompt: str) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_rules_context</a>(file_path: Optional[str] = None, include_manual: Optional[List[str]] = None) -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_skills_prompt</a>() -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to_async</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">launch</a>(path: str = '/', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_model</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">policy</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">policy</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">query</a>(question: str, **kwargs) -> 'RAGResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag_query</a>(question: str, **kwargs) -> 'RAGResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieval_config</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieve</a>(query: str, **kwargs) -> 'ContextPack'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rules_manager</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">session_id</a>() -> Optional[str]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">start</a>(prompt: str, **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', **kwargs)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">switch_model</a>(new_model: str) -> None</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>(value)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">context_manager</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">current_plan</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">default_completion_checker</a>(task, agent_output)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">delete_state</a>(key: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">display_token_usage</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">execute_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_agent_details</a>(agent_name)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_state</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_status</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_todo_markdown</a>() -> str</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">has_state</a>(key: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">increment_state</a>(key: str, amount: float = 1, default: float = 0) -> float</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">restore_session_state</a>(session_id: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
|
||||
* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
|
||||
* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">astart</a>()</code>
|
||||
* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">start</a>()</code>
|
||||
* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">achat</a>(message: str, **kwargs) -> str</code>
|
||||
* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">chat</a>(message: str, **kwargs) -> str</code>
|
||||
* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">name</a>() -> str</code>
|
||||
* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">rag</a>() -> Optional['RAG']</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_codebase_with_gitingest</a>(project_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_integration_points</a>(project_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_test_patterns</a>(project_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">build_implementation_blueprint</a>(feature_request: str, context_analysis: Dict[str, Any] = None) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">compile_context_documentation</a>(project_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_quality_gates</a>(requirements: List[str]) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_validation_framework</a>(project_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">execute_prp</a>(prp_file_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">extract_implementation_patterns</a>(project_path: str, ast_analysis: Dict[str, Any] = None) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">generate_comprehensive_prp</a>(feature_request: str, context_analysis: Dict[str, Any] = None) -> str</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">generate_feature_prp</a>(feature_request: str) -> str</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">get_agent_interaction_summary</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">log_debug</a>(message: str, **kwargs)</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">perform_ast_analysis</a>(project_path: str) -> Dict[str, Any]</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">save_comprehensive_session_report</a>()</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">save_markdown_output</a>(content: str, filename: str, section_title: str = 'Output')</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">setup_logging</a>()</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">setup_output_directories</a>()</code>
|
||||
* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">start</a>(input_text: str) -> str</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">aresearch</a>(query: str, instructions: Optional[str] = None, model: Optional[str] = None, summary_mode: Optional[Literal['auto', 'detailed', 'concise']] = None, web_search: Optional[bool] = None, code_interpreter: Optional[bool] = None, mcp_servers: Optional[List[Dict[str, Any]]] = None, file_ids: Optional[List[str]] = None, file_search: Optional[bool] = None, file_search_stores: Optional[List[str]] = None) -> DeepResearchResponse</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">async_openai_client</a>()</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">clarify</a>(query: str, model: Optional[str] = None) -> str</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">follow_up</a>(query: str, previous_interaction_id: str, model: Optional[str] = None) -> DeepResearchResponse</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">gemini_client</a>()</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">openai_client</a>()</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">research</a>(query: str, instructions: Optional[str] = None, model: Optional[str] = None, summary_mode: Optional[Literal['auto', 'detailed', 'concise']] = None, web_search: Optional[bool] = None, code_interpreter: Optional[bool] = None, mcp_servers: Optional[List[Dict[str, Any]]] = None, file_ids: Optional[List[str]] = None, file_search: Optional[bool] = None, file_search_stores: Optional[List[str]] = None, stream: bool = True) -> DeepResearchResponse</code>
|
||||
* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">rewrite_query</a>(query: str, model: Optional[str] = None) -> str</code>
|
||||
* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">achat</a>(prompt: str, temperature: float = 0.2, tools: Optional[List[Any]] = None, output_json: Optional[str] = None, output_pydantic: Optional[Any] = None, reasoning_steps: bool = False, **kwargs) -> Union[str, Dict[str, Any]]</code>
|
||||
* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">agenerate_image</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
|
||||
* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">chat</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
|
||||
* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">generate_image</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
|
||||
* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">litellm</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">context_manager</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">current_plan</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">default_completion_checker</a>(task, agent_output)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">delete_state</a>(key: str) -> bool</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">display_token_usage</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">execute_task</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_agent_details</a>(agent_name)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_state</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_status</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_todo_markdown</a>() -> str</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">has_state</a>(key: str) -> bool</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">increment_state</a>(key: str, amount: float = 1, default: float = 0) -> float</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">restore_session_state</a>(session_id: str) -> bool</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
|
||||
* <code title="class PraisonAIAgents">PraisonAIAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
|
||||
* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">agent</a>()</code>
|
||||
* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand</a>(prompt: str, strategy: ExpandStrategy = ..., context: Optional[str] = None) -> ExpandResult</code>
|
||||
* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_basic</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
|
||||
* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_creative</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
|
||||
* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_detailed</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
|
||||
* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_structured</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">add_abbreviation</a>(abbrev: str, expansion: str) -> None</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">add_abbreviations</a>(abbreviations: Dict[str, str]) -> None</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">agent</a>()</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite</a>(query: str, strategy: RewriteStrategy = ..., chat_history: Optional[List[Dict[str, str]]] = None, context: Optional[str] = None, num_queries: int = None) -> RewriteResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_basic</a>(query: str) -> RewriteResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_contextual</a>(query: str, chat_history: List[Dict[str, str]]) -> RewriteResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_hyde</a>(query: str) -> RewriteResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_multi_query</a>(query: str, num_queries: int = None) -> RewriteResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_step_back</a>(query: str) -> RewriteResult</code>
|
||||
* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_sub_queries</a>(query: str) -> RewriteResult</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_context_agent</a>(llm: Optional[Union[str, Any]] = None, **kwargs) -> ContextAgent</code>
|
||||
|
||||
# Tools
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import BaseTool, FunctionTool, ToolRegistry, Tools, get_registry, get_tool, register_tool, tool, validate_tool
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">__call__</a>(**kwargs) -> Any</code>
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">get_schema</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">run</a>(**kwargs) -> Any</code>
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">safe_run</a>(**kwargs) -> ToolResult</code>
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate</a>() -> bool</code>
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_class</a>() -> bool</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">__call__</a>(*args, **kwargs) -> Any</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">injected_params</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">run</a>(**kwargs) -> Any</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">clear</a>() -> None</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_plugins</a>() -> int</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_all</a>() -> Dict[str, Union[BaseTool, Callable]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_base_tools</a>() -> List[BaseTool]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_tools</a>() -> List[str]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, overwrite: bool = False) -> None</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">unregister</a>(name: str) -> bool</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_registry</a>() -> ToolRegistry</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_tool</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register_tool</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None) -> None</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">tool</a>(func: Optional[Callable] = None) -> Union[FunctionTool, Callable[[Callable], FunctionTool]]</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_tool</a>(tool: Any) -> bool</code>
|
||||
|
||||
# Workflows
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Loop, Parallel, Pipeline, Repeat, Route, Workflow, WorkflowStep, loop, parallel, repeat, route
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">arun</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False) -> Dict[str, Any]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">astart</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False) -> Dict[str, Any]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">from_template</a>(uri: str, config: Optional[Dict[str, Any]] = None, offline: bool = False, **kwargs) -> 'Workflow'</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">memory_config</a>() -> Optional[Dict[str, Any]]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_step_complete</a>() -> Optional[Callable]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_step_error</a>() -> Optional[Callable]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_step_start</a>() -> Optional[Callable]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_workflow_complete</a>() -> Optional[Callable]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_workflow_start</a>() -> Optional[Callable]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">planning_llm</a>() -> Optional[str]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">reasoning</a>() -> bool</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">run</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False, stream: bool = None) -> Dict[str, Any]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">start</a>(input: str = '', **kwargs) -> Dict[str, Any]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">stream</a>() -> bool</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Workflow">Workflow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>() -> bool</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">async_execution</a>() -> bool</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">branch_condition</a>() -> Optional[Dict[str, List[str]]]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">context_from</a>() -> Optional[List[str]]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">evaluator</a>()</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">executor</a>()</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">max_retries</a>() -> int</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">next_steps</a>() -> Optional[List[str]]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_error</a>() -> str</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">output_file</a>() -> Optional[str]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">output_json</a>() -> Optional[Any]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">output_pydantic</a>() -> Optional[Any]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">output_variable</a>() -> Optional[str]</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">quality_check</a>() -> bool</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">rerun</a>() -> bool</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">retain_full_context</a>() -> bool</code>
|
||||
* <code title="class WorkflowStep">WorkflowStep.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">loop</a>(step: Any, over: Optional[str] = None, from_csv: Optional[str] = None, from_file: Optional[str] = None, var_name: str = 'item') -> Loop</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">parallel</a>(steps: List) -> Parallel</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">repeat</a>(step: Any, until: Optional[Callable[[WorkflowContext], bool]] = None, max_iterations: int = 10) -> Repeat</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">route</a>(routes: Dict[str, List], default: Optional[List] = None) -> Route</code>
|
||||
|
||||
# DB
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import db
|
||||
```
|
||||
|
||||
# Memory
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Memory
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_context_for_task</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_in_output: Optional[bool] = None) -> str</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">calculate_quality_metrics</a>(output: str, expected_output: str, llm: Optional[str] = None, custom_prompt: Optional[str] = None) -> Dict[str, float]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">compute_quality_score</a>(completeness: float, relevance: float, clarity: float, accuracy: float, weights: Dict[str, float] = None) -> float</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">finalize_task_output</a>(content: str, agent_name: str, quality_score: float, threshold: float = 0.7, metrics: Dict[str, Any] = None, task_id: str = None)</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_all_memories</a>() -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_all</a>()</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_entity_only</a>()</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_long_term</a>()</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_short_term</a>()</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_user_memory</a>()</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search</a>(query: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_entity</a>(query: str, limit: int = 5) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_long_term</a>(query: str, limit: int = 5, relevance_cutoff: float = 0.0, min_quality: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_short_term</a>(query: str, limit: int = 5, min_quality: float = 0.0, relevance_cutoff: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_user_memory</a>(user_id: str, query: str, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_with_quality</a>(query: str, min_quality: float = 0.0, memory_type: Literal['short', 'long'] = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_entity</a>(name: str, type_: str, desc: str, relations: str)</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_long_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None)</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_quality</a>(text: str, quality_score: float, task_id: Optional[str] = None, iteration: Optional[int] = None, metrics: Optional[Dict[str, float]] = None, memory_type: Literal['short', 'long'] = 'long') -> None</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_short_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None)</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_user_memory</a>(user_id: str, text: str, extra: Dict[str, Any] = None)</code>
|
||||
|
||||
# Knowledge
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Chunking, Knowledge
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">SUPPORTED_CHUNKERS</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">__call__</a>(text: Union[str, List[str]], **kwargs) -> Union[List[Any], List[List[Any]]]</code>
|
||||
* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">chunk</a>(text: Union[str, List[str]], **kwargs) -> Union[List[Any], List[List[Any]]]</code>
|
||||
* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">chunker</a>()</code>
|
||||
* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">embedding_model</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">add</a>(file_path, user_id = None, agent_id = None, run_id = None, metadata = None)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">chunker</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">config</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">delete</a>(memory_id)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">delete_all</a>(user_id = None, agent_id = None, run_id = None)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">get</a>(memory_id)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">get_all</a>(user_id = None, agent_id = None, run_id = None)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">get_corpus_stats</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">history</a>(memory_id)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">index</a>(path: str, incremental: bool = True, force: bool = False, include_glob: list = None, exclude_glob: list = None, user_id: str = None, agent_id: str = None, run_id: str = None)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">markdown</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">memory</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">normalize_content</a>(content)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">reset</a>()</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">search</a>(query, user_id = None, agent_id = None, run_id = None, rerank = None, **kwargs)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">store</a>(content, user_id = None, agent_id = None, run_id = None, metadata = None)</code>
|
||||
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">update</a>(memory_id, data)</code>
|
||||
|
||||
# RAG
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import RAG, RAGCitation, RAGConfig, RAGResult
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">aquery</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> RAGResult</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">aretrieve</a>(query: str, **kwargs) -> ContextPack</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">astream</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> AsyncIterator[str]</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">get_citations</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> List[Citation]</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">llm</a>()</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">query</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> RAGResult</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">retrieve</a>(query: str, **kwargs) -> ContextPack</code>
|
||||
* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">stream</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> Iterator[str]</code>
|
||||
* <code title="class RAGCitation">RAGCitation.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'Citation'</code>
|
||||
* <code title="class RAGCitation">RAGCitation.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class RAGConfig">RAGConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'RAGConfig'</code>
|
||||
* <code title="class RAGConfig">RAGConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">format_answer_with_citations</a>() -> str</code>
|
||||
* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'RAGResult'</code>
|
||||
* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">has_citations</a>() -> bool</code>
|
||||
* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
|
||||
# Handoff
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Handoff, RECOMMENDED_PROMPT_PREFIX, handoff, handoff_filters, prompt_with_handoff_instructions
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">default_tool_description</a>() -> str</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">default_tool_name</a>() -> str</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">execute_async</a>(source_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None) -> HandoffResult</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">execute_programmatic</a>(source_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None) -> HandoffResult</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_tool_function</a>(source_agent: 'Agent') -> Callable</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_description</a>() -> str</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_name</a>() -> str</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">handoff</a>(agent: 'Agent', tool_name_override: Optional[str] = None, tool_description_override: Optional[str] = None, on_handoff: Optional[Callable] = None, input_type: Optional[type] = None, input_filter: Optional[Callable[[HandoffInputData], HandoffInputData]] = None, config: Optional[HandoffConfig] = None, context_policy: Optional[str] = None, timeout_seconds: Optional[float] = None, max_concurrent: Optional[int] = None, detect_cycles: Optional[bool] = None, max_depth: Optional[int] = None) -> Handoff</code>
|
||||
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">keep_last_n_messages</a>(n: int) -> Callable[[HandoffInputData], HandoffInputData]</code>
|
||||
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">remove_all_tools</a>(data: HandoffInputData) -> HandoffInputData</code>
|
||||
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">remove_system_messages</a>(data: HandoffInputData) -> HandoffInputData</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">prompt_with_handoff_instructions</a>(base_prompt: str, agent: 'Agent') -> str</code>
|
||||
|
||||
# Guardrails
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import LLMGuardrail
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class LLMGuardrail">LLMGuardrail.<a href="./src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py">__call__</a>(task_output: TaskOutput) -> Tuple[bool, Union[str, TaskOutput]]</code>
|
||||
|
||||
# Skills
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import SkillLoader, SkillManager, SkillMetadata, SkillProperties
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">activate</a>(skill: LoadedSkill) -> bool</code>
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load</a>(skill_path: str, activate: bool = False) -> Optional[LoadedSkill]</code>
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_all_resources</a>(skill: LoadedSkill) -> None</code>
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_assets</a>(skill: LoadedSkill) -> dict</code>
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_metadata</a>(skill_path: str) -> Optional[LoadedSkill]</code>
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_references</a>(skill: LoadedSkill) -> dict</code>
|
||||
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_scripts</a>(skill: LoadedSkill) -> dict</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate</a>(skill: LoadedSkill) -> bool</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate_by_name</a>(name: str) -> bool</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill</a>(skill_path: str) -> Optional[LoadedSkill]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">clear</a>() -> None</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills</a>() -> List[SkillMetadata]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_instructions</a>(name: str) -> Optional[str]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skill</a>(name: str) -> Optional[LoadedSkill]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">load_resources</a>(name: str) -> bool</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skill_names</a>() -> List[str]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skills</a>() -> List[LoadedSkill]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">to_prompt</a>() -> str</code>
|
||||
* <code title="class SkillMetadata">SkillMetadata.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">from_properties</a>(props: SkillProperties) -> 'SkillMetadata'</code>
|
||||
* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">to_dict</a>() -> dict</code>
|
||||
|
||||
# Session
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Session
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">Agent</a>(name: str, role: str = 'Assistant', instructions: Optional[str] = None, tools: Optional[List[Any]] = None, memory: bool = True, knowledge: Optional[List[str]] = None, **kwargs) -> 'Agent'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">add_knowledge</a>(source: str) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">add_memory</a>(text: str, memory_type: str = 'long', **metadata) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">chat</a>(message: str, **kwargs) -> str</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">clear_memory</a>(memory_type: str = 'all') -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">create_agent</a>(*args, **kwargs) -> 'Agent'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">get_context</a>(query: str, max_items: int = 3) -> str</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">get_state</a>(key: str, default: Any = None) -> Any</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">increment_state</a>(key: str, increment: int = 1, default: int = 0) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">knowledge</a>() -> 'Knowledge'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">memory</a>() -> 'Memory'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">restore_state</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">save_state</a>(state_data: Dict[str, Any]) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">search_knowledge</a>(query: str, limit: int = 5) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">search_memory</a>(query: str, memory_type: str = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">send_message</a>(message: str, **kwargs) -> str</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">set_state</a>(key: str, value: Any) -> None</code>
|
||||
|
||||
# Telemetry
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import get_telemetry
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">get_telemetry</a>() -> 'MinimalTelemetry'</code>
|
||||
|
||||
# Observability
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import FlowDisplay, obs, track_workflow
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class FlowDisplay">FlowDisplay.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">display</a>()</code>
|
||||
* <code title="class FlowDisplay">FlowDisplay.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">start</a>()</code>
|
||||
* <code title="class FlowDisplay">FlowDisplay.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">stop</a>()</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">track_workflow</a>()</code>
|
||||
|
||||
# Context
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import ContextManager, ManagerConfig
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">capture_llm_boundary</a>(messages: List[Dict[str, Any]], tools: List[Dict[str, Any]]) -> SnapshotHookData</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">estimate_tokens</a>(text: str, validate: bool = False) -> Tuple[int, Optional[EstimationMetrics]]</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_history</a>() -> List[Dict[str, Any]]</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_last_snapshot_hook</a>() -> Optional[SnapshotHookData]</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_resolved_config</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_stats</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_tool_budget</a>(tool_name: str) -> int</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">process</a>(messages: List[Dict[str, Any]], system_prompt: str = '', tools: Optional[List[Dict[str, Any]]] = None, trigger: Literal['turn', 'tool_call', 'manual', 'overflow'] = 'turn') -> Dict[str, Any]</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">register_snapshot_callback</a>(callback: Callable[[SnapshotHookData], None]) -> None</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">reset</a>() -> None</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">set_tool_budget</a>(tool_name: str, max_tokens: int, protected: bool = False) -> None</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">truncate_tool_output</a>(tool_name: str, output: str) -> str</code>
|
||||
* <code title="class ManagerConfig">ManagerConfig.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">from_env</a>() -> 'ManagerConfig'</code>
|
||||
* <code title="class ManagerConfig">ManagerConfig.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">merge</a>(**overrides) -> 'ManagerConfig'</code>
|
||||
* <code title="class ManagerConfig">ManagerConfig.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
|
||||
# Display
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import async_display_callbacks, clean_triple_backticks, display_error, display_generating, display_instruction, display_interaction, display_self_reflection, display_tool_call, error_logs, register_display_callback, sync_display_callbacks
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">clean_triple_backticks</a>(text: str) -> str</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_error</a>(message: str, console = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_generating</a>(content: str = '', start_time: Optional[float] = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_instruction</a>(message: str, console = None, agent_name: str = None, agent_role: str = None, agent_tools: List[str] = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_interaction</a>(message, response, markdown = True, generation_time = None, console = None, agent_name = None, agent_role = None, agent_tools = None, task_name = None, task_description = None, task_id = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_self_reflection</a>(message: str, console = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_tool_call</a>(message: str, console = None, tool_name: str = None, tool_input: dict = None, tool_output: str = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">register_display_callback</a>(display_type: str, callback_fn, is_async: bool = False)</code>
|
||||
|
||||
# Other
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import AutoRagConfig, Citation, CodeExecutionStep, DeepResearchResponse, ExpandResult, ExpandStrategy, FileSearchCall, MCPCall, Provider, RagRetrievalPolicy, ReasoningStep, RewriteResult, RewriteStrategy, Task, WebSearchCall, warmup
|
||||
```
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class AutoRagConfig">AutoRagConfig.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">from_dict</a>(data: Dict[str, Any]) -> 'AutoRagConfig'</code>
|
||||
* <code title="class AutoRagConfig">AutoRagConfig.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class Citation">Citation.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'Citation'</code>
|
||||
* <code title="class Citation">Citation.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class DeepResearchResponse">DeepResearchResponse.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">get_all_sources</a>() -> List[Dict[str, str]]</code>
|
||||
* <code title="class DeepResearchResponse">DeepResearchResponse.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">get_citation_text</a>(citation: Citation) -> str</code>
|
||||
* <code title="class RewriteResult">RewriteResult.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">all_queries</a>() -> List[str]</code>
|
||||
* <code title="class RewriteResult">RewriteResult.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">primary_query</a>() -> str</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">execute_callback</a>(task_output: TaskOutput) -> None</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">execute_callback_sync</a>(task_output: TaskOutput) -> None</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">initialize_memory</a>()</code>
|
||||
* <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">store_in_memory</a>(content: str, agent_name: str = None, task_id: str = None)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/__init__.py">warmup</a>(include_litellm: bool = False, include_openai: bool = True) -> dict</code>
|
||||
|
||||
# Wrapper (praisonai)
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonai import CloudProvider, Deploy, DeployConfig, DeployType, PraisonAI, __version__
|
||||
```
|
||||
|
||||
# CLI
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="cli">praisonai <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai acp acp-main <a href="./src/praisonai/praisonai/cli/commands/acp.py">--help</a></code>
|
||||
* <code title="cli">praisonai agents create <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
|
||||
* <code title="cli">praisonai agents info <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
|
||||
* <code title="cli">praisonai agents list <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
|
||||
* <code title="cli">praisonai audit agent-centric <a href="./src/praisonai/praisonai/cli/commands/audit.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark agent <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark benchmark-callback <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark cli <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark compare <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark litellm <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark profile <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark sdk <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai benchmark workflow <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
|
||||
* <code title="cli">praisonai call call-main <a href="./src/praisonai/praisonai/cli/commands/call.py">--help</a></code>
|
||||
* <code title="cli">praisonai chat <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai chat chat-main <a href="./src/praisonai/praisonai/cli/commands/chat.py">--help</a></code>
|
||||
* <code title="cli">praisonai code <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai code code-main <a href="./src/praisonai/praisonai/cli/commands/code.py">--help</a></code>
|
||||
* <code title="cli">praisonai commit commit-main <a href="./src/praisonai/praisonai/cli/commands/commit.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion bash <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion completion-callback <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion fish <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai completion zsh <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
|
||||
* <code title="cli">praisonai config get <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config list <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config path <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config reset <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai config set <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
|
||||
* <code title="cli">praisonai context add <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context clear <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context compact <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context export <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context show <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai context stats <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug acp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug debug-callback <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug interactive <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug lsp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai debug trace <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy aws <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy azure <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy docker <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai deploy gcp <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
|
||||
* <code title="cli">praisonai diag diag-callback <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
|
||||
* <code title="cli">praisonai diag export <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs api-md <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs generate <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs list <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs report <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs run <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs run-all <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs serve <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai docs stats <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor config <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor db <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor doctor-callback <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor env <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor mcp <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor network <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor performance <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor selftest <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor tools <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai endpoints list <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
|
||||
* <code title="cli">praisonai endpoints test <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
|
||||
* <code title="cli">praisonai environment check <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
|
||||
* <code title="cli">praisonai environment doctor <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
|
||||
* <code title="cli">praisonai environment view <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
|
||||
* <code title="cli">praisonai eval accuracy <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
|
||||
* <code title="cli">praisonai eval performance <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples info <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples list <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples report <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples run <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples run-all <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai examples stats <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
|
||||
* <code title="cli">praisonai hooks add <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
|
||||
* <code title="cli">praisonai hooks list <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
|
||||
* <code title="cli">praisonai hooks remove <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge add <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge index <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge list <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai knowledge search <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp logs <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp lsp-callback <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp start <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp status <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai lsp stop <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp add <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp list <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp mcp-callback <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp remove <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai mcp test <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory add <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory clear <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory search <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai memory show <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
|
||||
* <code title="cli">praisonai package install <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
|
||||
* <code title="cli">praisonai package list <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
|
||||
* <code title="cli">praisonai package uninstall <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile imports <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile optimize <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile profile-callback <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile query <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile snapshot <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile startup <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai profile suite <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag chat <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag eval <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag index <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag query <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai rag serve <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
|
||||
* <code title="cli">praisonai realtime realtime-main <a href="./src/praisonai/praisonai/cli/commands/realtime.py">--help</a></code>
|
||||
* <code title="cli">praisonai recipe install <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
|
||||
* <code title="cli">praisonai recipe list <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
|
||||
* <code title="cli">praisonai recipe run <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
|
||||
* <code title="cli">praisonai registry list <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
|
||||
* <code title="cli">praisonai registry serve <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
|
||||
* <code title="cli">praisonai research research-main <a href="./src/praisonai/praisonai/cli/commands/research.py">--help</a></code>
|
||||
* <code title="cli">praisonai retrieval index <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
|
||||
* <code title="cli">praisonai retrieval query <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
|
||||
* <code title="cli">praisonai retrieval search <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
|
||||
* <code title="cli">praisonai rules add <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
|
||||
* <code title="cli">praisonai rules clear <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
|
||||
* <code title="cli">praisonai rules list <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
|
||||
* <code title="cli">praisonai run <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
|
||||
* <code title="cli">praisonai run run-main <a href="./src/praisonai/praisonai/cli/commands/run.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule delete <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule describe <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule logs <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule restart <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule schedule-callback <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule start <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule stats <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai schedule stop <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve serve-callback <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve start <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve status <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai serve stop <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
|
||||
* <code title="cli">praisonai session delete <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session export <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session import <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session list <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session resume <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai session show <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills create <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills install <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills list <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai skills validate <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise check <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise fix <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise init <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai standardise report <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
|
||||
* <code title="cli">praisonai templates create <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
|
||||
* <code title="cli">praisonai templates list <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
|
||||
* <code title="cli">praisonai test info <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
|
||||
* <code title="cli">praisonai test run <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
|
||||
* <code title="cli">praisonai todo add <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
|
||||
* <code title="cli">praisonai todo done <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
|
||||
* <code title="cli">praisonai todo list <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
|
||||
* <code title="cli">praisonai tools info <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
|
||||
* <code title="cli">praisonai tools list <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
|
||||
* <code title="cli">praisonai tools test <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces disable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces enable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces list <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai traces status <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
|
||||
* <code title="cli">praisonai train train-main <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui chat <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui code <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui gradio <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui realtime <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai ui ui-main <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
|
||||
* <code title="cli">praisonai version check <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
|
||||
* <code title="cli">praisonai version show <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
|
||||
* <code title="cli">praisonai version version-callback <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
|
||||
* <code title="cli">praisonai workflow create <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
|
||||
* <code title="cli">praisonai workflow list <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
|
||||
* <code title="cli">praisonai workflow run <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
|
||||
|
||||
# TypeScript
|
||||
|
||||
Types/Exports:
|
||||
```ts
|
||||
export { Agent, Agents, PraisonAIAgents, Router } from "./agent";
|
||||
export type { PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig } from "./agent";
|
||||
export { ContextAgent, createContextAgent } from "./agent/context";
|
||||
export { Handoff, handoff, handoffFilters } from "./agent/handoff";
|
||||
export { ImageAgent, createImageAgent } from "./agent/image";
|
||||
export { PromptExpanderAgent, createPromptExpanderAgent } from "./agent/prompt-expander";
|
||||
export { QueryRewriterAgent, createQueryRewriterAgent } from "./agent/query-rewriter";
|
||||
export { DeepResearchAgent, createDeepResearchAgent } from "./agent/research";
|
||||
export { RouterAgent, createRouter, routeConditions } from "./agent/router";
|
||||
export { // Agent loop
|
||||
createAgentLoop, // DevTools
|
||||
enableDevTools, // MCP
|
||||
createMCP, // Middleware (renamed to avoid conflicts)
|
||||
createCachingMiddleware, // Models
|
||||
createModel, // Multimodal
|
||||
createImagePart, // Next.js
|
||||
createRouteHandler, // OAuth for MCP
|
||||
type OAuthClientProvider, // Server adapters
|
||||
createHttpHandler, // Speech & Transcription
|
||||
generateSpeech, // Telemetry (AI SDK v6 parity)
|
||||
configureTelemetry, // Tool Approval (AI SDK v6 parity)
|
||||
ApprovalManager, // Tools
|
||||
defineTool, // UI Message (AI SDK v6 parity)
|
||||
convertToModelMessages, AIAgentStep, AIEmbedManyResult, AIEmbedOptions, AIEmbedResult, AIFilePart, AIGenerateImageOptions, AIGenerateImageResult, AIGenerateObjectOptions, AIGenerateObjectResult, AIGenerateTextOptions, AIGenerateTextResult, AIImagePart, AIMiddleware, AIMiddlewareConfig, AIModelMessage, AISpan, AISpanKind, AISpanOptions, AISpanStatus, AIStreamObjectOptions, AIStreamObjectResult, AIStreamTextOptions, AIStreamTextResult, AITelemetryEvent, AITelemetrySettings, AITextPart, AIToolDefinition, AITracer, AgentLoop, DANGEROUS_PATTERNS, MODEL_ALIASES, SPEECH_MODELS, TRANSCRIPTION_MODELS, ToolApprovalDeniedError, ToolApprovalTimeoutError, aiEmbed, aiEmbedMany, aiGenerateImage, aiGenerateObject, aiGenerateText, aiStreamObject, aiStreamText, applyMiddleware, autoEnableDevTools, base64ToUint8Array, clearAICache, clearEvents, closeAllMCPClients, closeMCPClient, convertToUIMessages, createAILoggingMiddleware, createAISpan, createApprovalResponse, createDangerousPatternChecker, createDevToolsMiddleware, createExpressHandler, createFastifyHandler, createFilePart, createHonoHandler, createMultimodalMessage, createNestHandler, createPagesHandler, createPdfPart, createSystemMessage, createTelemetryMiddleware, createTelemetrySettings, createTextMessage, createTextPart, createToolSet, disableAITelemetry, disableDevTools, enableAITelemetry, functionToTool, getAICacheStats, getApprovalManager, getDevToolsState, getDevToolsUrl, getEvents, getMCPClient, getModel, getTelemetrySettings, getToolsNeedingApproval, getTracer, hasModelAlias, hasPendingApprovals, initOpenTelemetry, isDangerous, isDataUrl, isDevToolsEnabled, isTelemetryEnabled, isUrl, listModelAliases, mcpToolsToAITools, parseModel, pipeUIMessageStreamToResponse, recordEvent, resolveModelAlias, safeValidateUIMessages, setApprovalManager, stopAfterSteps, stopWhen, stopWhenNoToolCalls, toMessageContent, toUIMessageStreamResponse, transcribe, uint8ArrayToBase64, validateUIMessages, withApproval, withSpan, wrapModel } from "./ai";
|
||||
export { AutoAgents, createAutoAgents } from "./auto";
|
||||
export { BaseCache, FileCache, MemoryCache, createFileCache, createMemoryCache } from "./cache";
|
||||
export { CLI_SPEC_VERSION, executeCommand, parseArgs } from "./cli";
|
||||
export { // Autonomy Mode
|
||||
AutonomyManager, // Background Jobs
|
||||
JobQueue, // Checkpoints
|
||||
CheckpointManager, // Cost Tracker
|
||||
CostTracker, // External Agents
|
||||
BaseExternalAgent, // Fast Context
|
||||
FastContext, // Flow Display
|
||||
FlowDisplay, // Git Integration
|
||||
GitManager, // Interactive TUI
|
||||
InteractiveTUI, // N8N Integration
|
||||
N8NIntegration, // Repo Map
|
||||
RepoMap, // Sandbox Executor
|
||||
SandboxExecutor, // Scheduler
|
||||
Scheduler, // Slash Commands
|
||||
SlashCommandHandler, AiderAgent, ClaudeCodeAgent, CodexCliAgent, CommandValidator, CostTokenUsage, DEFAULT_BLOCKED_COMMANDS, DEFAULT_BLOCKED_PATHS, DEFAULT_IGNORE_PATTERNS, DiffViewer, FileCheckpointStorage, FileJobStorage, GeminiCliAgent, GenericExternalAgent, HistoryManager, MODEL_PRICING, MODE_POLICIES, MemoryCheckpointStorage, MemoryJobStorage, StatusDisplay, cliApprovalPrompt, createAutonomyManager, createCheckpointManager, createCostTracker, createDiffViewer, createExternalAgent, createFastContext, createFileCheckpointStorage, createFileJobStorage, createFlowDisplay, createGitManager, createHistoryManager, createInteractiveTUI, createJobQueue, createN8NIntegration, createRepoMap, createSandboxExecutor, createScheduler, createSlashCommandHandler, createStatusDisplay, cronExpressions, estimateTokens, executeSlashCommand, externalAgentAsTool, formatCost, getExternalAgentRegistry, getQuickContext, getRepoTree, isSlashCommand, parseSlashCommand, registerCommand, renderWorkflow, sandboxExec, triggerN8NWebhook } from "./cli/features";
|
||||
export { createDbAdapter, db, getDefaultDbAdapter, setDefaultDbAdapter } from "./db";
|
||||
export type { DbAdapter, DbConfig, DbMessage, DbRun, DbTrace } from "./db";
|
||||
export { MemoryPostgresAdapter, NeonPostgresAdapter, PostgresSessionStorage, createMemoryPostgres, createNeonPostgres, createPostgresSessionStorage } from "./db/postgres";
|
||||
export { MemoryRedisAdapter, UpstashRedisAdapter, createMemoryRedis, createUpstashRedis } from "./db/redis";
|
||||
export { SQLiteAdapter, createSQLiteAdapter } from "./db/sqlite";
|
||||
export { EvalSuite, accuracyEval, performanceEval, reliabilityEval } from "./eval";
|
||||
export { AgentEventBus, AgentEvents, EventEmitterPubSub, PubSub, createEventBus, createPubSub } from "./events";
|
||||
export { LLMGuardrail, createLLMGuardrail } from "./guardrails/llm-guardrail";
|
||||
export { // Computer Use
|
||||
createComputerUse, ComputerUseClient, createCLIApprovalPrompt, createComputerUseAgent } from "./integrations/computer-use";
|
||||
export { BaseObservabilityProvider, ConsoleObservabilityProvider, LangfuseObservabilityProvider, MemoryObservabilityProvider, ObservabilityTraceContext, createConsoleObservability, createLangfuseObservability, createMemoryObservability } from "./integrations/observability";
|
||||
export { // Natural Language Postgres
|
||||
createNLPostgres, NLPostgresClient, NLPostgresConfig, createPostgresTool } from "./integrations/postgres";
|
||||
export { // Slack
|
||||
createSlackBot, SlackBot, parseSlackMessage, verifySlackSignature } from "./integrations/slack";
|
||||
export { BaseVectorStore, ChromaVectorStore, MemoryVectorStore, PineconeVectorStore, QdrantVectorStore, VectorQueryResult, WeaviateVectorStore, createChromaStore, createMemoryVectorStore, createPineconeStore, createQdrantStore, createWeaviateStore } from "./integrations/vector";
|
||||
export { BaseVoiceProvider, ElevenLabsVoiceProvider, OpenAIVoiceProvider, createElevenLabsVoice, createOpenAIVoice } from "./integrations/voice";
|
||||
export { GraphRAG, GraphStore, createGraphRAG } from "./knowledge/graph-rag";
|
||||
export { BaseReranker, CohereReranker, CrossEncoderReranker, LLMReranker, createCohereReranker, createCrossEncoderReranker, createLLMReranker } from "./knowledge/reranker";
|
||||
export { // Provider classes
|
||||
OpenAIProvider, // Provider factory and utilities
|
||||
createProvider, // Provider registry (extensibility API)
|
||||
ProviderRegistry, // Types
|
||||
type LLMProvider, AnthropicProvider, BaseProvider, GoogleProvider, ProviderMessage, ProviderToolDefinition, createProviderRegistry, getAvailableProviders, getDefaultProvider, getDefaultRegistry, hasProvider, isProviderAvailable, listProviders, parseModelString, registerBuiltinProviders, registerProvider, unregisterProvider } from "./llm/providers";
|
||||
export { ADAPTERS, AISDK_PROVIDERS, COMMUNITY_PROVIDERS, PROVIDER_ALIASES } from "./llm/providers/ai-sdk/types";
|
||||
export { AutoMemory, AutoMemoryKnowledgeBase, AutoMemoryVectorStore, DEFAULT_POLICIES, createAutoMemory, createLLMSummarizer } from "./memory/auto-memory";
|
||||
export { FileMemory, createFileMemory } from "./memory/file-memory";
|
||||
export { Memory, createMemory } from "./memory/memory";
|
||||
export type { MemoryConfig, MemoryEntry } from "./memory/memory";
|
||||
export { // Adapters
|
||||
NoopObservabilityAdapter, // Constants
|
||||
OBSERVABILITY_TOOLS, // Global adapter management
|
||||
setObservabilityAdapter, // Types
|
||||
type SpanKind, ConsoleObservabilityAdapter, MemoryObservabilityAdapter, clearAdapterCache, createConsoleAdapter, createMemoryAdapter, createObservabilityAdapter, getObservabilityAdapter, getObservabilityToolInfo, hasObservabilityToolEnvVar, listObservabilityTools, noopAdapter, resetObservabilityAdapter, trace } from "./observability";
|
||||
export { Plan, PlanStep, PlanStorage, PlanningAgent, TaskAgent, TodoItem, TodoList, createPlan, createPlanStorage, createPlanningAgent, createTaskAgent, createTodoList } from "./planning";
|
||||
export { SkillManager, createSkillManager, parseSkillFile } from "./skills";
|
||||
export { AgentTelemetry, TelemetryCollector, cleanupTelemetry, createAgentTelemetry, disableTelemetry, enableTelemetry, getTelemetry } from "./telemetry";
|
||||
export { BaseTool, FunctionTool, ToolRegistry, ToolResult, ToolValidationError, createTool, getRegistry, getTool, registerTool, tool, validateTool } from "./tools";
|
||||
export { airweaveSearch, bedrockBrowserClick, bedrockBrowserFill, bedrockBrowserNavigate, bedrockCodeInterpreter, codeExecution, codeMode, createCustomTool, exaSearch, firecrawlCrawl, firecrawlScrape, parallelSearch, perplexitySearch, registerCustomTool, registerLocalTool, registerNpmTool, superagentGuard, superagentRedact, superagentVerify, tavilyCrawl, tavilyExtract, tavilySearch, valyuBioSearch, valyuCompanyResearch, valyuEconomicsSearch, valyuFinanceSearch, valyuPaperSearch, valyuPatentSearch, valyuSecSearch, valyuWebSearch } from "./tools/builtins";
|
||||
export { MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getToolsRegistry, resetToolsRegistry } from "./tools/registry";
|
||||
export type { InstallHints, PraisonTool, RedactionHooks, RegisteredTool, ToolCapabilities, ToolExecutionContext, ToolExecutionResult, ToolFactory, ToolHooks, ToolInstallStatus, ToolLimits, ToolLogger, ToolMetadata, ToolMiddleware, ToolParameterProperty, ToolParameterSchema } from "./tools/registry";
|
||||
export { registerBuiltinTools, tools } from "./tools/tools";
|
||||
export { Workflow, loop, parallel, repeat, route } from "./workflows";
|
||||
export type { StepResult, WorkflowContext, WorkflowStep } from "./workflows";
|
||||
export { createWorkflowFromYAML, loadWorkflowFromFile, parseYAMLWorkflow, validateWorkflowDefinition } from "./workflows/yaml-parser";
|
||||
```
|
||||
|
||||
# Optional Plugins
|
||||
|
||||
External tools are available via `praisonai-tools` package:
|
||||
|
||||
```bash
|
||||
pip install praisonai-tools
|
||||
```
|
||||
|
||||
See [PraisonAI-tools](https://github.com/MervinPraison/PraisonAI-tools) for available tools.
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=3.6.2" \
|
||||
"praisonai>=3.7.8" \
|
||||
"praisonai[chat]" \
|
||||
"embedchain[github,youtube]"
|
||||
|
||||
|
||||
@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=3.6.2" \
|
||||
"praisonai>=3.7.8" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[chat]" \
|
||||
"praisonai[realtime]" \
|
||||
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=3.6.2" \
|
||||
"praisonai>=3.7.8" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[crewai]"
|
||||
|
||||
|
||||
@@ -0,0 +1,96 @@
|
||||
# Consolidated Params Examples
|
||||
|
||||
Examples demonstrating the **Agent-Centric API** with consolidated parameters.
|
||||
|
||||
## Precedence Ladder
|
||||
|
||||
```
|
||||
Instance > Config > Array > Dict > String > Bool > Default
|
||||
```
|
||||
|
||||
## Quick Reference
|
||||
|
||||
| Feature | Presets | Example |
|
||||
|---------|---------|---------|
|
||||
| `memory` | file, sqlite, redis, postgres, mem0, mongodb | `memory="sqlite"` |
|
||||
| `output` | minimal, normal, verbose, debug, silent | `output="verbose"` |
|
||||
| `execution` | fast, balanced, thorough, unlimited | `execution="balanced"` |
|
||||
| `planning` | reasoning, read_only, auto | `planning="reasoning"` |
|
||||
| `reflection` | minimal, standard, thorough | `reflection="standard"` |
|
||||
| `guardrails` | strict, permissive, safety | `guardrails="strict"` |
|
||||
| `web` | duckduckgo, tavily, google, bing, serper | `web="duckduckgo"` |
|
||||
| `context` | sliding_window, summarize, truncate | `context="sliding_window"` |
|
||||
| `autonomy` | suggest, auto_edit, full_auto | `autonomy="suggest"` |
|
||||
| `caching` | enabled, disabled, prompt | `caching="prompt"` |
|
||||
|
||||
## Examples
|
||||
|
||||
### Basic Examples (Single Feature)
|
||||
|
||||
| File | Feature | Description |
|
||||
|------|---------|-------------|
|
||||
| `basic_agent.py` | Agent | Minimal agent with memory |
|
||||
| `basic_memory.py` | memory | SQLite memory preset |
|
||||
| `basic_output.py` | output | Verbose output preset |
|
||||
| `basic_execution.py` | execution | Execution control |
|
||||
| `basic_guardrails.py` | guardrails | Callable validator |
|
||||
| `basic_reflection.py` | reflection | Self-reflection preset |
|
||||
| `basic_web.py` | web | Web search preset |
|
||||
| `basic_planning.py` | planning | Planning preset |
|
||||
| `basic_autonomy.py` | autonomy | Autonomy preset |
|
||||
| `basic_caching.py` | caching | Caching preset |
|
||||
| `basic_knowledge.py` | knowledge | RAG with sources |
|
||||
| `basic_context.py` | context | Context management |
|
||||
| `basic_hooks.py` | hooks | Lifecycle callbacks |
|
||||
|
||||
### Multi-Agent Examples
|
||||
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `basic_agents.py` | Multi-agent with memory and planning |
|
||||
|
||||
### Workflow Examples
|
||||
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `basic_workflow.py` | Simple workflow with output preset |
|
||||
| `basic_workflow_agentlike.py` | Workflow with agent-like params |
|
||||
| `basic_step_override.py` | Step-level param overrides |
|
||||
| `advanced_workflow_full_features.py` | All consolidated params |
|
||||
|
||||
### Advanced Examples
|
||||
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `advanced_output_execution.py` | Combined output + execution |
|
||||
|
||||
## Usage Forms
|
||||
|
||||
Each consolidated param supports multiple input forms:
|
||||
|
||||
```python
|
||||
# Bool - enable with defaults
|
||||
memory=True
|
||||
|
||||
# String preset
|
||||
memory="sqlite"
|
||||
|
||||
# Dict config
|
||||
memory={"backend": "sqlite", "user_id": "user123"}
|
||||
|
||||
# Config instance
|
||||
memory=MemoryConfig(backend="sqlite", user_id="user123")
|
||||
|
||||
# Array with overrides (for some params)
|
||||
guardrails=["strict", {"max_retries": 10}]
|
||||
```
|
||||
|
||||
## Running Examples
|
||||
|
||||
```bash
|
||||
# Set API key
|
||||
export OPENAI_API_KEY=your_key_here
|
||||
|
||||
# Run any example
|
||||
python basic_agent.py
|
||||
```
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Autonomy Example - Agent-Centric API
|
||||
|
||||
Demonstrates autonomy with consolidated params.
|
||||
Presets: suggest, auto_edit, full_auto
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable autonomy with preset
|
||||
agent = Agent(
|
||||
instructions="You are an autonomous assistant.",
|
||||
autonomy="suggest", # Presets: suggest, auto_edit, full_auto
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Help me organize my project files.")
|
||||
print(response)
|
||||
@@ -0,0 +1,23 @@
|
||||
"""
|
||||
Basic Caching Example - Agent-Centric API
|
||||
|
||||
Demonstrates caching with consolidated params.
|
||||
Presets: enabled, disabled, prompt
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable caching with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with caching enabled.",
|
||||
caching="prompt", # Presets: enabled, disabled, prompt
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
# First call - will cache
|
||||
response = agent.start("What is the capital of France?")
|
||||
print(response)
|
||||
|
||||
# Second call - may use cache
|
||||
response = agent.start("What is the capital of France?")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Context Example - Agent-Centric API
|
||||
|
||||
Demonstrates context management with consolidated params.
|
||||
Presets: sliding_window, summarize, truncate
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable context management with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with context management.",
|
||||
context="sliding_window", # Presets: sliding_window, summarize, truncate
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Tell me a long story about a dragon.")
|
||||
print(response)
|
||||
@@ -0,0 +1,28 @@
|
||||
"""
|
||||
Basic Hooks Example - Agent-Centric API
|
||||
|
||||
Demonstrates lifecycle hooks with consolidated params.
|
||||
Valid keys: on_step, on_tool_call, middleware
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Define hook callbacks
|
||||
def on_step_callback(step_info):
|
||||
print(f"Step: {step_info}")
|
||||
|
||||
def on_tool_call_callback(tool_info):
|
||||
print(f"Tool called: {tool_info}")
|
||||
|
||||
# Basic: Enable hooks with dict
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
hooks={
|
||||
"on_step": on_step_callback,
|
||||
"on_tool_call": on_tool_call_callback,
|
||||
},
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("What is 2 + 2?")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Knowledge (RAG) Example - Agent-Centric API
|
||||
|
||||
Demonstrates knowledge with consolidated params.
|
||||
Supports: bool, list of sources, dict config, KnowledgeConfig
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable knowledge with list of sources
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with document knowledge.",
|
||||
knowledge=["docs/"], # List of file/folder paths
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("What does the documentation say about installation?")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Planning Example - Agent-Centric API
|
||||
|
||||
Demonstrates planning with consolidated params.
|
||||
Presets: reasoning, read_only, auto
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable planning with preset
|
||||
agent = Agent(
|
||||
instructions="You are a strategic planner.",
|
||||
planning="reasoning", # Presets: reasoning, read_only, auto
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Plan a 3-day trip to Tokyo.")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Reflection Example - Agent-Centric API
|
||||
|
||||
Demonstrates reflection (self-reflect) with consolidated params.
|
||||
Presets: minimal, standard, thorough
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable reflection with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant that reflects on your answers.",
|
||||
reflection="standard", # Presets: minimal, standard, thorough
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("Explain quantum computing in simple terms.")
|
||||
print(response)
|
||||
@@ -0,0 +1,18 @@
|
||||
"""
|
||||
Basic Web Search Example - Agent-Centric API
|
||||
|
||||
Demonstrates web search with consolidated params.
|
||||
Presets: duckduckgo, tavily, google, bing, serper, search_only, fetch_only
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable web search with preset
|
||||
agent = Agent(
|
||||
instructions="You are a research assistant with web access.",
|
||||
web="duckduckgo", # Presets: duckduckgo, tavily, google, bing, serper
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.start("What are the latest AI developments in 2024?")
|
||||
print(response)
|
||||
@@ -0,0 +1,63 @@
|
||||
"""
|
||||
Streaming Example with Profiling
|
||||
|
||||
Key Points:
|
||||
1. output="stream" preset enables streaming by default
|
||||
2. stream=True in start() is redundant when using output="stream" (but doesn't hurt)
|
||||
3. Profiler.enable() MUST be called before profiling works
|
||||
4. Use Profiler.streaming() context manager for TTFT metrics
|
||||
"""
|
||||
from praisonai.profiler import Profiler, profile, profile_imports
|
||||
|
||||
# IMPORTANT: Enable profiler BEFORE any profiling operations
|
||||
Profiler.enable()
|
||||
|
||||
# Profile imports
|
||||
with profile_imports():
|
||||
from praisonaiagents import Agent
|
||||
|
||||
@profile
|
||||
def main():
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
output="stream" # This already enables streaming
|
||||
)
|
||||
|
||||
print("\nStreaming response:")
|
||||
print("-" * 40)
|
||||
|
||||
# Use Profiler.streaming() to track TTFT (Time To First Token)
|
||||
with Profiler.streaming("llm_stream") as tracker:
|
||||
first_chunk = True
|
||||
for chunk in agent.start("Write a short paragraph about the history of computing"):
|
||||
if first_chunk:
|
||||
tracker.first_token() # Mark TTFT
|
||||
first_chunk = False
|
||||
tracker.chunk() # Count chunks
|
||||
print(chunk, end="", flush=True)
|
||||
|
||||
print("\n" + "-" * 40)
|
||||
|
||||
# Run with profiling blocks
|
||||
with Profiler.block("full_workflow"):
|
||||
with Profiler.block("setup"):
|
||||
pass
|
||||
|
||||
with Profiler.block("execution"):
|
||||
result = main()
|
||||
|
||||
with Profiler.block("cleanup"):
|
||||
pass
|
||||
|
||||
# Generate report
|
||||
Profiler.report()
|
||||
|
||||
# Show streaming-specific stats
|
||||
streaming_records = Profiler.get_streaming_records()
|
||||
if streaming_records:
|
||||
print("\nStreaming Metrics:")
|
||||
for record in streaming_records:
|
||||
print(f" {record.name}: TTFT={record.ttft_ms:.2f}ms, Total={record.total_ms:.2f}ms, Chunks={record.chunk_count}")
|
||||
|
||||
stats = Profiler.get_statistics()
|
||||
print(f"\nMedian execution time: {stats['p50']:.2f}ms")
|
||||
@@ -476,6 +476,62 @@ def _init_telemetry():
|
||||
_init_telemetry()
|
||||
|
||||
|
||||
def warmup(include_litellm: bool = False, include_openai: bool = True) -> dict:
|
||||
"""
|
||||
Pre-import heavy dependencies to reduce first-call latency.
|
||||
|
||||
NOTE: For default OpenAI usage (llm="gpt-4o-mini"), warmup is NOT needed.
|
||||
The default path uses the native OpenAI SDK which is fast (~100ms import).
|
||||
|
||||
Warmup is only beneficial when using LiteLLM backend, which is triggered by:
|
||||
- Using "/" in model name (e.g., llm="openai/gpt-4o-mini")
|
||||
- Passing a dict config (e.g., llm={"model": "gpt-4o-mini"})
|
||||
- Using base_url parameter
|
||||
|
||||
Args:
|
||||
include_litellm: Pre-import LiteLLM (~2-3s). Only needed for multi-provider support.
|
||||
include_openai: Pre-import OpenAI SDK (~100ms). Default path, usually fast.
|
||||
|
||||
Returns:
|
||||
dict: Timing information for each component warmed up
|
||||
|
||||
Example:
|
||||
# For LiteLLM multi-provider usage:
|
||||
from praisonaiagents import warmup
|
||||
warmup(include_litellm=True) # Pre-load LiteLLM
|
||||
|
||||
agent = Agent(llm="anthropic/claude-3-sonnet") # Now faster
|
||||
|
||||
# For default OpenAI usage, no warmup needed:
|
||||
agent = Agent(llm="gpt-4o-mini") # Already fast!
|
||||
"""
|
||||
import time
|
||||
timings = {}
|
||||
|
||||
if include_openai:
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
import openai
|
||||
timings['openai'] = (time.perf_counter() - start) * 1000
|
||||
except ImportError:
|
||||
timings['openai'] = -1 # Not available
|
||||
|
||||
if include_litellm:
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
import litellm
|
||||
# Also configure litellm to avoid first-call overhead
|
||||
litellm.telemetry = False
|
||||
litellm.set_verbose = False
|
||||
litellm.drop_params = True
|
||||
litellm.modify_params = True
|
||||
timings['litellm'] = (time.perf_counter() - start) * 1000
|
||||
except ImportError:
|
||||
timings['litellm'] = -1 # Not available
|
||||
|
||||
return timings
|
||||
|
||||
|
||||
__all__ = [
|
||||
# Core classes (lazy loaded)
|
||||
'Agent',
|
||||
@@ -646,4 +702,6 @@ __all__ = [
|
||||
# Parse Utilities
|
||||
'is_policy_string',
|
||||
'parse_policy_string',
|
||||
# Performance utilities
|
||||
'warmup',
|
||||
]
|
||||
@@ -254,10 +254,11 @@ class Agent:
|
||||
instructions: Optional[str] = None,
|
||||
# LLM configuration
|
||||
llm: Optional[Union[str, Any]] = None,
|
||||
function_calling_llm: Optional[Any] = None,
|
||||
llm_config: Optional[Dict[str, Any]] = None,
|
||||
base_url: Optional[str] = None,
|
||||
api_key: Optional[str] = None,
|
||||
model: Optional[Union[str, Any]] = None, # Alias for llm=
|
||||
function_calling_llm: Optional[Any] = None, # DEPRECATED: use llm= with LLMConfig
|
||||
llm_config: Optional[Dict[str, Any]] = None, # DEPRECATED: use llm= with LLMConfig
|
||||
base_url: Optional[str] = None, # Kept separate (connection/auth)
|
||||
api_key: Optional[str] = None, # Kept separate (connection/auth)
|
||||
# Tools
|
||||
tools: Optional[List[Any]] = None,
|
||||
allow_delegation: bool = False,
|
||||
@@ -446,14 +447,27 @@ class Agent:
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve OUTPUT param using unified resolver
|
||||
# Supports: None, str preset, list [preset, overrides], OutputConfig
|
||||
# DEFAULT: "actions" mode (minimal overhead, multi-agent safe)
|
||||
# Can be overridden by PRAISONAI_OUTPUT env var
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
from ..config.presets import DEFAULT_OUTPUT_MODE
|
||||
|
||||
# Check for env var override
|
||||
env_output = os.environ.get('PRAISONAI_OUTPUT', '').lower()
|
||||
if env_output and env_output in OUTPUT_PRESETS and output is None:
|
||||
output = env_output
|
||||
|
||||
# Use default output mode if not specified
|
||||
if output is None:
|
||||
output = DEFAULT_OUTPUT_MODE
|
||||
|
||||
_output_config = resolve(
|
||||
value=output,
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=OutputConfig(),
|
||||
default=OutputConfig(), # OutputConfig defaults to actions mode
|
||||
)
|
||||
if _output_config:
|
||||
verbose = _output_config.verbose
|
||||
@@ -462,8 +476,24 @@ class Agent:
|
||||
metrics = _output_config.metrics
|
||||
reasoning_steps = _output_config.reasoning_steps
|
||||
output_style = getattr(_output_config, 'style', None)
|
||||
actions_trace = getattr(_output_config, 'actions_trace', True) # Default True
|
||||
json_output = getattr(_output_config, 'json_output', False)
|
||||
else:
|
||||
verbose, markdown, stream, metrics, reasoning_steps = True, True, False, False, False
|
||||
# Fallback defaults match actions mode
|
||||
verbose, markdown, stream, metrics, reasoning_steps = False, False, False, False, False
|
||||
actions_trace = True
|
||||
json_output = False
|
||||
|
||||
# Enable actions output mode if configured
|
||||
# This registers callbacks to capture tool calls and final output
|
||||
if actions_trace:
|
||||
try:
|
||||
from ..output.actions import enable_actions_mode, is_actions_mode_enabled
|
||||
if not is_actions_mode_enabled():
|
||||
output_format = "jsonl" if json_output else "text"
|
||||
enable_actions_mode(redact=True, use_color=True, format=output_format)
|
||||
except ImportError:
|
||||
pass # Actions module not available
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve EXECUTION param using unified resolver
|
||||
@@ -783,13 +813,30 @@ class Agent:
|
||||
self._llm_config = llm_config or {}
|
||||
self._llm_configurable = self._llm_config.get('configurable', False)
|
||||
|
||||
# ============================================================
|
||||
# LLM CONSOLIDATION: Handle model= alias and deprecation warnings
|
||||
# Precedence: llm= > model= > default
|
||||
# ============================================================
|
||||
import warnings
|
||||
|
||||
# Handle model= alias for llm= (NO warnings - both are valid)
|
||||
if llm is None and model is not None:
|
||||
llm = model # model= is an alias for llm=
|
||||
|
||||
# Legacy params (llm_config, function_calling_llm) are accepted silently
|
||||
# for backward compatibility - NO deprecation warnings per policy
|
||||
|
||||
# Store rate limiter (optional, zero overhead when None)
|
||||
self._rate_limiter = rate_limiter
|
||||
|
||||
# Store OpenAI client parameters for lazy initialization
|
||||
# Store OpenAI client parameters for lazy initialization (kept separate)
|
||||
self._openai_api_key = api_key
|
||||
self._openai_base_url = base_url
|
||||
self.__openai_client = None
|
||||
|
||||
# Expose base_url and api_key as properties for tests
|
||||
self.base_url = base_url
|
||||
self.api_key = api_key
|
||||
|
||||
# If base_url is provided, always create a custom LLM instance
|
||||
if base_url:
|
||||
@@ -957,9 +1004,14 @@ Your Goal: {self.goal}
|
||||
self.tools.append(internet_search)
|
||||
logging.info("Model does not support native web search. Added DuckDuckGo fallback tool.")
|
||||
|
||||
# Log warning if web_fetch is enabled but model doesn't support it
|
||||
# Raise error if web_fetch is explicitly enabled but model doesn't support it
|
||||
# Web fetch is only supported by Anthropic/Claude models
|
||||
if web_fetch and not self._model_supports_web_fetch():
|
||||
logging.warning(f"Model '{self.llm}' does not support native web fetch. Web fetch will be ignored.")
|
||||
raise ValueError(
|
||||
f"web_fetch is only supported on Anthropic/Claude models. "
|
||||
f"Model '{self.llm}' does not support web fetch. "
|
||||
f"Either use a Claude model (e.g., 'anthropic/claude-sonnet-4') or disable fetch with web=WebConfig(fetch=False)."
|
||||
)
|
||||
|
||||
# Initialize guardrail settings
|
||||
self.guardrail = guardrail
|
||||
@@ -1042,6 +1094,9 @@ Your Goal: {self.goal}
|
||||
self._context_param = context # Store raw param for lazy init
|
||||
self._context_manager = None # Lazy initialized on first use
|
||||
self._context_manager_initialized = False
|
||||
|
||||
# Action trace mode - handled via display callbacks, not separate emitter
|
||||
self._actions_trace = actions_trace
|
||||
|
||||
@property
|
||||
def auto_memory(self):
|
||||
|
||||
@@ -17,7 +17,7 @@ Supported Expansion Strategies:
|
||||
Example:
|
||||
from praisonaiagents import PromptExpanderAgent, ExpandStrategy
|
||||
|
||||
agent = PromptExpanderAgent(verbose=True)
|
||||
agent = PromptExpanderAgent()
|
||||
|
||||
# Basic expansion
|
||||
result = agent.expand("write a movie script in 3 lines")
|
||||
@@ -29,7 +29,7 @@ Example:
|
||||
|
||||
# With tools for context gathering
|
||||
from praisonaiagents.tools import internet_search
|
||||
agent = PromptExpanderAgent(tools=[internet_search], verbose=True)
|
||||
agent = PromptExpanderAgent(tools=[internet_search])
|
||||
result = agent.expand("latest AI developments")
|
||||
"""
|
||||
|
||||
@@ -73,13 +73,12 @@ class PromptExpanderAgent:
|
||||
|
||||
Attributes:
|
||||
name: Name of the agent
|
||||
model: LLM model to use for expansion
|
||||
verbose: Whether to print detailed logs
|
||||
model: LLM model to use for expansion (alias for llm=)
|
||||
temperature: Temperature for LLM generation (higher = more creative)
|
||||
tools: Optional tools for context gathering
|
||||
|
||||
Example:
|
||||
agent = PromptExpanderAgent(model="gpt-4o-mini", verbose=True)
|
||||
agent = PromptExpanderAgent(model="gpt-4o-mini")
|
||||
result = agent.expand("write a poem", strategy=ExpandStrategy.CREATIVE)
|
||||
print(result.expanded_prompt)
|
||||
"""
|
||||
@@ -230,8 +229,7 @@ Expanded prompt:"""
|
||||
backstory="You are an expert at understanding user intent and transforming brief requests into comprehensive, detailed prompts.",
|
||||
tools=self.tools,
|
||||
llm=self.model,
|
||||
verbose=self.verbose,
|
||||
markdown=False
|
||||
output={"verbose": self.verbose, "markdown": False}
|
||||
)
|
||||
return self._agent
|
||||
|
||||
|
||||
@@ -15,7 +15,7 @@ Supported Rewriting Strategies:
|
||||
Example:
|
||||
from praisonaiagents import QueryRewriterAgent, RewriteStrategy
|
||||
|
||||
agent = QueryRewriterAgent(verbose=True)
|
||||
agent = QueryRewriterAgent()
|
||||
|
||||
# Basic rewriting
|
||||
result = agent.rewrite("AI trends")
|
||||
@@ -34,7 +34,7 @@ Example:
|
||||
|
||||
# With search tools for context-aware rewriting
|
||||
from praisonaiagents.tools import internet_search
|
||||
agent = QueryRewriterAgent(tools=[internet_search], verbose=True)
|
||||
agent = QueryRewriterAgent(tools=[internet_search])
|
||||
result = agent.rewrite("latest AI developments") # Searches first, then rewrites
|
||||
"""
|
||||
|
||||
@@ -96,13 +96,12 @@ class QueryRewriterAgent:
|
||||
|
||||
Attributes:
|
||||
name: Name of the agent
|
||||
model: LLM model to use for rewriting
|
||||
verbose: Whether to print detailed logs
|
||||
model: LLM model to use for rewriting (alias for llm=)
|
||||
max_queries: Maximum number of queries to generate for multi-query strategy
|
||||
abbreviations: Dictionary of common abbreviations to expand
|
||||
|
||||
Example:
|
||||
agent = QueryRewriterAgent(model="gpt-4o-mini", verbose=True)
|
||||
agent = QueryRewriterAgent(model="gpt-4o-mini")
|
||||
result = agent.rewrite("ML best practices", strategy=RewriteStrategy.MULTI_QUERY)
|
||||
for query in result.rewritten_queries:
|
||||
print(query)
|
||||
@@ -288,8 +287,7 @@ Improved version:"""
|
||||
backstory="You are an expert at understanding user intent and transforming queries for optimal information retrieval.",
|
||||
tools=self.tools,
|
||||
llm=self.model,
|
||||
verbose=self.verbose,
|
||||
markdown=False
|
||||
output={"verbose": self.verbose, "markdown": False}
|
||||
)
|
||||
return self._agent
|
||||
|
||||
|
||||
@@ -148,6 +148,7 @@ class Agents:
|
||||
guardrails: Optional[Any] = None, # Union[bool, Callable, GuardrailConfig] - validation
|
||||
web: Optional[Any] = None, # Union[bool, WebConfig] - web search/fetch
|
||||
reflection: Optional[Any] = None, # Union[bool, ReflectionConfig] - self-reflection
|
||||
caching: Optional[Any] = None, # Union[bool, CachingConfig] - caching
|
||||
):
|
||||
"""
|
||||
Initialize PraisonAIAgents with consolidated feature parameters.
|
||||
@@ -177,6 +178,7 @@ class Agents:
|
||||
self._guardrails = guardrails
|
||||
self._web = web
|
||||
self._reflection = reflection
|
||||
self._caching = caching
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Extract values from consolidated params using UNIFIED CANONICAL resolver
|
||||
# Precedence: Instance > Config > Dict > Array > String > Bool > Default
|
||||
|
||||
@@ -74,6 +74,17 @@ class AutoAgents(Agents):
|
||||
api_key: Optional[str] = None,
|
||||
max_agents: int = 3, # Maximum number of agents
|
||||
autonomy: Optional[Any] = None, # Union[bool, dict, AutonomyConfig] - Enable autonomy for all agents
|
||||
# ============================================================
|
||||
# CONSOLIDATED PARAMS (new SDK contract - take precedence)
|
||||
# ============================================================
|
||||
output: Optional[Any] = None, # Union[str, OutputConfig] - overrides verbose/markdown
|
||||
reflection: Optional[Any] = None, # Union[bool, ReflectionConfig] - overrides self_reflect/max_reflect/min_reflect/reflect_llm
|
||||
caching: Optional[Any] = None, # Union[bool, CachingConfig] - overrides cache
|
||||
knowledge: Optional[Any] = None, # Union[bool, List[str], KnowledgeConfig] - overrides knowledge_sources/embedder_config
|
||||
execution: Optional[Any] = None, # Union[str, ExecutionConfig] - overrides max_iter
|
||||
guardrails: Optional[Any] = None, # Union[bool, Callable, GuardrailConfig]
|
||||
web: Optional[Any] = None, # Union[bool, WebConfig]
|
||||
hooks: Optional[Any] = None, # HooksConfig
|
||||
):
|
||||
"""Initialize AutoAgents with configuration for automatic agent and task creation."""
|
||||
if max_agents < 1:
|
||||
@@ -112,6 +123,16 @@ class AutoAgents(Agents):
|
||||
self.api_key = api_key
|
||||
self.autonomy = autonomy # Store autonomy config for agents
|
||||
|
||||
# Store consolidated params (new SDK contract - take precedence over legacy)
|
||||
self._output = output
|
||||
self._reflection = reflection
|
||||
self._caching = caching
|
||||
self._knowledge = knowledge
|
||||
self._execution = execution
|
||||
self._guardrails = guardrails
|
||||
self._web = web
|
||||
self._hooks = hooks
|
||||
|
||||
# Display initial instruction
|
||||
if self.verbose:
|
||||
display_instruction(f"🎯 Main Task: {self.instructions}")
|
||||
@@ -129,14 +150,21 @@ class AutoAgents(Agents):
|
||||
self._display_agents_and_tasks(agents, tasks)
|
||||
|
||||
# Initialize parent class with generated agents and tasks
|
||||
# Use consolidated output= instead of legacy verbose=
|
||||
super().__init__(
|
||||
agents=agents,
|
||||
tasks=tasks,
|
||||
verbose=verbose,
|
||||
completion_checker=completion_checker,
|
||||
max_retries=max_retries,
|
||||
process=process,
|
||||
manager_llm=manager_llm or self.llm
|
||||
manager_llm=manager_llm or self.llm,
|
||||
output=self._output, # Consolidated output param
|
||||
execution=self._execution,
|
||||
hooks=self._hooks,
|
||||
memory=self.memory,
|
||||
reflection=self._reflection,
|
||||
caching=self._caching,
|
||||
guardrails=self._guardrails,
|
||||
web=self._web,
|
||||
autonomy=self.autonomy,
|
||||
)
|
||||
|
||||
def _display_agents_and_tasks(self, agents: List[Agent], tasks: List[Task]):
|
||||
@@ -431,38 +459,33 @@ DO NOT use strings for tasks. Each task MUST be a complete object with all four
|
||||
agent_tools = self._assign_tools_to_agent(agent_config)
|
||||
|
||||
# Create the agent with all parameters
|
||||
# Consolidated params take precedence over legacy params
|
||||
# Use consolidated knowledge if provided, else fall back to legacy knowledge_sources
|
||||
effective_knowledge = self._knowledge if self._knowledge is not None else self.knowledge_sources
|
||||
|
||||
agent = Agent(
|
||||
name=agent_config.name,
|
||||
role=agent_config.role,
|
||||
goal=agent_config.goal,
|
||||
backstory=agent_config.backstory,
|
||||
tools=agent_tools, # Use assigned tools
|
||||
verbose=self.verbose >= 1,
|
||||
allow_code_execution=self.allow_code_execution,
|
||||
memory=self.memory,
|
||||
markdown=self.markdown,
|
||||
self_reflect=self.self_reflect,
|
||||
max_reflect=self.max_reflect,
|
||||
min_reflect=self.min_reflect,
|
||||
llm=self.llm,
|
||||
function_calling_llm=self.function_calling_llm,
|
||||
llm=self.llm, # Consolidated LLM param
|
||||
code_execution_mode=self.code_execution_mode,
|
||||
embedder_config=self.embedder_config,
|
||||
knowledge=self.knowledge_sources,
|
||||
use_system_prompt=self.use_system_prompt,
|
||||
cache=self.cache,
|
||||
allow_delegation=self.allow_delegation,
|
||||
step_callback=self.step_callback,
|
||||
system_template=self.system_template,
|
||||
prompt_template=self.prompt_template,
|
||||
response_template=self.response_template,
|
||||
max_rpm=self.max_rpm,
|
||||
max_execution_time=self.max_execution_time,
|
||||
max_iter=self.max_iter,
|
||||
reflect_llm=self.reflect_llm,
|
||||
base_url=self.base_url,
|
||||
api_key=self.api_key,
|
||||
autonomy=self.autonomy # Pass autonomy config to agents
|
||||
# Consolidated params (new SDK contract)
|
||||
output=self._output, # Overrides verbose/markdown
|
||||
reflection=self._reflection, # Overrides self_reflect/max_reflect/min_reflect/reflect_llm
|
||||
caching=self._caching, # Overrides cache
|
||||
knowledge=effective_knowledge, # Overrides knowledge_sources/embedder_config
|
||||
execution=self._execution, # Overrides max_iter
|
||||
guardrails=self._guardrails,
|
||||
web=self._web,
|
||||
hooks=self._hooks,
|
||||
autonomy=self.autonomy,
|
||||
)
|
||||
agents.append(agent)
|
||||
|
||||
|
||||
@@ -376,7 +376,7 @@ class SubagentDelegator:
|
||||
return result
|
||||
|
||||
async def _create_agent(self, profile: AgentProfile, task: DelegationTask) -> Any:
|
||||
"""Create an agent from profile."""
|
||||
"""Create an agent from profile using consolidated params."""
|
||||
if self.agent_factory:
|
||||
return self.agent_factory(profile.name)
|
||||
|
||||
@@ -387,14 +387,17 @@ class SubagentDelegator:
|
||||
# Filter tools based on profile
|
||||
tools = self._get_tools_for_profile(profile)
|
||||
|
||||
# Use consolidated params (protocol-compliant)
|
||||
# output='silent' replaces verbose=False
|
||||
# execution={max_iter: N} replaces max_iter=N
|
||||
agent = Agent(
|
||||
name=profile.name,
|
||||
role=profile.name.title(),
|
||||
goal=task.objective,
|
||||
backstory=profile.system_prompt,
|
||||
tools=tools,
|
||||
verbose=False,
|
||||
max_iter=min(task.max_steps, profile.max_steps),
|
||||
output='silent',
|
||||
execution={'max_iter': min(task.max_steps, profile.max_steps)},
|
||||
)
|
||||
|
||||
return agent
|
||||
|
||||
@@ -391,10 +391,21 @@ class OutputConfig:
|
||||
|
||||
Consolidates: verbose, markdown, stream, metrics, reasoning_steps, output_style
|
||||
|
||||
DEFAULT: output="actions" (minimal overhead, multi-agent safe)
|
||||
|
||||
Usage:
|
||||
# Simple preset
|
||||
# Default is actions mode (tool calls + final output only)
|
||||
Agent(instructions="...") # Uses output="actions"
|
||||
|
||||
# Verbose mode with Rich streaming
|
||||
Agent(output="verbose")
|
||||
|
||||
# Plain mode (final output only, no action trace)
|
||||
Agent(output="plain")
|
||||
|
||||
# JSON mode for piping
|
||||
Agent(output="json")
|
||||
|
||||
# With config
|
||||
Agent(output=OutputConfig(
|
||||
verbose=True,
|
||||
@@ -404,11 +415,11 @@ class OutputConfig:
|
||||
reasoning_steps=True,
|
||||
))
|
||||
"""
|
||||
# Verbosity
|
||||
verbose: bool = True
|
||||
# Verbosity - False by default for actions mode
|
||||
verbose: bool = False
|
||||
|
||||
# Formatting
|
||||
markdown: bool = True
|
||||
# Formatting - False by default for actions mode
|
||||
markdown: bool = False
|
||||
|
||||
# Streaming
|
||||
stream: bool = False
|
||||
@@ -422,6 +433,14 @@ class OutputConfig:
|
||||
# Output style (custom styling)
|
||||
style: Optional[Any] = None
|
||||
|
||||
# Actions trace mode - shows tool calls, agent lifecycle, final output
|
||||
# When True, suppresses verbose output and shows action-level trace instead
|
||||
# DEFAULT: True for minimal overhead
|
||||
actions_trace: bool = True
|
||||
|
||||
# JSON output mode - emit JSONL events for piping
|
||||
json_output: bool = False
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary."""
|
||||
return {
|
||||
@@ -430,6 +449,8 @@ class OutputConfig:
|
||||
"stream": self.stream,
|
||||
"metrics": self.metrics,
|
||||
"reasoning_steps": self.reasoning_steps,
|
||||
"actions_trace": self.actions_trace,
|
||||
"json_output": self.json_output,
|
||||
}
|
||||
|
||||
|
||||
|
||||
@@ -41,6 +41,27 @@ MEMORY_URL_SCHEMES: Dict[str, str] = {
|
||||
# =============================================================================
|
||||
|
||||
OUTPUT_PRESETS: Dict[str, Dict[str, Any]] = {
|
||||
# Actions preset - DEFAULT for SDK
|
||||
# Shows action trace (tool calls, agent lifecycle) + final output
|
||||
# No verbose panels, no streaming tokens, just action-level trace
|
||||
# Minimal overhead, multi-agent safe
|
||||
"actions": {
|
||||
"verbose": False,
|
||||
"markdown": False,
|
||||
"stream": False,
|
||||
"metrics": False,
|
||||
"reasoning_steps": False,
|
||||
"actions_trace": True, # Special flag for action trace mode
|
||||
},
|
||||
# Plain preset - final output only, no action trace
|
||||
"plain": {
|
||||
"verbose": False,
|
||||
"markdown": False,
|
||||
"stream": False,
|
||||
"metrics": False,
|
||||
"reasoning_steps": False,
|
||||
"actions_trace": False,
|
||||
},
|
||||
"minimal": {
|
||||
"verbose": False,
|
||||
"markdown": False,
|
||||
@@ -76,8 +97,29 @@ OUTPUT_PRESETS: Dict[str, Dict[str, Any]] = {
|
||||
"metrics": False,
|
||||
"reasoning_steps": False,
|
||||
},
|
||||
# Streaming preset - enables streaming by default
|
||||
"stream": {
|
||||
"verbose": True,
|
||||
"markdown": True,
|
||||
"stream": True,
|
||||
"metrics": False,
|
||||
"reasoning_steps": False,
|
||||
},
|
||||
# JSON preset - JSONL output for piping
|
||||
"json": {
|
||||
"verbose": False,
|
||||
"markdown": False,
|
||||
"stream": False,
|
||||
"metrics": False,
|
||||
"reasoning_steps": False,
|
||||
"actions_trace": True,
|
||||
"json_output": True, # Output as JSONL
|
||||
},
|
||||
}
|
||||
|
||||
# Default output mode - can be overridden by PRAISONAI_OUTPUT env var
|
||||
DEFAULT_OUTPUT_MODE = "actions"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Execution Presets
|
||||
|
||||
@@ -1430,6 +1430,8 @@ Now provide your final answer using this result."""
|
||||
task_id: Optional[str] = None,
|
||||
execute_tool_fn: Optional[Callable] = None,
|
||||
stream: bool = True,
|
||||
stream_callback: Optional[Callable] = None,
|
||||
emit_events: bool = False,
|
||||
**kwargs
|
||||
) -> str:
|
||||
"""Enhanced get_response with all OpenAI-like features"""
|
||||
@@ -1489,6 +1491,19 @@ Now provide your final answer using this result."""
|
||||
# Disable litellm debug messages
|
||||
litellm.set_verbose = False
|
||||
|
||||
# Setup StreamEvent emission if enabled
|
||||
_emit = emit_events and stream_callback is not None
|
||||
if _emit:
|
||||
from ..streaming.events import StreamEvent, StreamEventType
|
||||
_first_token_emitted = False
|
||||
_last_content_time = None
|
||||
_request_start_perf = time.perf_counter()
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.REQUEST_START,
|
||||
timestamp=_request_start_perf,
|
||||
metadata={"model": self.model, "provider": "litellm"}
|
||||
))
|
||||
|
||||
# Format tools if provided
|
||||
formatted_tools = self._format_tools_for_litellm(tools)
|
||||
|
||||
|
||||
@@ -582,6 +582,8 @@ class OpenAIClient:
|
||||
console: Optional[Console] = None,
|
||||
display_fn: Optional[Callable] = None,
|
||||
reasoning_steps: bool = False,
|
||||
stream_callback: Optional[Callable] = None,
|
||||
emit_events: bool = False,
|
||||
**kwargs
|
||||
) -> Optional[ChatCompletion]:
|
||||
"""
|
||||
@@ -596,11 +598,18 @@ class OpenAIClient:
|
||||
console: Console for output
|
||||
display_fn: Display function for live updates
|
||||
reasoning_steps: Whether to show reasoning steps
|
||||
stream_callback: Optional callback for StreamEvent emission
|
||||
emit_events: Whether to emit StreamEvents (requires stream_callback)
|
||||
**kwargs: Additional parameters for the API
|
||||
|
||||
Returns:
|
||||
ChatCompletion object or None if error
|
||||
"""
|
||||
# Lazy import StreamEvent types only when needed
|
||||
_emit = emit_events and stream_callback is not None
|
||||
if _emit:
|
||||
from ..streaming.events import StreamEvent, StreamEventType
|
||||
|
||||
try:
|
||||
# Default start time and console if not provided
|
||||
if start_time is None:
|
||||
@@ -608,6 +617,15 @@ class OpenAIClient:
|
||||
if console is None:
|
||||
console = self.console
|
||||
|
||||
# Emit REQUEST_START event
|
||||
request_start_perf = time.perf_counter()
|
||||
if _emit:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.REQUEST_START,
|
||||
timestamp=request_start_perf,
|
||||
metadata={"model": model, "message_count": len(messages)}
|
||||
))
|
||||
|
||||
# Create the response stream
|
||||
response_stream = self.sync_client.chat.completions.create(
|
||||
model=model,
|
||||
@@ -615,29 +633,81 @@ class OpenAIClient:
|
||||
temperature=temperature,
|
||||
tools=tools if tools else None,
|
||||
stream=True,
|
||||
stream_options={"include_usage": True} if _emit else None,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
# Emit HEADERS_RECEIVED event (stream object created means headers received)
|
||||
if _emit:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.HEADERS_RECEIVED,
|
||||
timestamp=time.perf_counter()
|
||||
))
|
||||
|
||||
full_response_text = ""
|
||||
reasoning_content = ""
|
||||
chunks = []
|
||||
first_token_emitted = False
|
||||
last_content_time = None
|
||||
ttft_logged = False
|
||||
|
||||
# If display function provided, use Live display
|
||||
if display_fn:
|
||||
with Live(
|
||||
display_fn("", start_time),
|
||||
console=console,
|
||||
refresh_per_second=4,
|
||||
refresh_per_second=10, # Increased for more responsive streaming
|
||||
transient=True,
|
||||
vertical_overflow="ellipsis",
|
||||
auto_refresh=True
|
||||
) as live:
|
||||
for chunk in response_stream:
|
||||
chunks.append(chunk)
|
||||
if chunk.choices[0].delta.content:
|
||||
full_response_text += chunk.choices[0].delta.content
|
||||
|
||||
# Check for content delta
|
||||
if chunk.choices and chunk.choices[0].delta.content:
|
||||
content = chunk.choices[0].delta.content
|
||||
full_response_text += content
|
||||
last_content_time = time.perf_counter()
|
||||
|
||||
# Log TTFT on first token
|
||||
if not ttft_logged:
|
||||
ttft_ms = (last_content_time - request_start_perf) * 1000
|
||||
logging.debug(f"TTFT (Time To First Token): {ttft_ms:.0f}ms")
|
||||
ttft_logged = True
|
||||
|
||||
# Emit FIRST_TOKEN on first content
|
||||
if _emit and not first_token_emitted:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.FIRST_TOKEN,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
first_token_emitted = True
|
||||
elif _emit:
|
||||
# Emit DELTA_TEXT for subsequent tokens
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.DELTA_TEXT,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
|
||||
live.update(display_fn(full_response_text, start_time))
|
||||
|
||||
# Handle tool calls streaming
|
||||
if _emit and chunk.choices and hasattr(chunk.choices[0].delta, 'tool_calls') and chunk.choices[0].delta.tool_calls:
|
||||
for tc in chunk.choices[0].delta.tool_calls:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.DELTA_TOOL_CALL,
|
||||
timestamp=time.perf_counter(),
|
||||
tool_call={
|
||||
"index": tc.index,
|
||||
"id": getattr(tc, 'id', None),
|
||||
"name": getattr(tc.function, 'name', None) if tc.function else None,
|
||||
"arguments": getattr(tc.function, 'arguments', None) if tc.function else None
|
||||
}
|
||||
))
|
||||
|
||||
# Update live display with reasoning content if enabled
|
||||
if reasoning_steps and hasattr(chunk.choices[0].delta, "reasoning_content"):
|
||||
rc = chunk.choices[0].delta.reasoning_content
|
||||
@@ -648,9 +718,60 @@ class OpenAIClient:
|
||||
# Clear the last generating display with a blank line
|
||||
console.print()
|
||||
else:
|
||||
# Just collect chunks without display
|
||||
# Just collect chunks without display, but still emit events
|
||||
for chunk in response_stream:
|
||||
chunks.append(chunk)
|
||||
|
||||
if chunk.choices and chunk.choices[0].delta.content:
|
||||
content = chunk.choices[0].delta.content
|
||||
last_content_time = time.perf_counter()
|
||||
|
||||
# Log TTFT on first token
|
||||
if not ttft_logged:
|
||||
ttft_ms = (last_content_time - request_start_perf) * 1000
|
||||
logging.debug(f"TTFT (Time To First Token): {ttft_ms:.0f}ms")
|
||||
ttft_logged = True
|
||||
|
||||
if _emit and not first_token_emitted:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.FIRST_TOKEN,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
first_token_emitted = True
|
||||
else:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.DELTA_TEXT,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
|
||||
# Handle tool calls streaming
|
||||
if _emit and chunk.choices and hasattr(chunk.choices[0].delta, 'tool_calls') and chunk.choices[0].delta.tool_calls:
|
||||
for tc in chunk.choices[0].delta.tool_calls:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.DELTA_TOOL_CALL,
|
||||
timestamp=time.perf_counter(),
|
||||
tool_call={
|
||||
"index": tc.index,
|
||||
"id": getattr(tc, 'id', None),
|
||||
"name": getattr(tc.function, 'name', None) if tc.function else None,
|
||||
"arguments": getattr(tc.function, 'arguments', None) if tc.function else None
|
||||
}
|
||||
))
|
||||
|
||||
# Emit LAST_TOKEN and STREAM_END events
|
||||
if _emit:
|
||||
if last_content_time:
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.LAST_TOKEN,
|
||||
timestamp=last_content_time
|
||||
))
|
||||
stream_callback(StreamEvent(
|
||||
type=StreamEventType.STREAM_END,
|
||||
timestamp=time.perf_counter(),
|
||||
metadata={"chunk_count": len(chunks)}
|
||||
))
|
||||
|
||||
final_response = process_stream_chunks(chunks)
|
||||
return final_response
|
||||
@@ -669,6 +790,8 @@ class OpenAIClient:
|
||||
console: Optional[Console] = None,
|
||||
display_fn: Optional[Callable] = None,
|
||||
reasoning_steps: bool = False,
|
||||
stream_callback: Optional[Callable] = None,
|
||||
emit_events: bool = False,
|
||||
**kwargs
|
||||
) -> Optional[ChatCompletion]:
|
||||
"""
|
||||
@@ -683,11 +806,18 @@ class OpenAIClient:
|
||||
console: Console for output
|
||||
display_fn: Display function for live updates
|
||||
reasoning_steps: Whether to show reasoning steps
|
||||
stream_callback: Optional callback for StreamEvent emission (can be sync or async)
|
||||
emit_events: Whether to emit StreamEvents (requires stream_callback)
|
||||
**kwargs: Additional parameters for the API
|
||||
|
||||
Returns:
|
||||
ChatCompletion object or None if error
|
||||
"""
|
||||
# Lazy import StreamEvent types only when needed
|
||||
_emit = emit_events and stream_callback is not None
|
||||
if _emit:
|
||||
from ..streaming.events import StreamEvent, StreamEventType
|
||||
|
||||
try:
|
||||
# Default start time and console if not provided
|
||||
if start_time is None:
|
||||
@@ -695,6 +825,19 @@ class OpenAIClient:
|
||||
if console is None:
|
||||
console = self.console
|
||||
|
||||
# Emit REQUEST_START event
|
||||
request_start_perf = time.perf_counter()
|
||||
if _emit:
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.REQUEST_START,
|
||||
timestamp=request_start_perf,
|
||||
metadata={"model": model, "message_count": len(messages)}
|
||||
)
|
||||
if asyncio.iscoroutinefunction(stream_callback):
|
||||
await stream_callback(event)
|
||||
else:
|
||||
stream_callback(event)
|
||||
|
||||
# Create the response stream
|
||||
response_stream = await self.async_client.chat.completions.create(
|
||||
model=model,
|
||||
@@ -702,29 +845,81 @@ class OpenAIClient:
|
||||
temperature=temperature,
|
||||
tools=tools if tools else None,
|
||||
stream=True,
|
||||
stream_options={"include_usage": True} if _emit else None,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
# Emit HEADERS_RECEIVED event
|
||||
if _emit:
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.HEADERS_RECEIVED,
|
||||
timestamp=time.perf_counter()
|
||||
)
|
||||
if asyncio.iscoroutinefunction(stream_callback):
|
||||
await stream_callback(event)
|
||||
else:
|
||||
stream_callback(event)
|
||||
|
||||
full_response_text = ""
|
||||
reasoning_content = ""
|
||||
chunks = []
|
||||
first_token_emitted = False
|
||||
last_content_time = None
|
||||
|
||||
async def emit_event(event: 'StreamEvent'):
|
||||
if asyncio.iscoroutinefunction(stream_callback):
|
||||
await stream_callback(event)
|
||||
else:
|
||||
stream_callback(event)
|
||||
|
||||
# If display function provided, use Live display
|
||||
if display_fn:
|
||||
with Live(
|
||||
display_fn("", start_time),
|
||||
console=console,
|
||||
refresh_per_second=4,
|
||||
refresh_per_second=10,
|
||||
transient=True,
|
||||
vertical_overflow="ellipsis",
|
||||
auto_refresh=True
|
||||
) as live:
|
||||
async for chunk in response_stream:
|
||||
chunks.append(chunk)
|
||||
if chunk.choices[0].delta.content:
|
||||
full_response_text += chunk.choices[0].delta.content
|
||||
|
||||
if chunk.choices and chunk.choices[0].delta.content:
|
||||
content = chunk.choices[0].delta.content
|
||||
full_response_text += content
|
||||
last_content_time = time.perf_counter()
|
||||
|
||||
if _emit and not first_token_emitted:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.FIRST_TOKEN,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
first_token_emitted = True
|
||||
elif _emit:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.DELTA_TEXT,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
|
||||
live.update(display_fn(full_response_text, start_time))
|
||||
|
||||
# Handle tool calls streaming
|
||||
if _emit and chunk.choices and hasattr(chunk.choices[0].delta, 'tool_calls') and chunk.choices[0].delta.tool_calls:
|
||||
for tc in chunk.choices[0].delta.tool_calls:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.DELTA_TOOL_CALL,
|
||||
timestamp=time.perf_counter(),
|
||||
tool_call={
|
||||
"index": tc.index,
|
||||
"id": getattr(tc, 'id', None),
|
||||
"name": getattr(tc.function, 'name', None) if tc.function else None,
|
||||
"arguments": getattr(tc.function, 'arguments', None) if tc.function else None
|
||||
}
|
||||
))
|
||||
|
||||
# Update live display with reasoning content if enabled
|
||||
if reasoning_steps and hasattr(chunk.choices[0].delta, "reasoning_content"):
|
||||
rc = chunk.choices[0].delta.reasoning_content
|
||||
@@ -738,6 +933,50 @@ class OpenAIClient:
|
||||
# Just collect chunks without display
|
||||
async for chunk in response_stream:
|
||||
chunks.append(chunk)
|
||||
|
||||
if _emit and chunk.choices and chunk.choices[0].delta.content:
|
||||
content = chunk.choices[0].delta.content
|
||||
last_content_time = time.perf_counter()
|
||||
|
||||
if not first_token_emitted:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.FIRST_TOKEN,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
first_token_emitted = True
|
||||
else:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.DELTA_TEXT,
|
||||
timestamp=last_content_time,
|
||||
content=content
|
||||
))
|
||||
|
||||
if _emit and chunk.choices and hasattr(chunk.choices[0].delta, 'tool_calls') and chunk.choices[0].delta.tool_calls:
|
||||
for tc in chunk.choices[0].delta.tool_calls:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.DELTA_TOOL_CALL,
|
||||
timestamp=time.perf_counter(),
|
||||
tool_call={
|
||||
"index": tc.index,
|
||||
"id": getattr(tc, 'id', None),
|
||||
"name": getattr(tc.function, 'name', None) if tc.function else None,
|
||||
"arguments": getattr(tc.function, 'arguments', None) if tc.function else None
|
||||
}
|
||||
))
|
||||
|
||||
# Emit LAST_TOKEN and STREAM_END events
|
||||
if _emit:
|
||||
if last_content_time:
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.LAST_TOKEN,
|
||||
timestamp=last_content_time
|
||||
))
|
||||
await emit_event(StreamEvent(
|
||||
type=StreamEventType.STREAM_END,
|
||||
timestamp=time.perf_counter(),
|
||||
metadata={"chunk_count": len(chunks)}
|
||||
))
|
||||
|
||||
final_response = process_stream_chunks(chunks)
|
||||
return final_response
|
||||
@@ -904,7 +1143,9 @@ class OpenAIClient:
|
||||
if display_fn and console:
|
||||
# When verbose (display_fn provided), use streaming for better UX
|
||||
try:
|
||||
with Live(display_fn("", start_time), console=console, refresh_per_second=4, transient=True) as live:
|
||||
request_start_perf = time.perf_counter()
|
||||
ttft_logged = False
|
||||
with Live(display_fn("", start_time), console=console, refresh_per_second=10, transient=True) as live:
|
||||
# Use streaming when display_fn is provided for progressive display
|
||||
response_stream = self.create_completion(
|
||||
messages=messages,
|
||||
@@ -922,6 +1163,11 @@ class OpenAIClient:
|
||||
for chunk in response_stream:
|
||||
chunks.append(chunk)
|
||||
if chunk.choices[0].delta.content:
|
||||
# Log TTFT on first token
|
||||
if not ttft_logged:
|
||||
ttft_ms = (time.perf_counter() - request_start_perf) * 1000
|
||||
logging.debug(f"TTFT (Time To First Token): {ttft_ms:.0f}ms")
|
||||
ttft_logged = True
|
||||
full_response_text += chunk.choices[0].delta.content
|
||||
live.update(display_fn(full_response_text, start_time))
|
||||
|
||||
|
||||
@@ -722,9 +722,8 @@ Workflow Finished: {self.workflow_finished} # ADDED: Workflow Finished Status
|
||||
goal="Manage the entire flow of tasks and delegate them to the right agent",
|
||||
backstory="Expert project manager to coordinate tasks among agents",
|
||||
llm=self.manager_llm,
|
||||
verbose=self.verbose,
|
||||
markdown=True,
|
||||
self_reflect=False
|
||||
output={"verbose": self.verbose, "markdown": True},
|
||||
reflection=False
|
||||
)
|
||||
|
||||
class ManagerInstructions(BaseModel):
|
||||
@@ -1384,9 +1383,8 @@ Workflow Finished: {self.workflow_finished} # ADDED: Workflow Finished Status
|
||||
goal="Manage the entire flow of tasks and delegate them to the right agent",
|
||||
backstory="Expert project manager to coordinate tasks among agents",
|
||||
llm=self.manager_llm,
|
||||
verbose=self.verbose,
|
||||
markdown=True,
|
||||
self_reflect=False
|
||||
output={"verbose": self.verbose, "markdown": True},
|
||||
reflection=False
|
||||
)
|
||||
|
||||
class ManagerInstructions(BaseModel):
|
||||
|
||||
@@ -0,0 +1,479 @@
|
||||
"""
|
||||
PraisonAI Agents Core Profiling Module
|
||||
|
||||
Lightweight, protocol-based profiling for the core SDK.
|
||||
Zero overhead when disabled. Opt-in only.
|
||||
|
||||
Features:
|
||||
- Pre-LLM latency breakdown
|
||||
- LLM client initialization timing
|
||||
- Tool resolution timing
|
||||
- Message serialization timing
|
||||
- Streaming TTFT tracking
|
||||
- Import timing
|
||||
- Async-safe
|
||||
|
||||
Usage:
|
||||
from praisonaiagents.profiling import Profiler, profile_block
|
||||
|
||||
# Enable profiling
|
||||
Profiler.enable()
|
||||
|
||||
# Profile a block
|
||||
with profile_block("my_operation"):
|
||||
do_something()
|
||||
|
||||
# Get report
|
||||
Profiler.report()
|
||||
"""
|
||||
|
||||
import time
|
||||
import os
|
||||
import threading
|
||||
from dataclasses import dataclass, field, asdict
|
||||
from typing import Dict, List, Optional, Any, Callable
|
||||
from contextlib import contextmanager
|
||||
import functools
|
||||
import json
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Data Classes
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class TimingRecord:
|
||||
"""Record of a single timing measurement."""
|
||||
name: str
|
||||
duration_ms: float
|
||||
category: str = "block"
|
||||
parent: str = ""
|
||||
timestamp: float = field(default_factory=time.time)
|
||||
metadata: Dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
class StreamingRecord:
|
||||
"""Record of streaming operation."""
|
||||
name: str
|
||||
ttft_ms: float # Time to first token
|
||||
total_ms: float
|
||||
chunk_count: int = 0
|
||||
timestamp: float = field(default_factory=time.time)
|
||||
|
||||
|
||||
@dataclass
|
||||
class PreLLMBreakdown:
|
||||
"""Breakdown of pre-LLM latency phases."""
|
||||
agent_init_ms: float = 0.0
|
||||
llm_client_init_ms: float = 0.0
|
||||
tool_resolution_ms: float = 0.0
|
||||
message_build_ms: float = 0.0
|
||||
context_management_ms: float = 0.0
|
||||
knowledge_retrieval_ms: float = 0.0
|
||||
guardrail_check_ms: float = 0.0
|
||||
total_pre_llm_ms: float = 0.0
|
||||
|
||||
def to_dict(self) -> Dict[str, float]:
|
||||
return asdict(self)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Streaming Tracker
|
||||
# ============================================================================
|
||||
|
||||
class StreamingTracker:
|
||||
"""Track streaming operations for TTFT metrics."""
|
||||
|
||||
def __init__(self, name: str):
|
||||
self.name = name
|
||||
self._start_time: Optional[float] = None
|
||||
self._first_token_time: Optional[float] = None
|
||||
self._end_time: Optional[float] = None
|
||||
self._chunk_count: int = 0
|
||||
|
||||
def start(self) -> None:
|
||||
self._start_time = time.perf_counter()
|
||||
|
||||
def first_token(self) -> None:
|
||||
if self._first_token_time is None:
|
||||
self._first_token_time = time.perf_counter()
|
||||
|
||||
def chunk(self) -> None:
|
||||
self._chunk_count += 1
|
||||
|
||||
def end(self) -> None:
|
||||
self._end_time = time.perf_counter()
|
||||
if self._start_time is not None:
|
||||
ttft_ms = 0.0
|
||||
if self._first_token_time is not None:
|
||||
ttft_ms = (self._first_token_time - self._start_time) * 1000
|
||||
total_ms = (self._end_time - self._start_time) * 1000
|
||||
Profiler.record_streaming(
|
||||
name=self.name,
|
||||
ttft_ms=ttft_ms,
|
||||
total_ms=total_ms,
|
||||
chunk_count=self._chunk_count
|
||||
)
|
||||
|
||||
@property
|
||||
def ttft_ms(self) -> float:
|
||||
if self._start_time and self._first_token_time:
|
||||
return (self._first_token_time - self._start_time) * 1000
|
||||
return 0.0
|
||||
|
||||
@property
|
||||
def elapsed_ms(self) -> float:
|
||||
if self._start_time:
|
||||
end = self._end_time or time.perf_counter()
|
||||
return (end - self._start_time) * 1000
|
||||
return 0.0
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Core Profiler
|
||||
# ============================================================================
|
||||
|
||||
class Profiler:
|
||||
"""
|
||||
Lightweight profiler for PraisonAI Agents core SDK.
|
||||
|
||||
Thread-safe singleton with zero overhead when disabled.
|
||||
"""
|
||||
|
||||
_lock = threading.Lock()
|
||||
_enabled: bool = False
|
||||
_timings: List[TimingRecord] = []
|
||||
_streaming: List[StreamingRecord] = []
|
||||
_pre_llm_breakdown: Optional[PreLLMBreakdown] = None
|
||||
_current_phases: Dict[str, float] = {} # Track in-progress phases
|
||||
_phase_stack: List[str] = [] # Track nested phases
|
||||
|
||||
@classmethod
|
||||
def enable(cls) -> None:
|
||||
"""Enable profiling."""
|
||||
cls._enabled = True
|
||||
|
||||
@classmethod
|
||||
def disable(cls) -> None:
|
||||
"""Disable profiling."""
|
||||
cls._enabled = False
|
||||
|
||||
@classmethod
|
||||
def is_enabled(cls) -> bool:
|
||||
"""Check if profiling is enabled."""
|
||||
return cls._enabled or os.environ.get('PRAISONAI_PROFILE', '').lower() in ('1', 'true', 'yes')
|
||||
|
||||
@classmethod
|
||||
def clear(cls) -> None:
|
||||
"""Clear all profiling data."""
|
||||
with cls._lock:
|
||||
cls._timings.clear()
|
||||
cls._streaming.clear()
|
||||
cls._pre_llm_breakdown = None
|
||||
cls._current_phases.clear()
|
||||
cls._phase_stack.clear()
|
||||
|
||||
@classmethod
|
||||
def record_timing(cls, name: str, duration_ms: float, category: str = "block",
|
||||
parent: str = "", metadata: Optional[Dict[str, Any]] = None) -> None:
|
||||
"""Record a timing measurement."""
|
||||
if not cls.is_enabled():
|
||||
return
|
||||
with cls._lock:
|
||||
cls._timings.append(TimingRecord(
|
||||
name=name,
|
||||
duration_ms=duration_ms,
|
||||
category=category,
|
||||
parent=parent,
|
||||
metadata=metadata or {}
|
||||
))
|
||||
|
||||
@classmethod
|
||||
def record_streaming(cls, name: str, ttft_ms: float, total_ms: float,
|
||||
chunk_count: int = 0) -> None:
|
||||
"""Record streaming metrics."""
|
||||
if not cls.is_enabled():
|
||||
return
|
||||
with cls._lock:
|
||||
cls._streaming.append(StreamingRecord(
|
||||
name=name,
|
||||
ttft_ms=ttft_ms,
|
||||
total_ms=total_ms,
|
||||
chunk_count=chunk_count
|
||||
))
|
||||
|
||||
@classmethod
|
||||
def start_phase(cls, phase_name: str) -> None:
|
||||
"""Start timing a phase (for pre-LLM breakdown)."""
|
||||
if not cls.is_enabled():
|
||||
return
|
||||
with cls._lock:
|
||||
cls._current_phases[phase_name] = time.perf_counter()
|
||||
cls._phase_stack.append(phase_name)
|
||||
|
||||
@classmethod
|
||||
def end_phase(cls, phase_name: str) -> float:
|
||||
"""End timing a phase and return duration in ms."""
|
||||
if not cls.is_enabled():
|
||||
return 0.0
|
||||
with cls._lock:
|
||||
start = cls._current_phases.pop(phase_name, None)
|
||||
if phase_name in cls._phase_stack:
|
||||
cls._phase_stack.remove(phase_name)
|
||||
if start is None:
|
||||
return 0.0
|
||||
duration_ms = (time.perf_counter() - start) * 1000
|
||||
# Record as timing
|
||||
parent = cls._phase_stack[-1] if cls._phase_stack else ""
|
||||
cls._timings.append(TimingRecord(
|
||||
name=phase_name,
|
||||
duration_ms=duration_ms,
|
||||
category="phase",
|
||||
parent=parent
|
||||
))
|
||||
return duration_ms
|
||||
|
||||
@classmethod
|
||||
@contextmanager
|
||||
def phase(cls, name: str, category: str = "phase"):
|
||||
"""Context manager for timing a phase."""
|
||||
if not cls.is_enabled():
|
||||
yield
|
||||
return
|
||||
|
||||
start = time.perf_counter()
|
||||
parent = ""
|
||||
with cls._lock:
|
||||
parent = cls._phase_stack[-1] if cls._phase_stack else ""
|
||||
cls._phase_stack.append(name)
|
||||
try:
|
||||
yield
|
||||
finally:
|
||||
duration_ms = (time.perf_counter() - start) * 1000
|
||||
with cls._lock:
|
||||
if name in cls._phase_stack:
|
||||
cls._phase_stack.remove(name)
|
||||
cls._timings.append(TimingRecord(
|
||||
name=name,
|
||||
duration_ms=duration_ms,
|
||||
category=category,
|
||||
parent=parent
|
||||
))
|
||||
|
||||
@classmethod
|
||||
@contextmanager
|
||||
def streaming(cls, name: str):
|
||||
"""Context manager for streaming profiling."""
|
||||
tracker = StreamingTracker(name)
|
||||
tracker.start()
|
||||
try:
|
||||
yield tracker
|
||||
finally:
|
||||
tracker.end()
|
||||
|
||||
@classmethod
|
||||
def set_pre_llm_breakdown(cls, breakdown: PreLLMBreakdown) -> None:
|
||||
"""Set the pre-LLM breakdown data."""
|
||||
if not cls.is_enabled():
|
||||
return
|
||||
with cls._lock:
|
||||
cls._pre_llm_breakdown = breakdown
|
||||
|
||||
@classmethod
|
||||
def get_timings(cls, category: Optional[str] = None) -> List[TimingRecord]:
|
||||
"""Get timing records."""
|
||||
with cls._lock:
|
||||
if category:
|
||||
return [t for t in cls._timings if t.category == category]
|
||||
return cls._timings.copy()
|
||||
|
||||
@classmethod
|
||||
def get_streaming_records(cls) -> List[StreamingRecord]:
|
||||
"""Get streaming records."""
|
||||
with cls._lock:
|
||||
return cls._streaming.copy()
|
||||
|
||||
@classmethod
|
||||
def get_pre_llm_breakdown(cls) -> Optional[PreLLMBreakdown]:
|
||||
"""Get pre-LLM breakdown."""
|
||||
with cls._lock:
|
||||
return cls._pre_llm_breakdown
|
||||
|
||||
@classmethod
|
||||
def get_summary(cls) -> Dict[str, Any]:
|
||||
"""Get profiling summary."""
|
||||
with cls._lock:
|
||||
total_time = sum(t.duration_ms for t in cls._timings)
|
||||
|
||||
# Group by category
|
||||
by_category: Dict[str, float] = {}
|
||||
for t in cls._timings:
|
||||
by_category[t.category] = by_category.get(t.category, 0) + t.duration_ms
|
||||
|
||||
# Top slowest
|
||||
slowest = sorted(cls._timings, key=lambda x: x.duration_ms, reverse=True)[:15]
|
||||
|
||||
# Pre-LLM breakdown
|
||||
pre_llm = cls._pre_llm_breakdown.to_dict() if cls._pre_llm_breakdown else {}
|
||||
|
||||
# Streaming stats
|
||||
streaming_stats = []
|
||||
for s in cls._streaming:
|
||||
streaming_stats.append({
|
||||
'name': s.name,
|
||||
'ttft_ms': s.ttft_ms,
|
||||
'total_ms': s.total_ms,
|
||||
'chunk_count': s.chunk_count
|
||||
})
|
||||
|
||||
return {
|
||||
'total_time_ms': total_time,
|
||||
'timing_count': len(cls._timings),
|
||||
'by_category': by_category,
|
||||
'slowest_operations': [(s.name, s.duration_ms, s.category) for s in slowest],
|
||||
'pre_llm_breakdown': pre_llm,
|
||||
'streaming': streaming_stats
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def report(cls, output: str = "console") -> str:
|
||||
"""Generate and output profiling report."""
|
||||
summary = cls.get_summary()
|
||||
|
||||
lines = [
|
||||
"=" * 70,
|
||||
"PraisonAI Agents Core Profiling Report",
|
||||
"=" * 70,
|
||||
"",
|
||||
f"Total Time: {summary['total_time_ms']:.2f}ms",
|
||||
f"Timing Records: {summary['timing_count']}",
|
||||
"",
|
||||
]
|
||||
|
||||
# Pre-LLM Breakdown (key for debugging the 7s delay)
|
||||
if summary['pre_llm_breakdown']:
|
||||
lines.append("## Pre-LLM Latency Breakdown")
|
||||
lines.append("-" * 50)
|
||||
for phase, ms in summary['pre_llm_breakdown'].items():
|
||||
if ms > 0:
|
||||
lines.append(f" {phase:<30}: {ms:>10.2f} ms")
|
||||
lines.append("")
|
||||
|
||||
# By Category
|
||||
lines.append("## By Category")
|
||||
lines.append("-" * 50)
|
||||
for cat, time_ms in summary['by_category'].items():
|
||||
lines.append(f" {cat}: {time_ms:.2f}ms")
|
||||
lines.append("")
|
||||
|
||||
# Slowest Operations
|
||||
lines.append("## Slowest Operations")
|
||||
lines.append("-" * 50)
|
||||
for name, time_ms, cat in summary['slowest_operations']:
|
||||
lines.append(f" {name:<40}: {time_ms:>10.2f}ms [{cat}]")
|
||||
lines.append("")
|
||||
|
||||
# Streaming Stats
|
||||
if summary['streaming']:
|
||||
lines.append("## Streaming Metrics")
|
||||
lines.append("-" * 50)
|
||||
for s in summary['streaming']:
|
||||
lines.append(f" {s['name']}: TTFT={s['ttft_ms']:.2f}ms, Total={s['total_ms']:.2f}ms, Chunks={s['chunk_count']}")
|
||||
lines.append("")
|
||||
|
||||
lines.append("=" * 70)
|
||||
|
||||
report_text = "\n".join(lines)
|
||||
|
||||
if output == "console":
|
||||
print(report_text)
|
||||
|
||||
return report_text
|
||||
|
||||
@classmethod
|
||||
def export_json(cls) -> str:
|
||||
"""Export profiling data as JSON."""
|
||||
summary = cls.get_summary()
|
||||
with cls._lock:
|
||||
data = {
|
||||
'summary': summary,
|
||||
'timings': [asdict(t) for t in cls._timings],
|
||||
'streaming': [asdict(s) for s in cls._streaming],
|
||||
}
|
||||
return json.dumps(data, indent=2, default=str)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Decorators
|
||||
# ============================================================================
|
||||
|
||||
def profile_func(func: Optional[Callable] = None, *, category: str = "function"):
|
||||
"""Decorator to profile a function."""
|
||||
def decorator(fn: Callable) -> Callable:
|
||||
@functools.wraps(fn)
|
||||
def wrapper(*args, **kwargs):
|
||||
if not Profiler.is_enabled():
|
||||
return fn(*args, **kwargs)
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
return fn(*args, **kwargs)
|
||||
finally:
|
||||
duration_ms = (time.perf_counter() - start) * 1000
|
||||
Profiler.record_timing(fn.__name__, duration_ms, category)
|
||||
return wrapper
|
||||
|
||||
if func is not None:
|
||||
return decorator(func)
|
||||
return decorator
|
||||
|
||||
|
||||
def profile_async(func: Optional[Callable] = None, *, category: str = "async"):
|
||||
"""Decorator to profile an async function."""
|
||||
def decorator(fn: Callable) -> Callable:
|
||||
@functools.wraps(fn)
|
||||
async def wrapper(*args, **kwargs):
|
||||
if not Profiler.is_enabled():
|
||||
return await fn(*args, **kwargs)
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
return await fn(*args, **kwargs)
|
||||
finally:
|
||||
duration_ms = (time.perf_counter() - start) * 1000
|
||||
Profiler.record_timing(fn.__name__, duration_ms, category)
|
||||
return wrapper
|
||||
|
||||
if func is not None:
|
||||
return decorator(func)
|
||||
return decorator
|
||||
|
||||
|
||||
@contextmanager
|
||||
def profile_block(name: str, category: str = "block"):
|
||||
"""Context manager for profiling a block of code."""
|
||||
if not Profiler.is_enabled():
|
||||
yield
|
||||
return
|
||||
|
||||
start = time.perf_counter()
|
||||
try:
|
||||
yield
|
||||
finally:
|
||||
duration_ms = (time.perf_counter() - start) * 1000
|
||||
Profiler.record_timing(name, duration_ms, category)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Exports
|
||||
# ============================================================================
|
||||
|
||||
__all__ = [
|
||||
'Profiler',
|
||||
'StreamingTracker',
|
||||
'TimingRecord',
|
||||
'StreamingRecord',
|
||||
'PreLLMBreakdown',
|
||||
'profile_func',
|
||||
'profile_async',
|
||||
'profile_block',
|
||||
]
|
||||
@@ -0,0 +1,75 @@
|
||||
"""
|
||||
PraisonAI Streaming Module.
|
||||
|
||||
Provides the StreamEvent protocol for pass-through streaming from LLM providers.
|
||||
|
||||
This module is lazily loaded to ensure zero performance impact when streaming
|
||||
features are not used.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents.streaming import (
|
||||
StreamEvent,
|
||||
StreamEventType,
|
||||
StreamMetrics,
|
||||
StreamEventEmitter,
|
||||
create_text_printer_callback,
|
||||
)
|
||||
"""
|
||||
|
||||
__all__ = [
|
||||
"StreamEvent",
|
||||
"StreamEventType",
|
||||
"StreamMetrics",
|
||||
"StreamEventEmitter",
|
||||
"StreamCallback",
|
||||
"AsyncStreamCallback",
|
||||
"create_text_printer_callback",
|
||||
"create_metrics_callback",
|
||||
"StreamLogger",
|
||||
"create_logging_callback",
|
||||
]
|
||||
|
||||
|
||||
def __getattr__(name: str):
|
||||
"""Lazy loading of streaming components."""
|
||||
if name in __all__:
|
||||
# Events module exports
|
||||
if name in (
|
||||
"StreamEvent", "StreamEventType", "StreamMetrics",
|
||||
"StreamEventEmitter", "StreamCallback", "AsyncStreamCallback",
|
||||
"create_text_printer_callback", "create_metrics_callback"
|
||||
):
|
||||
from .events import (
|
||||
StreamEvent,
|
||||
StreamEventType,
|
||||
StreamMetrics,
|
||||
StreamEventEmitter,
|
||||
StreamCallback,
|
||||
AsyncStreamCallback,
|
||||
create_text_printer_callback,
|
||||
create_metrics_callback,
|
||||
)
|
||||
|
||||
_events_exports = {
|
||||
"StreamEvent": StreamEvent,
|
||||
"StreamEventType": StreamEventType,
|
||||
"StreamMetrics": StreamMetrics,
|
||||
"StreamEventEmitter": StreamEventEmitter,
|
||||
"StreamCallback": StreamCallback,
|
||||
"AsyncStreamCallback": AsyncStreamCallback,
|
||||
"create_text_printer_callback": create_text_printer_callback,
|
||||
"create_metrics_callback": create_metrics_callback,
|
||||
}
|
||||
return _events_exports.get(name)
|
||||
|
||||
# Logging module exports
|
||||
if name in ("StreamLogger", "create_logging_callback"):
|
||||
from .logging import StreamLogger, create_logging_callback
|
||||
|
||||
_logging_exports = {
|
||||
"StreamLogger": StreamLogger,
|
||||
"create_logging_callback": create_logging_callback,
|
||||
}
|
||||
return _logging_exports.get(name)
|
||||
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
@@ -0,0 +1,300 @@
|
||||
"""
|
||||
StreamEvent protocol for PraisonAI streaming.
|
||||
|
||||
This module defines the minimal streaming event protocol that both OpenAI SDK
|
||||
and LiteLLM streaming paths map their native chunks/events into.
|
||||
|
||||
Design principles:
|
||||
- Zero overhead when not used (lazy imports, no global state)
|
||||
- Multi-agent safe (per-agent callbacks, no shared mutable state)
|
||||
- Async-safe (separate sync/async callback interfaces)
|
||||
- Provider-agnostic (same events for OpenAI, LiteLLM, etc.)
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, Protocol
|
||||
import time
|
||||
|
||||
|
||||
class StreamEventType(Enum):
|
||||
"""Types of streaming events emitted during LLM response streaming."""
|
||||
|
||||
REQUEST_START = "request_start" # Before API call is made
|
||||
HEADERS_RECEIVED = "headers_received" # When HTTP 200 headers arrive
|
||||
FIRST_TOKEN = "first_token" # First content delta received (TTFT marker)
|
||||
DELTA_TEXT = "delta_text" # Text content delta
|
||||
DELTA_TOOL_CALL = "delta_tool_call" # Tool call delta (function name, args chunk)
|
||||
TOOL_CALL_END = "tool_call_end" # Tool call complete
|
||||
LAST_TOKEN = "last_token" # Final content delta
|
||||
STREAM_END = "stream_end" # Stream completed successfully
|
||||
ERROR = "error" # Error during streaming
|
||||
|
||||
|
||||
@dataclass
|
||||
class StreamEvent:
|
||||
"""
|
||||
A single streaming event emitted during LLM response streaming.
|
||||
|
||||
Attributes:
|
||||
type: The type of event (see StreamEventType)
|
||||
timestamp: High-precision timestamp (time.perf_counter())
|
||||
content: Text content for DELTA_TEXT events
|
||||
tool_call: Tool call data for DELTA_TOOL_CALL events
|
||||
metadata: Additional event-specific metadata
|
||||
error: Error message for ERROR events
|
||||
"""
|
||||
type: StreamEventType
|
||||
timestamp: float = field(default_factory=time.perf_counter)
|
||||
content: Optional[str] = None
|
||||
tool_call: Optional[Dict[str, Any]] = None
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
error: Optional[str] = None
|
||||
|
||||
def __repr__(self) -> str:
|
||||
parts = [f"StreamEvent({self.type.value}"]
|
||||
if self.content:
|
||||
preview = self.content[:20] + "..." if len(self.content) > 20 else self.content
|
||||
parts.append(f", content={preview!r}")
|
||||
if self.tool_call:
|
||||
parts.append(f", tool_call={self.tool_call.get('name', 'unknown')}")
|
||||
if self.error:
|
||||
parts.append(f", error={self.error!r}")
|
||||
parts.append(")")
|
||||
return "".join(parts)
|
||||
|
||||
|
||||
class StreamCallback(Protocol):
|
||||
"""Protocol for synchronous stream event callbacks."""
|
||||
|
||||
def __call__(self, event: StreamEvent) -> None:
|
||||
"""Called when a stream event is emitted."""
|
||||
...
|
||||
|
||||
|
||||
class AsyncStreamCallback(Protocol):
|
||||
"""Protocol for asynchronous stream event callbacks."""
|
||||
|
||||
async def __call__(self, event: StreamEvent) -> None:
|
||||
"""Called when a stream event is emitted (async)."""
|
||||
...
|
||||
|
||||
|
||||
@dataclass
|
||||
class StreamMetrics:
|
||||
"""
|
||||
Timing metrics for a streaming response.
|
||||
|
||||
Tracks key timestamps to measure:
|
||||
- TTFT (Time To First Token): How long until first token arrives
|
||||
- Stream Duration: How long the token streaming takes
|
||||
- Total Time: End-to-end request time
|
||||
|
||||
All times are in seconds, measured with time.perf_counter() for precision.
|
||||
"""
|
||||
request_start: float = 0.0
|
||||
headers_received: float = 0.0
|
||||
first_token: float = 0.0
|
||||
last_token: float = 0.0
|
||||
stream_end: float = 0.0
|
||||
token_count: int = 0
|
||||
|
||||
@property
|
||||
def ttft(self) -> float:
|
||||
"""Time To First Token in seconds (first_token - request_start)."""
|
||||
if self.first_token and self.request_start:
|
||||
return self.first_token - self.request_start
|
||||
return 0.0
|
||||
|
||||
@property
|
||||
def stream_duration(self) -> float:
|
||||
"""Duration of token streaming in seconds (last_token - first_token)."""
|
||||
if self.last_token and self.first_token:
|
||||
return self.last_token - self.first_token
|
||||
return 0.0
|
||||
|
||||
@property
|
||||
def total_time(self) -> float:
|
||||
"""Total request time in seconds (stream_end - request_start)."""
|
||||
if self.stream_end and self.request_start:
|
||||
return self.stream_end - self.request_start
|
||||
return 0.0
|
||||
|
||||
@property
|
||||
def tokens_per_second(self) -> float:
|
||||
"""Token generation rate (tokens / stream_duration)."""
|
||||
if self.stream_duration > 0 and self.token_count > 0:
|
||||
return self.token_count / self.stream_duration
|
||||
return 0.0
|
||||
|
||||
def update_from_event(self, event: StreamEvent) -> None:
|
||||
"""Update metrics from a StreamEvent."""
|
||||
if event.type == StreamEventType.REQUEST_START:
|
||||
self.request_start = event.timestamp
|
||||
elif event.type == StreamEventType.HEADERS_RECEIVED:
|
||||
self.headers_received = event.timestamp
|
||||
elif event.type == StreamEventType.FIRST_TOKEN:
|
||||
self.first_token = event.timestamp
|
||||
self.token_count = 1
|
||||
elif event.type == StreamEventType.DELTA_TEXT:
|
||||
self.token_count += 1
|
||||
elif event.type == StreamEventType.LAST_TOKEN:
|
||||
self.last_token = event.timestamp
|
||||
elif event.type == StreamEventType.STREAM_END:
|
||||
self.stream_end = event.timestamp
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert metrics to dictionary for logging/display."""
|
||||
return {
|
||||
"ttft_ms": round(self.ttft * 1000, 1),
|
||||
"stream_duration_ms": round(self.stream_duration * 1000, 1),
|
||||
"total_time_ms": round(self.total_time * 1000, 1),
|
||||
"token_count": self.token_count,
|
||||
"tokens_per_second": round(self.tokens_per_second, 1),
|
||||
}
|
||||
|
||||
def format_summary(self) -> str:
|
||||
"""Format metrics as a human-readable summary string."""
|
||||
return (
|
||||
f"TTFT: {self.ttft*1000:.0f}ms | "
|
||||
f"Stream: {self.stream_duration*1000:.0f}ms | "
|
||||
f"Total: {self.total_time*1000:.0f}ms | "
|
||||
f"Tokens: {self.token_count} ({self.tokens_per_second:.1f}/s)"
|
||||
)
|
||||
|
||||
|
||||
class StreamEventEmitter:
|
||||
"""
|
||||
Manages stream event callbacks for an agent or streaming session.
|
||||
|
||||
Thread-safe and multi-agent safe - each agent has its own emitter instance.
|
||||
Supports both sync and async callbacks.
|
||||
|
||||
Usage:
|
||||
emitter = StreamEventEmitter()
|
||||
emitter.add_callback(my_callback)
|
||||
|
||||
# During streaming:
|
||||
emitter.emit(StreamEvent(type=StreamEventType.DELTA_TEXT, content="Hello"))
|
||||
"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._callbacks: List[StreamCallback] = []
|
||||
self._async_callbacks: List[AsyncStreamCallback] = []
|
||||
self._metrics: Optional[StreamMetrics] = None
|
||||
self._collect_metrics: bool = False
|
||||
|
||||
def add_callback(self, callback: StreamCallback) -> None:
|
||||
"""Add a synchronous callback to receive stream events."""
|
||||
self._callbacks.append(callback)
|
||||
|
||||
def remove_callback(self, callback: StreamCallback) -> None:
|
||||
"""Remove a synchronous callback."""
|
||||
if callback in self._callbacks:
|
||||
self._callbacks.remove(callback)
|
||||
|
||||
def add_async_callback(self, callback: AsyncStreamCallback) -> None:
|
||||
"""Add an asynchronous callback to receive stream events."""
|
||||
self._async_callbacks.append(callback)
|
||||
|
||||
def remove_async_callback(self, callback: AsyncStreamCallback) -> None:
|
||||
"""Remove an asynchronous callback."""
|
||||
if callback in self._async_callbacks:
|
||||
self._async_callbacks.remove(callback)
|
||||
|
||||
def enable_metrics(self) -> None:
|
||||
"""Enable metrics collection for this streaming session."""
|
||||
self._collect_metrics = True
|
||||
self._metrics = StreamMetrics()
|
||||
|
||||
def get_metrics(self) -> Optional[StreamMetrics]:
|
||||
"""Get collected metrics (None if metrics not enabled)."""
|
||||
return self._metrics
|
||||
|
||||
def reset_metrics(self) -> None:
|
||||
"""Reset metrics for a new streaming session."""
|
||||
if self._collect_metrics:
|
||||
self._metrics = StreamMetrics()
|
||||
|
||||
def emit(self, event: StreamEvent) -> None:
|
||||
"""
|
||||
Emit a stream event to all registered callbacks.
|
||||
|
||||
This is the synchronous emission path. For async streaming,
|
||||
use emit_async().
|
||||
"""
|
||||
# Update metrics if enabled
|
||||
if self._collect_metrics and self._metrics:
|
||||
self._metrics.update_from_event(event)
|
||||
|
||||
# Call all sync callbacks
|
||||
for callback in self._callbacks:
|
||||
try:
|
||||
callback(event)
|
||||
except Exception:
|
||||
# Don't let callback errors break streaming
|
||||
pass
|
||||
|
||||
async def emit_async(self, event: StreamEvent) -> None:
|
||||
"""
|
||||
Emit a stream event to all registered callbacks (async version).
|
||||
|
||||
Calls both sync and async callbacks.
|
||||
"""
|
||||
# Update metrics if enabled
|
||||
if self._collect_metrics and self._metrics:
|
||||
self._metrics.update_from_event(event)
|
||||
|
||||
# Call sync callbacks
|
||||
for callback in self._callbacks:
|
||||
try:
|
||||
callback(event)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Call async callbacks
|
||||
for callback in self._async_callbacks:
|
||||
try:
|
||||
await callback(event)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
@property
|
||||
def has_callbacks(self) -> bool:
|
||||
"""Check if any callbacks are registered."""
|
||||
return bool(self._callbacks or self._async_callbacks)
|
||||
|
||||
|
||||
def create_text_printer_callback(flush: bool = True) -> StreamCallback:
|
||||
"""
|
||||
Create a simple callback that prints text deltas to stdout.
|
||||
|
||||
Args:
|
||||
flush: Whether to flush stdout after each print (default True)
|
||||
|
||||
Returns:
|
||||
A StreamCallback that prints DELTA_TEXT content
|
||||
"""
|
||||
def printer(event: StreamEvent) -> None:
|
||||
if event.type == StreamEventType.DELTA_TEXT and event.content:
|
||||
print(event.content, end="", flush=flush)
|
||||
elif event.type == StreamEventType.STREAM_END:
|
||||
print() # Newline at end
|
||||
|
||||
return printer
|
||||
|
||||
|
||||
def create_metrics_callback(metrics: StreamMetrics) -> StreamCallback:
|
||||
"""
|
||||
Create a callback that updates a StreamMetrics instance.
|
||||
|
||||
Args:
|
||||
metrics: The StreamMetrics instance to update
|
||||
|
||||
Returns:
|
||||
A StreamCallback that updates the metrics
|
||||
"""
|
||||
def updater(event: StreamEvent) -> None:
|
||||
metrics.update_from_event(event)
|
||||
|
||||
return updater
|
||||
@@ -0,0 +1,207 @@
|
||||
"""
|
||||
Streaming logging utilities for PraisonAI.
|
||||
|
||||
Provides guarded logging for streaming events with clear timestamps
|
||||
for request_start, headers_received, first_token, last_token, and stream_end.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents.streaming.logging import StreamLogger
|
||||
|
||||
logger = StreamLogger(verbose=True, metrics=True)
|
||||
logger.log_request_start(model="gpt-4o-mini")
|
||||
# ... streaming ...
|
||||
logger.log_first_token()
|
||||
# ... more tokens ...
|
||||
logger.log_stream_end()
|
||||
print(logger.get_metrics_summary())
|
||||
"""
|
||||
|
||||
import logging
|
||||
import time
|
||||
from typing import Optional, Dict, Any
|
||||
|
||||
from .events import StreamMetrics, StreamEvent, StreamEventType
|
||||
|
||||
|
||||
class StreamLogger:
|
||||
"""
|
||||
Guarded logging for streaming events with timing metrics.
|
||||
|
||||
Only logs when verbose=True or metrics=True to ensure zero overhead
|
||||
when logging is disabled.
|
||||
|
||||
Attributes:
|
||||
verbose: Whether to log detailed streaming events
|
||||
metrics: Whether to collect and display timing metrics
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
verbose: bool = False,
|
||||
metrics: bool = False,
|
||||
logger: Optional[logging.Logger] = None
|
||||
):
|
||||
self.verbose = verbose
|
||||
self.metrics = metrics
|
||||
self._logger = logger or logging.getLogger(__name__)
|
||||
self._metrics = StreamMetrics() if metrics else None
|
||||
self._enabled = verbose or metrics
|
||||
|
||||
def log_request_start(
|
||||
self,
|
||||
model: Optional[str] = None,
|
||||
message_count: Optional[int] = None
|
||||
) -> None:
|
||||
"""Log when the streaming request is initiated."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
timestamp = time.perf_counter()
|
||||
if self._metrics:
|
||||
self._metrics.request_start = timestamp
|
||||
|
||||
if self.verbose:
|
||||
extra = f" model={model}" if model else ""
|
||||
extra += f" messages={message_count}" if message_count else ""
|
||||
self._logger.info(f"[STREAM] REQUEST_START{extra}")
|
||||
|
||||
def log_headers_received(self) -> None:
|
||||
"""Log when HTTP response headers are received."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
timestamp = time.perf_counter()
|
||||
if self._metrics:
|
||||
self._metrics.headers_received = timestamp
|
||||
|
||||
if self.verbose:
|
||||
self._logger.info("[STREAM] HEADERS_RECEIVED")
|
||||
|
||||
def log_first_token(self, content: Optional[str] = None) -> None:
|
||||
"""Log when the first content token is received (TTFT marker)."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
timestamp = time.perf_counter()
|
||||
if self._metrics:
|
||||
self._metrics.first_token = timestamp
|
||||
self._metrics.token_count = 1
|
||||
|
||||
if self.verbose:
|
||||
preview = content[:20] + "..." if content and len(content) > 20 else content
|
||||
self._logger.info(f"[STREAM] FIRST_TOKEN content={preview!r}")
|
||||
|
||||
def log_delta_text(self, content: Optional[str] = None) -> None:
|
||||
"""Log a text delta (only when verbose, not for every token)."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
if self._metrics:
|
||||
self._metrics.token_count += 1
|
||||
|
||||
# Don't log every delta to avoid noise - just track metrics
|
||||
|
||||
def log_last_token(self) -> None:
|
||||
"""Log when the last content token is received."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
timestamp = time.perf_counter()
|
||||
if self._metrics:
|
||||
self._metrics.last_token = timestamp
|
||||
|
||||
if self.verbose:
|
||||
self._logger.info("[STREAM] LAST_TOKEN")
|
||||
|
||||
def log_stream_end(self, chunk_count: Optional[int] = None) -> None:
|
||||
"""Log when the stream ends."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
timestamp = time.perf_counter()
|
||||
if self._metrics:
|
||||
self._metrics.stream_end = timestamp
|
||||
|
||||
if self.verbose:
|
||||
extra = f" chunks={chunk_count}" if chunk_count else ""
|
||||
self._logger.info(f"[STREAM] STREAM_END{extra}")
|
||||
|
||||
def log_error(self, error: str) -> None:
|
||||
"""Log a streaming error."""
|
||||
if self.verbose:
|
||||
self._logger.error(f"[STREAM] ERROR: {error}")
|
||||
|
||||
def get_metrics(self) -> Optional[StreamMetrics]:
|
||||
"""Get the collected metrics (None if metrics not enabled)."""
|
||||
return self._metrics
|
||||
|
||||
def get_metrics_summary(self) -> str:
|
||||
"""Get a formatted summary of streaming metrics."""
|
||||
if not self._metrics:
|
||||
return "Metrics not enabled"
|
||||
return self._metrics.format_summary()
|
||||
|
||||
def get_metrics_dict(self) -> Optional[Dict[str, Any]]:
|
||||
"""Get metrics as a dictionary."""
|
||||
if not self._metrics:
|
||||
return None
|
||||
return self._metrics.to_dict()
|
||||
|
||||
def update_from_event(self, event: StreamEvent) -> None:
|
||||
"""Update logger state from a StreamEvent."""
|
||||
if not self._enabled:
|
||||
return
|
||||
|
||||
if self._metrics:
|
||||
self._metrics.update_from_event(event)
|
||||
|
||||
if self.verbose:
|
||||
if event.type == StreamEventType.REQUEST_START:
|
||||
self.log_request_start()
|
||||
elif event.type == StreamEventType.HEADERS_RECEIVED:
|
||||
self.log_headers_received()
|
||||
elif event.type == StreamEventType.FIRST_TOKEN:
|
||||
self.log_first_token(event.content)
|
||||
elif event.type == StreamEventType.LAST_TOKEN:
|
||||
self.log_last_token()
|
||||
elif event.type == StreamEventType.STREAM_END:
|
||||
self.log_stream_end()
|
||||
elif event.type == StreamEventType.ERROR:
|
||||
self.log_error(event.error or "Unknown error")
|
||||
|
||||
|
||||
def create_logging_callback(
|
||||
verbose: bool = False,
|
||||
metrics: bool = False,
|
||||
logger: Optional[logging.Logger] = None
|
||||
) -> tuple:
|
||||
"""
|
||||
Create a StreamLogger and a callback function for use with streaming.
|
||||
|
||||
Args:
|
||||
verbose: Whether to log detailed events
|
||||
metrics: Whether to collect timing metrics
|
||||
logger: Optional custom logger
|
||||
|
||||
Returns:
|
||||
Tuple of (StreamLogger, callback_function)
|
||||
|
||||
Usage:
|
||||
stream_logger, callback = create_logging_callback(verbose=True, metrics=True)
|
||||
|
||||
# Pass callback to streaming method
|
||||
response = client.process_stream_response(
|
||||
...,
|
||||
stream_callback=callback,
|
||||
emit_events=True
|
||||
)
|
||||
|
||||
# After streaming, get metrics
|
||||
print(stream_logger.get_metrics_summary())
|
||||
"""
|
||||
stream_logger = StreamLogger(verbose=verbose, metrics=metrics, logger=logger)
|
||||
|
||||
def callback(event: StreamEvent) -> None:
|
||||
stream_logger.update_from_event(event)
|
||||
|
||||
return stream_logger, callback
|
||||
@@ -0,0 +1,68 @@
|
||||
"""
|
||||
Trace Module for PraisonAI Agents.
|
||||
|
||||
Provides lightweight action tracing for the `output="actions"` mode.
|
||||
Shows agent lifecycle events, tool calls, and final output without
|
||||
verbose internal details.
|
||||
|
||||
Zero Performance Impact:
|
||||
- All imports are lazy loaded via __getattr__
|
||||
- NoOpSink is the default (zero overhead when not used)
|
||||
- Disabled emitter has near-zero overhead
|
||||
|
||||
Usage:
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Simple usage - shows action trace
|
||||
agent = Agent(instructions="...", output="actions")
|
||||
agent.start("Do something")
|
||||
|
||||
# Advanced - capture to file
|
||||
from praisonaiagents.trace import ActionTraceConfig
|
||||
|
||||
agent = Agent(
|
||||
instructions="...",
|
||||
output="actions",
|
||||
trace=ActionTraceConfig(
|
||||
sink_type="jsonl",
|
||||
file_path="trace.jsonl",
|
||||
)
|
||||
)
|
||||
"""
|
||||
|
||||
__all__ = [
|
||||
# Core types
|
||||
"ActionEvent",
|
||||
"ActionEventType",
|
||||
"ActionTraceConfig",
|
||||
# Sinks
|
||||
"TraceSink",
|
||||
"NoOpSink",
|
||||
"ListSink",
|
||||
# Emitter
|
||||
"TraceEmitter",
|
||||
# Redaction
|
||||
"redact_dict",
|
||||
"REDACT_KEYS",
|
||||
]
|
||||
|
||||
|
||||
def __getattr__(name: str):
|
||||
"""Lazy load module components to avoid import overhead."""
|
||||
if name in ("ActionEvent", "ActionEventType", "ActionTraceConfig"):
|
||||
from .protocol import ActionEvent, ActionEventType, ActionTraceConfig
|
||||
return locals()[name]
|
||||
|
||||
if name in ("TraceSink", "NoOpSink", "ListSink"):
|
||||
from .protocol import TraceSink, NoOpSink, ListSink
|
||||
return locals()[name]
|
||||
|
||||
if name == "TraceEmitter":
|
||||
from .protocol import TraceEmitter
|
||||
return TraceEmitter
|
||||
|
||||
if name in ("redact_dict", "REDACT_KEYS"):
|
||||
from .redact import redact_dict, REDACT_KEYS
|
||||
return locals()[name]
|
||||
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
@@ -0,0 +1,398 @@
|
||||
"""
|
||||
Action Trace Protocol for PraisonAI Agents.
|
||||
|
||||
Lightweight protocol for tracing agent actions. Uses only stdlib
|
||||
to ensure zero dependencies and minimal overhead.
|
||||
|
||||
Schema Version: 1.0
|
||||
"""
|
||||
|
||||
import json
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
|
||||
|
||||
|
||||
# Schema version for forward compatibility
|
||||
SCHEMA_VERSION = "1.0"
|
||||
|
||||
|
||||
class ActionEventType(str, Enum):
|
||||
"""Types of action events."""
|
||||
AGENT_START = "agent_start"
|
||||
AGENT_END = "agent_end"
|
||||
TOOL_START = "tool_start"
|
||||
TOOL_END = "tool_end"
|
||||
ERROR = "error"
|
||||
OUTPUT = "output"
|
||||
|
||||
|
||||
@dataclass
|
||||
class ActionEvent:
|
||||
"""
|
||||
Lightweight action trace event.
|
||||
|
||||
Represents a single action in the agent execution trace.
|
||||
Designed for minimal memory footprint and fast serialization.
|
||||
"""
|
||||
event_type: str
|
||||
timestamp: float
|
||||
schema_version: str = SCHEMA_VERSION
|
||||
agent_id: Optional[str] = None
|
||||
agent_name: Optional[str] = None
|
||||
tool_name: Optional[str] = None
|
||||
tool_args: Optional[Dict[str, Any]] = None
|
||||
tool_result_summary: Optional[str] = None
|
||||
duration_ms: Optional[float] = None
|
||||
status: Optional[str] = None # ok, error
|
||||
error_message: Optional[str] = None
|
||||
metadata: Dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary, excluding None values."""
|
||||
result = {
|
||||
"schema_version": self.schema_version,
|
||||
"event_type": self.event_type,
|
||||
"timestamp": self.timestamp,
|
||||
}
|
||||
|
||||
# Add optional fields only if set
|
||||
if self.agent_id is not None:
|
||||
result["agent_id"] = self.agent_id
|
||||
if self.agent_name is not None:
|
||||
result["agent_name"] = self.agent_name
|
||||
if self.tool_name is not None:
|
||||
result["tool_name"] = self.tool_name
|
||||
if self.tool_args is not None:
|
||||
result["tool_args"] = self.tool_args
|
||||
if self.tool_result_summary is not None:
|
||||
result["tool_result_summary"] = self.tool_result_summary
|
||||
if self.duration_ms is not None:
|
||||
result["duration_ms"] = self.duration_ms
|
||||
if self.status is not None:
|
||||
result["status"] = self.status
|
||||
if self.error_message is not None:
|
||||
result["error_message"] = self.error_message
|
||||
if self.metadata:
|
||||
result["metadata"] = self.metadata
|
||||
|
||||
return result
|
||||
|
||||
def to_json(self) -> str:
|
||||
"""Convert to JSON string."""
|
||||
return json.dumps(self.to_dict(), default=str)
|
||||
|
||||
|
||||
@runtime_checkable
|
||||
class TraceSink(Protocol):
|
||||
"""
|
||||
Protocol for trace event sinks.
|
||||
|
||||
Implementations receive action events and handle them
|
||||
(e.g., print to stdout, write to file, send to server).
|
||||
"""
|
||||
|
||||
def emit(self, event: ActionEvent) -> None:
|
||||
"""Emit an action event."""
|
||||
...
|
||||
|
||||
def flush(self) -> None:
|
||||
"""Flush any buffered events."""
|
||||
...
|
||||
|
||||
def close(self) -> None:
|
||||
"""Close the sink and release resources."""
|
||||
...
|
||||
|
||||
|
||||
class NoOpSink:
|
||||
"""
|
||||
No-operation sink that discards all events.
|
||||
|
||||
Used as the default sink when tracing is disabled.
|
||||
Has near-zero overhead.
|
||||
"""
|
||||
|
||||
__slots__ = ()
|
||||
|
||||
def emit(self, event: ActionEvent) -> None:
|
||||
"""Discard the event."""
|
||||
pass
|
||||
|
||||
def flush(self) -> None:
|
||||
"""No-op."""
|
||||
pass
|
||||
|
||||
def close(self) -> None:
|
||||
"""No-op."""
|
||||
pass
|
||||
|
||||
|
||||
class ListSink:
|
||||
"""
|
||||
Sink that collects events in a list.
|
||||
|
||||
Useful for testing and programmatic access to trace events.
|
||||
"""
|
||||
|
||||
__slots__ = ("_events",)
|
||||
|
||||
def __init__(self):
|
||||
self._events: List[ActionEvent] = []
|
||||
|
||||
def emit(self, event: ActionEvent) -> None:
|
||||
"""Add event to the list."""
|
||||
self._events.append(event)
|
||||
|
||||
def flush(self) -> None:
|
||||
"""No-op for list sink."""
|
||||
pass
|
||||
|
||||
def close(self) -> None:
|
||||
"""No-op for list sink."""
|
||||
pass
|
||||
|
||||
def get_events(self) -> List[ActionEvent]:
|
||||
"""Get all collected events."""
|
||||
return self._events.copy()
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Clear all collected events."""
|
||||
self._events.clear()
|
||||
|
||||
|
||||
@dataclass
|
||||
class ActionTraceConfig:
|
||||
"""
|
||||
Configuration for action tracing.
|
||||
|
||||
Usage:
|
||||
# Default (disabled)
|
||||
config = ActionTraceConfig()
|
||||
|
||||
# Enable with stdout
|
||||
config = ActionTraceConfig(enabled=True, sink_type="stdout")
|
||||
|
||||
# Enable with JSONL file
|
||||
config = ActionTraceConfig(
|
||||
enabled=True,
|
||||
sink_type="jsonl",
|
||||
file_path="trace.jsonl",
|
||||
)
|
||||
"""
|
||||
enabled: bool = True
|
||||
redact: bool = True
|
||||
compact: bool = False
|
||||
sink_type: str = "noop" # noop, stdout, jsonl, file
|
||||
file_path: Optional[str] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary."""
|
||||
return {
|
||||
"enabled": self.enabled,
|
||||
"redact": self.redact,
|
||||
"compact": self.compact,
|
||||
"sink_type": self.sink_type,
|
||||
"file_path": self.file_path,
|
||||
}
|
||||
|
||||
|
||||
class TraceEmitter:
|
||||
"""
|
||||
Emitter for action trace events.
|
||||
|
||||
Provides a high-level API for emitting trace events.
|
||||
Handles redaction and sink management.
|
||||
|
||||
Usage:
|
||||
sink = ListSink()
|
||||
emitter = TraceEmitter(sink=sink)
|
||||
|
||||
emitter.agent_start("researcher")
|
||||
emitter.tool_start("search", {"query": "AI"})
|
||||
emitter.tool_end("search", duration_ms=100, status="ok")
|
||||
emitter.agent_end("researcher", duration_ms=500)
|
||||
"""
|
||||
|
||||
__slots__ = ("_sink", "_enabled", "_redact", "_agent_starts")
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
sink: Optional[TraceSink] = None,
|
||||
enabled: bool = True,
|
||||
redact: bool = True,
|
||||
):
|
||||
self._sink = sink or NoOpSink()
|
||||
self._enabled = enabled
|
||||
self._redact = redact
|
||||
self._agent_starts: Dict[str, float] = {} # Track agent start times
|
||||
|
||||
def _emit(self, event: ActionEvent) -> None:
|
||||
"""Internal emit with enabled check."""
|
||||
if not self._enabled:
|
||||
return
|
||||
self._sink.emit(event)
|
||||
|
||||
def _redact_args(self, args: Optional[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
|
||||
"""Redact sensitive data from args if enabled."""
|
||||
if args is None or not self._redact:
|
||||
return args
|
||||
|
||||
from .redact import redact_dict
|
||||
return redact_dict(args)
|
||||
|
||||
def agent_start(
|
||||
self,
|
||||
agent_name: str,
|
||||
agent_id: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Emit agent start event."""
|
||||
ts = time.time()
|
||||
self._agent_starts[agent_name] = ts
|
||||
|
||||
self._emit(ActionEvent(
|
||||
event_type=ActionEventType.AGENT_START.value,
|
||||
timestamp=ts,
|
||||
agent_name=agent_name,
|
||||
agent_id=agent_id,
|
||||
metadata=metadata or {},
|
||||
))
|
||||
|
||||
def agent_end(
|
||||
self,
|
||||
agent_name: str,
|
||||
agent_id: Optional[str] = None,
|
||||
duration_ms: Optional[float] = None,
|
||||
status: str = "ok",
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Emit agent end event."""
|
||||
ts = time.time()
|
||||
|
||||
# Calculate duration if not provided
|
||||
if duration_ms is None and agent_name in self._agent_starts:
|
||||
start_ts = self._agent_starts.pop(agent_name, None)
|
||||
if start_ts:
|
||||
duration_ms = (ts - start_ts) * 1000
|
||||
|
||||
self._emit(ActionEvent(
|
||||
event_type=ActionEventType.AGENT_END.value,
|
||||
timestamp=ts,
|
||||
agent_name=agent_name,
|
||||
agent_id=agent_id,
|
||||
duration_ms=duration_ms,
|
||||
status=status,
|
||||
metadata=metadata or {},
|
||||
))
|
||||
|
||||
def tool_start(
|
||||
self,
|
||||
tool_name: str,
|
||||
tool_args: Optional[Dict[str, Any]] = None,
|
||||
agent_name: Optional[str] = None,
|
||||
agent_id: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Emit tool start event."""
|
||||
self._emit(ActionEvent(
|
||||
event_type=ActionEventType.TOOL_START.value,
|
||||
timestamp=time.time(),
|
||||
tool_name=tool_name,
|
||||
tool_args=self._redact_args(tool_args),
|
||||
agent_name=agent_name,
|
||||
agent_id=agent_id,
|
||||
metadata=metadata or {},
|
||||
))
|
||||
|
||||
def tool_end(
|
||||
self,
|
||||
tool_name: str,
|
||||
duration_ms: float,
|
||||
status: str = "ok",
|
||||
result_summary: Optional[str] = None,
|
||||
agent_name: Optional[str] = None,
|
||||
agent_id: Optional[str] = None,
|
||||
error_message: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Emit tool end event."""
|
||||
self._emit(ActionEvent(
|
||||
event_type=ActionEventType.TOOL_END.value,
|
||||
timestamp=time.time(),
|
||||
tool_name=tool_name,
|
||||
duration_ms=duration_ms,
|
||||
status=status,
|
||||
tool_result_summary=result_summary,
|
||||
agent_name=agent_name,
|
||||
agent_id=agent_id,
|
||||
error_message=error_message,
|
||||
metadata=metadata or {},
|
||||
))
|
||||
|
||||
def error(
|
||||
self,
|
||||
message: str,
|
||||
tool_name: Optional[str] = None,
|
||||
agent_name: Optional[str] = None,
|
||||
agent_id: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Emit error event."""
|
||||
self._emit(ActionEvent(
|
||||
event_type=ActionEventType.ERROR.value,
|
||||
timestamp=time.time(),
|
||||
error_message=message,
|
||||
tool_name=tool_name,
|
||||
agent_name=agent_name,
|
||||
agent_id=agent_id,
|
||||
status="error",
|
||||
metadata=metadata or {},
|
||||
))
|
||||
|
||||
def output(
|
||||
self,
|
||||
content: str,
|
||||
agent_name: Optional[str] = None,
|
||||
agent_id: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Emit final output event."""
|
||||
# Truncate long output for summary
|
||||
summary = content[:500] + "..." if len(content) > 500 else content
|
||||
|
||||
self._emit(ActionEvent(
|
||||
event_type=ActionEventType.OUTPUT.value,
|
||||
timestamp=time.time(),
|
||||
tool_result_summary=summary,
|
||||
agent_name=agent_name,
|
||||
agent_id=agent_id,
|
||||
metadata=metadata or {},
|
||||
))
|
||||
|
||||
def flush(self) -> None:
|
||||
"""Flush the sink."""
|
||||
self._sink.flush()
|
||||
|
||||
def close(self) -> None:
|
||||
"""Close the sink."""
|
||||
self._sink.close()
|
||||
|
||||
|
||||
# Global default emitter (NoOp by default)
|
||||
_default_emitter: Optional[TraceEmitter] = None
|
||||
|
||||
|
||||
def get_default_emitter() -> TraceEmitter:
|
||||
"""Get the default trace emitter."""
|
||||
global _default_emitter
|
||||
if _default_emitter is None:
|
||||
_default_emitter = TraceEmitter(sink=NoOpSink(), enabled=False)
|
||||
return _default_emitter
|
||||
|
||||
|
||||
def set_default_emitter(emitter: TraceEmitter) -> None:
|
||||
"""Set the default trace emitter."""
|
||||
global _default_emitter
|
||||
_default_emitter = emitter
|
||||
@@ -0,0 +1,149 @@
|
||||
"""
|
||||
Redaction utilities for action trace.
|
||||
|
||||
Provides deterministic redaction of sensitive data in tool arguments
|
||||
and results. Uses only stdlib for zero dependencies.
|
||||
"""
|
||||
|
||||
from typing import Any, Dict, Set
|
||||
import re
|
||||
|
||||
# Keys that should always be redacted (case-insensitive matching)
|
||||
REDACT_KEYS: Set[str] = {
|
||||
# API keys and tokens
|
||||
"api_key",
|
||||
"apikey",
|
||||
"api-key",
|
||||
"secret",
|
||||
"secret_key",
|
||||
"secretkey",
|
||||
"private_key",
|
||||
"privatekey",
|
||||
# Authentication
|
||||
"password",
|
||||
"passwd",
|
||||
"pwd",
|
||||
"token",
|
||||
"bearer",
|
||||
"authorization",
|
||||
"auth",
|
||||
"auth_token",
|
||||
"access_token",
|
||||
"refresh_token",
|
||||
# Session and cookies
|
||||
"cookie",
|
||||
"session",
|
||||
"session_id",
|
||||
"sessionid",
|
||||
"credential",
|
||||
"credentials",
|
||||
# Database
|
||||
"connection_string",
|
||||
"connectionstring",
|
||||
"database_url",
|
||||
"db_url",
|
||||
"dburl",
|
||||
"db_password",
|
||||
"db_pass",
|
||||
# Cloud provider specific
|
||||
"aws_secret",
|
||||
"aws_secret_access_key",
|
||||
"azure_key",
|
||||
"gcp_key",
|
||||
"openai_api_key",
|
||||
"anthropic_api_key",
|
||||
}
|
||||
|
||||
# Compiled regex for case-insensitive matching
|
||||
_REDACT_PATTERN = re.compile(
|
||||
r"(" + "|".join(re.escape(k) for k in REDACT_KEYS) + r")",
|
||||
re.IGNORECASE
|
||||
)
|
||||
|
||||
REDACTED_VALUE = "[REDACTED]"
|
||||
|
||||
|
||||
def _should_redact(key: str) -> bool:
|
||||
"""Check if a key should be redacted."""
|
||||
# Normalize key for comparison
|
||||
normalized = key.lower().replace("-", "_").replace(" ", "_")
|
||||
|
||||
# Check exact match first
|
||||
if normalized in REDACT_KEYS:
|
||||
return True
|
||||
|
||||
# Check if any redact key is contained in the normalized key
|
||||
for redact_key in REDACT_KEYS:
|
||||
if redact_key in normalized:
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
|
||||
def redact_dict(data: Dict[str, Any], enabled: bool = True) -> Dict[str, Any]:
|
||||
"""
|
||||
Redact sensitive values from a dictionary.
|
||||
|
||||
Args:
|
||||
data: Dictionary to redact
|
||||
enabled: If False, returns data unchanged
|
||||
|
||||
Returns:
|
||||
New dictionary with sensitive values redacted
|
||||
"""
|
||||
if not enabled:
|
||||
return data
|
||||
|
||||
if not data:
|
||||
return {}
|
||||
|
||||
return _redact_value(data)
|
||||
|
||||
|
||||
def _redact_value(value: Any) -> Any:
|
||||
"""Recursively redact sensitive values."""
|
||||
if isinstance(value, dict):
|
||||
return {k: _redact_key_value(k, v) for k, v in value.items()}
|
||||
elif isinstance(value, list):
|
||||
return [_redact_value(item) for item in value]
|
||||
else:
|
||||
return value
|
||||
|
||||
|
||||
def _redact_key_value(key: str, value: Any) -> Any:
|
||||
"""Redact a value if its key is sensitive."""
|
||||
if _should_redact(key):
|
||||
return REDACTED_VALUE
|
||||
|
||||
# Recursively process nested structures
|
||||
return _redact_value(value)
|
||||
|
||||
|
||||
def redact_string(text: str, enabled: bool = True) -> str:
|
||||
"""
|
||||
Redact potential secrets from a string.
|
||||
|
||||
This is a best-effort function that looks for common patterns
|
||||
like "api_key=xxx" or "password: xxx" in strings.
|
||||
|
||||
Args:
|
||||
text: String to redact
|
||||
enabled: If False, returns text unchanged
|
||||
|
||||
Returns:
|
||||
String with potential secrets redacted
|
||||
"""
|
||||
if not enabled or not text:
|
||||
return text
|
||||
|
||||
# Pattern for key=value or key: value
|
||||
patterns = [
|
||||
(r'(["\']?)(' + '|'.join(re.escape(k) for k in REDACT_KEYS) + r')(["\']?\s*[:=]\s*["\']?)([^"\'\s,}\]]+)',
|
||||
r'\1\2\3[REDACTED]'),
|
||||
]
|
||||
|
||||
result = text
|
||||
for pattern, replacement in patterns:
|
||||
result = re.sub(pattern, replacement, result, flags=re.IGNORECASE)
|
||||
|
||||
return result
|
||||
@@ -254,6 +254,10 @@ class WorkflowStep:
|
||||
knowledge: Optional[Any] = None # Union[bool, List[str], KnowledgeConfig] - RAG
|
||||
web: Optional[Any] = None # Union[bool, WebConfig] - web search/fetch
|
||||
reflection: Optional[Any] = None # Union[bool, ReflectionConfig] - self-reflection
|
||||
memory: Optional[Any] = None # Union[bool, MemoryConfig] - step-level memory
|
||||
planning: Optional[Any] = None # Union[bool, PlanningConfig] - step-level planning
|
||||
hooks: Optional[Any] = None # Union[List, HooksConfig] - step lifecycle hooks
|
||||
caching: Optional[Any] = None # Union[bool, CachingConfig] - step-level caching
|
||||
|
||||
# Status tracking
|
||||
status: str = "pending" # pending, running, completed, failed, skipped
|
||||
@@ -278,6 +282,10 @@ class WorkflowStep:
|
||||
_knowledge_config: Optional[Any] = field(default=None, repr=False)
|
||||
_web_config: Optional[Any] = field(default=None, repr=False)
|
||||
_reflection_config: Optional[Any] = field(default=None, repr=False)
|
||||
_memory_config: Optional[Any] = field(default=None, repr=False)
|
||||
_planning_config: Optional[Any] = field(default=None, repr=False)
|
||||
_hooks_config: Optional[Any] = field(default=None, repr=False)
|
||||
_caching_config: Optional[Any] = field(default=None, repr=False)
|
||||
|
||||
def __post_init__(self):
|
||||
"""Resolve consolidated params to internal values."""
|
||||
@@ -370,6 +378,62 @@ class WorkflowStep:
|
||||
config_class=ReflectionConfig, presets=REFLECTION_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve memory (NEW for feature parity)
|
||||
try:
|
||||
from ..config.feature_configs import MemoryConfig
|
||||
from ..config.presets import MEMORY_PRESETS
|
||||
except ImportError:
|
||||
MemoryConfig = None
|
||||
MEMORY_PRESETS = {}
|
||||
if MemoryConfig and self.memory is not None:
|
||||
self._memory_config = resolve(
|
||||
value=self.memory, param_name="memory",
|
||||
config_class=MemoryConfig, presets=MEMORY_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve planning (NEW for feature parity)
|
||||
try:
|
||||
from ..config.feature_configs import PlanningConfig
|
||||
from ..config.presets import PLANNING_PRESETS
|
||||
except ImportError:
|
||||
PlanningConfig = None
|
||||
PLANNING_PRESETS = {}
|
||||
if PlanningConfig and self.planning is not None:
|
||||
self._planning_config = resolve(
|
||||
value=self.planning, param_name="planning",
|
||||
config_class=PlanningConfig, presets=PLANNING_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve hooks (NEW for feature parity)
|
||||
try:
|
||||
from ..config.feature_configs import HooksConfig
|
||||
except ImportError:
|
||||
HooksConfig = None
|
||||
if HooksConfig and self.hooks is not None:
|
||||
# Hooks don't have presets, just config class
|
||||
if isinstance(self.hooks, list):
|
||||
self._hooks_config = HooksConfig(callbacks=self.hooks)
|
||||
elif hasattr(self.hooks, 'callbacks'):
|
||||
self._hooks_config = self.hooks
|
||||
else:
|
||||
self._hooks_config = self.hooks
|
||||
|
||||
# Resolve caching (NEW for feature parity)
|
||||
try:
|
||||
from ..config.feature_configs import CachingConfig
|
||||
from ..config.presets import CACHING_PRESETS
|
||||
except ImportError:
|
||||
CachingConfig = None
|
||||
CACHING_PRESETS = {}
|
||||
if CachingConfig and self.caching is not None:
|
||||
self._caching_config = resolve(
|
||||
value=self.caching, param_name="caching",
|
||||
config_class=CachingConfig, presets=CACHING_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Property accessors for backward compatibility
|
||||
@property
|
||||
@@ -507,6 +571,8 @@ class Workflow:
|
||||
guardrails: Optional[Any] = None # Union[bool, Callable, GuardrailConfig] - validation
|
||||
web: Optional[Any] = None # Union[bool, WebConfig] - web search/fetch
|
||||
reflection: Optional[Any] = None # Union[bool, ReflectionConfig] - self-reflection
|
||||
execution: Optional[Any] = None # Union[str, ExecutionConfig] - execution control
|
||||
caching: Optional[Any] = None # Union[bool, CachingConfig] - caching
|
||||
|
||||
# Status tracking
|
||||
status: str = "not_started" # not_started, running, completed, failed
|
||||
|
||||
@@ -0,0 +1,232 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Detailed profiler to identify the exact source of streaming delay.
|
||||
Traces every step from agent.start() to HTTP request.
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
import functools
|
||||
|
||||
os.environ['LOGLEVEL'] = 'DEBUG'
|
||||
|
||||
# Microsecond precision timestamps
|
||||
def ts():
|
||||
return time.perf_counter()
|
||||
|
||||
start_time = ts()
|
||||
|
||||
def log(msg):
|
||||
elapsed = (ts() - start_time) * 1000
|
||||
print(f"[{elapsed:8.2f}ms] {msg}")
|
||||
|
||||
log("Script starting...")
|
||||
|
||||
# ============================================================
|
||||
# PATCH 1: OpenAI client initialization
|
||||
# ============================================================
|
||||
import openai
|
||||
|
||||
original_openai_init = openai.OpenAI.__init__
|
||||
|
||||
@functools.wraps(original_openai_init)
|
||||
def traced_openai_init(self, *args, **kwargs):
|
||||
t0 = ts()
|
||||
result = original_openai_init(self, *args, **kwargs)
|
||||
log(f"OpenAI.__init__() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
openai.OpenAI.__init__ = traced_openai_init
|
||||
|
||||
# ============================================================
|
||||
# PATCH 2: OpenAI completions.create
|
||||
# ============================================================
|
||||
original_create = openai.resources.chat.completions.Completions.create
|
||||
|
||||
@functools.wraps(original_create)
|
||||
def traced_create(self, *args, **kwargs):
|
||||
log(f">>> OpenAI.create() CALLED - stream={kwargs.get('stream', False)}")
|
||||
t0 = ts()
|
||||
result = original_create(self, *args, **kwargs)
|
||||
log(f"<<< OpenAI.create() RETURNED in {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
openai.resources.chat.completions.Completions.create = traced_create
|
||||
|
||||
# ============================================================
|
||||
# PATCH 3: httpx.Client.send (actual HTTP request)
|
||||
# ============================================================
|
||||
import httpx
|
||||
|
||||
original_send = httpx.Client.send
|
||||
|
||||
@functools.wraps(original_send)
|
||||
def traced_send(self, request, *args, **kwargs):
|
||||
log(f">>> HTTPX.send() {request.method} {request.url}")
|
||||
t0 = ts()
|
||||
result = original_send(self, request, *args, **kwargs)
|
||||
log(f"<<< HTTPX.send() returned in {(ts()-t0)*1000:.2f}ms - status={result.status_code}")
|
||||
return result
|
||||
|
||||
httpx.Client.send = traced_send
|
||||
|
||||
# ============================================================
|
||||
# PATCH 4: Rich Live display
|
||||
# ============================================================
|
||||
from rich.live import Live
|
||||
|
||||
original_live_init = Live.__init__
|
||||
original_live_enter = Live.__enter__
|
||||
original_live_exit = Live.__exit__
|
||||
|
||||
@functools.wraps(original_live_init)
|
||||
def traced_live_init(self, *args, **kwargs):
|
||||
log(f">>> Live.__init__() called")
|
||||
t0 = ts()
|
||||
result = original_live_init(self, *args, **kwargs)
|
||||
log(f"<<< Live.__init__() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
@functools.wraps(original_live_enter)
|
||||
def traced_live_enter(self):
|
||||
log(f">>> Live.__enter__() called")
|
||||
t0 = ts()
|
||||
result = original_live_enter(self)
|
||||
log(f"<<< Live.__enter__() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
@functools.wraps(original_live_exit)
|
||||
def traced_live_exit(self, *args):
|
||||
log(f">>> Live.__exit__() called")
|
||||
t0 = ts()
|
||||
result = original_live_exit(self, *args)
|
||||
log(f"<<< Live.__exit__() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
Live.__init__ = traced_live_init
|
||||
Live.__enter__ = traced_live_enter
|
||||
Live.__exit__ = traced_live_exit
|
||||
|
||||
log("Patches applied, importing praisonaiagents...")
|
||||
|
||||
# ============================================================
|
||||
# Import and trace Agent
|
||||
# ============================================================
|
||||
t0 = ts()
|
||||
from praisonaiagents import Agent
|
||||
log(f"Agent import took {(ts()-t0)*1000:.2f}ms")
|
||||
|
||||
# ============================================================
|
||||
# PATCH 5: Agent methods
|
||||
# ============================================================
|
||||
from praisonaiagents.agent.agent import Agent as AgentClass
|
||||
|
||||
original_chat_completion = AgentClass._chat_completion
|
||||
original_format_tools = AgentClass._format_tools_for_completion
|
||||
|
||||
@functools.wraps(original_chat_completion)
|
||||
def traced_chat_completion(self, messages, temperature=1.0, tools=None, stream=True,
|
||||
reasoning_steps=False, task_name=None, task_description=None, task_id=None):
|
||||
log(f">>> Agent._chat_completion() stream={stream}, _using_custom_llm={self._using_custom_llm}")
|
||||
t0 = ts()
|
||||
result = original_chat_completion(self, messages, temperature, tools, stream,
|
||||
reasoning_steps, task_name, task_description, task_id)
|
||||
log(f"<<< Agent._chat_completion() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
@functools.wraps(original_format_tools)
|
||||
def traced_format_tools(self, tools):
|
||||
log(f">>> Agent._format_tools_for_completion() tools={tools}")
|
||||
t0 = ts()
|
||||
result = original_format_tools(self, tools)
|
||||
log(f"<<< Agent._format_tools_for_completion() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
AgentClass._chat_completion = traced_chat_completion
|
||||
AgentClass._format_tools_for_completion = traced_format_tools
|
||||
|
||||
# ============================================================
|
||||
# PATCH 6: OpenAIClient methods
|
||||
# ============================================================
|
||||
from praisonaiagents.llm.openai_client import OpenAIClient
|
||||
|
||||
original_chat_with_tools = OpenAIClient.chat_completion_with_tools
|
||||
original_process_stream = OpenAIClient.process_stream_response
|
||||
original_create_completion = OpenAIClient.create_completion
|
||||
original_format_tools_client = OpenAIClient.format_tools
|
||||
|
||||
@functools.wraps(original_chat_with_tools)
|
||||
def traced_chat_with_tools(self, *args, **kwargs):
|
||||
log(f">>> OpenAIClient.chat_completion_with_tools() stream={kwargs.get('stream', True)}")
|
||||
t0 = ts()
|
||||
result = original_chat_with_tools(self, *args, **kwargs)
|
||||
log(f"<<< OpenAIClient.chat_completion_with_tools() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
@functools.wraps(original_process_stream)
|
||||
def traced_process_stream(self, *args, **kwargs):
|
||||
log(f">>> OpenAIClient.process_stream_response()")
|
||||
t0 = ts()
|
||||
result = original_process_stream(self, *args, **kwargs)
|
||||
log(f"<<< OpenAIClient.process_stream_response() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
@functools.wraps(original_create_completion)
|
||||
def traced_create_completion(self, *args, **kwargs):
|
||||
log(f">>> OpenAIClient.create_completion() stream={kwargs.get('stream', False)}")
|
||||
t0 = ts()
|
||||
result = original_create_completion(self, *args, **kwargs)
|
||||
log(f"<<< OpenAIClient.create_completion() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
@functools.wraps(original_format_tools_client)
|
||||
def traced_format_tools_client(self, tools):
|
||||
log(f">>> OpenAIClient.format_tools() tools count={len(tools) if tools else 0}")
|
||||
t0 = ts()
|
||||
result = original_format_tools_client(self, tools)
|
||||
log(f"<<< OpenAIClient.format_tools() took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
OpenAIClient.chat_completion_with_tools = traced_chat_with_tools
|
||||
OpenAIClient.process_stream_response = traced_process_stream
|
||||
OpenAIClient.create_completion = traced_create_completion
|
||||
OpenAIClient.format_tools = traced_format_tools_client
|
||||
|
||||
# ============================================================
|
||||
# PATCH 7: sync_client property (lazy init)
|
||||
# ============================================================
|
||||
original_sync_client_getter = OpenAIClient.sync_client.fget
|
||||
|
||||
def traced_sync_client_getter(self):
|
||||
log(f">>> OpenAIClient.sync_client property accessed")
|
||||
t0 = ts()
|
||||
result = original_sync_client_getter(self)
|
||||
log(f"<<< OpenAIClient.sync_client took {(ts()-t0)*1000:.2f}ms")
|
||||
return result
|
||||
|
||||
OpenAIClient.sync_client = property(traced_sync_client_getter)
|
||||
|
||||
log("All patches applied. Creating agent...")
|
||||
|
||||
# ============================================================
|
||||
# RUN THE TEST
|
||||
# ============================================================
|
||||
t0 = ts()
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant"
|
||||
)
|
||||
log(f"Agent created in {(ts()-t0)*1000:.2f}ms")
|
||||
log(f"Agent.stream={agent.stream}, Agent.verbose={agent.verbose}")
|
||||
|
||||
log("=" * 60)
|
||||
log("Starting agent.start()...")
|
||||
log("=" * 60)
|
||||
|
||||
t0 = ts()
|
||||
result = agent.start("Say hello in one word")
|
||||
log(f"agent.start() completed in {(ts()-t0)*1000:.2f}ms")
|
||||
|
||||
log("=" * 60)
|
||||
log("DONE")
|
||||
log("=" * 60)
|
||||
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "praisonaiagents"
|
||||
version = "0.10.10"
|
||||
version = "0.11.4"
|
||||
description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@@ -0,0 +1,24 @@
|
||||
"""
|
||||
Streaming Example with TTFT Metrics
|
||||
|
||||
This example demonstrates true pass-through streaming with timing metrics.
|
||||
When verbose output is enabled, tokens are displayed as they arrive from the provider.
|
||||
|
||||
Key timing metrics:
|
||||
- TTFT (Time To First Token): Time from request to first token received
|
||||
- Stream Duration: Time from first to last token
|
||||
- Total Time: End-to-end request time
|
||||
"""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.config import OutputConfig
|
||||
|
||||
# Create agent with verbose output (shows streaming progress)
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
llm="gpt-4o-mini",
|
||||
output=OutputConfig(verbose=True) # Show generation progress
|
||||
)
|
||||
|
||||
# Run the agent - verbose mode shows streaming progress via Rich Live display
|
||||
result = agent.start("Write a short paragraph about the history of computing")
|
||||
print(f"\n--- Response ---\n{result}")
|
||||
@@ -1,11 +0,0 @@
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Use chat method with stream=True for streaming responses
|
||||
for chunk in agent.chat("Write a short paragraph about the history of computing", stream=True):
|
||||
print(chunk, end="", flush=True)
|
||||
print() # Final newline
|
||||
@@ -179,25 +179,27 @@ class TestAgentWebFetchParameter:
|
||||
"""Test the web_fetch parameter in Agent class."""
|
||||
|
||||
def test_agent_init_with_web_fetch_true(self):
|
||||
"""Test Agent initialization with web_fetch=True."""
|
||||
"""Test Agent initialization with web=WebConfig(fetch=True)."""
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
agent = Agent(
|
||||
name="Test Agent",
|
||||
llm="anthropic/claude-3-5-sonnet-latest",
|
||||
web_fetch=True
|
||||
web=WebConfig(fetch=True)
|
||||
)
|
||||
assert agent.web_fetch is True
|
||||
|
||||
def test_agent_init_with_web_fetch_dict(self):
|
||||
"""Test Agent initialization with web_fetch as dict."""
|
||||
"""Test Agent initialization with web=WebConfig(fetch=True)."""
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
web_fetch_config = {"max_uses": 10, "allowed_domains": ["example.com"]}
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
# Now using consolidated web= param with WebConfig
|
||||
agent = Agent(
|
||||
name="Test Agent",
|
||||
llm="anthropic/claude-3-5-sonnet-latest",
|
||||
web_fetch=web_fetch_config
|
||||
web=WebConfig(fetch=True)
|
||||
)
|
||||
assert agent.web_fetch == web_fetch_config
|
||||
assert agent.web_fetch is True
|
||||
|
||||
def test_agent_init_without_web_fetch(self):
|
||||
"""Test Agent initialization without web_fetch."""
|
||||
@@ -208,10 +210,11 @@ class TestAgentWebFetchParameter:
|
||||
def test_agent_passes_web_fetch_to_llm(self):
|
||||
"""Test that Agent passes web_fetch to LLM instance."""
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
agent = Agent(
|
||||
name="Test Agent",
|
||||
llm="anthropic/claude-3-5-sonnet-latest",
|
||||
web_fetch=True
|
||||
web=WebConfig(fetch=True)
|
||||
)
|
||||
assert agent.llm_instance.web_fetch is True
|
||||
|
||||
@@ -270,12 +273,13 @@ class TestWebFetchIntegration:
|
||||
def test_web_fetch_with_anthropic(self):
|
||||
"""Test actual web fetch with Anthropic API."""
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
|
||||
agent = Agent(
|
||||
name="Web Fetch Agent",
|
||||
instructions="You are a helpful assistant that can fetch web content.",
|
||||
llm="anthropic/claude-3-5-sonnet-latest",
|
||||
web_fetch=True
|
||||
web=WebConfig(fetch=True)
|
||||
)
|
||||
|
||||
# This would make an actual API call
|
||||
|
||||
@@ -0,0 +1,123 @@
|
||||
"""
|
||||
Tests for wrapper agent modernization - ensuring legacy args are mapped to consolidated params.
|
||||
|
||||
TDD: These tests verify that wrapper classes (PromptExpanderAgent, QueryRewriterAgent)
|
||||
correctly use consolidated params (output=) instead of legacy args (verbose=, markdown=).
|
||||
"""
|
||||
|
||||
|
||||
class TestPromptExpanderAgentModernization:
|
||||
"""Test PromptExpanderAgent uses consolidated output param."""
|
||||
|
||||
def test_agent_uses_output_config_not_legacy_args(self):
|
||||
"""PromptExpanderAgent should pass output= to Agent, not verbose=/markdown=."""
|
||||
from praisonaiagents.agent.prompt_expander_agent import PromptExpanderAgent
|
||||
|
||||
# Create wrapper with verbose=True
|
||||
expander = PromptExpanderAgent(verbose=True)
|
||||
|
||||
# Access the lazy-initialized agent
|
||||
agent = expander.agent
|
||||
|
||||
# Verify: Agent should have output config set, not legacy verbose/markdown as direct args
|
||||
# The Agent stores resolved output in self.verbose and self.markdown after resolution
|
||||
# But the key is that the wrapper passed output= dict, not verbose=/markdown= directly
|
||||
assert hasattr(agent, 'verbose')
|
||||
assert hasattr(agent, 'markdown')
|
||||
# verbose should be True (from output config)
|
||||
assert agent.verbose == True
|
||||
# markdown should be False (from output config)
|
||||
assert agent.markdown == False
|
||||
|
||||
def test_agent_verbose_false_propagates(self):
|
||||
"""PromptExpanderAgent with verbose=False should propagate correctly."""
|
||||
from praisonaiagents.agent.prompt_expander_agent import PromptExpanderAgent
|
||||
|
||||
expander = PromptExpanderAgent(verbose=False)
|
||||
agent = expander.agent
|
||||
|
||||
assert agent.verbose == False
|
||||
assert agent.markdown == False
|
||||
|
||||
|
||||
class TestQueryRewriterAgentModernization:
|
||||
"""Test QueryRewriterAgent uses consolidated output param."""
|
||||
|
||||
def test_agent_uses_output_config_not_legacy_args(self):
|
||||
"""QueryRewriterAgent should pass output= to Agent, not verbose=/markdown=."""
|
||||
from praisonaiagents.agent.query_rewriter_agent import QueryRewriterAgent
|
||||
|
||||
# Create wrapper with verbose=True
|
||||
rewriter = QueryRewriterAgent(verbose=True)
|
||||
|
||||
# Access the lazy-initialized agent
|
||||
agent = rewriter.agent
|
||||
|
||||
# Verify output config was applied
|
||||
assert agent.verbose == True
|
||||
assert agent.markdown == False
|
||||
|
||||
def test_agent_verbose_false_propagates(self):
|
||||
"""QueryRewriterAgent with verbose=False should propagate correctly."""
|
||||
from praisonaiagents.agent.query_rewriter_agent import QueryRewriterAgent
|
||||
|
||||
rewriter = QueryRewriterAgent(verbose=False)
|
||||
agent = rewriter.agent
|
||||
|
||||
assert agent.verbose == False
|
||||
assert agent.markdown == False
|
||||
|
||||
|
||||
class TestProcessManagerAgentModernization:
|
||||
"""Test Process class manager agents use consolidated params."""
|
||||
|
||||
def test_manager_agent_creation_uses_consolidated_params(self):
|
||||
"""Process manager agent should use output= and reflection=, not legacy args."""
|
||||
# This is a structural test - we verify the code pattern
|
||||
import inspect
|
||||
from praisonaiagents.process.process import Process
|
||||
|
||||
# Get source of hierarchical method (sync version)
|
||||
source = inspect.getsource(Process.hierarchical)
|
||||
|
||||
# After fix: should contain output= and reflection=
|
||||
assert 'output=' in source, "Process.hierarchical should use output= consolidated param"
|
||||
assert 'reflection=' in source, "Process.hierarchical should use reflection= consolidated param"
|
||||
|
||||
# Should NOT contain legacy args passed to Agent
|
||||
assert 'self_reflect=' not in source, "Process.hierarchical should not use legacy self_reflect="
|
||||
|
||||
|
||||
class TestAutoAgentsConsolidatedParams:
|
||||
"""Test AutoAgents already uses consolidated params correctly."""
|
||||
|
||||
def test_autoagents_has_consolidated_params(self):
|
||||
"""AutoAgents should accept consolidated params."""
|
||||
import inspect
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
|
||||
# Should have consolidated params
|
||||
assert 'output' in params
|
||||
assert 'reflection' in params
|
||||
assert 'caching' in params
|
||||
assert 'knowledge' in params
|
||||
assert 'execution' in params
|
||||
assert 'guardrails' in params
|
||||
assert 'web' in params
|
||||
assert 'hooks' in params
|
||||
|
||||
def test_autoagents_consolidated_takes_precedence(self):
|
||||
"""AutoAgents consolidated params should override legacy params."""
|
||||
import inspect
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
|
||||
# Get source of _create_agents_and_tasks
|
||||
source = inspect.getsource(AutoAgents._create_agents_and_tasks)
|
||||
|
||||
# Should pass consolidated params to Agent
|
||||
assert 'output=self._output' in source
|
||||
assert 'reflection=self._reflection' in source
|
||||
assert 'caching=self._caching' in source
|
||||
@@ -0,0 +1,113 @@
|
||||
"""
|
||||
TDD Tests for AutoAgents SDK Parity.
|
||||
|
||||
Tests that AutoAgents correctly maps legacy params to consolidated params
|
||||
and passes them through to Agent instances.
|
||||
"""
|
||||
import pytest
|
||||
from unittest.mock import patch, MagicMock
|
||||
|
||||
|
||||
class TestAutoAgentsLegacyParamMapping:
|
||||
"""Test that AutoAgents maps legacy params to consolidated params."""
|
||||
|
||||
def test_autoagents_accepts_legacy_verbose_param(self):
|
||||
"""AutoAgents should accept verbose param (legacy)."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
assert 'verbose' in params
|
||||
|
||||
def test_autoagents_accepts_legacy_markdown_param(self):
|
||||
"""AutoAgents should accept markdown param (legacy)."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
assert 'markdown' in params
|
||||
|
||||
def test_autoagents_accepts_legacy_self_reflect_param(self):
|
||||
"""AutoAgents should accept self_reflect param (legacy)."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
assert 'self_reflect' in params
|
||||
|
||||
def test_autoagents_accepts_legacy_cache_param(self):
|
||||
"""AutoAgents should accept cache param (legacy)."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
assert 'cache' in params
|
||||
|
||||
def test_autoagents_accepts_consolidated_output_param(self):
|
||||
"""AutoAgents should accept consolidated output param."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
# This test will FAIL initially - AutoAgents doesn't have output param yet
|
||||
assert 'output' in params, "AutoAgents should accept consolidated 'output' param"
|
||||
|
||||
def test_autoagents_accepts_consolidated_reflection_param(self):
|
||||
"""AutoAgents should accept consolidated reflection param."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
# This test will FAIL initially - AutoAgents doesn't have reflection param yet
|
||||
assert 'reflection' in params, "AutoAgents should accept consolidated 'reflection' param"
|
||||
|
||||
def test_autoagents_accepts_consolidated_caching_param(self):
|
||||
"""AutoAgents should accept consolidated caching param."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
# This test will FAIL initially - AutoAgents doesn't have caching param yet
|
||||
assert 'caching' in params, "AutoAgents should accept consolidated 'caching' param"
|
||||
|
||||
def test_autoagents_accepts_consolidated_knowledge_param(self):
|
||||
"""AutoAgents should accept consolidated knowledge param."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
sig = inspect.signature(AutoAgents.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
# This test will FAIL initially - AutoAgents doesn't have knowledge param yet
|
||||
assert 'knowledge' in params, "AutoAgents should accept consolidated 'knowledge' param"
|
||||
|
||||
|
||||
class TestAutoAgentsParamPrecedence:
|
||||
"""Test that consolidated params take precedence over legacy params."""
|
||||
|
||||
def test_consolidated_output_overrides_legacy_verbose(self):
|
||||
"""Consolidated output param should override legacy verbose."""
|
||||
# This tests the mapping logic once implemented
|
||||
pass # Placeholder - will be implemented after AutoAgents is updated
|
||||
|
||||
def test_consolidated_reflection_overrides_legacy_self_reflect(self):
|
||||
"""Consolidated reflection param should override legacy self_reflect."""
|
||||
pass # Placeholder
|
||||
|
||||
def test_consolidated_caching_overrides_legacy_cache(self):
|
||||
"""Consolidated caching param should override legacy cache."""
|
||||
pass # Placeholder
|
||||
|
||||
|
||||
class TestAutoAgentsAgentCreation:
|
||||
"""Test that AutoAgents creates Agent instances with correct params."""
|
||||
|
||||
@patch('praisonaiagents.agents.autoagents.AutoAgents._generate_config')
|
||||
@patch('praisonaiagents.agents.autoagents.AutoAgents._create_agents_and_tasks')
|
||||
def test_agent_receives_consolidated_params(self, mock_create, mock_config):
|
||||
"""Agents created by AutoAgents should receive consolidated params."""
|
||||
# Setup mocks to avoid LLM calls
|
||||
mock_config.return_value = MagicMock()
|
||||
mock_create.return_value = ([], [])
|
||||
|
||||
# This test verifies the param passing logic
|
||||
# Will be more detailed once implementation is done
|
||||
pass
|
||||
@@ -0,0 +1,124 @@
|
||||
"""
|
||||
TDD tests for delegator.py protocol compliance.
|
||||
|
||||
Tests that SubagentDelegator creates agents using consolidated params
|
||||
instead of legacy params like verbose=, max_iter=.
|
||||
"""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
|
||||
class TestDelegatorProtocolCompliance:
|
||||
"""Test that delegator uses consolidated params when creating agents."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_agent_uses_output_not_verbose(self):
|
||||
"""Delegator should use output='silent' instead of verbose=False."""
|
||||
from praisonaiagents.agents.delegator import SubagentDelegator, DelegationTask
|
||||
from praisonaiagents.agents.profiles import AgentProfile
|
||||
|
||||
# Create a delegator
|
||||
delegator = SubagentDelegator()
|
||||
|
||||
# Create a profile and task
|
||||
profile = AgentProfile(
|
||||
name="test_agent",
|
||||
system_prompt="Test prompt",
|
||||
max_steps=10,
|
||||
)
|
||||
task = DelegationTask(
|
||||
task_id="test-1",
|
||||
agent_name="test_agent",
|
||||
objective="Test task",
|
||||
max_steps=5,
|
||||
)
|
||||
|
||||
# Mock Agent to capture how it's called (Agent is imported inside _create_agent)
|
||||
with patch('praisonaiagents.agent.agent.Agent') as MockAgent:
|
||||
MockAgent.return_value = Mock()
|
||||
|
||||
await delegator._create_agent(profile, task)
|
||||
|
||||
# Verify Agent was called
|
||||
MockAgent.assert_called_once()
|
||||
call_kwargs = MockAgent.call_args[1]
|
||||
|
||||
# Should NOT have verbose= param
|
||||
assert 'verbose' not in call_kwargs, "Should not use legacy verbose= param"
|
||||
|
||||
# Should have output= param with 'silent' preset
|
||||
assert 'output' in call_kwargs, "Should use consolidated output= param"
|
||||
assert call_kwargs['output'] == 'silent', "Should use output='silent' for quiet mode"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_agent_uses_execution_not_max_iter(self):
|
||||
"""Delegator should use execution= instead of max_iter=."""
|
||||
from praisonaiagents.agents.delegator import SubagentDelegator, DelegationTask
|
||||
from praisonaiagents.agents.profiles import AgentProfile
|
||||
|
||||
delegator = SubagentDelegator()
|
||||
|
||||
profile = AgentProfile(
|
||||
name="test_agent",
|
||||
system_prompt="Test prompt",
|
||||
max_steps=10,
|
||||
)
|
||||
task = DelegationTask(
|
||||
task_id="test-2",
|
||||
agent_name="test_agent",
|
||||
objective="Test task",
|
||||
max_steps=5,
|
||||
)
|
||||
|
||||
with patch('praisonaiagents.agent.agent.Agent') as MockAgent:
|
||||
MockAgent.return_value = Mock()
|
||||
|
||||
await delegator._create_agent(profile, task)
|
||||
|
||||
call_kwargs = MockAgent.call_args[1]
|
||||
|
||||
# Should NOT have max_iter= param
|
||||
assert 'max_iter' not in call_kwargs, "Should not use legacy max_iter= param"
|
||||
|
||||
# Should have execution= param with max_iter in config
|
||||
assert 'execution' in call_kwargs, "Should use consolidated execution= param"
|
||||
exec_config = call_kwargs['execution']
|
||||
assert isinstance(exec_config, dict), "execution should be a dict config"
|
||||
assert 'max_iter' in exec_config, "execution config should contain max_iter"
|
||||
assert exec_config['max_iter'] == 5, "max_iter should be min(task.max_steps, profile.max_steps)"
|
||||
|
||||
|
||||
class TestDelegatorBackwardCompatibility:
|
||||
"""Test that delegator still works correctly after modernization."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_agent_returns_valid_agent(self):
|
||||
"""Created agent should be usable."""
|
||||
from praisonaiagents.agents.delegator import SubagentDelegator, DelegationTask
|
||||
from praisonaiagents.agents.profiles import AgentProfile
|
||||
|
||||
delegator = SubagentDelegator()
|
||||
|
||||
profile = AgentProfile(
|
||||
name="test_agent",
|
||||
system_prompt="You are a helpful assistant.",
|
||||
max_steps=10,
|
||||
)
|
||||
task = DelegationTask(
|
||||
task_id="test-3",
|
||||
agent_name="test_agent",
|
||||
objective="Say hello",
|
||||
max_steps=5,
|
||||
)
|
||||
|
||||
with patch('praisonaiagents.agent.agent.Agent') as MockAgent:
|
||||
mock_agent = Mock()
|
||||
mock_agent.chat = Mock(return_value="Hello!")
|
||||
MockAgent.return_value = mock_agent
|
||||
|
||||
agent = await delegator._create_agent(profile, task)
|
||||
|
||||
# Agent should be returned
|
||||
assert agent is not None
|
||||
assert agent == mock_agent
|
||||
@@ -0,0 +1 @@
|
||||
"""Unit tests for streaming module."""
|
||||
@@ -0,0 +1,387 @@
|
||||
"""
|
||||
Unit tests for streaming events module.
|
||||
|
||||
Tests cover:
|
||||
- StreamEvent creation and representation
|
||||
- StreamEventType enum values
|
||||
- StreamMetrics calculations (TTFT, stream duration, total time)
|
||||
- StreamEventEmitter callback management
|
||||
- create_text_printer_callback and create_metrics_callback helpers
|
||||
"""
|
||||
|
||||
import time
|
||||
from praisonaiagents.streaming.events import (
|
||||
StreamEvent,
|
||||
StreamEventType,
|
||||
StreamMetrics,
|
||||
StreamEventEmitter,
|
||||
create_text_printer_callback,
|
||||
create_metrics_callback,
|
||||
)
|
||||
|
||||
|
||||
class TestStreamEventType:
|
||||
"""Tests for StreamEventType enum."""
|
||||
|
||||
def test_event_types_exist(self):
|
||||
"""All required event types should exist."""
|
||||
assert StreamEventType.REQUEST_START.value == "request_start"
|
||||
assert StreamEventType.HEADERS_RECEIVED.value == "headers_received"
|
||||
assert StreamEventType.FIRST_TOKEN.value == "first_token"
|
||||
assert StreamEventType.DELTA_TEXT.value == "delta_text"
|
||||
assert StreamEventType.DELTA_TOOL_CALL.value == "delta_tool_call"
|
||||
assert StreamEventType.TOOL_CALL_END.value == "tool_call_end"
|
||||
assert StreamEventType.LAST_TOKEN.value == "last_token"
|
||||
assert StreamEventType.STREAM_END.value == "stream_end"
|
||||
assert StreamEventType.ERROR.value == "error"
|
||||
|
||||
|
||||
class TestStreamEvent:
|
||||
"""Tests for StreamEvent dataclass."""
|
||||
|
||||
def test_create_basic_event(self):
|
||||
"""Create a basic event with type only."""
|
||||
event = StreamEvent(type=StreamEventType.REQUEST_START)
|
||||
assert event.type == StreamEventType.REQUEST_START
|
||||
assert event.timestamp > 0
|
||||
assert event.content is None
|
||||
assert event.tool_call is None
|
||||
assert event.metadata is None
|
||||
assert event.error is None
|
||||
|
||||
def test_create_event_with_content(self):
|
||||
"""Create an event with content."""
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.DELTA_TEXT,
|
||||
content="Hello"
|
||||
)
|
||||
assert event.type == StreamEventType.DELTA_TEXT
|
||||
assert event.content == "Hello"
|
||||
|
||||
def test_create_event_with_tool_call(self):
|
||||
"""Create an event with tool call data."""
|
||||
tool_data = {"name": "calculator", "arguments": '{"x": 1}'}
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.DELTA_TOOL_CALL,
|
||||
tool_call=tool_data
|
||||
)
|
||||
assert event.type == StreamEventType.DELTA_TOOL_CALL
|
||||
assert event.tool_call == tool_data
|
||||
|
||||
def test_create_event_with_metadata(self):
|
||||
"""Create an event with metadata."""
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.REQUEST_START,
|
||||
metadata={"model": "gpt-4o-mini", "message_count": 2}
|
||||
)
|
||||
assert event.metadata["model"] == "gpt-4o-mini"
|
||||
assert event.metadata["message_count"] == 2
|
||||
|
||||
def test_create_error_event(self):
|
||||
"""Create an error event."""
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.ERROR,
|
||||
error="Connection timeout"
|
||||
)
|
||||
assert event.type == StreamEventType.ERROR
|
||||
assert event.error == "Connection timeout"
|
||||
|
||||
def test_event_repr(self):
|
||||
"""Event repr should be informative."""
|
||||
event = StreamEvent(
|
||||
type=StreamEventType.DELTA_TEXT,
|
||||
content="Hello world"
|
||||
)
|
||||
repr_str = repr(event)
|
||||
assert "DELTA_TEXT" in repr_str or "delta_text" in repr_str
|
||||
assert "Hello world" in repr_str
|
||||
|
||||
|
||||
class TestStreamMetrics:
|
||||
"""Tests for StreamMetrics dataclass."""
|
||||
|
||||
def test_default_metrics(self):
|
||||
"""Default metrics should be zero."""
|
||||
metrics = StreamMetrics()
|
||||
assert metrics.request_start == 0.0
|
||||
assert metrics.headers_received == 0.0
|
||||
assert metrics.first_token == 0.0
|
||||
assert metrics.last_token == 0.0
|
||||
assert metrics.stream_end == 0.0
|
||||
assert metrics.token_count == 0
|
||||
|
||||
def test_ttft_calculation(self):
|
||||
"""TTFT should be first_token - request_start."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.request_start = 100.0
|
||||
metrics.first_token = 100.5
|
||||
assert metrics.ttft == 0.5
|
||||
|
||||
def test_ttft_zero_when_no_first_token(self):
|
||||
"""TTFT should be 0 when first_token not set."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.request_start = 100.0
|
||||
assert metrics.ttft == 0.0
|
||||
|
||||
def test_stream_duration_calculation(self):
|
||||
"""Stream duration should be last_token - first_token."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.first_token = 100.0
|
||||
metrics.last_token = 102.0
|
||||
assert metrics.stream_duration == 2.0
|
||||
|
||||
def test_total_time_calculation(self):
|
||||
"""Total time should be stream_end - request_start."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.request_start = 100.0
|
||||
metrics.stream_end = 103.0
|
||||
assert metrics.total_time == 3.0
|
||||
|
||||
def test_tokens_per_second(self):
|
||||
"""Tokens per second calculation."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.first_token = 100.0
|
||||
metrics.last_token = 102.0 # 2 second duration
|
||||
metrics.token_count = 100
|
||||
assert metrics.tokens_per_second == 50.0
|
||||
|
||||
def test_tokens_per_second_zero_duration(self):
|
||||
"""Tokens per second should be 0 when duration is 0."""
|
||||
metrics = StreamMetrics()
|
||||
assert metrics.tokens_per_second == 0.0
|
||||
|
||||
def test_update_from_event(self):
|
||||
"""Metrics should update from events."""
|
||||
metrics = StreamMetrics()
|
||||
|
||||
# Request start
|
||||
event1 = StreamEvent(type=StreamEventType.REQUEST_START, timestamp=100.0)
|
||||
metrics.update_from_event(event1)
|
||||
assert metrics.request_start == 100.0
|
||||
|
||||
# Headers received
|
||||
event2 = StreamEvent(type=StreamEventType.HEADERS_RECEIVED, timestamp=100.2)
|
||||
metrics.update_from_event(event2)
|
||||
assert metrics.headers_received == 100.2
|
||||
|
||||
# First token
|
||||
event3 = StreamEvent(type=StreamEventType.FIRST_TOKEN, timestamp=100.5)
|
||||
metrics.update_from_event(event3)
|
||||
assert metrics.first_token == 100.5
|
||||
assert metrics.token_count == 1
|
||||
|
||||
# Delta text
|
||||
event4 = StreamEvent(type=StreamEventType.DELTA_TEXT, timestamp=100.6)
|
||||
metrics.update_from_event(event4)
|
||||
assert metrics.token_count == 2
|
||||
|
||||
# Last token
|
||||
event5 = StreamEvent(type=StreamEventType.LAST_TOKEN, timestamp=102.0)
|
||||
metrics.update_from_event(event5)
|
||||
assert metrics.last_token == 102.0
|
||||
|
||||
# Stream end
|
||||
event6 = StreamEvent(type=StreamEventType.STREAM_END, timestamp=102.1)
|
||||
metrics.update_from_event(event6)
|
||||
assert metrics.stream_end == 102.1
|
||||
|
||||
def test_to_dict(self):
|
||||
"""Metrics should convert to dict."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.request_start = 100.0
|
||||
metrics.first_token = 100.5
|
||||
metrics.last_token = 102.0
|
||||
metrics.stream_end = 102.1
|
||||
metrics.token_count = 50
|
||||
|
||||
d = metrics.to_dict()
|
||||
assert "ttft_ms" in d
|
||||
assert "stream_duration_ms" in d
|
||||
assert "total_time_ms" in d
|
||||
assert "token_count" in d
|
||||
assert "tokens_per_second" in d
|
||||
|
||||
def test_format_summary(self):
|
||||
"""Metrics should format as summary string."""
|
||||
metrics = StreamMetrics()
|
||||
metrics.request_start = 100.0
|
||||
metrics.first_token = 100.5
|
||||
metrics.last_token = 102.0
|
||||
metrics.stream_end = 102.1
|
||||
metrics.token_count = 50
|
||||
|
||||
summary = metrics.format_summary()
|
||||
assert "TTFT" in summary
|
||||
assert "Stream" in summary
|
||||
assert "Total" in summary
|
||||
assert "Tokens" in summary
|
||||
|
||||
|
||||
class TestStreamEventEmitter:
|
||||
"""Tests for StreamEventEmitter."""
|
||||
|
||||
def test_create_emitter(self):
|
||||
"""Create an emitter."""
|
||||
emitter = StreamEventEmitter()
|
||||
assert not emitter.has_callbacks
|
||||
|
||||
def test_add_callback(self):
|
||||
"""Add a callback."""
|
||||
emitter = StreamEventEmitter()
|
||||
events = []
|
||||
|
||||
def callback(event):
|
||||
events.append(event)
|
||||
|
||||
emitter.add_callback(callback)
|
||||
assert emitter.has_callbacks
|
||||
|
||||
def test_remove_callback(self):
|
||||
"""Remove a callback."""
|
||||
emitter = StreamEventEmitter()
|
||||
events = []
|
||||
|
||||
def callback(event):
|
||||
events.append(event)
|
||||
|
||||
emitter.add_callback(callback)
|
||||
emitter.remove_callback(callback)
|
||||
assert not emitter.has_callbacks
|
||||
|
||||
def test_emit_calls_callbacks(self):
|
||||
"""Emit should call all callbacks."""
|
||||
emitter = StreamEventEmitter()
|
||||
events1 = []
|
||||
events2 = []
|
||||
|
||||
emitter.add_callback(lambda e: events1.append(e))
|
||||
emitter.add_callback(lambda e: events2.append(e))
|
||||
|
||||
event = StreamEvent(type=StreamEventType.DELTA_TEXT, content="Hello")
|
||||
emitter.emit(event)
|
||||
|
||||
assert len(events1) == 1
|
||||
assert len(events2) == 1
|
||||
assert events1[0].content == "Hello"
|
||||
|
||||
def test_emit_with_metrics(self):
|
||||
"""Emit should update metrics when enabled."""
|
||||
emitter = StreamEventEmitter()
|
||||
emitter.enable_metrics()
|
||||
|
||||
emitter.emit(StreamEvent(type=StreamEventType.REQUEST_START, timestamp=100.0))
|
||||
emitter.emit(StreamEvent(type=StreamEventType.FIRST_TOKEN, timestamp=100.5))
|
||||
emitter.emit(StreamEvent(type=StreamEventType.STREAM_END, timestamp=102.0))
|
||||
|
||||
metrics = emitter.get_metrics()
|
||||
assert metrics is not None
|
||||
assert metrics.request_start == 100.0
|
||||
assert metrics.first_token == 100.5
|
||||
assert metrics.stream_end == 102.0
|
||||
|
||||
def test_callback_error_does_not_break_emission(self):
|
||||
"""Callback errors should not break other callbacks."""
|
||||
emitter = StreamEventEmitter()
|
||||
events = []
|
||||
|
||||
def bad_callback(event):
|
||||
raise ValueError("Test error")
|
||||
|
||||
def good_callback(event):
|
||||
events.append(event)
|
||||
|
||||
emitter.add_callback(bad_callback)
|
||||
emitter.add_callback(good_callback)
|
||||
|
||||
event = StreamEvent(type=StreamEventType.DELTA_TEXT)
|
||||
emitter.emit(event) # Should not raise
|
||||
|
||||
assert len(events) == 1
|
||||
|
||||
def test_reset_metrics(self):
|
||||
"""Reset metrics should create new metrics."""
|
||||
emitter = StreamEventEmitter()
|
||||
emitter.enable_metrics()
|
||||
|
||||
emitter.emit(StreamEvent(type=StreamEventType.REQUEST_START, timestamp=100.0))
|
||||
emitter.reset_metrics()
|
||||
|
||||
metrics = emitter.get_metrics()
|
||||
assert metrics.request_start == 0.0
|
||||
|
||||
|
||||
class TestHelperFunctions:
|
||||
"""Tests for helper functions."""
|
||||
|
||||
def test_create_text_printer_callback(self, capsys):
|
||||
"""Text printer callback should print content."""
|
||||
callback = create_text_printer_callback(flush=True)
|
||||
|
||||
callback(StreamEvent(type=StreamEventType.DELTA_TEXT, content="Hello"))
|
||||
callback(StreamEvent(type=StreamEventType.DELTA_TEXT, content=" World"))
|
||||
callback(StreamEvent(type=StreamEventType.STREAM_END))
|
||||
|
||||
captured = capsys.readouterr()
|
||||
assert "Hello World" in captured.out
|
||||
|
||||
def test_create_metrics_callback(self):
|
||||
"""Metrics callback should update metrics."""
|
||||
metrics = StreamMetrics()
|
||||
callback = create_metrics_callback(metrics)
|
||||
|
||||
callback(StreamEvent(type=StreamEventType.REQUEST_START, timestamp=100.0))
|
||||
callback(StreamEvent(type=StreamEventType.FIRST_TOKEN, timestamp=100.5))
|
||||
|
||||
assert metrics.request_start == 100.0
|
||||
assert metrics.first_token == 100.5
|
||||
|
||||
|
||||
class TestStreamingEventOrdering:
|
||||
"""Tests for event ordering and pass-through behavior."""
|
||||
|
||||
def test_events_emitted_immediately(self):
|
||||
"""Events should be emitted immediately, not buffered."""
|
||||
emitter = StreamEventEmitter()
|
||||
timestamps = []
|
||||
|
||||
def callback(event):
|
||||
timestamps.append((event.type, time.perf_counter()))
|
||||
|
||||
emitter.add_callback(callback)
|
||||
|
||||
# Simulate streaming with small delays
|
||||
emitter.emit(StreamEvent(type=StreamEventType.REQUEST_START))
|
||||
time.sleep(0.01)
|
||||
emitter.emit(StreamEvent(type=StreamEventType.FIRST_TOKEN))
|
||||
time.sleep(0.01)
|
||||
emitter.emit(StreamEvent(type=StreamEventType.DELTA_TEXT))
|
||||
|
||||
# Verify events were captured in order
|
||||
assert len(timestamps) == 3
|
||||
assert timestamps[0][0] == StreamEventType.REQUEST_START
|
||||
assert timestamps[1][0] == StreamEventType.FIRST_TOKEN
|
||||
assert timestamps[2][0] == StreamEventType.DELTA_TEXT
|
||||
|
||||
# Verify timestamps are increasing (no buffering)
|
||||
assert timestamps[0][1] < timestamps[1][1] < timestamps[2][1]
|
||||
|
||||
def test_no_buffering_before_first_token(self):
|
||||
"""Events should not be buffered before first token."""
|
||||
emitter = StreamEventEmitter()
|
||||
emitter.enable_metrics()
|
||||
|
||||
# Emit request start
|
||||
t1 = time.perf_counter()
|
||||
emitter.emit(StreamEvent(type=StreamEventType.REQUEST_START, timestamp=t1))
|
||||
|
||||
# Small delay (simulating network)
|
||||
time.sleep(0.05)
|
||||
|
||||
# Emit first token
|
||||
t2 = time.perf_counter()
|
||||
emitter.emit(StreamEvent(type=StreamEventType.FIRST_TOKEN, timestamp=t2))
|
||||
|
||||
metrics = emitter.get_metrics()
|
||||
|
||||
# TTFT should reflect the actual delay
|
||||
assert metrics.ttft >= 0.04 # Allow some tolerance
|
||||
@@ -0,0 +1,236 @@
|
||||
"""
|
||||
Tests for Gap Closure - LLM Consolidation + Parity
|
||||
|
||||
TDD: These tests define the expected behavior for:
|
||||
1. GAP A: No deprecation warnings for model/llm alias
|
||||
2. GAP B: YAML parser supports consolidated params
|
||||
3. GAP C: Wrapper agents use output= (not verbose/markdown)
|
||||
4. GAP D: AutoAgents uses consolidated llm= (not function_calling_llm)
|
||||
5. GAP E: model= and llm= are aliases with NO warnings
|
||||
"""
|
||||
import pytest
|
||||
import warnings
|
||||
|
||||
|
||||
class TestNoDeprecationWarnings:
|
||||
"""GAP A + E: No deprecation warnings for model/llm or legacy params."""
|
||||
|
||||
def test_no_warning_for_model_alias(self):
|
||||
"""model= should work without any deprecation warning."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(instructions="Test", model="gpt-4o-mini")
|
||||
|
||||
# Should NOT emit any deprecation warnings
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
def test_no_warning_for_llm_param(self):
|
||||
"""llm= should work without any deprecation warning."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(instructions="Test", llm="gpt-4o-mini")
|
||||
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
def test_no_warning_for_llm_config(self):
|
||||
"""llm_config= should work without deprecation warning (backward compat)."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(instructions="Test", llm_config={"temperature": 0.7})
|
||||
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
def test_no_warning_for_function_calling_llm(self):
|
||||
"""function_calling_llm= should work without deprecation warning (backward compat)."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(instructions="Test", function_calling_llm="gpt-4o-mini")
|
||||
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
def test_model_and_llm_are_equivalent(self):
|
||||
"""model= and llm= should produce identical behavior."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent1 = Agent(instructions="Test", llm="gpt-4o")
|
||||
agent2 = Agent(instructions="Test", model="gpt-4o")
|
||||
|
||||
assert agent1.llm == agent2.llm == "gpt-4o"
|
||||
|
||||
|
||||
class TestAutoAgentsConsolidation:
|
||||
"""GAP D: AutoAgents uses consolidated llm= (not function_calling_llm)."""
|
||||
|
||||
def test_autoagents_does_not_pass_function_calling_llm_to_agent(self):
|
||||
"""AutoAgents should not pass function_calling_llm= to Agent()."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
|
||||
# Get the source code of the _create_agents_and_tasks method
|
||||
source = inspect.getsource(AutoAgents._create_agents_and_tasks)
|
||||
|
||||
# Should NOT contain function_calling_llm= in Agent() call
|
||||
# This is a static analysis test
|
||||
assert "function_calling_llm=self.function_calling_llm" not in source, \
|
||||
"AutoAgents._create_agents_and_tasks still passes function_calling_llm= to Agent()"
|
||||
|
||||
def test_autoagents_accepts_llm_param(self):
|
||||
"""AutoAgents should accept llm= parameter."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
|
||||
# Should not raise
|
||||
auto = AutoAgents(instructions="Test task", llm="gpt-4o-mini")
|
||||
assert auto.llm == "gpt-4o-mini"
|
||||
|
||||
def test_autoagents_no_deprecation_warnings(self):
|
||||
"""AutoAgents should not emit deprecation warnings."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
auto = AutoAgents(
|
||||
instructions="Test task",
|
||||
llm="gpt-4o-mini",
|
||||
function_calling_llm="gpt-4o-mini" # Legacy param
|
||||
)
|
||||
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
|
||||
class TestYAMLParserConsolidation:
|
||||
"""GAP B: YAML parser supports consolidated params."""
|
||||
|
||||
def test_yaml_parser_maps_legacy_reflection_fields(self):
|
||||
"""YAML parser should map legacy reflect_llm/min_reflect/max_reflect to reflection config."""
|
||||
from praisonaiagents.workflows.yaml_parser import YAMLWorkflowParser
|
||||
|
||||
yaml_content = """
|
||||
roles:
|
||||
researcher:
|
||||
role: Researcher
|
||||
goal: Research topics
|
||||
backstory: Expert researcher
|
||||
reflect_llm: gpt-4o
|
||||
min_reflect: 2
|
||||
max_reflect: 5
|
||||
tasks:
|
||||
- description: Research AI
|
||||
expected_output: Report
|
||||
"""
|
||||
|
||||
import yaml
|
||||
config = yaml.safe_load(yaml_content)
|
||||
|
||||
parser = YAMLWorkflowParser()
|
||||
# The parser should handle legacy fields without error
|
||||
# and map them appropriately
|
||||
agent = parser._create_agent("researcher", config["roles"]["researcher"])
|
||||
|
||||
# Legacy fields should be stored for later use
|
||||
assert hasattr(agent, '_yaml_reflect_llm')
|
||||
assert hasattr(agent, '_yaml_min_reflect')
|
||||
assert hasattr(agent, '_yaml_max_reflect')
|
||||
|
||||
def test_yaml_parser_supports_new_reflection_structure(self):
|
||||
"""YAML parser should support new reflection: structure."""
|
||||
from praisonaiagents.workflows.yaml_parser import YAMLWorkflowParser
|
||||
|
||||
yaml_content = """
|
||||
roles:
|
||||
researcher:
|
||||
role: Researcher
|
||||
goal: Research topics
|
||||
backstory: Expert researcher
|
||||
reflection:
|
||||
enabled: true
|
||||
max_iterations: 5
|
||||
min_iterations: 2
|
||||
tasks:
|
||||
- description: Research AI
|
||||
expected_output: Report
|
||||
"""
|
||||
|
||||
import yaml
|
||||
config = yaml.safe_load(yaml_content)
|
||||
|
||||
parser = YAMLWorkflowParser()
|
||||
agent = parser._create_agent("researcher", config["roles"]["researcher"])
|
||||
|
||||
# Should handle new structure
|
||||
assert agent is not None
|
||||
|
||||
|
||||
class TestWrapperAgentsModernization:
|
||||
"""GAP C: Wrapper agents use output= (not verbose/markdown)."""
|
||||
|
||||
def test_prompt_expander_agent_uses_output_in_agent_call(self):
|
||||
"""PromptExpanderAgent should use output= when creating internal Agent."""
|
||||
from praisonaiagents.agent.prompt_expander_agent import PromptExpanderAgent
|
||||
import inspect
|
||||
|
||||
# Get the source of the agent property
|
||||
source = inspect.getsource(PromptExpanderAgent.agent.fget)
|
||||
|
||||
# Should use output= not verbose= or markdown=
|
||||
assert "output=" in source, "PromptExpanderAgent.agent should use output="
|
||||
assert "verbose=" not in source or "output=" in source, \
|
||||
"PromptExpanderAgent.agent should not pass verbose= directly to Agent()"
|
||||
|
||||
def test_query_rewriter_agent_uses_output_in_agent_call(self):
|
||||
"""QueryRewriterAgent should use output= when creating internal Agent."""
|
||||
from praisonaiagents.agent.query_rewriter_agent import QueryRewriterAgent
|
||||
import inspect
|
||||
|
||||
# Get the source of the agent property
|
||||
source = inspect.getsource(QueryRewriterAgent.agent.fget)
|
||||
|
||||
# Should use output= not verbose= or markdown=
|
||||
assert "output=" in source, "QueryRewriterAgent.agent should use output="
|
||||
assert "verbose=" not in source or "output=" in source, \
|
||||
"QueryRewriterAgent.agent should not pass verbose= directly to Agent()"
|
||||
|
||||
def test_prompt_expander_accepts_model_param(self):
|
||||
"""PromptExpanderAgent should accept model= parameter."""
|
||||
from praisonaiagents.agent.prompt_expander_agent import PromptExpanderAgent
|
||||
|
||||
agent = PromptExpanderAgent(model="gpt-4o-mini")
|
||||
assert agent.model == "gpt-4o-mini"
|
||||
|
||||
def test_query_rewriter_accepts_model_param(self):
|
||||
"""QueryRewriterAgent should accept model= parameter."""
|
||||
from praisonaiagents.agent.query_rewriter_agent import QueryRewriterAgent
|
||||
|
||||
agent = QueryRewriterAgent(model="gpt-4o-mini")
|
||||
assert agent.model == "gpt-4o-mini"
|
||||
|
||||
|
||||
class TestAutoAgentsNoLegacyVerboseMarkdown:
|
||||
"""AutoAgents should not pass verbose/markdown to Agent when output= is set."""
|
||||
|
||||
def test_autoagents_uses_output_not_verbose_markdown(self):
|
||||
"""AutoAgents should use output= and not pass verbose/markdown when output is set."""
|
||||
from praisonaiagents.agents.autoagents import AutoAgents
|
||||
import inspect
|
||||
|
||||
source = inspect.getsource(AutoAgents._create_agents_and_tasks)
|
||||
|
||||
# Should pass output= to Agent
|
||||
assert "output=self._output" in source or "output=" in source, \
|
||||
"AutoAgents should pass output= to Agent()"
|
||||
|
||||
# Should NOT pass verbose= or markdown= directly
|
||||
assert "verbose=self.verbose" not in source, \
|
||||
"AutoAgents should not pass verbose= to Agent()"
|
||||
@@ -0,0 +1,215 @@
|
||||
"""
|
||||
Tests for LLM parameter consolidation.
|
||||
|
||||
TDD: These tests define the expected behavior for:
|
||||
1. Agent accepts `llm=` consolidated usage (new)
|
||||
2. Agent accepts `model=` alias (new)
|
||||
3. Agent still accepts `llm_config=` and `function_calling_llm=` but maps them internally (deprecated)
|
||||
4. base_url/api_key remain separate and unchanged
|
||||
5. Deprecation warnings emitted only when legacy params are used
|
||||
"""
|
||||
import pytest
|
||||
import warnings
|
||||
|
||||
|
||||
class TestLLMConsolidation:
|
||||
"""Tests for LLM parameter consolidation in Agent."""
|
||||
|
||||
def test_agent_accepts_llm_string(self):
|
||||
"""Agent accepts llm= as a string model name."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="Test agent",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
assert agent.llm == "gpt-4o-mini"
|
||||
|
||||
def test_agent_accepts_model_alias(self):
|
||||
"""Agent accepts model= as an alias for llm=."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="Test agent",
|
||||
model="gpt-4o-mini"
|
||||
)
|
||||
# model= should behave identically to llm=
|
||||
assert agent.llm == "gpt-4o-mini"
|
||||
|
||||
def test_model_and_llm_are_equivalent(self):
|
||||
"""model= and llm= produce identical agents."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent1 = Agent(instructions="Test", llm="gpt-4o")
|
||||
agent2 = Agent(instructions="Test", model="gpt-4o")
|
||||
|
||||
assert agent1.llm == agent2.llm
|
||||
|
||||
def test_llm_takes_precedence_over_model(self):
|
||||
"""If both llm= and model= are provided, llm= takes precedence."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o",
|
||||
model="gpt-3.5-turbo" # Should be ignored
|
||||
)
|
||||
assert agent.llm == "gpt-4o"
|
||||
|
||||
def test_llm_config_still_works_without_warning(self):
|
||||
"""llm_config= still works without deprecation warning (backward compat)."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm_config={"temperature": 0.7}
|
||||
)
|
||||
# Should NOT emit deprecation warning (per new policy)
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
def test_function_calling_llm_still_works_without_warning(self):
|
||||
"""function_calling_llm= still works without deprecation warning (backward compat)."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
function_calling_llm="gpt-4o-mini"
|
||||
)
|
||||
# Should NOT emit deprecation warning (per new policy)
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
def test_base_url_remains_separate(self):
|
||||
"""base_url= remains a separate parameter, not consolidated."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o",
|
||||
base_url="https://custom.api.com/v1"
|
||||
)
|
||||
assert agent.base_url == "https://custom.api.com/v1"
|
||||
|
||||
def test_api_key_remains_separate(self):
|
||||
"""api_key= remains a separate parameter, not consolidated."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o",
|
||||
api_key="sk-test-key"
|
||||
)
|
||||
assert agent.api_key == "sk-test-key"
|
||||
|
||||
def test_no_deprecation_warning_on_normal_path(self):
|
||||
"""No deprecation warnings when using only new consolidated params."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o",
|
||||
base_url="https://api.openai.com/v1",
|
||||
api_key="sk-test"
|
||||
)
|
||||
# Should NOT emit deprecation warnings for llm/base_url/api_key
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
llm_related = [x for x in deprecation_warnings
|
||||
if "llm_config" in str(x.message).lower()
|
||||
or "function_calling_llm" in str(x.message).lower()]
|
||||
assert len(llm_related) == 0
|
||||
|
||||
|
||||
class TestWebFetchGating:
|
||||
"""Tests for web_fetch gating (Claude-only)."""
|
||||
|
||||
def test_non_claude_model_with_web_fetch_raises_error(self):
|
||||
"""Non-Claude model + web fetch requested → error."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
|
||||
# This should raise an error or warning when fetch is explicitly requested
|
||||
with pytest.raises((ValueError, RuntimeError)) as exc_info:
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o", # OpenAI model - does NOT support fetch
|
||||
web=WebConfig(fetch=True) # Explicitly request fetch
|
||||
)
|
||||
# Force initialization to trigger the check
|
||||
_ = agent.web
|
||||
|
||||
assert "fetch" in str(exc_info.value).lower() or "claude" in str(exc_info.value).lower()
|
||||
|
||||
def test_claude_model_with_web_fetch_allowed(self):
|
||||
"""Claude model + web fetch requested → allowed."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
|
||||
# This should work without error
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="anthropic/claude-sonnet-4", # Claude model - supports fetch
|
||||
web=WebConfig(fetch=True)
|
||||
)
|
||||
# Should not raise
|
||||
assert agent is not None
|
||||
|
||||
def test_web_enabled_without_fetch_works_on_any_model(self):
|
||||
"""web enabled with search only (no fetch) works on any model."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
|
||||
# Web search (not fetch) should work on any model that supports it
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o-search-preview", # OpenAI search model
|
||||
web=WebConfig(search=True, fetch=False) # Explicitly disable fetch
|
||||
)
|
||||
# Should not raise - web search is allowed
|
||||
assert agent is not None
|
||||
|
||||
def test_web_fetch_false_on_non_claude_no_error(self):
|
||||
"""web=True with fetch=False on non-Claude should not error."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.config.feature_configs import WebConfig
|
||||
|
||||
agent = Agent(
|
||||
instructions="Test",
|
||||
llm="gpt-4o",
|
||||
web=WebConfig(search=True, fetch=False) # Explicitly disable fetch
|
||||
)
|
||||
assert agent is not None
|
||||
|
||||
|
||||
class TestWrapperAgentConsolidation:
|
||||
"""Tests for wrapper agents using consolidated params."""
|
||||
|
||||
def test_prompt_expander_accepts_model_param(self):
|
||||
"""PromptExpanderAgent accepts model= parameter."""
|
||||
from praisonaiagents.agent.prompt_expander_agent import PromptExpanderAgent
|
||||
|
||||
agent = PromptExpanderAgent(model="gpt-4o-mini")
|
||||
# PromptExpanderAgent stores model in self.model attribute
|
||||
assert agent.model == "gpt-4o-mini"
|
||||
|
||||
def test_prompt_expander_model_is_used(self):
|
||||
"""PromptExpanderAgent uses the model parameter correctly."""
|
||||
from praisonaiagents.agent.prompt_expander_agent import PromptExpanderAgent
|
||||
|
||||
# Should accept model= parameter without error
|
||||
agent = PromptExpanderAgent(model="gpt-4o-mini")
|
||||
assert agent is not None
|
||||
assert agent.model == "gpt-4o-mini"
|
||||
|
||||
def test_query_rewriter_accepts_model_param(self):
|
||||
"""QueryRewriterAgent accepts model= parameter."""
|
||||
from praisonaiagents.agent.query_rewriter_agent import QueryRewriterAgent
|
||||
|
||||
agent = QueryRewriterAgent(model="gpt-4o-mini")
|
||||
assert agent.model == "gpt-4o-mini"
|
||||
@@ -0,0 +1,371 @@
|
||||
"""
|
||||
Unit tests for the core SDK profiling module.
|
||||
|
||||
Tests cover:
|
||||
- Profiler enable/disable
|
||||
- Timing recording
|
||||
- Streaming tracking
|
||||
- Phase tracking
|
||||
- Report generation
|
||||
- Zero overhead when disabled
|
||||
"""
|
||||
|
||||
import pytest
|
||||
import time
|
||||
from unittest.mock import patch
|
||||
|
||||
|
||||
class TestProfilerBasics:
|
||||
"""Test basic Profiler functionality."""
|
||||
|
||||
def test_profiler_disabled_by_default(self):
|
||||
"""Profiler should be disabled by default."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
Profiler.disable() # Ensure clean state
|
||||
assert not Profiler.is_enabled()
|
||||
|
||||
def test_profiler_enable_disable(self):
|
||||
"""Test enable/disable functionality."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.disable()
|
||||
assert not Profiler.is_enabled()
|
||||
|
||||
Profiler.enable()
|
||||
assert Profiler.is_enabled()
|
||||
|
||||
Profiler.disable()
|
||||
assert not Profiler.is_enabled()
|
||||
|
||||
def test_profiler_env_var_enable(self):
|
||||
"""Test enabling via environment variable."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
with patch.dict('os.environ', {'PRAISONAI_PROFILE': '1'}):
|
||||
assert Profiler.is_enabled()
|
||||
|
||||
with patch.dict('os.environ', {'PRAISONAI_PROFILE': 'true'}):
|
||||
assert Profiler.is_enabled()
|
||||
|
||||
with patch.dict('os.environ', {'PRAISONAI_PROFILE': 'yes'}):
|
||||
assert Profiler.is_enabled()
|
||||
|
||||
def test_profiler_clear(self):
|
||||
"""Test clearing profiling data."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.record_timing("test", 100.0)
|
||||
assert len(Profiler.get_timings()) > 0
|
||||
|
||||
Profiler.clear()
|
||||
assert len(Profiler.get_timings()) == 0
|
||||
Profiler.disable()
|
||||
|
||||
|
||||
class TestTimingRecording:
|
||||
"""Test timing recording functionality."""
|
||||
|
||||
def test_record_timing_when_enabled(self):
|
||||
"""Timing should be recorded when profiler is enabled."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
Profiler.record_timing("test_op", 123.45, category="test")
|
||||
|
||||
timings = Profiler.get_timings()
|
||||
assert len(timings) == 1
|
||||
assert timings[0].name == "test_op"
|
||||
assert timings[0].duration_ms == 123.45
|
||||
assert timings[0].category == "test"
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
def test_record_timing_when_disabled(self):
|
||||
"""Timing should NOT be recorded when profiler is disabled."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.disable()
|
||||
Profiler.clear()
|
||||
|
||||
Profiler.record_timing("test_op", 123.45)
|
||||
|
||||
timings = Profiler.get_timings()
|
||||
assert len(timings) == 0
|
||||
|
||||
def test_record_timing_with_metadata(self):
|
||||
"""Timing should include metadata."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
Profiler.record_timing("test_op", 100.0, metadata={"key": "value"})
|
||||
|
||||
timings = Profiler.get_timings()
|
||||
assert timings[0].metadata == {"key": "value"}
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
|
||||
class TestPhaseTracking:
|
||||
"""Test phase tracking functionality."""
|
||||
|
||||
def test_phase_context_manager(self):
|
||||
"""Phase context manager should record timing."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
with Profiler.phase("test_phase"):
|
||||
time.sleep(0.01) # 10ms
|
||||
|
||||
timings = Profiler.get_timings(category="phase")
|
||||
assert len(timings) == 1
|
||||
assert timings[0].name == "test_phase"
|
||||
assert timings[0].duration_ms >= 10 # At least 10ms
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
def test_nested_phases(self):
|
||||
"""Nested phases should track parent."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
with Profiler.phase("outer"):
|
||||
with Profiler.phase("inner"):
|
||||
time.sleep(0.005)
|
||||
|
||||
timings = Profiler.get_timings(category="phase")
|
||||
assert len(timings) == 2
|
||||
|
||||
inner = next(t for t in timings if t.name == "inner")
|
||||
assert inner.parent == "outer"
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
|
||||
class TestStreamingTracker:
|
||||
"""Test streaming tracker functionality."""
|
||||
|
||||
def test_streaming_ttft(self):
|
||||
"""Streaming tracker should measure TTFT."""
|
||||
from praisonaiagents.profiling import Profiler, StreamingTracker
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
tracker = StreamingTracker("test_stream")
|
||||
tracker.start()
|
||||
time.sleep(0.01) # 10ms to first token
|
||||
tracker.first_token()
|
||||
time.sleep(0.02) # 20ms more
|
||||
tracker.end()
|
||||
|
||||
assert tracker.ttft_ms >= 10
|
||||
assert tracker.elapsed_ms >= 30
|
||||
|
||||
records = Profiler.get_streaming_records()
|
||||
assert len(records) == 1
|
||||
assert records[0].name == "test_stream"
|
||||
assert records[0].ttft_ms >= 10
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
def test_streaming_context_manager(self):
|
||||
"""Streaming context manager should work."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
with Profiler.streaming("test_stream") as tracker:
|
||||
time.sleep(0.01)
|
||||
tracker.first_token()
|
||||
tracker.chunk()
|
||||
tracker.chunk()
|
||||
|
||||
records = Profiler.get_streaming_records()
|
||||
assert len(records) == 1
|
||||
assert records[0].chunk_count == 2
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
|
||||
class TestProfileDecorators:
|
||||
"""Test profiling decorators."""
|
||||
|
||||
def test_profile_func_decorator(self):
|
||||
"""profile_func decorator should record function timing."""
|
||||
from praisonaiagents.profiling import Profiler, profile_func
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
@profile_func
|
||||
def slow_function():
|
||||
time.sleep(0.01)
|
||||
return "done"
|
||||
|
||||
result = slow_function()
|
||||
assert result == "done"
|
||||
|
||||
timings = Profiler.get_timings(category="function")
|
||||
assert len(timings) == 1
|
||||
assert timings[0].name == "slow_function"
|
||||
assert timings[0].duration_ms >= 10
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
def test_profile_func_disabled(self):
|
||||
"""profile_func should have zero overhead when disabled."""
|
||||
from praisonaiagents.profiling import Profiler, profile_func
|
||||
|
||||
Profiler.disable()
|
||||
Profiler.clear()
|
||||
|
||||
@profile_func
|
||||
def fast_function():
|
||||
return "done"
|
||||
|
||||
result = fast_function()
|
||||
assert result == "done"
|
||||
|
||||
timings = Profiler.get_timings()
|
||||
assert len(timings) == 0
|
||||
|
||||
|
||||
class TestProfileBlock:
|
||||
"""Test profile_block context manager."""
|
||||
|
||||
def test_profile_block(self):
|
||||
"""profile_block should record block timing."""
|
||||
from praisonaiagents.profiling import Profiler, profile_block
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
with profile_block("my_block", category="custom"):
|
||||
time.sleep(0.01)
|
||||
|
||||
timings = Profiler.get_timings(category="custom")
|
||||
assert len(timings) == 1
|
||||
assert timings[0].name == "my_block"
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
def test_profile_block_disabled(self):
|
||||
"""profile_block should have zero overhead when disabled."""
|
||||
from praisonaiagents.profiling import Profiler, profile_block
|
||||
|
||||
Profiler.disable()
|
||||
Profiler.clear()
|
||||
|
||||
with profile_block("my_block"):
|
||||
pass
|
||||
|
||||
timings = Profiler.get_timings()
|
||||
assert len(timings) == 0
|
||||
|
||||
|
||||
class TestReporting:
|
||||
"""Test report generation."""
|
||||
|
||||
def test_get_summary(self):
|
||||
"""get_summary should return structured data."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
Profiler.record_timing("op1", 100.0, category="cat1")
|
||||
Profiler.record_timing("op2", 200.0, category="cat2")
|
||||
|
||||
summary = Profiler.get_summary()
|
||||
|
||||
assert summary['total_time_ms'] == 300.0
|
||||
assert summary['timing_count'] == 2
|
||||
assert 'cat1' in summary['by_category']
|
||||
assert 'cat2' in summary['by_category']
|
||||
assert len(summary['slowest_operations']) == 2
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
def test_export_json(self):
|
||||
"""export_json should return valid JSON."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
import json
|
||||
|
||||
Profiler.enable()
|
||||
Profiler.clear()
|
||||
|
||||
Profiler.record_timing("test", 100.0)
|
||||
|
||||
json_str = Profiler.export_json()
|
||||
data = json.loads(json_str)
|
||||
|
||||
assert 'summary' in data
|
||||
assert 'timings' in data
|
||||
assert len(data['timings']) == 1
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
|
||||
class TestWarmup:
|
||||
"""Test warmup function."""
|
||||
|
||||
def test_warmup_returns_timings(self):
|
||||
"""warmup should return timing information."""
|
||||
from praisonaiagents import warmup
|
||||
|
||||
result = warmup(include_litellm=False, include_openai=False)
|
||||
assert isinstance(result, dict)
|
||||
|
||||
def test_warmup_with_litellm(self):
|
||||
"""warmup with litellm should return litellm timing."""
|
||||
from praisonaiagents import warmup
|
||||
|
||||
result = warmup(include_litellm=True, include_openai=False)
|
||||
assert 'litellm' in result
|
||||
# Should be positive (imported) or -1 (not available)
|
||||
assert result['litellm'] > 0 or result['litellm'] == -1
|
||||
|
||||
|
||||
class TestZeroOverhead:
|
||||
"""Test that profiling has zero overhead when disabled."""
|
||||
|
||||
def test_record_timing_overhead(self):
|
||||
"""record_timing should be fast when disabled."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
start = time.perf_counter()
|
||||
for _ in range(10000):
|
||||
Profiler.record_timing("test", 100.0)
|
||||
elapsed = (time.perf_counter() - start) * 1000
|
||||
|
||||
# Should complete 10k calls in under 10ms when disabled
|
||||
assert elapsed < 10, f"record_timing took {elapsed}ms for 10k calls"
|
||||
|
||||
def test_phase_context_overhead(self):
|
||||
"""phase context manager should be fast when disabled."""
|
||||
from praisonaiagents.profiling import Profiler
|
||||
|
||||
Profiler.disable()
|
||||
|
||||
start = time.perf_counter()
|
||||
for _ in range(1000):
|
||||
with Profiler.phase("test"):
|
||||
pass
|
||||
elapsed = (time.perf_counter() - start) * 1000
|
||||
|
||||
# Should complete 1k calls in under 10ms when disabled
|
||||
assert elapsed < 10, f"phase took {elapsed}ms for 1k calls"
|
||||
@@ -0,0 +1,169 @@
|
||||
"""
|
||||
Tests for the 'stream' output preset and streaming behavior.
|
||||
|
||||
Verifies:
|
||||
1. output="stream" is a valid preset string
|
||||
2. Streaming path yields chunks without buffering
|
||||
3. LLM call count == 1 for simple streaming case
|
||||
4. Precedence: start(stream=...) overrides OutputConfig.stream
|
||||
"""
|
||||
|
||||
import pytest
|
||||
import warnings
|
||||
|
||||
|
||||
class TestStreamPresetValidation:
|
||||
"""Test that 'stream' is a valid output preset."""
|
||||
|
||||
def test_stream_preset_exists_in_output_presets(self):
|
||||
"""'stream' should be a valid key in OUTPUT_PRESETS."""
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
assert "stream" in OUTPUT_PRESETS, "Missing 'stream' preset in OUTPUT_PRESETS"
|
||||
assert OUTPUT_PRESETS["stream"]["stream"] is True, "'stream' preset should have stream=True"
|
||||
|
||||
def test_stream_preset_resolves_correctly(self):
|
||||
"""output='stream' should resolve to OutputConfig with stream=True."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
result = resolve(
|
||||
value="stream",
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
)
|
||||
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.stream is True
|
||||
assert result.verbose is True # stream preset enables verbose
|
||||
|
||||
def test_all_output_presets_are_valid(self):
|
||||
"""All documented presets should be valid."""
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
expected_presets = {"minimal", "normal", "verbose", "debug", "silent", "stream"}
|
||||
actual_presets = set(OUTPUT_PRESETS.keys())
|
||||
|
||||
assert expected_presets.issubset(actual_presets), \
|
||||
f"Missing presets: {expected_presets - actual_presets}"
|
||||
|
||||
def test_invalid_preset_raises_helpful_error(self):
|
||||
"""Invalid preset should raise error listing valid options including 'stream'."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
resolve(
|
||||
value="invalid_preset",
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
)
|
||||
|
||||
error_msg = str(exc_info.value).lower()
|
||||
assert "invalid_preset" in error_msg
|
||||
assert "stream" in error_msg, "Error should list 'stream' as valid preset"
|
||||
|
||||
|
||||
class TestStreamPresetWithOverrides:
|
||||
"""Test array form with stream preset and overrides."""
|
||||
|
||||
def test_stream_preset_with_override_to_disable(self):
|
||||
"""['stream', {'stream': False}] should override stream to False."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
result = resolve(
|
||||
value=["stream", {"stream": False}],
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.stream is False # Override takes effect
|
||||
assert result.verbose is True # Base preset value preserved
|
||||
|
||||
def test_verbose_preset_with_stream_override(self):
|
||||
"""['verbose', {'stream': True}] should enable streaming."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
result = resolve(
|
||||
value=["verbose", {"stream": True}],
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.stream is True
|
||||
assert result.metrics is True # verbose preset has metrics=True
|
||||
|
||||
|
||||
class TestStreamPrecedence:
|
||||
"""Test precedence: start(stream=...) should override OutputConfig.stream."""
|
||||
|
||||
def test_start_stream_kwarg_overrides_output_config(self):
|
||||
"""start(stream=True) should enable streaming even if output='silent'."""
|
||||
# This is a behavioral test - we verify the logic in start() method
|
||||
# The actual streaming behavior is tested in integration tests
|
||||
|
||||
# Verify the start method checks kwargs['stream'] first
|
||||
import inspect
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
|
||||
source = inspect.getsource(Agent.start)
|
||||
|
||||
# start() should check kwargs.get('stream', ...) OR getattr(self, 'stream', ...)
|
||||
assert "kwargs.get('stream'" in source or "stream" in source, \
|
||||
"start() should check stream kwarg"
|
||||
|
||||
|
||||
class TestNoDeprecationWarnings:
|
||||
"""Ensure no deprecation warnings for stream preset."""
|
||||
|
||||
def test_stream_preset_no_warnings(self):
|
||||
"""Using output='stream' should not emit any warnings."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
warnings.simplefilter("always")
|
||||
|
||||
resolve(
|
||||
value="stream",
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
)
|
||||
|
||||
deprecation_warnings = [x for x in w if issubclass(x.category, DeprecationWarning)]
|
||||
assert len(deprecation_warnings) == 0, \
|
||||
f"Unexpected warnings: {[str(x.message) for x in deprecation_warnings]}"
|
||||
|
||||
|
||||
class TestOutputConfigStreamField:
|
||||
"""Test OutputConfig has stream field."""
|
||||
|
||||
def test_output_config_has_stream_field(self):
|
||||
"""OutputConfig should have a stream field."""
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
config = OutputConfig()
|
||||
assert hasattr(config, 'stream'), "OutputConfig missing 'stream' field"
|
||||
|
||||
def test_output_config_stream_default_is_false(self):
|
||||
"""OutputConfig.stream should default to False."""
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
|
||||
config = OutputConfig()
|
||||
assert config.stream is False, "OutputConfig.stream should default to False"
|
||||
@@ -0,0 +1 @@
|
||||
"""Tests for the trace module."""
|
||||
@@ -0,0 +1,450 @@
|
||||
"""
|
||||
Tests for the trace protocol module.
|
||||
|
||||
TDD tests for ActionEvent, TraceSink protocol, and redaction.
|
||||
"""
|
||||
|
||||
import time
|
||||
import json
|
||||
|
||||
|
||||
class TestActionEvent:
|
||||
"""Tests for ActionEvent dataclass."""
|
||||
|
||||
def test_action_event_creation_minimal(self):
|
||||
"""Test creating ActionEvent with minimal fields."""
|
||||
from praisonaiagents.trace.protocol import ActionEvent
|
||||
|
||||
event = ActionEvent(
|
||||
event_type="agent_start",
|
||||
timestamp=1736665496.123,
|
||||
)
|
||||
|
||||
assert event.event_type == "agent_start"
|
||||
assert event.timestamp == 1736665496.123
|
||||
assert event.schema_version == "1.0"
|
||||
assert event.agent_id is None
|
||||
assert event.agent_name is None
|
||||
assert event.tool_name is None
|
||||
|
||||
def test_action_event_creation_full(self):
|
||||
"""Test creating ActionEvent with all fields."""
|
||||
from praisonaiagents.trace.protocol import ActionEvent
|
||||
|
||||
event = ActionEvent(
|
||||
event_type="tool_end",
|
||||
timestamp=1736665497.456,
|
||||
agent_id="agent-123",
|
||||
agent_name="researcher",
|
||||
tool_name="web_search",
|
||||
tool_args={"query": "AI trends"},
|
||||
tool_result_summary="Found 10 results",
|
||||
duration_ms=800.5,
|
||||
status="ok",
|
||||
error_message=None,
|
||||
metadata={"provider": "duckduckgo"},
|
||||
)
|
||||
|
||||
assert event.event_type == "tool_end"
|
||||
assert event.agent_name == "researcher"
|
||||
assert event.tool_name == "web_search"
|
||||
assert event.tool_args == {"query": "AI trends"}
|
||||
assert event.duration_ms == 800.5
|
||||
assert event.status == "ok"
|
||||
assert event.metadata == {"provider": "duckduckgo"}
|
||||
|
||||
def test_action_event_to_dict(self):
|
||||
"""Test ActionEvent.to_dict() method."""
|
||||
from praisonaiagents.trace.protocol import ActionEvent
|
||||
|
||||
event = ActionEvent(
|
||||
event_type="agent_start",
|
||||
timestamp=1736665496.123,
|
||||
agent_name="writer",
|
||||
)
|
||||
|
||||
d = event.to_dict()
|
||||
|
||||
assert d["schema_version"] == "1.0"
|
||||
assert d["event_type"] == "agent_start"
|
||||
assert d["timestamp"] == 1736665496.123
|
||||
assert d["agent_name"] == "writer"
|
||||
# None values should be excluded
|
||||
assert "tool_name" not in d or d["tool_name"] is None
|
||||
|
||||
def test_action_event_to_json(self):
|
||||
"""Test ActionEvent.to_json() method."""
|
||||
from praisonaiagents.trace.protocol import ActionEvent
|
||||
|
||||
event = ActionEvent(
|
||||
event_type="tool_start",
|
||||
timestamp=1736665497.0,
|
||||
tool_name="read_file",
|
||||
tool_args={"path": "/tmp/test.txt"},
|
||||
)
|
||||
|
||||
json_str = event.to_json()
|
||||
parsed = json.loads(json_str)
|
||||
|
||||
assert parsed["event_type"] == "tool_start"
|
||||
assert parsed["tool_name"] == "read_file"
|
||||
assert parsed["tool_args"] == {"path": "/tmp/test.txt"}
|
||||
|
||||
def test_action_event_types(self):
|
||||
"""Test all valid event types."""
|
||||
from praisonaiagents.trace.protocol import ActionEvent, ActionEventType
|
||||
|
||||
valid_types = [
|
||||
ActionEventType.AGENT_START,
|
||||
ActionEventType.AGENT_END,
|
||||
ActionEventType.TOOL_START,
|
||||
ActionEventType.TOOL_END,
|
||||
ActionEventType.ERROR,
|
||||
ActionEventType.OUTPUT,
|
||||
]
|
||||
|
||||
for event_type in valid_types:
|
||||
event = ActionEvent(
|
||||
event_type=event_type.value,
|
||||
timestamp=time.time(),
|
||||
)
|
||||
assert event.event_type == event_type.value
|
||||
|
||||
|
||||
class TestRedaction:
|
||||
"""Tests for redaction functionality."""
|
||||
|
||||
def test_redact_api_key(self):
|
||||
"""Test redacting api_key field."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {"api_key": "sk-1234567890abcdef", "query": "hello"}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
assert redacted["api_key"] == "[REDACTED]"
|
||||
assert redacted["query"] == "hello"
|
||||
|
||||
def test_redact_multiple_sensitive_keys(self):
|
||||
"""Test redacting multiple sensitive keys."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {
|
||||
"api_key": "sk-secret",
|
||||
"password": "mypassword123",
|
||||
"token": "bearer-token",
|
||||
"authorization": "Bearer xyz",
|
||||
"secret": "top-secret",
|
||||
"normal_field": "visible",
|
||||
}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
assert redacted["api_key"] == "[REDACTED]"
|
||||
assert redacted["password"] == "[REDACTED]"
|
||||
assert redacted["token"] == "[REDACTED]"
|
||||
assert redacted["authorization"] == "[REDACTED]"
|
||||
assert redacted["secret"] == "[REDACTED]"
|
||||
assert redacted["normal_field"] == "visible"
|
||||
|
||||
def test_redact_nested_dict(self):
|
||||
"""Test redacting nested dictionaries."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {
|
||||
"config": {
|
||||
"api_key": "sk-nested",
|
||||
"endpoint": "https://api.example.com",
|
||||
},
|
||||
"name": "test",
|
||||
}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
assert redacted["config"]["api_key"] == "[REDACTED]"
|
||||
assert redacted["config"]["endpoint"] == "https://api.example.com"
|
||||
assert redacted["name"] == "test"
|
||||
|
||||
def test_redact_list_of_dicts(self):
|
||||
"""Test redacting list containing dictionaries."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {
|
||||
"items": [
|
||||
{"name": "item1", "secret": "hidden1"},
|
||||
{"name": "item2", "secret": "hidden2"},
|
||||
]
|
||||
}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
assert redacted["items"][0]["name"] == "item1"
|
||||
assert redacted["items"][0]["secret"] == "[REDACTED]"
|
||||
assert redacted["items"][1]["secret"] == "[REDACTED]"
|
||||
|
||||
def test_redact_case_insensitive(self):
|
||||
"""Test that redaction is case-insensitive."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {
|
||||
"API_KEY": "key1",
|
||||
"Api_Key": "key2",
|
||||
"apiKey": "key3",
|
||||
"APIKEY": "key4",
|
||||
}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
assert redacted["API_KEY"] == "[REDACTED]"
|
||||
assert redacted["Api_Key"] == "[REDACTED]"
|
||||
assert redacted["apiKey"] == "[REDACTED]"
|
||||
assert redacted["APIKEY"] == "[REDACTED]"
|
||||
|
||||
def test_redact_connection_strings(self):
|
||||
"""Test redacting database connection strings."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {
|
||||
"connection_string": "postgresql://user:pass@host/db",
|
||||
"database_url": "mysql://root:secret@localhost/mydb",
|
||||
"db_url": "redis://default:password@redis:6379",
|
||||
}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
assert redacted["connection_string"] == "[REDACTED]"
|
||||
assert redacted["database_url"] == "[REDACTED]"
|
||||
assert redacted["db_url"] == "[REDACTED]"
|
||||
|
||||
def test_redact_preserves_original(self):
|
||||
"""Test that redaction doesn't modify original dict."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
original = {"api_key": "secret", "name": "test"}
|
||||
redacted = redact_dict(original)
|
||||
|
||||
assert original["api_key"] == "secret"
|
||||
assert redacted["api_key"] == "[REDACTED]"
|
||||
|
||||
def test_redact_empty_dict(self):
|
||||
"""Test redacting empty dictionary."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
assert redact_dict({}) == {}
|
||||
|
||||
def test_redact_none_values(self):
|
||||
"""Test handling None values."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {"api_key": None, "name": "test"}
|
||||
redacted = redact_dict(data)
|
||||
|
||||
# None values for sensitive keys should still be redacted
|
||||
assert redacted["api_key"] == "[REDACTED]"
|
||||
assert redacted["name"] == "test"
|
||||
|
||||
def test_redact_disabled(self):
|
||||
"""Test disabling redaction."""
|
||||
from praisonaiagents.trace.redact import redact_dict
|
||||
|
||||
data = {"api_key": "visible", "name": "test"}
|
||||
result = redact_dict(data, enabled=False)
|
||||
|
||||
assert result["api_key"] == "visible"
|
||||
assert result["name"] == "test"
|
||||
|
||||
|
||||
class TestTraceSink:
|
||||
"""Tests for TraceSink protocol."""
|
||||
|
||||
def test_noop_sink(self):
|
||||
"""Test NoOpSink does nothing."""
|
||||
from praisonaiagents.trace.protocol import NoOpSink, ActionEvent
|
||||
|
||||
sink = NoOpSink()
|
||||
event = ActionEvent(event_type="agent_start", timestamp=time.time())
|
||||
|
||||
# Should not raise
|
||||
sink.emit(event)
|
||||
sink.flush()
|
||||
sink.close()
|
||||
|
||||
def test_list_sink(self):
|
||||
"""Test ListSink collects events."""
|
||||
from praisonaiagents.trace.protocol import ListSink, ActionEvent
|
||||
|
||||
sink = ListSink()
|
||||
|
||||
event1 = ActionEvent(event_type="agent_start", timestamp=1.0)
|
||||
event2 = ActionEvent(event_type="tool_start", timestamp=2.0)
|
||||
|
||||
sink.emit(event1)
|
||||
sink.emit(event2)
|
||||
|
||||
events = sink.get_events()
|
||||
assert len(events) == 2
|
||||
assert events[0].event_type == "agent_start"
|
||||
assert events[1].event_type == "tool_start"
|
||||
|
||||
def test_list_sink_clear(self):
|
||||
"""Test ListSink.clear() method."""
|
||||
from praisonaiagents.trace.protocol import ListSink, ActionEvent
|
||||
|
||||
sink = ListSink()
|
||||
sink.emit(ActionEvent(event_type="test", timestamp=1.0))
|
||||
|
||||
assert len(sink.get_events()) == 1
|
||||
|
||||
sink.clear()
|
||||
|
||||
assert len(sink.get_events()) == 0
|
||||
|
||||
|
||||
class TestTraceEmitter:
|
||||
"""Tests for TraceEmitter class."""
|
||||
|
||||
def test_emitter_with_noop_sink(self):
|
||||
"""Test TraceEmitter with NoOpSink."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, NoOpSink
|
||||
|
||||
emitter = TraceEmitter(sink=NoOpSink())
|
||||
|
||||
# Should not raise
|
||||
emitter.agent_start("test-agent", agent_id="123")
|
||||
emitter.tool_start("web_search", {"query": "test"})
|
||||
emitter.tool_end("web_search", duration_ms=100, status="ok")
|
||||
emitter.agent_end("test-agent", duration_ms=500)
|
||||
|
||||
def test_emitter_with_list_sink(self):
|
||||
"""Test TraceEmitter collects events."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, ListSink
|
||||
|
||||
sink = ListSink()
|
||||
emitter = TraceEmitter(sink=sink)
|
||||
|
||||
emitter.agent_start("researcher")
|
||||
emitter.tool_start("search", {"q": "AI"})
|
||||
emitter.tool_end("search", duration_ms=100, status="ok")
|
||||
emitter.agent_end("researcher", duration_ms=200)
|
||||
|
||||
events = sink.get_events()
|
||||
assert len(events) == 4
|
||||
assert events[0].event_type == "agent_start"
|
||||
assert events[1].event_type == "tool_start"
|
||||
assert events[2].event_type == "tool_end"
|
||||
assert events[3].event_type == "agent_end"
|
||||
|
||||
def test_emitter_redacts_by_default(self):
|
||||
"""Test TraceEmitter redacts sensitive data by default."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, ListSink
|
||||
|
||||
sink = ListSink()
|
||||
emitter = TraceEmitter(sink=sink, redact=True)
|
||||
|
||||
emitter.tool_start("api_call", {"api_key": "sk-secret", "query": "test"})
|
||||
|
||||
events = sink.get_events()
|
||||
assert events[0].tool_args["api_key"] == "[REDACTED]"
|
||||
assert events[0].tool_args["query"] == "test"
|
||||
|
||||
def test_emitter_disabled(self):
|
||||
"""Test TraceEmitter when disabled."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, ListSink
|
||||
|
||||
sink = ListSink()
|
||||
emitter = TraceEmitter(sink=sink, enabled=False)
|
||||
|
||||
emitter.agent_start("test")
|
||||
emitter.tool_start("tool", {})
|
||||
|
||||
# No events should be emitted
|
||||
assert len(sink.get_events()) == 0
|
||||
|
||||
def test_emitter_error_event(self):
|
||||
"""Test TraceEmitter error event."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, ListSink
|
||||
|
||||
sink = ListSink()
|
||||
emitter = TraceEmitter(sink=sink)
|
||||
|
||||
emitter.error("Something went wrong", tool_name="failing_tool")
|
||||
|
||||
events = sink.get_events()
|
||||
assert len(events) == 1
|
||||
assert events[0].event_type == "error"
|
||||
assert events[0].error_message == "Something went wrong"
|
||||
assert events[0].tool_name == "failing_tool"
|
||||
|
||||
def test_emitter_output_event(self):
|
||||
"""Test TraceEmitter output event for final agent output."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, ListSink
|
||||
|
||||
sink = ListSink()
|
||||
emitter = TraceEmitter(sink=sink)
|
||||
|
||||
emitter.output("The analysis shows three major trends...")
|
||||
|
||||
events = sink.get_events()
|
||||
assert len(events) == 1
|
||||
assert events[0].event_type == "output"
|
||||
assert "three major trends" in events[0].tool_result_summary
|
||||
|
||||
|
||||
class TestActionTraceConfig:
|
||||
"""Tests for ActionTraceConfig."""
|
||||
|
||||
def test_config_defaults(self):
|
||||
"""Test ActionTraceConfig default values."""
|
||||
from praisonaiagents.trace.protocol import ActionTraceConfig
|
||||
|
||||
config = ActionTraceConfig()
|
||||
|
||||
assert config.enabled is True
|
||||
assert config.redact is True
|
||||
assert config.compact is False
|
||||
assert config.sink_type == "noop"
|
||||
assert config.file_path is None
|
||||
|
||||
def test_config_custom(self):
|
||||
"""Test ActionTraceConfig custom values."""
|
||||
from praisonaiagents.trace.protocol import ActionTraceConfig
|
||||
|
||||
config = ActionTraceConfig(
|
||||
enabled=True,
|
||||
redact=False,
|
||||
compact=True,
|
||||
sink_type="jsonl",
|
||||
file_path="/tmp/trace.jsonl",
|
||||
)
|
||||
|
||||
assert config.redact is False
|
||||
assert config.compact is True
|
||||
assert config.sink_type == "jsonl"
|
||||
assert config.file_path == "/tmp/trace.jsonl"
|
||||
|
||||
|
||||
class TestPerformance:
|
||||
"""Performance tests for trace module."""
|
||||
|
||||
def test_noop_sink_overhead(self):
|
||||
"""Test that NoOpSink has minimal overhead."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, NoOpSink, ActionEvent
|
||||
|
||||
emitter = TraceEmitter(sink=NoOpSink())
|
||||
|
||||
start = time.perf_counter()
|
||||
for _ in range(10000):
|
||||
emitter.tool_start("test", {"arg": "value"})
|
||||
emitter.tool_end("test", duration_ms=1, status="ok")
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
# Should complete 10000 iterations in under 100ms
|
||||
assert elapsed < 0.1, f"NoOpSink too slow: {elapsed:.3f}s for 10000 iterations"
|
||||
|
||||
def test_disabled_emitter_overhead(self):
|
||||
"""Test that disabled emitter has near-zero overhead."""
|
||||
from praisonaiagents.trace.protocol import TraceEmitter, ListSink
|
||||
|
||||
emitter = TraceEmitter(sink=ListSink(), enabled=False)
|
||||
|
||||
start = time.perf_counter()
|
||||
for _ in range(10000):
|
||||
emitter.tool_start("test", {"arg": "value"})
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
# Should complete 10000 iterations in under 500ms (very conservative)
|
||||
assert elapsed < 0.5, f"Disabled emitter too slow: {elapsed:.3f}s"
|
||||
Generated
+1
-1
@@ -2422,7 +2422,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "praisonaiagents"
|
||||
version = "0.10.10"
|
||||
version = "0.11.4"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "aiohttp" },
|
||||
|
||||
@@ -0,0 +1,65 @@
|
||||
"""
|
||||
Guardrails - Advanced Example
|
||||
|
||||
Demonstrates advanced guardrails patterns including:
|
||||
- Multi-agent configuration
|
||||
- Custom callbacks/handlers
|
||||
- Error handling
|
||||
- All available options
|
||||
|
||||
Expected Output:
|
||||
Comprehensive demonstration of guardrails with multiple agents.
|
||||
"""
|
||||
from praisonaiagents import Agent, Task, PraisonAIAgents
|
||||
|
||||
# ============================================================
|
||||
# Section 1: Custom Configuration
|
||||
# ============================================================
|
||||
|
||||
# Define custom guardrails configuration
|
||||
# config = ...
|
||||
|
||||
# ============================================================
|
||||
# Section 2: Multi-Agent Setup
|
||||
# ============================================================
|
||||
|
||||
agent1 = Agent(
|
||||
name="Agent1",
|
||||
instructions="You are the first agent",
|
||||
# guardrails=config,
|
||||
)
|
||||
|
||||
agent2 = Agent(
|
||||
name="Agent2",
|
||||
instructions="You are the second agent",
|
||||
# guardrails=config,
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Section 3: Task Definition
|
||||
# ============================================================
|
||||
|
||||
task = Task(
|
||||
description="Demonstrate guardrails with multiple agents",
|
||||
agent=agent1,
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Section 4: Execution
|
||||
# ============================================================
|
||||
|
||||
agents = PraisonAIAgents(agents=[agent1, agent2], tasks=[task])
|
||||
result = agents.start()
|
||||
print(result)
|
||||
|
||||
# ============================================================
|
||||
# Section 5: All Options Reference
|
||||
# ============================================================
|
||||
"""
|
||||
Guardrails Options:
|
||||
──────────────────
|
||||
| Option | Type | Default | Description |
|
||||
|-----------------|----------|---------|----------------------|
|
||||
| option1 | str | None | Description here |
|
||||
| option2 | bool | False | Description here |
|
||||
"""
|
||||
@@ -0,0 +1,19 @@
|
||||
"""
|
||||
Guardrails - Basic Example
|
||||
|
||||
Demonstrates minimal usage of guardrails with a single agent.
|
||||
|
||||
Expected Output:
|
||||
Agent response demonstrating guardrails functionality.
|
||||
"""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic guardrails usage
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
# guardrails=... # Configure guardrails here
|
||||
)
|
||||
|
||||
# Run the agent
|
||||
result = agent.start("Hello! Demonstrate guardrails functionality.")
|
||||
print(result)
|
||||
@@ -3,8 +3,8 @@ class Praisonai < Formula
|
||||
|
||||
desc "AI tools for various AI applications"
|
||||
homepage "https://github.com/MervinPraison/PraisonAI"
|
||||
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.6.2.tar.gz"
|
||||
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.6.2.tar.gz | shasum -a 256`.split.first
|
||||
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.7.8.tar.gz"
|
||||
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.7.8.tar.gz | shasum -a 256`.split.first
|
||||
license "MIT"
|
||||
|
||||
depends_on "[email protected]"
|
||||
|
||||
@@ -0,0 +1,17 @@
|
||||
"""
|
||||
Development utilities for PraisonAI.
|
||||
|
||||
This module contains development-only tools that are NOT imported during normal runtime.
|
||||
"""
|
||||
|
||||
__all__ = ["generate_api_md", "ApiMdGenerator"]
|
||||
|
||||
|
||||
def __getattr__(name: str):
|
||||
"""Lazy load development utilities."""
|
||||
if name in ("generate_api_md", "ApiMdGenerator"):
|
||||
from .api_md import generate_api_md, ApiMdGenerator
|
||||
if name == "generate_api_md":
|
||||
return generate_api_md
|
||||
return ApiMdGenerator
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
@@ -0,0 +1,981 @@
|
||||
"""
|
||||
API Markdown Generator for PraisonAI.
|
||||
|
||||
Generates a comprehensive api.md file documenting all public API surfaces:
|
||||
- Python Core SDK (praisonaiagents)
|
||||
- Python Wrapper/Integrations (praisonai)
|
||||
- CLI commands
|
||||
- TypeScript package (praisonai-ts)
|
||||
|
||||
Uses AST-based static analysis to avoid importing heavy dependencies.
|
||||
|
||||
Example output format (OpenAI SDK style):
|
||||
|
||||
# Agents
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import Agent, AgentConfig
|
||||
from praisonaiagents.types import RunResult
|
||||
```
|
||||
|
||||
Methods:
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent.py">start</a>(prompt: str, **kwargs) -> RunResult</code>
|
||||
|
||||
Usage:
|
||||
python -m praisonai._dev.api_md --write
|
||||
python -m praisonai._dev.api_md --check
|
||||
python -m praisonai._dev.api_md --stdout
|
||||
"""
|
||||
|
||||
import ast
|
||||
import re
|
||||
import sys
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Set, Tuple
|
||||
|
||||
|
||||
@dataclass
|
||||
class SymbolInfo:
|
||||
"""Information about a discovered symbol."""
|
||||
name: str
|
||||
kind: str # 'class', 'function', 'type', 'constant'
|
||||
module_path: str # e.g., 'praisonaiagents.agent.agent'
|
||||
file_path: str # relative to repo root
|
||||
line_number: int
|
||||
signature: Optional[str] = None
|
||||
return_type: Optional[str] = None
|
||||
methods: List["MethodInfo"] = field(default_factory=list)
|
||||
docstring: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class MethodInfo:
|
||||
"""Information about a class method."""
|
||||
name: str
|
||||
signature: str
|
||||
return_type: Optional[str]
|
||||
line_number: int
|
||||
|
||||
|
||||
@dataclass
|
||||
class CLICommand:
|
||||
"""Information about a CLI command."""
|
||||
command_path: str # e.g., 'praisonai docs api-md'
|
||||
help_text: Optional[str]
|
||||
file_path: str
|
||||
line_number: int
|
||||
|
||||
|
||||
@dataclass
|
||||
class TSExport:
|
||||
"""Information about a TypeScript export."""
|
||||
name: str
|
||||
kind: str # 'class', 'function', 'type', 'const'
|
||||
source_file: str
|
||||
is_type: bool = False
|
||||
|
||||
|
||||
class ApiMdGenerator:
|
||||
"""
|
||||
Generates api.md from source code using AST analysis.
|
||||
|
||||
Design principles:
|
||||
- AST-first: Never import modules that may have heavy dependencies
|
||||
- Deterministic: Stable ordering for reproducible output
|
||||
- Comprehensive: Cover all public exports
|
||||
"""
|
||||
|
||||
# Section groupings for organizing exports
|
||||
SECTION_GROUPS = {
|
||||
'Shared Types': ['TaskOutput', 'ReflectionOutput', 'ToolResult', 'ToolValidationError',
|
||||
'GuardrailResult', 'StepResult', 'WorkflowContext', 'HandoffResult',
|
||||
'HandoffInputData', 'HandoffConfig', 'ContextPolicy', 'HandoffError',
|
||||
'HandoffCycleError', 'HandoffDepthError', 'HandoffTimeoutError'],
|
||||
'Agents': ['Agent', 'Agents', 'PraisonAIAgents', 'ImageAgent', 'ContextAgent',
|
||||
'DeepResearchAgent', 'QueryRewriterAgent', 'PromptExpanderAgent',
|
||||
'AutoAgents', 'AutoRagAgent', 'PlanningAgent', 'create_context_agent'],
|
||||
'Tools': ['Tools', 'BaseTool', 'tool', 'FunctionTool', 'ToolRegistry',
|
||||
'get_registry', 'register_tool', 'get_tool', 'validate_tool'],
|
||||
'Workflows': ['Workflow', 'WorkflowStep', 'Pipeline', 'Route', 'Parallel',
|
||||
'Loop', 'Repeat', 'route', 'parallel', 'loop', 'repeat'],
|
||||
'DB': ['db', 'DbAdapter', 'AsyncDbAdapter'],
|
||||
'Memory': ['Memory', 'MemoryConfig', 'MemoryBackend'],
|
||||
'Knowledge': ['Knowledge', 'Chunking', 'ChunkingStrategy', 'KnowledgeConfig'],
|
||||
'RAG': ['RAG', 'RAGConfig', 'RAGResult', 'RAGCitation', 'RetrievalConfig',
|
||||
'RetrievalPolicy', 'CitationsMode', 'ContextPack'],
|
||||
'Handoff': ['Handoff', 'handoff', 'handoff_filters', 'RECOMMENDED_PROMPT_PREFIX',
|
||||
'prompt_with_handoff_instructions'],
|
||||
'Guardrails': ['LLMGuardrail', 'GuardrailConfig', 'GuardrailAction', 'GUARDRAIL_PRESETS'],
|
||||
'Planning': ['Plan', 'PlanStep', 'TodoList', 'TodoItem', 'PlanStorage',
|
||||
'ApprovalCallback', 'READ_ONLY_TOOLS', 'RESTRICTED_TOOLS', 'PlanningConfig'],
|
||||
'Skills': ['SkillManager', 'SkillProperties', 'SkillMetadata', 'SkillLoader', 'SkillsConfig'],
|
||||
'Session': ['Session'],
|
||||
'MCP': ['MCP'],
|
||||
'Telemetry': ['get_telemetry', 'enable_telemetry', 'disable_telemetry',
|
||||
'enable_performance_mode', 'disable_performance_mode',
|
||||
'cleanup_telemetry_resources', 'MinimalTelemetry', 'TelemetryCollector'],
|
||||
'Observability': ['obs', 'FlowDisplay', 'track_workflow'],
|
||||
'Context': ['FastContext', 'FastContextResult', 'FileMatch', 'LineRange',
|
||||
'ContextManager', 'ManagerConfig'],
|
||||
'UI': ['AGUI', 'A2A'],
|
||||
'Config': ['MemoryConfig', 'KnowledgeConfig', 'PlanningConfig', 'ReflectionConfig',
|
||||
'GuardrailConfig', 'WebConfig', 'OutputConfig', 'ExecutionConfig',
|
||||
'TemplateConfig', 'CachingConfig', 'HooksConfig', 'SkillsConfig',
|
||||
'AutonomyConfig', 'OutputPreset', 'ExecutionPreset', 'AutonomyLevel',
|
||||
'WebSearchProvider', 'MultiAgentHooksConfig', 'MultiAgentOutputConfig',
|
||||
'MultiAgentExecutionConfig', 'MultiAgentPlanningConfig', 'MultiAgentMemoryConfig'],
|
||||
'Display': ['display_interaction', 'display_self_reflection', 'display_instruction',
|
||||
'display_tool_call', 'display_error', 'display_generating',
|
||||
'clean_triple_backticks', 'error_logs', 'register_display_callback',
|
||||
'sync_display_callbacks', 'async_display_callbacks'],
|
||||
'Utilities': ['resolve', 'ArrayMode', 'resolve_memory', 'resolve_knowledge',
|
||||
'resolve_output', 'resolve_execution', 'resolve_web', 'resolve_planning',
|
||||
'resolve_reflection', 'resolve_context', 'resolve_autonomy',
|
||||
'resolve_caching', 'resolve_hooks', 'resolve_skills', 'resolve_routing',
|
||||
'resolve_guardrails', 'resolve_guardrail_policies', 'is_policy_string',
|
||||
'parse_policy_string'],
|
||||
}
|
||||
|
||||
def __init__(self, repo_root: Optional[Path] = None):
|
||||
"""Initialize the generator with repository root path."""
|
||||
if repo_root is None:
|
||||
# Auto-detect repo root
|
||||
repo_root = self._find_repo_root()
|
||||
self.repo_root = Path(repo_root).resolve()
|
||||
|
||||
# Package paths
|
||||
self.agents_pkg = self.repo_root / "src" / "praisonai-agents" / "praisonaiagents"
|
||||
self.wrapper_pkg = self.repo_root / "src" / "praisonai" / "praisonai"
|
||||
self.ts_pkg = self.repo_root / "src" / "praisonai-ts"
|
||||
|
||||
# Discovered symbols
|
||||
self.agents_symbols: Dict[str, SymbolInfo] = {}
|
||||
self.wrapper_symbols: Dict[str, SymbolInfo] = {}
|
||||
self.cli_commands: List[CLICommand] = []
|
||||
self.ts_exports: List[TSExport] = []
|
||||
|
||||
def _find_repo_root(self) -> Path:
|
||||
"""Find repository root by looking for .git directory."""
|
||||
current = Path.cwd()
|
||||
while current != current.parent:
|
||||
if (current / ".git").exists():
|
||||
return current
|
||||
current = current.parent
|
||||
# Fallback to expected location
|
||||
return Path("/Users/praison/praisonai-package")
|
||||
|
||||
def discover_all(self) -> None:
|
||||
"""Discover all public API symbols."""
|
||||
self._discover_python_exports(self.agents_pkg, "praisonaiagents", self.agents_symbols)
|
||||
self._discover_python_exports(self.wrapper_pkg, "praisonai", self.wrapper_symbols)
|
||||
self._discover_cli_commands()
|
||||
self._discover_ts_exports()
|
||||
|
||||
def _discover_python_exports(
|
||||
self,
|
||||
pkg_path: Path,
|
||||
pkg_name: str,
|
||||
symbols: Dict[str, SymbolInfo]
|
||||
) -> None:
|
||||
"""Discover Python exports from __init__.py using AST."""
|
||||
init_file = pkg_path / "__init__.py"
|
||||
if not init_file.exists():
|
||||
return
|
||||
|
||||
try:
|
||||
with open(init_file, 'r', encoding='utf-8') as f:
|
||||
source = f.read()
|
||||
tree = ast.parse(source)
|
||||
except (SyntaxError, UnicodeDecodeError):
|
||||
return
|
||||
|
||||
# Extract __all__ if present
|
||||
all_exports: Set[str] = set()
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.Assign):
|
||||
for target in node.targets:
|
||||
if isinstance(target, ast.Name) and target.id == '__all__':
|
||||
if isinstance(node.value, ast.List):
|
||||
for elt in node.value.elts:
|
||||
if isinstance(elt, ast.Constant) and isinstance(elt.value, str):
|
||||
all_exports.add(elt.value)
|
||||
|
||||
# Track imports to find source files
|
||||
import_sources: Dict[str, Tuple[str, str]] = {} # name -> (module, original_name)
|
||||
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.ImportFrom) and node.module:
|
||||
for alias in node.names:
|
||||
name = alias.asname if alias.asname else alias.name
|
||||
import_sources[name] = (node.module, alias.name)
|
||||
|
||||
# Parse __getattr__ for lazy-loaded symbols
|
||||
lazy_sources = self._parse_getattr_lazy_imports(tree)
|
||||
import_sources.update(lazy_sources)
|
||||
|
||||
# For each export, find its definition
|
||||
for export_name in sorted(all_exports):
|
||||
if export_name in import_sources:
|
||||
module_path, original_name = import_sources[export_name]
|
||||
# Resolve to file
|
||||
symbol_info = self._resolve_symbol(
|
||||
pkg_path, pkg_name, module_path, original_name, export_name
|
||||
)
|
||||
if symbol_info:
|
||||
symbols[export_name] = symbol_info
|
||||
else:
|
||||
# Defined in __init__.py itself
|
||||
symbol_info = self._find_symbol_in_file(
|
||||
init_file, export_name, pkg_name
|
||||
)
|
||||
if symbol_info:
|
||||
symbols[export_name] = symbol_info
|
||||
|
||||
def _parse_getattr_lazy_imports(self, tree: ast.Module) -> Dict[str, Tuple[str, str]]:
|
||||
"""
|
||||
Parse __getattr__ function to extract lazy-loaded imports.
|
||||
|
||||
Looks for patterns like:
|
||||
if name == "Agent":
|
||||
from .agent.agent import Agent
|
||||
return Agent
|
||||
"""
|
||||
lazy_sources: Dict[str, Tuple[str, str]] = {}
|
||||
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.FunctionDef) and node.name == '__getattr__':
|
||||
# Walk through ALL nodes in the function to find if statements
|
||||
for stmt in ast.walk(node):
|
||||
if isinstance(stmt, ast.If):
|
||||
# Check if this is `if name == "SomeName":`
|
||||
symbol_name = self._extract_name_comparison(stmt.test)
|
||||
if symbol_name:
|
||||
# Look for import statement in the body
|
||||
for inner_stmt in stmt.body:
|
||||
if isinstance(inner_stmt, ast.ImportFrom) and inner_stmt.module:
|
||||
for alias in inner_stmt.names:
|
||||
imported_name = alias.name
|
||||
lazy_sources[symbol_name] = (inner_stmt.module, imported_name)
|
||||
break
|
||||
break
|
||||
|
||||
return lazy_sources
|
||||
|
||||
def _extract_name_comparison(self, test: ast.expr) -> Optional[str]:
|
||||
"""
|
||||
Extract the string value from comparisons like `name == "Agent"`.
|
||||
Also handles `name in ("A", "B", "C")` patterns.
|
||||
"""
|
||||
if isinstance(test, ast.Compare):
|
||||
# Handle: name == "Agent"
|
||||
if (len(test.ops) == 1 and
|
||||
isinstance(test.ops[0], ast.Eq) and
|
||||
isinstance(test.left, ast.Name) and test.left.id == 'name'):
|
||||
if len(test.comparators) == 1:
|
||||
comp = test.comparators[0]
|
||||
if isinstance(comp, ast.Constant) and isinstance(comp.value, str):
|
||||
return comp.value
|
||||
# Handle: name in ("A", "B", "C")
|
||||
if (len(test.ops) == 1 and
|
||||
isinstance(test.ops[0], ast.In) and
|
||||
isinstance(test.left, ast.Name) and test.left.id == 'name'):
|
||||
# Return first item for now (we'll get others via elif)
|
||||
if len(test.comparators) == 1:
|
||||
comp = test.comparators[0]
|
||||
if isinstance(comp, ast.Tuple):
|
||||
for elt in comp.elts:
|
||||
if isinstance(elt, ast.Constant) and isinstance(elt.value, str):
|
||||
return elt.value
|
||||
return None
|
||||
|
||||
def _resolve_symbol(
|
||||
self,
|
||||
pkg_path: Path,
|
||||
pkg_name: str,
|
||||
module_path: str,
|
||||
original_name: str,
|
||||
export_name: str
|
||||
) -> Optional[SymbolInfo]:
|
||||
"""Resolve a symbol to its definition file."""
|
||||
file_path = None
|
||||
|
||||
# Handle relative imports (starting with .)
|
||||
if module_path.startswith('.'):
|
||||
# Convert relative to absolute
|
||||
parts = module_path.lstrip('.').split('.')
|
||||
rel_depth = len(module_path) - len(module_path.lstrip('.'))
|
||||
if rel_depth == 1:
|
||||
# Same package
|
||||
file_path = pkg_path
|
||||
else:
|
||||
file_path = pkg_path.parent
|
||||
for _ in range(rel_depth - 1):
|
||||
file_path = file_path.parent
|
||||
for part in parts:
|
||||
if part:
|
||||
file_path = file_path / part
|
||||
# Handle absolute imports starting with package name
|
||||
elif module_path.startswith(pkg_name + '.') or module_path == pkg_name:
|
||||
rel_path = module_path[len(pkg_name):].lstrip('.')
|
||||
parts = rel_path.split('.') if rel_path else []
|
||||
file_path = pkg_path
|
||||
for part in parts:
|
||||
file_path = file_path / part
|
||||
else:
|
||||
# Treat as relative import within package (e.g., 'agent.agent' -> pkg_path/agent/agent.py)
|
||||
# This handles lazy imports in __getattr__ that use implicit relative paths
|
||||
parts = module_path.split('.')
|
||||
file_path = pkg_path
|
||||
for part in parts:
|
||||
file_path = file_path / part
|
||||
|
||||
if file_path is None:
|
||||
return None
|
||||
|
||||
# Try as directory with __init__.py or as .py file
|
||||
if file_path.is_dir():
|
||||
init_file = file_path / "__init__.py"
|
||||
if init_file.exists():
|
||||
return self._find_symbol_in_file(init_file, original_name, pkg_name, export_name)
|
||||
|
||||
py_file = file_path.with_suffix('.py')
|
||||
if py_file.exists():
|
||||
return self._find_symbol_in_file(py_file, original_name, pkg_name, export_name)
|
||||
|
||||
return None
|
||||
|
||||
def _find_symbol_in_file(
|
||||
self,
|
||||
file_path: Path,
|
||||
symbol_name: str,
|
||||
pkg_name: str,
|
||||
export_name: Optional[str] = None
|
||||
) -> Optional[SymbolInfo]:
|
||||
"""Find a symbol definition in a Python file."""
|
||||
if not file_path.exists():
|
||||
return None
|
||||
|
||||
try:
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
source = f.read()
|
||||
tree = ast.parse(source)
|
||||
except (SyntaxError, UnicodeDecodeError):
|
||||
return None
|
||||
|
||||
rel_path = self._get_relative_path(file_path)
|
||||
module_path = self._file_to_module(file_path, pkg_name)
|
||||
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.ClassDef) and node.name == symbol_name:
|
||||
methods = self._extract_methods(node)
|
||||
return SymbolInfo(
|
||||
name=export_name or symbol_name,
|
||||
kind='class',
|
||||
module_path=module_path,
|
||||
file_path=rel_path,
|
||||
line_number=node.lineno,
|
||||
signature=self._extract_class_signature(node),
|
||||
methods=methods,
|
||||
docstring=ast.get_docstring(node)
|
||||
)
|
||||
elif isinstance(node, ast.FunctionDef) and node.name == symbol_name:
|
||||
return SymbolInfo(
|
||||
name=export_name or symbol_name,
|
||||
kind='function',
|
||||
module_path=module_path,
|
||||
file_path=rel_path,
|
||||
line_number=node.lineno,
|
||||
signature=self._extract_function_signature(node),
|
||||
return_type=self._extract_return_type(node),
|
||||
docstring=ast.get_docstring(node)
|
||||
)
|
||||
elif isinstance(node, ast.AsyncFunctionDef) and node.name == symbol_name:
|
||||
return SymbolInfo(
|
||||
name=export_name or symbol_name,
|
||||
kind='function',
|
||||
module_path=module_path,
|
||||
file_path=rel_path,
|
||||
line_number=node.lineno,
|
||||
signature=self._extract_function_signature(node),
|
||||
return_type=self._extract_return_type(node),
|
||||
docstring=ast.get_docstring(node)
|
||||
)
|
||||
elif isinstance(node, ast.Assign):
|
||||
for target in node.targets:
|
||||
if isinstance(target, ast.Name) and target.id == symbol_name:
|
||||
return SymbolInfo(
|
||||
name=export_name or symbol_name,
|
||||
kind='constant',
|
||||
module_path=module_path,
|
||||
file_path=rel_path,
|
||||
line_number=node.lineno
|
||||
)
|
||||
|
||||
# Check for re-exports in __init__.py
|
||||
if file_path.name == "__init__.py":
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.ImportFrom) and node.module:
|
||||
for alias in node.names:
|
||||
name = alias.asname if alias.asname else alias.name
|
||||
if name == symbol_name:
|
||||
# Recursively resolve
|
||||
return self._resolve_symbol(
|
||||
file_path.parent, pkg_name,
|
||||
'.' + node.module if not node.module.startswith('.') else node.module,
|
||||
alias.name, export_name or symbol_name
|
||||
)
|
||||
|
||||
return None
|
||||
|
||||
def _extract_methods(self, class_node: ast.ClassDef) -> List[MethodInfo]:
|
||||
"""Extract public methods from a class."""
|
||||
methods = []
|
||||
for node in class_node.body:
|
||||
if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)):
|
||||
if not node.name.startswith('_') or node.name in ('__init__', '__call__'):
|
||||
methods.append(MethodInfo(
|
||||
name=node.name,
|
||||
signature=self._extract_function_signature(node),
|
||||
return_type=self._extract_return_type(node),
|
||||
line_number=node.lineno
|
||||
))
|
||||
return sorted(methods, key=lambda m: m.name)
|
||||
|
||||
def _extract_function_signature(self, node: ast.FunctionDef) -> str:
|
||||
"""Extract function signature as string."""
|
||||
args = []
|
||||
|
||||
# Regular args
|
||||
defaults_offset = len(node.args.args) - len(node.args.defaults)
|
||||
for i, arg in enumerate(node.args.args):
|
||||
if arg.arg == 'self' or arg.arg == 'cls':
|
||||
continue
|
||||
arg_str = arg.arg
|
||||
if arg.annotation:
|
||||
arg_str += f": {self._annotation_to_str(arg.annotation)}"
|
||||
if i >= defaults_offset:
|
||||
default = node.args.defaults[i - defaults_offset]
|
||||
arg_str += f" = {self._default_to_str(default)}"
|
||||
args.append(arg_str)
|
||||
|
||||
# *args
|
||||
if node.args.vararg:
|
||||
arg_str = f"*{node.args.vararg.arg}"
|
||||
if node.args.vararg.annotation:
|
||||
arg_str += f": {self._annotation_to_str(node.args.vararg.annotation)}"
|
||||
args.append(arg_str)
|
||||
|
||||
# **kwargs
|
||||
if node.args.kwarg:
|
||||
arg_str = f"**{node.args.kwarg.arg}"
|
||||
if node.args.kwarg.annotation:
|
||||
arg_str += f": {self._annotation_to_str(node.args.kwarg.annotation)}"
|
||||
args.append(arg_str)
|
||||
|
||||
return f"({', '.join(args)})"
|
||||
|
||||
def _extract_class_signature(self, node: ast.ClassDef) -> str:
|
||||
"""Extract class __init__ signature."""
|
||||
for item in node.body:
|
||||
if isinstance(item, ast.FunctionDef) and item.name == '__init__':
|
||||
return self._extract_function_signature(item)
|
||||
return "()"
|
||||
|
||||
def _extract_return_type(self, node: ast.FunctionDef) -> Optional[str]:
|
||||
"""Extract return type annotation."""
|
||||
if node.returns:
|
||||
return self._annotation_to_str(node.returns)
|
||||
return None
|
||||
|
||||
def _annotation_to_str(self, node: ast.expr) -> str:
|
||||
"""Convert AST annotation to string."""
|
||||
if isinstance(node, ast.Name):
|
||||
return node.id
|
||||
elif isinstance(node, ast.Constant):
|
||||
return repr(node.value)
|
||||
elif isinstance(node, ast.Subscript):
|
||||
value = self._annotation_to_str(node.value)
|
||||
slice_val = self._annotation_to_str(node.slice)
|
||||
return f"{value}[{slice_val}]"
|
||||
elif isinstance(node, ast.Attribute):
|
||||
return f"{self._annotation_to_str(node.value)}.{node.attr}"
|
||||
elif isinstance(node, ast.Tuple):
|
||||
elts = ', '.join(self._annotation_to_str(e) for e in node.elts)
|
||||
return elts
|
||||
elif isinstance(node, ast.BinOp) and isinstance(node.op, ast.BitOr):
|
||||
left = self._annotation_to_str(node.left)
|
||||
right = self._annotation_to_str(node.right)
|
||||
return f"{left} | {right}"
|
||||
elif isinstance(node, ast.List):
|
||||
elts = ', '.join(self._annotation_to_str(e) for e in node.elts)
|
||||
return f"[{elts}]"
|
||||
return "Any"
|
||||
|
||||
def _default_to_str(self, node: ast.expr) -> str:
|
||||
"""Convert default value to string."""
|
||||
if isinstance(node, ast.Constant):
|
||||
return repr(node.value)
|
||||
elif isinstance(node, ast.Name):
|
||||
return node.id
|
||||
elif isinstance(node, ast.List):
|
||||
return "[]"
|
||||
elif isinstance(node, ast.Dict):
|
||||
return "{}"
|
||||
elif isinstance(node, ast.Call):
|
||||
return "..."
|
||||
return "..."
|
||||
|
||||
def _get_relative_path(self, file_path: Path) -> str:
|
||||
"""Get path relative to repo root."""
|
||||
try:
|
||||
return "./" + str(file_path.relative_to(self.repo_root))
|
||||
except ValueError:
|
||||
return str(file_path)
|
||||
|
||||
def _file_to_module(self, file_path: Path, pkg_name: str) -> str:
|
||||
"""Convert file path to module path."""
|
||||
try:
|
||||
if pkg_name == "praisonaiagents":
|
||||
rel = file_path.relative_to(self.agents_pkg.parent)
|
||||
else:
|
||||
rel = file_path.relative_to(self.wrapper_pkg.parent)
|
||||
parts = list(rel.parts)
|
||||
if parts[-1] == "__init__.py":
|
||||
parts = parts[:-1]
|
||||
elif parts[-1].endswith('.py'):
|
||||
parts[-1] = parts[-1][:-3]
|
||||
return '.'.join(parts)
|
||||
except ValueError:
|
||||
return pkg_name
|
||||
|
||||
def _discover_cli_commands(self) -> None:
|
||||
"""Discover CLI commands from Typer apps."""
|
||||
commands_dir = self.wrapper_pkg / "cli" / "commands"
|
||||
if not commands_dir.exists():
|
||||
return
|
||||
|
||||
for py_file in sorted(commands_dir.glob("*.py")):
|
||||
if py_file.name.startswith('_'):
|
||||
continue
|
||||
self._parse_typer_commands(py_file)
|
||||
|
||||
# Also check main.py for argparse commands
|
||||
main_py = self.wrapper_pkg / "cli" / "main.py"
|
||||
if main_py.exists():
|
||||
self._parse_main_commands(main_py)
|
||||
|
||||
def _parse_typer_commands(self, file_path: Path) -> None:
|
||||
"""Parse Typer command definitions from a file."""
|
||||
try:
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
source = f.read()
|
||||
tree = ast.parse(source)
|
||||
except (SyntaxError, UnicodeDecodeError):
|
||||
return
|
||||
|
||||
rel_path = self._get_relative_path(file_path)
|
||||
command_name = file_path.stem
|
||||
|
||||
# Find @app.command() decorators
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.FunctionDef):
|
||||
for decorator in node.decorator_list:
|
||||
if self._is_command_decorator(decorator):
|
||||
cmd_name = self._extract_command_name(decorator, node.name)
|
||||
help_text = ast.get_docstring(node)
|
||||
self.cli_commands.append(CLICommand(
|
||||
command_path=f"praisonai {command_name} {cmd_name}".strip(),
|
||||
help_text=help_text[:100] if help_text else None,
|
||||
file_path=rel_path,
|
||||
line_number=node.lineno
|
||||
))
|
||||
|
||||
def _is_command_decorator(self, decorator: ast.expr) -> bool:
|
||||
"""Check if decorator is @app.command() or similar."""
|
||||
if isinstance(decorator, ast.Call):
|
||||
if isinstance(decorator.func, ast.Attribute):
|
||||
return decorator.func.attr in ('command', 'callback')
|
||||
elif isinstance(decorator, ast.Attribute):
|
||||
return decorator.attr in ('command', 'callback')
|
||||
return False
|
||||
|
||||
def _extract_command_name(self, decorator: ast.expr, func_name: str) -> str:
|
||||
"""Extract command name from decorator or function name."""
|
||||
if isinstance(decorator, ast.Call):
|
||||
for arg in decorator.args:
|
||||
if isinstance(arg, ast.Constant) and isinstance(arg.value, str):
|
||||
return arg.value
|
||||
for kw in decorator.keywords:
|
||||
if kw.arg == 'name' and isinstance(kw.value, ast.Constant):
|
||||
return kw.value.value
|
||||
# Convert function name: some_command -> some-command
|
||||
return func_name.replace('_', '-')
|
||||
|
||||
def _parse_main_commands(self, file_path: Path) -> None:
|
||||
"""Parse main CLI commands from argparse in main.py."""
|
||||
# Add base commands that are handled in main.py
|
||||
rel_path = self._get_relative_path(file_path)
|
||||
base_commands = [
|
||||
("praisonai", "Main CLI entry point"),
|
||||
("praisonai run", "Run agents from YAML file"),
|
||||
("praisonai chat", "Terminal chat interface"),
|
||||
("praisonai code", "Terminal code assistant"),
|
||||
]
|
||||
for cmd, help_text in base_commands:
|
||||
self.cli_commands.append(CLICommand(
|
||||
command_path=cmd,
|
||||
help_text=help_text,
|
||||
file_path=rel_path,
|
||||
line_number=1
|
||||
))
|
||||
|
||||
def _discover_ts_exports(self) -> None:
|
||||
"""Discover TypeScript exports from index.ts."""
|
||||
index_file = self.ts_pkg / "src" / "index.ts"
|
||||
if not index_file.exists():
|
||||
return
|
||||
|
||||
try:
|
||||
with open(index_file, 'r', encoding='utf-8') as f:
|
||||
content = f.read()
|
||||
except (IOError, UnicodeDecodeError):
|
||||
return
|
||||
|
||||
# Parse export statements using regex
|
||||
# export { Name1, Name2 } from './path'
|
||||
export_pattern = r"export\s*\{([^}]+)\}\s*from\s*['\"]([^'\"]+)['\"]"
|
||||
type_export_pattern = r"export\s+type\s*\{([^}]+)\}\s*from\s*['\"]([^'\"]+)['\"]"
|
||||
|
||||
for match in re.finditer(export_pattern, content):
|
||||
names = match.group(1)
|
||||
source = match.group(2)
|
||||
for name in names.split(','):
|
||||
name = name.strip()
|
||||
if ' as ' in name:
|
||||
name = name.split(' as ')[1].strip()
|
||||
if name and not name.startswith('type '):
|
||||
self.ts_exports.append(TSExport(
|
||||
name=name,
|
||||
kind='export',
|
||||
source_file=source,
|
||||
is_type=False
|
||||
))
|
||||
|
||||
for match in re.finditer(type_export_pattern, content):
|
||||
names = match.group(1)
|
||||
source = match.group(2)
|
||||
for name in names.split(','):
|
||||
name = name.strip()
|
||||
if ' as ' in name:
|
||||
name = name.split(' as ')[1].strip()
|
||||
if name:
|
||||
self.ts_exports.append(TSExport(
|
||||
name=name,
|
||||
kind='type',
|
||||
source_file=source,
|
||||
is_type=True
|
||||
))
|
||||
|
||||
def generate(self) -> str:
|
||||
"""Generate the api.md content."""
|
||||
self.discover_all()
|
||||
|
||||
lines = [
|
||||
"# PraisonAI API Reference",
|
||||
"",
|
||||
"This file is auto-generated. Do not edit manually.",
|
||||
"Regenerate with: `praisonai docs api-md --write`",
|
||||
"",
|
||||
]
|
||||
|
||||
# Group symbols by section
|
||||
sections = self._group_symbols_by_section()
|
||||
|
||||
# Generate each section
|
||||
section_order = [
|
||||
'Shared Types', 'Agents', 'Tools', 'Workflows', 'DB', 'Memory',
|
||||
'Knowledge', 'RAG', 'Handoff', 'Guardrails', 'Planning', 'Skills',
|
||||
'Session', 'MCP', 'Telemetry', 'Observability', 'Context', 'UI',
|
||||
'Config', 'Display', 'Utilities'
|
||||
]
|
||||
|
||||
for section_name in section_order:
|
||||
if section_name in sections and sections[section_name]:
|
||||
lines.extend(self._generate_section(section_name, sections[section_name]))
|
||||
|
||||
# Handle remaining symbols not in predefined sections
|
||||
remaining = self._get_remaining_symbols(sections)
|
||||
if remaining:
|
||||
lines.extend(self._generate_section('Other', remaining))
|
||||
|
||||
# Wrapper package exports
|
||||
if self.wrapper_symbols:
|
||||
lines.extend(self._generate_wrapper_section())
|
||||
|
||||
# CLI section
|
||||
if self.cli_commands:
|
||||
lines.extend(self._generate_cli_section())
|
||||
|
||||
# TypeScript section
|
||||
if self.ts_exports:
|
||||
lines.extend(self._generate_ts_section())
|
||||
|
||||
# Optional Plugins section
|
||||
lines.extend(self._generate_plugins_section())
|
||||
|
||||
return '\n'.join(lines)
|
||||
|
||||
def _group_symbols_by_section(self) -> Dict[str, List[SymbolInfo]]:
|
||||
"""Group symbols by their section."""
|
||||
sections: Dict[str, List[SymbolInfo]] = {}
|
||||
|
||||
for section_name, symbol_names in self.SECTION_GROUPS.items():
|
||||
section_symbols = []
|
||||
for name in symbol_names:
|
||||
if name in self.agents_symbols:
|
||||
section_symbols.append(self.agents_symbols[name])
|
||||
if section_symbols:
|
||||
sections[section_name] = sorted(section_symbols, key=lambda s: s.name)
|
||||
|
||||
return sections
|
||||
|
||||
def _get_remaining_symbols(self, sections: Dict[str, List[SymbolInfo]]) -> List[SymbolInfo]:
|
||||
"""Get symbols not in any predefined section."""
|
||||
used_names = set()
|
||||
for symbol_list in sections.values():
|
||||
for symbol in symbol_list:
|
||||
used_names.add(symbol.name)
|
||||
|
||||
remaining = []
|
||||
for name, symbol in self.agents_symbols.items():
|
||||
if name not in used_names:
|
||||
remaining.append(symbol)
|
||||
|
||||
return sorted(remaining, key=lambda s: s.name)
|
||||
|
||||
def _generate_section(self, section_name: str, symbols: List[SymbolInfo]) -> List[str]:
|
||||
"""Generate a section of the API documentation."""
|
||||
lines = [
|
||||
f"# {section_name}",
|
||||
"",
|
||||
]
|
||||
|
||||
# Types block
|
||||
imports = []
|
||||
for symbol in symbols:
|
||||
if symbol.module_path.startswith('praisonaiagents'):
|
||||
imports.append(symbol.name)
|
||||
|
||||
if imports:
|
||||
lines.append("Types:")
|
||||
lines.append("```python")
|
||||
# Group imports by module
|
||||
lines.append(f"from praisonaiagents import {', '.join(sorted(imports))}")
|
||||
lines.append("```")
|
||||
lines.append("")
|
||||
|
||||
# Methods block
|
||||
methods_lines = []
|
||||
for symbol in symbols:
|
||||
if symbol.kind == 'class' and symbol.methods:
|
||||
for method in symbol.methods:
|
||||
if method.name == '__init__':
|
||||
continue
|
||||
ret_type = f" -> {method.return_type}" if method.return_type else ""
|
||||
methods_lines.append(
|
||||
f'* <code title="class {symbol.name}">{symbol.name}.'
|
||||
f'<a href="{symbol.file_path}">{method.name}</a>'
|
||||
f'{method.signature}{ret_type}</code>'
|
||||
)
|
||||
elif symbol.kind == 'function':
|
||||
ret_type = f" -> {symbol.return_type}" if symbol.return_type else ""
|
||||
module_prefix = symbol.module_path.split('.')[0]
|
||||
methods_lines.append(
|
||||
f'* <code title="function">{module_prefix}.'
|
||||
f'<a href="{symbol.file_path}">{symbol.name}</a>'
|
||||
f'{symbol.signature or "()"}{ret_type}</code>'
|
||||
)
|
||||
|
||||
if methods_lines:
|
||||
lines.append("Methods:")
|
||||
lines.append("")
|
||||
lines.extend(methods_lines)
|
||||
lines.append("")
|
||||
|
||||
return lines
|
||||
|
||||
def _generate_wrapper_section(self) -> List[str]:
|
||||
"""Generate section for praisonai wrapper package."""
|
||||
lines = [
|
||||
"# Wrapper (praisonai)",
|
||||
"",
|
||||
"Types:",
|
||||
"```python",
|
||||
]
|
||||
|
||||
imports = sorted(self.wrapper_symbols.keys())
|
||||
lines.append(f"from praisonai import {', '.join(imports)}")
|
||||
lines.append("```")
|
||||
lines.append("")
|
||||
|
||||
return lines
|
||||
|
||||
def _generate_cli_section(self) -> List[str]:
|
||||
"""Generate CLI commands section."""
|
||||
lines = [
|
||||
"# CLI",
|
||||
"",
|
||||
"Methods:",
|
||||
"",
|
||||
]
|
||||
|
||||
# Sort and deduplicate commands
|
||||
seen = set()
|
||||
for cmd in sorted(self.cli_commands, key=lambda c: c.command_path):
|
||||
if cmd.command_path in seen:
|
||||
continue
|
||||
seen.add(cmd.command_path)
|
||||
lines.append(
|
||||
f'* <code title="cli">{cmd.command_path} '
|
||||
f'<a href="{cmd.file_path}">--help</a></code>'
|
||||
)
|
||||
|
||||
lines.append("")
|
||||
return lines
|
||||
|
||||
def _generate_ts_section(self) -> List[str]:
|
||||
"""Generate TypeScript exports section."""
|
||||
lines = [
|
||||
"# TypeScript",
|
||||
"",
|
||||
"Types/Exports:",
|
||||
"```ts",
|
||||
]
|
||||
|
||||
# Group by source file
|
||||
by_source: Dict[str, List[TSExport]] = {}
|
||||
for export in self.ts_exports:
|
||||
if export.source_file not in by_source:
|
||||
by_source[export.source_file] = []
|
||||
by_source[export.source_file].append(export)
|
||||
|
||||
for source in sorted(by_source.keys()):
|
||||
exports = by_source[source]
|
||||
regular = [e.name for e in exports if not e.is_type]
|
||||
types = [e.name for e in exports if e.is_type]
|
||||
|
||||
if regular:
|
||||
lines.append(f'export {{ {", ".join(sorted(regular))} }} from "{source}";')
|
||||
if types:
|
||||
lines.append(f'export type {{ {", ".join(sorted(types))} }} from "{source}";')
|
||||
|
||||
lines.append("```")
|
||||
lines.append("")
|
||||
return lines
|
||||
|
||||
def _generate_plugins_section(self) -> List[str]:
|
||||
"""Generate optional plugins section."""
|
||||
return [
|
||||
"# Optional Plugins",
|
||||
"",
|
||||
"External tools are available via `praisonai-tools` package:",
|
||||
"",
|
||||
"```bash",
|
||||
"pip install praisonai-tools",
|
||||
"```",
|
||||
"",
|
||||
"See [PraisonAI-tools](https://github.com/MervinPraison/PraisonAI-tools) for available tools.",
|
||||
"",
|
||||
]
|
||||
|
||||
|
||||
def generate_api_md(
|
||||
repo_root: Optional[Path] = None,
|
||||
output_path: Optional[Path] = None,
|
||||
check: bool = False,
|
||||
stdout: bool = False
|
||||
) -> int:
|
||||
"""
|
||||
Generate api.md file.
|
||||
|
||||
Args:
|
||||
repo_root: Repository root path (auto-detected if None)
|
||||
output_path: Output file path (defaults to repo_root/api.md)
|
||||
check: If True, check if existing file matches (exit 1 if different)
|
||||
stdout: If True, print to stdout instead of writing file
|
||||
|
||||
Returns:
|
||||
Exit code (0 for success, 1 for check failure)
|
||||
"""
|
||||
generator = ApiMdGenerator(repo_root)
|
||||
content = generator.generate()
|
||||
|
||||
if stdout:
|
||||
print(content)
|
||||
return 0
|
||||
|
||||
if output_path is None:
|
||||
output_path = generator.repo_root / "api.md"
|
||||
|
||||
if check:
|
||||
if output_path.exists():
|
||||
with open(output_path, 'r', encoding='utf-8') as f:
|
||||
existing = f.read()
|
||||
if existing == content:
|
||||
print(f"✓ {output_path} is up to date")
|
||||
return 0
|
||||
else:
|
||||
print(f"✗ {output_path} is out of date")
|
||||
print("Run `praisonai docs api-md --write` to regenerate")
|
||||
return 1
|
||||
else:
|
||||
print(f"✗ {output_path} does not exist")
|
||||
print("Run `praisonai docs api-md --write` to generate")
|
||||
return 1
|
||||
|
||||
# Write the file
|
||||
with open(output_path, 'w', encoding='utf-8') as f:
|
||||
f.write(content)
|
||||
|
||||
print(f"✓ Generated {output_path}")
|
||||
return 0
|
||||
|
||||
|
||||
def main():
|
||||
"""CLI entry point for the generator."""
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Generate api.md for PraisonAI"
|
||||
)
|
||||
parser.add_argument(
|
||||
'--write', action='store_true', default=True,
|
||||
help='Write api.md file (default)'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--check', action='store_true',
|
||||
help='Check if api.md is up to date (exit 1 if not)'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--stdout', action='store_true',
|
||||
help='Print to stdout instead of writing file'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--output', '-o', type=Path,
|
||||
help='Output file path (default: repo_root/api.md)'
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
exit_code = generate_api_md(
|
||||
output_path=args.output,
|
||||
check=args.check,
|
||||
stdout=args.stdout
|
||||
)
|
||||
sys.exit(exit_code)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -141,11 +141,18 @@ def main_callback(
|
||||
)
|
||||
set_output_controller(state.output_controller)
|
||||
|
||||
# If no command provided, show help or handle legacy behavior
|
||||
# If no command provided, start interactive mode
|
||||
if ctx.invoked_subcommand is None:
|
||||
# Check if there are remaining args (legacy behavior)
|
||||
# This is handled by the legacy adapter in main.py
|
||||
pass
|
||||
from praisonai.cli.interactive.async_tui import AsyncTUI, AsyncTUIConfig
|
||||
|
||||
tui_config = AsyncTUIConfig(
|
||||
model="gpt-4o-mini",
|
||||
show_logo=True,
|
||||
show_status_bar=state.output_format != OutputFormat.json,
|
||||
)
|
||||
|
||||
tui = AsyncTUI(config=tui_config)
|
||||
tui.run()
|
||||
|
||||
|
||||
def get_output_controller() -> OutputController:
|
||||
@@ -266,6 +273,115 @@ def register_commands():
|
||||
app.add_typer(test_app, name="test", help="Run test suite with tier and provider options")
|
||||
app.add_typer(examples_app, name="examples", help="Run and manage example files")
|
||||
|
||||
# Register standardise command
|
||||
try:
|
||||
standardise_app = typer.Typer(name="standardise", help="Documentation and examples standardisation (FDEP)")
|
||||
|
||||
@standardise_app.command("check")
|
||||
def standardise_check(
|
||||
path: str = typer.Option(".", "--path", "-p", help="Project root path"),
|
||||
feature: str = typer.Option(None, "--feature", help="Specific feature slug"),
|
||||
scope: str = typer.Option("all", "--scope", help="Scope: all, docs, examples, sdk, cli"),
|
||||
ci: bool = typer.Option(False, "--ci", help="CI mode"),
|
||||
):
|
||||
"""Check for standardisation issues."""
|
||||
from .commands.standardise import _run_check
|
||||
import argparse
|
||||
args = argparse.Namespace(path=path, feature=feature, scope=scope, ci=ci, dry_run=True)
|
||||
_run_check(args)
|
||||
|
||||
@standardise_app.command("report")
|
||||
def standardise_report(
|
||||
path: str = typer.Option(".", "--path", "-p", help="Project root path"),
|
||||
format: str = typer.Option("text", "--format", "-f", help="Format: text, json, markdown"),
|
||||
output: str = typer.Option(None, "--output", "-o", help="Output file"),
|
||||
ci: bool = typer.Option(False, "--ci", help="CI mode"),
|
||||
):
|
||||
"""Generate detailed report."""
|
||||
from .commands.standardise import _run_report
|
||||
import argparse
|
||||
args = argparse.Namespace(path=path, format=format, output=output, ci=ci, feature=None, scope="all", dry_run=True)
|
||||
_run_report(args)
|
||||
|
||||
@standardise_app.command("fix")
|
||||
def standardise_fix(
|
||||
path: str = typer.Option(".", "--path", "-p", help="Project root path"),
|
||||
feature: str = typer.Option(None, "--feature", help="Specific feature slug"),
|
||||
apply: bool = typer.Option(False, "--apply", help="Actually apply changes"),
|
||||
no_backup: bool = typer.Option(False, "--no-backup", help="Don't create backups"),
|
||||
):
|
||||
"""Fix standardisation issues."""
|
||||
from .commands.standardise import _run_fix
|
||||
import argparse
|
||||
args = argparse.Namespace(path=path, feature=feature, apply=apply, no_backup=no_backup, scope="all", ci=False, dry_run=not apply)
|
||||
_run_fix(args)
|
||||
|
||||
@standardise_app.command("init")
|
||||
def standardise_init(
|
||||
feature: str = typer.Argument(..., help="Feature slug to initialise"),
|
||||
path: str = typer.Option(".", "--path", "-p", help="Project root path"),
|
||||
apply: bool = typer.Option(False, "--apply", help="Actually create files"),
|
||||
):
|
||||
"""Initialise a new feature with all required artifacts."""
|
||||
from .commands.standardise import _run_init
|
||||
import argparse
|
||||
args = argparse.Namespace(feature=feature, path=path, apply=apply, scope="all", ci=False, dry_run=not apply)
|
||||
_run_init(args)
|
||||
|
||||
@standardise_app.command("ai")
|
||||
def standardise_ai(
|
||||
feature: str = typer.Argument(..., help="Feature slug to generate content for"),
|
||||
gen_type: str = typer.Option("all", "--type", "-t", help="Type: docs, examples, all"),
|
||||
apply: bool = typer.Option(False, "--apply", help="Actually create files"),
|
||||
verify: bool = typer.Option(False, "--verify", help="Verify with AI"),
|
||||
model: str = typer.Option("gpt-4o-mini", "--model", help="LLM model"),
|
||||
path: str = typer.Option(".", "--path", "-p", help="Project root path"),
|
||||
):
|
||||
"""AI-powered generation of docs/examples."""
|
||||
from .commands.standardise import _run_ai
|
||||
import argparse
|
||||
args = argparse.Namespace(feature=feature, type=gen_type, apply=apply, verify=verify, model=model, path=path, scope="all", ci=False, dry_run=not apply)
|
||||
_run_ai(args)
|
||||
|
||||
@standardise_app.command("checkpoint")
|
||||
def standardise_checkpoint(
|
||||
message: str = typer.Option(None, "--message", "-m", help="Checkpoint message"),
|
||||
path: str = typer.Option(".", "--path", "-p", help="Repository path"),
|
||||
):
|
||||
"""Create an undo checkpoint."""
|
||||
from .commands.standardise import _run_checkpoint
|
||||
import argparse
|
||||
args = argparse.Namespace(message=message, path=path)
|
||||
_run_checkpoint(args)
|
||||
|
||||
@standardise_app.command("undo")
|
||||
def standardise_undo(
|
||||
checkpoint: str = typer.Option(None, "--checkpoint", help="Checkpoint ID"),
|
||||
list_checkpoints: bool = typer.Option(False, "--list", help="List checkpoints"),
|
||||
path: str = typer.Option(".", "--path", "-p", help="Repository path"),
|
||||
):
|
||||
"""Undo to a previous checkpoint."""
|
||||
from .commands.standardise import _run_undo
|
||||
import argparse
|
||||
args = argparse.Namespace(checkpoint=checkpoint, list=list_checkpoints, path=path)
|
||||
_run_undo(args)
|
||||
|
||||
@standardise_app.command("redo")
|
||||
def standardise_redo(
|
||||
path: str = typer.Option(".", "--path", "-p", help="Repository path"),
|
||||
):
|
||||
"""Redo after an undo."""
|
||||
from .commands.standardise import _run_redo
|
||||
import argparse
|
||||
args = argparse.Namespace(path=path)
|
||||
_run_redo(args)
|
||||
|
||||
app.add_typer(standardise_app, name="standardise", help="Documentation and examples standardisation (FDEP)")
|
||||
# Also register as 'standardize' for US spelling
|
||||
app.add_typer(standardise_app, name="standardize", help="Documentation and examples standardisation (FDEP)")
|
||||
except Exception:
|
||||
pass # Graceful degradation if standardise module not available
|
||||
|
||||
# Register TUI and queue commands
|
||||
tui_app = create_tui_debug_app()
|
||||
queue_app = create_queue_app()
|
||||
|
||||
@@ -0,0 +1,94 @@
|
||||
"""
|
||||
PraisonAI Branding - Single Source of Truth.
|
||||
|
||||
This module provides unified branding assets (logo, version, product name)
|
||||
for all interactive UIs. All frontends should import from here.
|
||||
|
||||
Usage:
|
||||
from praisonai.cli.branding import get_logo, get_version, PRODUCT_NAME
|
||||
"""
|
||||
|
||||
# Product name
|
||||
PRODUCT_NAME = "Praison AI"
|
||||
|
||||
# ASCII Art Logos - responsive to terminal width
|
||||
LOGO_LARGE = r"""
|
||||
██████╗ ██████╗ █████╗ ██╗███████╗ ██████╗ ███╗ ██╗ █████╗ ██╗
|
||||
██╔══██╗██╔══██╗██╔══██╗██║██╔════╝██╔═══██╗████╗ ██║ ██╔══██╗██║
|
||||
██████╔╝██████╔╝███████║██║███████╗██║ ██║██╔██╗ ██║ ███████║██║
|
||||
██╔═══╝ ██╔══██╗██╔══██║██║╚════██║██║ ██║██║╚██╗██║ ██╔══██║██║
|
||||
██║ ██║ ██║██║ ██║██║███████║╚██████╔╝██║ ╚████║ ██║ ██║██║
|
||||
╚═╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚═╝╚══════╝ ╚═════╝ ╚═╝ ╚═══╝ ╚═╝ ╚═╝╚═╝
|
||||
"""
|
||||
|
||||
LOGO_MEDIUM = r"""
|
||||
╔═╗┬─┐┌─┐┬┌─┐┌─┐┌┐┌ ╔═╗╦
|
||||
╠═╝├┬┘├─┤│└─┐│ ││││ ╠═╣║
|
||||
╩ ┴└─┴ ┴┴└─┘└─┘┘└┘ ╩ ╩╩
|
||||
"""
|
||||
|
||||
LOGO_SMALL = "▶ Praison AI"
|
||||
|
||||
LOGO_MINIMAL = "Praison AI"
|
||||
|
||||
|
||||
def get_version() -> str:
|
||||
"""Get PraisonAI version string."""
|
||||
try:
|
||||
from praisonai import __version__
|
||||
return __version__
|
||||
except Exception:
|
||||
return "1.0.0"
|
||||
|
||||
|
||||
def get_logo(width: int = 80) -> str:
|
||||
"""
|
||||
Get appropriate logo based on terminal width.
|
||||
|
||||
Args:
|
||||
width: Terminal width in characters
|
||||
|
||||
Returns:
|
||||
ASCII art logo string appropriate for the width
|
||||
"""
|
||||
if width >= 75:
|
||||
return LOGO_LARGE
|
||||
elif width >= 40:
|
||||
return LOGO_MEDIUM
|
||||
else:
|
||||
return LOGO_SMALL
|
||||
|
||||
|
||||
def get_banner(width: int = 80, show_version: bool = True, model: str = None) -> str:
|
||||
"""
|
||||
Get full banner with logo, version, and optional model info.
|
||||
|
||||
Args:
|
||||
width: Terminal width
|
||||
show_version: Whether to include version
|
||||
model: Optional model name to display
|
||||
|
||||
Returns:
|
||||
Complete banner string
|
||||
"""
|
||||
lines = []
|
||||
|
||||
# Logo
|
||||
logo = get_logo(width)
|
||||
lines.append(logo.strip())
|
||||
lines.append("")
|
||||
|
||||
# Version and model
|
||||
version_line = f" v{get_version()}"
|
||||
if model:
|
||||
version_line += f" · Model: {model}"
|
||||
lines.append(version_line)
|
||||
lines.append("")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def get_welcome_tips() -> str:
|
||||
"""Get welcome tips for new sessions."""
|
||||
return """ Type your message and press Enter. Use /help for commands.
|
||||
Use PageUp/PageDown or Ctrl+Up/Down to scroll."""
|
||||
@@ -67,6 +67,7 @@ def chat_main(
|
||||
workspace: Optional[str] = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
|
||||
no_acp: bool = typer.Option(False, "--no-acp", help="Disable ACP tools"),
|
||||
no_lsp: bool = typer.Option(False, "--no-lsp", help="Disable LSP tools"),
|
||||
safe_mode: bool = typer.Option(False, "--safe", help="Safe mode: require approval for file writes and commands"),
|
||||
autonomy: bool = typer.Option(True, "--autonomy/--no-autonomy", help="Enable agent autonomy for complex tasks"),
|
||||
# NEW: Agent-like consolidated params for ALL GREEN consistency
|
||||
knowledge: Optional[str] = typer.Option(
|
||||
@@ -93,8 +94,46 @@ def chat_main(
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
# NEW: Additional consolidated params for ALL GREEN feature parity
|
||||
planning: Optional[str] = typer.Option(
|
||||
None, "--planning",
|
||||
help="Enable planning mode. Use --planning for default, --planning=thorough for preset",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
context: Optional[str] = typer.Option(
|
||||
None, "--context",
|
||||
help="Enable context management. Use --context for default",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
output: Optional[str] = typer.Option(
|
||||
None, "--output", "-o",
|
||||
help="Output mode (default: actions). Options: actions, plain, verbose, json, silent",
|
||||
),
|
||||
execution: Optional[str] = typer.Option(
|
||||
None, "--execution",
|
||||
help="Execution preset. Use --execution=fast, --execution=thorough, --execution=unlimited",
|
||||
),
|
||||
hooks: Optional[str] = typer.Option(
|
||||
None, "--hooks",
|
||||
help="Hooks config file path for lifecycle callbacks",
|
||||
),
|
||||
caching: Optional[str] = typer.Option(
|
||||
None, "--caching",
|
||||
help="Enable caching. Use --caching for default, --caching=redis for preset",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
profile: bool = typer.Option(False, "--profile", help="Enable CLI profiling (timing breakdown)"),
|
||||
profile_deep: bool = typer.Option(False, "--profile-deep", help="Enable deep profiling (cProfile stats, higher overhead)"),
|
||||
debug: bool = typer.Option(False, "--debug", help="Enable debug logging to ~/.praisonai/async_tui_debug.log"),
|
||||
# UI backend selection
|
||||
ui_backend: str = typer.Option("auto", "--ui-backend", help="UI backend: auto, plain, rich, mg (middle-ground)"),
|
||||
json_output: bool = typer.Option(False, "--json", help="Output JSON (forces plain backend)"),
|
||||
no_color: bool = typer.Option(False, "--no-color", help="Disable colors"),
|
||||
theme: str = typer.Option("default", "--theme", help="UI theme: default, dark, light, minimal"),
|
||||
compact: bool = typer.Option(False, "--compact", help="Compact output mode"),
|
||||
):
|
||||
"""
|
||||
Start terminal-native interactive chat mode.
|
||||
@@ -112,7 +151,6 @@ def chat_main(
|
||||
praisonai chat "Summarize this" --file README.md
|
||||
praisonai chat "What is 2+2?" --profile
|
||||
"""
|
||||
import asyncio
|
||||
import os
|
||||
|
||||
# Set workspace if provided
|
||||
@@ -135,55 +173,38 @@ def chat_main(
|
||||
typer.echo(" Use: praisonai chat \"your prompt\" --profile", err=True)
|
||||
|
||||
# Parse memory flag: --no-memory takes precedence, then --memory value
|
||||
memory_value = _parse_memory_flag(memory, no_memory)
|
||||
# TODO: Pass memory_value to TUI when memory support is added
|
||||
_parse_memory_flag(memory, no_memory)
|
||||
|
||||
# Try InteractiveCore first (preferred terminal-native implementation)
|
||||
try:
|
||||
from praisonai.cli.interactive import InteractiveCore, InteractiveConfig
|
||||
from praisonai.cli.interactive.frontends import RichFrontend
|
||||
|
||||
config = InteractiveConfig(
|
||||
model=model,
|
||||
session_id=session_id,
|
||||
continue_session=continue_session,
|
||||
workspace=workspace or None,
|
||||
verbose=verbose,
|
||||
memory=memory_value,
|
||||
files=list(file) if file else [],
|
||||
autonomy=autonomy,
|
||||
)
|
||||
|
||||
core = InteractiveCore(config=config)
|
||||
|
||||
if prompt:
|
||||
# Single prompt mode
|
||||
async def run_prompt():
|
||||
if continue_session:
|
||||
core.continue_session()
|
||||
response = await core.prompt(prompt)
|
||||
print(response)
|
||||
|
||||
asyncio.run(run_prompt())
|
||||
else:
|
||||
# Interactive REPL mode
|
||||
frontend = RichFrontend(core=core, config=config)
|
||||
asyncio.run(frontend.run())
|
||||
|
||||
except ImportError:
|
||||
# Fallback to legacy terminal-native interactive mode
|
||||
_run_legacy_terminal_chat(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
verbose=verbose,
|
||||
memory=memory,
|
||||
tools=tools,
|
||||
user_id=user_id,
|
||||
session_id=session_id,
|
||||
continue_session=continue_session,
|
||||
workspace=workspace,
|
||||
no_acp=no_acp,
|
||||
no_lsp=no_lsp,
|
||||
)
|
||||
# Set approval mode based on --safe flag
|
||||
import os
|
||||
if safe_mode:
|
||||
os.environ["PRAISON_APPROVAL_MODE"] = "prompt"
|
||||
else:
|
||||
os.environ["PRAISON_APPROVAL_MODE"] = "auto"
|
||||
|
||||
# Use the async TUI (non-blocking, scrollable output)
|
||||
from praisonai.cli.interactive.async_tui import AsyncTUI, AsyncTUIConfig
|
||||
|
||||
tui_config = AsyncTUIConfig(
|
||||
model=model or "gpt-4o-mini",
|
||||
show_logo=not compact,
|
||||
show_status_bar=not compact,
|
||||
session_id=session_id,
|
||||
workspace=workspace,
|
||||
debug=debug,
|
||||
)
|
||||
|
||||
tui = AsyncTUI(config=tui_config)
|
||||
|
||||
if prompt:
|
||||
# Single prompt mode - direct response, no streaming
|
||||
response = tui.run_single(prompt)
|
||||
if response:
|
||||
print(response)
|
||||
else:
|
||||
# Interactive split-pane TUI mode
|
||||
tui.run()
|
||||
|
||||
|
||||
def _run_profiled_chat(
|
||||
@@ -221,7 +242,6 @@ def _run_profiled_chat(
|
||||
"name": "ChatAgent",
|
||||
"role": "Assistant",
|
||||
"goal": "Help the user",
|
||||
"verbose": verbose,
|
||||
}
|
||||
if model:
|
||||
agent_config["llm"] = model
|
||||
|
||||
@@ -23,6 +23,7 @@ def code_main(
|
||||
file: Optional[List[str]] = typer.Option(None, "--file", "-f", help="Attach file(s) to context"),
|
||||
no_acp: bool = typer.Option(False, "--no-acp", help="Disable ACP tools (file operations)"),
|
||||
no_lsp: bool = typer.Option(False, "--no-lsp", help="Disable LSP tools (code intelligence)"),
|
||||
safe_mode: bool = typer.Option(False, "--safe", help="Safe mode: require approval for file writes and commands"),
|
||||
session_id: Optional[str] = typer.Option(None, "--session", "-s", help="Session ID to resume"),
|
||||
continue_session: bool = typer.Option(False, "--continue", "-c", help="Continue last session"),
|
||||
autonomy: bool = typer.Option(True, "--autonomy/--no-autonomy", help="Enable agent autonomy for complex tasks"),
|
||||
@@ -54,6 +55,12 @@ def code_main(
|
||||
# Enable code-specific environment
|
||||
os.environ["PRAISONAI_CODE_MODE"] = "true"
|
||||
|
||||
# Set approval mode based on --safe flag
|
||||
if safe_mode:
|
||||
os.environ["PRAISON_APPROVAL_MODE"] = "prompt"
|
||||
else:
|
||||
os.environ["PRAISON_APPROVAL_MODE"] = "auto"
|
||||
|
||||
# Handle profiling for single prompt mode
|
||||
if prompt and (profile or profile_deep):
|
||||
_run_profiled_code(
|
||||
|
||||
@@ -813,3 +813,47 @@ def docs_report(
|
||||
|
||||
typer.echo(output)
|
||||
raise typer.Exit(exit_code)
|
||||
|
||||
|
||||
@app.command("api-md")
|
||||
def docs_api_md(
|
||||
write: bool = typer.Option(
|
||||
True,
|
||||
"--write", "-w",
|
||||
help="Write api.md file (default)",
|
||||
),
|
||||
check: bool = typer.Option(
|
||||
False,
|
||||
"--check", "-c",
|
||||
help="Check if api.md is up to date (exit 1 if not)",
|
||||
),
|
||||
stdout: bool = typer.Option(
|
||||
False,
|
||||
"--stdout", "-s",
|
||||
help="Print to stdout instead of writing file",
|
||||
),
|
||||
output: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--output", "-o",
|
||||
help="Output file path (default: repo_root/api.md)",
|
||||
),
|
||||
):
|
||||
"""
|
||||
Generate or check the api.md API reference file.
|
||||
|
||||
This command generates a comprehensive API reference document
|
||||
covering all public exports from praisonaiagents, praisonai, CLI, and TypeScript.
|
||||
|
||||
Examples:
|
||||
praisonai docs api-md # Generate api.md
|
||||
praisonai docs api-md --check # Check if api.md is up to date
|
||||
praisonai docs api-md --stdout # Print to stdout
|
||||
"""
|
||||
from praisonai._dev.api_md import generate_api_md
|
||||
|
||||
exit_code = generate_api_md(
|
||||
output_path=output,
|
||||
check=check,
|
||||
stdout=stdout
|
||||
)
|
||||
raise typer.Exit(exit_code)
|
||||
@@ -29,6 +29,7 @@ def run_main(
|
||||
max_tokens: int = typer.Option(16000, "--max-tokens", help="Maximum output tokens"),
|
||||
profile: bool = typer.Option(False, "--profile", help="Enable CLI profiling (timing breakdown)"),
|
||||
profile_deep: bool = typer.Option(False, "--profile-deep", help="Enable deep profiling (cProfile stats, higher overhead)"),
|
||||
output_mode: Optional[str] = typer.Option(None, "--output", "-o", help="Output mode: actions, verbose, silent, stream"),
|
||||
):
|
||||
"""
|
||||
Run agents from a file or prompt.
|
||||
@@ -108,6 +109,7 @@ def run_main(
|
||||
memory=memory,
|
||||
tools=tools,
|
||||
max_tokens=max_tokens,
|
||||
output_mode=output_mode,
|
||||
)
|
||||
else:
|
||||
# Run as prompt
|
||||
@@ -120,6 +122,7 @@ def run_main(
|
||||
memory=memory,
|
||||
tools=tools,
|
||||
max_tokens=max_tokens,
|
||||
output_mode=output_mode,
|
||||
)
|
||||
|
||||
|
||||
@@ -134,6 +137,7 @@ def _run_from_file(
|
||||
memory: bool = False,
|
||||
tools: Optional[str] = None,
|
||||
max_tokens: int = 16000,
|
||||
output_mode: Optional[str] = None,
|
||||
):
|
||||
"""Run agents from a YAML file."""
|
||||
output = get_output_controller()
|
||||
@@ -178,12 +182,37 @@ def _run_prompt(
|
||||
memory: bool = False,
|
||||
tools: Optional[str] = None,
|
||||
max_tokens: int = 16000,
|
||||
output_mode: Optional[str] = None,
|
||||
):
|
||||
"""Run a direct prompt."""
|
||||
output = get_output_controller()
|
||||
|
||||
try:
|
||||
# Use existing handle_direct_prompt
|
||||
# If output_mode is "actions", use direct Agent with actions preset
|
||||
if output_mode == "actions":
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent_config = {
|
||||
"name": "RunAgent",
|
||||
"role": "Assistant",
|
||||
"goal": "Complete the task",
|
||||
"output": "actions", # Use actions preset
|
||||
}
|
||||
if model:
|
||||
agent_config["llm"] = model
|
||||
|
||||
agent = Agent(**agent_config)
|
||||
result = agent.start(prompt)
|
||||
|
||||
output.emit_result(
|
||||
message="Prompt completed",
|
||||
data={"result": str(result) if result else None}
|
||||
)
|
||||
|
||||
# Don't print result again - actions mode already shows output
|
||||
return
|
||||
|
||||
# Use existing handle_direct_prompt for other modes
|
||||
from praisonai.cli.main import PraisonAI
|
||||
|
||||
praison = PraisonAI()
|
||||
|
||||
@@ -0,0 +1,694 @@
|
||||
"""
|
||||
CLI commands for the FDEP standardisation system.
|
||||
|
||||
Commands:
|
||||
- praisonai standardise check - Check for standardisation issues
|
||||
- praisonai standardise report - Generate detailed report
|
||||
- praisonai standardise fix - Fix issues (with --apply)
|
||||
- praisonai standardise init - Initialise a new feature
|
||||
- praisonai standardise ai - AI-powered generation
|
||||
- praisonai standardise checkpoint - Create undo checkpoint
|
||||
- praisonai standardise undo - Undo to previous checkpoint
|
||||
- praisonai standardise redo - Redo after undo
|
||||
"""
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def _lazy_import_engine():
|
||||
"""Lazy import to avoid heavy imports at CLI startup."""
|
||||
from praisonai.standardise import StandardiseEngine, StandardiseConfig
|
||||
return StandardiseEngine, StandardiseConfig
|
||||
|
||||
|
||||
def standardise_command(args=None):
|
||||
"""Main entry point for standardise command."""
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser(
|
||||
prog="praisonai standardise",
|
||||
description="Standardise documentation and examples (FDEP)",
|
||||
)
|
||||
|
||||
subparsers = parser.add_subparsers(dest="subcommand", help="Subcommands")
|
||||
|
||||
# check subcommand
|
||||
check_parser = subparsers.add_parser(
|
||||
"check",
|
||||
help="Check for standardisation issues (default)",
|
||||
)
|
||||
_add_common_args(check_parser)
|
||||
|
||||
# report subcommand
|
||||
report_parser = subparsers.add_parser(
|
||||
"report",
|
||||
help="Generate detailed report",
|
||||
)
|
||||
_add_common_args(report_parser)
|
||||
report_parser.add_argument(
|
||||
"--format", "-f",
|
||||
choices=["text", "json", "markdown"],
|
||||
default="text",
|
||||
help="Report format (default: text)",
|
||||
)
|
||||
report_parser.add_argument(
|
||||
"--output", "-o",
|
||||
type=str,
|
||||
help="Output file path (default: stdout)",
|
||||
)
|
||||
|
||||
# fix subcommand
|
||||
fix_parser = subparsers.add_parser(
|
||||
"fix",
|
||||
help="Fix standardisation issues",
|
||||
)
|
||||
_add_common_args(fix_parser)
|
||||
fix_parser.add_argument(
|
||||
"--apply",
|
||||
action="store_true",
|
||||
help="Actually apply changes (default: dry-run)",
|
||||
)
|
||||
fix_parser.add_argument(
|
||||
"--no-backup",
|
||||
action="store_true",
|
||||
help="Don't create backups before changes",
|
||||
)
|
||||
|
||||
# init subcommand
|
||||
init_parser = subparsers.add_parser(
|
||||
"init",
|
||||
help="Initialise a new feature with all required artifacts",
|
||||
)
|
||||
init_parser.add_argument(
|
||||
"feature",
|
||||
type=str,
|
||||
help="Feature slug to initialise",
|
||||
)
|
||||
_add_common_args(init_parser)
|
||||
init_parser.add_argument(
|
||||
"--apply",
|
||||
action="store_true",
|
||||
help="Actually create files (default: dry-run)",
|
||||
)
|
||||
|
||||
# ai subcommand
|
||||
ai_parser = subparsers.add_parser(
|
||||
"ai",
|
||||
help="AI-powered generation of docs/examples",
|
||||
)
|
||||
ai_parser.add_argument(
|
||||
"feature",
|
||||
type=str,
|
||||
help="Feature slug to generate content for",
|
||||
)
|
||||
ai_parser.add_argument(
|
||||
"--type", "-t",
|
||||
choices=["docs", "examples", "all"],
|
||||
default="all",
|
||||
help="Type of content to generate",
|
||||
)
|
||||
ai_parser.add_argument(
|
||||
"--apply",
|
||||
action="store_true",
|
||||
help="Actually create files (default: dry-run preview)",
|
||||
)
|
||||
ai_parser.add_argument(
|
||||
"--verify",
|
||||
action="store_true",
|
||||
help="Verify generated content with AI",
|
||||
)
|
||||
ai_parser.add_argument(
|
||||
"--model",
|
||||
type=str,
|
||||
default="gpt-4o-mini",
|
||||
help="LLM model to use (default: gpt-4o-mini)",
|
||||
)
|
||||
_add_common_args(ai_parser)
|
||||
|
||||
# checkpoint subcommand
|
||||
checkpoint_parser = subparsers.add_parser(
|
||||
"checkpoint",
|
||||
help="Create an undo checkpoint",
|
||||
)
|
||||
checkpoint_parser.add_argument(
|
||||
"--message", "-m",
|
||||
type=str,
|
||||
help="Checkpoint message",
|
||||
)
|
||||
checkpoint_parser.add_argument(
|
||||
"--path", "-p",
|
||||
type=str,
|
||||
default=".",
|
||||
help="Repository path",
|
||||
)
|
||||
|
||||
# undo subcommand
|
||||
undo_parser = subparsers.add_parser(
|
||||
"undo",
|
||||
help="Undo to a previous checkpoint",
|
||||
)
|
||||
undo_parser.add_argument(
|
||||
"--checkpoint",
|
||||
type=str,
|
||||
help="Specific checkpoint ID to restore",
|
||||
)
|
||||
undo_parser.add_argument(
|
||||
"--list",
|
||||
action="store_true",
|
||||
help="List available checkpoints",
|
||||
)
|
||||
undo_parser.add_argument(
|
||||
"--path", "-p",
|
||||
type=str,
|
||||
default=".",
|
||||
help="Repository path",
|
||||
)
|
||||
|
||||
# redo subcommand
|
||||
redo_parser = subparsers.add_parser(
|
||||
"redo",
|
||||
help="Redo after an undo",
|
||||
)
|
||||
redo_parser.add_argument(
|
||||
"--path", "-p",
|
||||
type=str,
|
||||
default=".",
|
||||
help="Repository path",
|
||||
)
|
||||
|
||||
# Parse args
|
||||
parsed = parser.parse_args(args)
|
||||
|
||||
# Default to check if no subcommand
|
||||
if not parsed.subcommand:
|
||||
parsed.subcommand = "check"
|
||||
parsed = parser.parse_args(["check"] + (args or []))
|
||||
|
||||
# Execute subcommand
|
||||
if parsed.subcommand == "check":
|
||||
return _run_check(parsed)
|
||||
elif parsed.subcommand == "report":
|
||||
return _run_report(parsed)
|
||||
elif parsed.subcommand == "fix":
|
||||
return _run_fix(parsed)
|
||||
elif parsed.subcommand == "init":
|
||||
return _run_init(parsed)
|
||||
elif parsed.subcommand == "ai":
|
||||
return _run_ai(parsed)
|
||||
elif parsed.subcommand == "checkpoint":
|
||||
return _run_checkpoint(parsed)
|
||||
elif parsed.subcommand == "undo":
|
||||
return _run_undo(parsed)
|
||||
elif parsed.subcommand == "redo":
|
||||
return _run_redo(parsed)
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _add_common_args(parser):
|
||||
"""Add common arguments to a parser."""
|
||||
parser.add_argument(
|
||||
"--path", "-p",
|
||||
type=str,
|
||||
default=".",
|
||||
help="Project root path (default: current directory)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--feature",
|
||||
type=str,
|
||||
help="Specific feature slug to check",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--scope",
|
||||
choices=["all", "docs", "examples", "sdk", "cli"],
|
||||
default="all",
|
||||
help="Scope of check (default: all)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--ci",
|
||||
action="store_true",
|
||||
help="CI mode (no prompts, machine-readable output)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--dry-run",
|
||||
action="store_true",
|
||||
default=True,
|
||||
help="Don't make changes (default: true)",
|
||||
)
|
||||
|
||||
|
||||
def _create_config(parsed):
|
||||
"""Create config from parsed arguments."""
|
||||
_, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = StandardiseConfig(
|
||||
project_root=Path(parsed.path).resolve() if hasattr(parsed, "path") else None,
|
||||
dry_run=getattr(parsed, "dry_run", True) and not getattr(parsed, "apply", False),
|
||||
backup=not getattr(parsed, "no_backup", False),
|
||||
scope=getattr(parsed, "scope", "all"),
|
||||
feature_filter=getattr(parsed, "feature", None),
|
||||
ci_mode=getattr(parsed, "ci", False),
|
||||
report_format=getattr(parsed, "format", "text"),
|
||||
)
|
||||
|
||||
return config
|
||||
|
||||
|
||||
def _run_check(parsed) -> int:
|
||||
"""Run the check subcommand."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = _create_config(parsed)
|
||||
engine = StandardiseEngine(config)
|
||||
|
||||
report = engine.check()
|
||||
|
||||
# Print report
|
||||
output = engine.reports.generate(report, "text")
|
||||
print(output)
|
||||
|
||||
# Return exit code
|
||||
if config.ci_mode:
|
||||
return engine.get_exit_code(report)
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_report(parsed) -> int:
|
||||
"""Run the report subcommand."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = _create_config(parsed)
|
||||
engine = StandardiseEngine(config)
|
||||
|
||||
report = engine.check()
|
||||
output = engine.reports.generate(report, parsed.format)
|
||||
|
||||
if parsed.output:
|
||||
Path(parsed.output).write_text(output, encoding="utf-8")
|
||||
print(f"Report saved to {parsed.output}")
|
||||
else:
|
||||
print(output)
|
||||
|
||||
if config.ci_mode:
|
||||
return engine.get_exit_code(report)
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_fix(parsed) -> int:
|
||||
"""Run the fix subcommand."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = _create_config(parsed)
|
||||
engine = StandardiseEngine(config)
|
||||
|
||||
actions = engine.fix(
|
||||
feature=parsed.feature,
|
||||
apply=parsed.apply,
|
||||
)
|
||||
|
||||
if not actions["planned"]:
|
||||
print("No fixes needed.")
|
||||
return 0
|
||||
|
||||
print(f"Planned actions ({len(actions['planned'])}):")
|
||||
for action in actions["planned"]:
|
||||
print(f" • {action}")
|
||||
|
||||
if parsed.apply:
|
||||
print(f"\nApplied actions ({len(actions['applied'])}):")
|
||||
for action in actions["applied"]:
|
||||
print(f" ✓ {action}")
|
||||
else:
|
||||
print("\nRun with --apply to execute these changes.")
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_init(parsed) -> int:
|
||||
"""Run the init subcommand."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = _create_config(parsed)
|
||||
engine = StandardiseEngine(config)
|
||||
|
||||
try:
|
||||
created = engine.init(parsed.feature)
|
||||
except ValueError as e:
|
||||
print(f"Error: {e}")
|
||||
return 2
|
||||
|
||||
if not created:
|
||||
print(f"Feature '{parsed.feature}' already has all required artifacts.")
|
||||
return 0
|
||||
|
||||
print(f"{'Would create' if config.dry_run else 'Created'} artifacts for '{parsed.feature}':")
|
||||
for artifact_type, path in created.items():
|
||||
status = "📝" if config.dry_run else "✓"
|
||||
print(f" {status} {artifact_type}: {path}")
|
||||
|
||||
if config.dry_run:
|
||||
print("\nRun with --apply to create these files.")
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_ai(parsed) -> int:
|
||||
"""Run the AI generation subcommand with ACP/LSP runtime support."""
|
||||
import asyncio
|
||||
from praisonai.standardise.ai_generator import AIGenerator
|
||||
from praisonai.standardise.models import ArtifactType, FeatureSlug
|
||||
|
||||
config = _create_config(parsed)
|
||||
|
||||
slug = FeatureSlug.from_string(parsed.feature)
|
||||
if not slug.is_valid:
|
||||
print(f"Error: Invalid feature slug: {slug.validation_error}")
|
||||
return 2
|
||||
|
||||
# Start ACP/LSP runtime for context gathering
|
||||
runtime = None
|
||||
try:
|
||||
from praisonai.cli.features.interactive_runtime import create_runtime
|
||||
runtime = create_runtime(
|
||||
workspace=str(config.sdk_root or config.project_root or "."),
|
||||
lsp=True,
|
||||
acp=False # ACP not needed for generation
|
||||
)
|
||||
# Start runtime in background
|
||||
asyncio.get_event_loop().run_until_complete(runtime.start())
|
||||
if runtime.lsp_ready:
|
||||
print("🔧 LSP server ready for code intelligence")
|
||||
except Exception:
|
||||
# Runtime is optional, continue without it
|
||||
pass
|
||||
|
||||
generator = AIGenerator(
|
||||
model=parsed.model,
|
||||
sdk_root=config.sdk_root,
|
||||
docs_root=config.docs_root,
|
||||
examples_root=config.examples_root,
|
||||
use_fast_context=True,
|
||||
)
|
||||
|
||||
# Determine which artifacts to generate
|
||||
artifact_types = []
|
||||
gen_type = getattr(parsed, "type", "all")
|
||||
|
||||
if gen_type in ["docs", "all"]:
|
||||
artifact_types.extend([
|
||||
ArtifactType.DOCS_CONCEPT,
|
||||
ArtifactType.DOCS_FEATURE,
|
||||
ArtifactType.DOCS_CLI,
|
||||
ArtifactType.DOCS_SDK,
|
||||
])
|
||||
|
||||
if gen_type in ["examples", "all"]:
|
||||
artifact_types.extend([
|
||||
ArtifactType.EXAMPLE_BASIC,
|
||||
ArtifactType.EXAMPLE_ADVANCED,
|
||||
])
|
||||
|
||||
print(f"🤖 AI Generation for '{slug.normalised}'")
|
||||
print("=" * 50)
|
||||
|
||||
results = []
|
||||
for artifact_type in artifact_types:
|
||||
print(f"\n📝 Generating {artifact_type.value}...")
|
||||
|
||||
try:
|
||||
# Generate with execution verification for examples
|
||||
content, output_path, verification_info = generator.generate(
|
||||
slug, artifact_type,
|
||||
dry_run=not parsed.apply,
|
||||
verify_execution=True,
|
||||
)
|
||||
|
||||
# Show verification results for examples
|
||||
if verification_info:
|
||||
if verification_info.get("execution_passed"):
|
||||
print(" ✅ Code verified: runs successfully")
|
||||
elif verification_info.get("requires_external"):
|
||||
libs = ", ".join(verification_info.get("missing_libraries", []))
|
||||
print(f" ⚠️ Requires external libraries: {libs}")
|
||||
elif not verification_info.get("syntax_valid"):
|
||||
print(f" ❌ Syntax error: {verification_info.get('error', 'Unknown')[:100]}")
|
||||
else:
|
||||
print(f" ❌ Execution failed after {verification_info.get('attempt', 1)} attempts")
|
||||
if verification_info.get("error"):
|
||||
print(f" Error: {verification_info['error'][:150]}")
|
||||
|
||||
# AI content verification (optional)
|
||||
if parsed.verify:
|
||||
print(" 🔍 AI content review...")
|
||||
is_valid, summary, issues = generator.verify(content, artifact_type, slug)
|
||||
if is_valid:
|
||||
print(f" ✅ {summary}")
|
||||
else:
|
||||
print(f" ⚠️ {summary}")
|
||||
for issue in issues[:3]:
|
||||
print(f" - {issue}")
|
||||
|
||||
# Check if we should write
|
||||
can_write = True
|
||||
if verification_info and not verification_info.get("success"):
|
||||
if not verification_info.get("requires_external"):
|
||||
can_write = False
|
||||
print(" ⛔ Not writing: code doesn't run")
|
||||
|
||||
if parsed.apply and output_path and can_write:
|
||||
print(f" ✓ Created: {output_path}")
|
||||
results.append((artifact_type.value, True, output_path))
|
||||
elif not parsed.apply:
|
||||
print(f" 📋 Preview ({len(content)} chars)")
|
||||
# Show first few lines
|
||||
preview_lines = content.split("\n")[:10]
|
||||
for line in preview_lines:
|
||||
print(f" {line[:60]}")
|
||||
if len(content.split("\n")) > 10:
|
||||
print(" ...")
|
||||
results.append((artifact_type.value, True, None))
|
||||
else:
|
||||
results.append((artifact_type.value, False, "Verification failed"))
|
||||
|
||||
except Exception as e:
|
||||
print(f" ❌ Error: {e}")
|
||||
results.append((artifact_type.value, False, str(e)))
|
||||
|
||||
print("\n" + "=" * 50)
|
||||
print("Summary:")
|
||||
success_count = sum(1 for _, success, _ in results if success)
|
||||
print(f" Generated: {success_count}/{len(results)}")
|
||||
|
||||
if not parsed.apply:
|
||||
print("\nRun with --apply to create these files.")
|
||||
|
||||
# Cleanup runtime
|
||||
if runtime:
|
||||
try:
|
||||
asyncio.get_event_loop().run_until_complete(runtime.stop())
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_checkpoint(parsed) -> int:
|
||||
"""Run the checkpoint subcommand."""
|
||||
from praisonai.standardise.undo_redo import UndoRedoManager
|
||||
|
||||
manager = UndoRedoManager(Path(parsed.path).resolve())
|
||||
|
||||
success, result = manager.create_checkpoint(parsed.message)
|
||||
|
||||
if success:
|
||||
print(f"✓ Checkpoint created: {result}")
|
||||
else:
|
||||
print(f"❌ Failed: {result}")
|
||||
return 1
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_undo(parsed) -> int:
|
||||
"""Run the undo subcommand."""
|
||||
from praisonai.standardise.undo_redo import UndoRedoManager
|
||||
|
||||
manager = UndoRedoManager(Path(parsed.path).resolve())
|
||||
|
||||
# List checkpoints if requested
|
||||
if getattr(parsed, "list", False):
|
||||
checkpoints = manager.list_checkpoints()
|
||||
if not checkpoints:
|
||||
print("No checkpoints found.")
|
||||
return 0
|
||||
|
||||
print("Available checkpoints:")
|
||||
for cp_id, date, message in checkpoints:
|
||||
print(f" • {cp_id} ({date}): {message[:50]}")
|
||||
return 0
|
||||
|
||||
# Undo to checkpoint
|
||||
success, result = manager.undo(parsed.checkpoint)
|
||||
|
||||
if success:
|
||||
print(f"✓ {result}")
|
||||
else:
|
||||
print(f"❌ {result}")
|
||||
return 1
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def _run_redo(parsed) -> int:
|
||||
"""Run the redo subcommand."""
|
||||
from praisonai.standardise.undo_redo import UndoRedoManager
|
||||
|
||||
manager = UndoRedoManager(Path(parsed.path).resolve())
|
||||
|
||||
success, result = manager.redo()
|
||||
|
||||
if success:
|
||||
print(f"✓ {result}")
|
||||
else:
|
||||
print(f"❌ {result}")
|
||||
return 1
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
# Click-based alternative for integration with main CLI
|
||||
def register_click_commands(app):
|
||||
"""Register click commands with the main CLI app."""
|
||||
try:
|
||||
import click
|
||||
except ImportError:
|
||||
return
|
||||
|
||||
@app.group(name="standardise")
|
||||
def standardise_group():
|
||||
"""Standardise documentation and examples (FDEP)."""
|
||||
pass
|
||||
|
||||
@standardise_group.command(name="check")
|
||||
@click.option("--path", "-p", default=".", help="Project root path")
|
||||
@click.option("--feature", help="Specific feature slug to check")
|
||||
@click.option("--scope", type=click.Choice(["all", "docs", "examples", "sdk", "cli"]), default="all")
|
||||
@click.option("--ci", is_flag=True, help="CI mode")
|
||||
def check_cmd(path, feature, scope, ci):
|
||||
"""Check for standardisation issues."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = StandardiseConfig(
|
||||
project_root=Path(path).resolve(),
|
||||
feature_filter=feature,
|
||||
scope=scope,
|
||||
ci_mode=ci,
|
||||
)
|
||||
engine = StandardiseEngine(config)
|
||||
report = engine.check()
|
||||
|
||||
output = engine.reports.generate(report, "text")
|
||||
click.echo(output)
|
||||
|
||||
if ci:
|
||||
sys.exit(engine.get_exit_code(report))
|
||||
|
||||
@standardise_group.command(name="report")
|
||||
@click.option("--path", "-p", default=".", help="Project root path")
|
||||
@click.option("--format", "-f", type=click.Choice(["text", "json", "markdown"]), default="text")
|
||||
@click.option("--output", "-o", help="Output file path")
|
||||
@click.option("--ci", is_flag=True, help="CI mode")
|
||||
def report_cmd(path, format, output, ci):
|
||||
"""Generate detailed report."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = StandardiseConfig(
|
||||
project_root=Path(path).resolve(),
|
||||
ci_mode=ci,
|
||||
)
|
||||
engine = StandardiseEngine(config)
|
||||
report = engine.check()
|
||||
|
||||
content = engine.reports.generate(report, format)
|
||||
|
||||
if output:
|
||||
Path(output).write_text(content, encoding="utf-8")
|
||||
click.echo(f"Report saved to {output}")
|
||||
else:
|
||||
click.echo(content)
|
||||
|
||||
@standardise_group.command(name="fix")
|
||||
@click.option("--path", "-p", default=".", help="Project root path")
|
||||
@click.option("--feature", help="Specific feature slug to fix")
|
||||
@click.option("--apply", is_flag=True, help="Actually apply changes")
|
||||
@click.option("--no-backup", is_flag=True, help="Don't create backups")
|
||||
def fix_cmd(path, feature, apply, no_backup):
|
||||
"""Fix standardisation issues."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = StandardiseConfig(
|
||||
project_root=Path(path).resolve(),
|
||||
feature_filter=feature,
|
||||
dry_run=not apply,
|
||||
backup=not no_backup,
|
||||
)
|
||||
engine = StandardiseEngine(config)
|
||||
|
||||
actions = engine.fix(feature=feature, apply=apply)
|
||||
|
||||
if not actions["planned"]:
|
||||
click.echo("No fixes needed.")
|
||||
return
|
||||
|
||||
click.echo(f"Planned actions ({len(actions['planned'])}):")
|
||||
for action in actions["planned"]:
|
||||
click.echo(f" • {action}")
|
||||
|
||||
if apply:
|
||||
click.echo(f"\nApplied actions ({len(actions['applied'])}):")
|
||||
for action in actions["applied"]:
|
||||
click.echo(f" ✓ {action}")
|
||||
else:
|
||||
click.echo("\nRun with --apply to execute these changes.")
|
||||
|
||||
@standardise_group.command(name="init")
|
||||
@click.argument("feature")
|
||||
@click.option("--path", "-p", default=".", help="Project root path")
|
||||
@click.option("--apply", is_flag=True, help="Actually create files")
|
||||
def init_cmd(feature, path, apply):
|
||||
"""Initialise a new feature with all required artifacts."""
|
||||
StandardiseEngine, StandardiseConfig = _lazy_import_engine()
|
||||
|
||||
config = StandardiseConfig(
|
||||
project_root=Path(path).resolve(),
|
||||
dry_run=not apply,
|
||||
)
|
||||
engine = StandardiseEngine(config)
|
||||
|
||||
try:
|
||||
created = engine.init(feature)
|
||||
except ValueError as e:
|
||||
click.echo(f"Error: {e}", err=True)
|
||||
sys.exit(2)
|
||||
|
||||
if not created:
|
||||
click.echo(f"Feature '{feature}' already has all required artifacts.")
|
||||
return
|
||||
|
||||
action_word = "Would create" if config.dry_run else "Created"
|
||||
click.echo(f"{action_word} artifacts for '{feature}':")
|
||||
for artifact_type, artifact_path in created.items():
|
||||
status = "📝" if config.dry_run else "✓"
|
||||
click.echo(f" {status} {artifact_type}: {artifact_path}")
|
||||
|
||||
if config.dry_run:
|
||||
click.echo("\nRun with --apply to create these files.")
|
||||
|
||||
return standardise_group
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(standardise_command())
|
||||
@@ -160,6 +160,8 @@ class ActionOrchestrator:
|
||||
|
||||
async def _create_fallback_plan(self, prompt: str, plan_id: str) -> ActionResult:
|
||||
"""Create a fallback plan when ACP is not available for planning."""
|
||||
import re # Import at function level for all pattern matching
|
||||
|
||||
# This is a simplified fallback - in production, this would use LLM
|
||||
steps = []
|
||||
|
||||
@@ -168,7 +170,6 @@ class ActionOrchestrator:
|
||||
|
||||
if "create" in prompt_lower or "new file" in prompt_lower:
|
||||
# Extract file path if mentioned
|
||||
import re
|
||||
file_match = re.search(r'(?:create|new)\s+(?:a\s+)?(?:file\s+)?(?:called\s+)?([^\s]+\.\w+)', prompt_lower)
|
||||
target = file_match.group(1) if file_match else "new_file.py"
|
||||
|
||||
@@ -188,7 +189,8 @@ class ActionOrchestrator:
|
||||
))
|
||||
|
||||
elif "edit" in prompt_lower or "modify" in prompt_lower or "change" in prompt_lower:
|
||||
file_match = re.search(r'(?:edit|modify|change)\s+([^\s]+\.\w+)', prompt_lower)
|
||||
# Match patterns like "edit file X", "edit X", "modify X"
|
||||
file_match = re.search(r'(?:edit|modify|change)\s+(?:file\s+)?([^\s]+(?:\.\w+)?)', prompt_lower)
|
||||
target = file_match.group(1) if file_match else ""
|
||||
|
||||
if target:
|
||||
@@ -197,11 +199,13 @@ class ActionOrchestrator:
|
||||
action_type=ActionType.FILE_EDIT,
|
||||
description=f"Edit file: {target}",
|
||||
target=target,
|
||||
params={"changes": prompt}
|
||||
params={"changes": prompt},
|
||||
status=ActionStatus.APPROVED # Auto-approve for fallback
|
||||
))
|
||||
|
||||
elif "delete" in prompt_lower or "remove" in prompt_lower:
|
||||
file_match = re.search(r'(?:delete|remove)\s+([^\s]+\.\w+)', prompt_lower)
|
||||
# Match patterns like "delete file X", "delete X", "remove X"
|
||||
file_match = re.search(r'(?:delete|remove)\s+(?:file\s+)?([^\s]+(?:\.\w+)?)', prompt_lower)
|
||||
target = file_match.group(1) if file_match else ""
|
||||
|
||||
if target:
|
||||
@@ -209,7 +213,8 @@ class ActionOrchestrator:
|
||||
id=self._generate_step_id(plan_id, 0),
|
||||
action_type=ActionType.FILE_DELETE,
|
||||
description=f"Delete file: {target}",
|
||||
target=target
|
||||
target=target,
|
||||
status=ActionStatus.APPROVED # Auto-approve for fallback
|
||||
))
|
||||
|
||||
elif "rename" in prompt_lower:
|
||||
@@ -218,19 +223,22 @@ class ActionOrchestrator:
|
||||
action_type=ActionType.REFACTOR,
|
||||
description="Rename operation",
|
||||
target="",
|
||||
params={"prompt": prompt}
|
||||
params={"prompt": prompt},
|
||||
status=ActionStatus.APPROVED # Auto-approve for fallback
|
||||
))
|
||||
|
||||
elif "run" in prompt_lower or "execute" in prompt_lower:
|
||||
cmd_match = re.search(r'(?:run|execute)\s+[`"\']?([^`"\']+)[`"\']?', prompt_lower)
|
||||
command = cmd_match.group(1) if cmd_match else ""
|
||||
elif "run" in prompt_lower or "execute" in prompt_lower or "command" in prompt_lower:
|
||||
# Match patterns like "run command: X", "execute X", "run X"
|
||||
cmd_match = re.search(r'(?:run|execute)\s+(?:command[:\s]+)?[`"\']?(.+?)[`"\']?$', prompt_lower)
|
||||
command = cmd_match.group(1).strip() if cmd_match else ""
|
||||
|
||||
if command:
|
||||
steps.append(ActionStep(
|
||||
id=self._generate_step_id(plan_id, 0),
|
||||
action_type=ActionType.SHELL_COMMAND,
|
||||
description=f"Execute: {command}",
|
||||
target=command
|
||||
target=command,
|
||||
status=ActionStatus.APPROVED # Auto-approve for fallback
|
||||
))
|
||||
|
||||
if not steps:
|
||||
|
||||
@@ -596,20 +596,34 @@ class CodeIntelligenceRouter:
|
||||
|
||||
def _extract_symbol_from_query(self, query: str) -> Optional[str]:
|
||||
"""Extract symbol name from query."""
|
||||
# Common patterns for symbol extraction
|
||||
# Common patterns for symbol extraction (order matters - more specific first)
|
||||
patterns = [
|
||||
r'(?:definition\s+of|where\s+is|find|show)\s+["\']?(\w+)["\']?',
|
||||
# "find all references to X" - capture X after "to"
|
||||
r'references?\s+to\s+["\']?(\w+)["\']?',
|
||||
# "definition of X" - capture X after "of"
|
||||
r'definition\s+of\s+["\']?(\w+)["\']?',
|
||||
# "where is X defined/used"
|
||||
r'where\s+is\s+["\']?(\w+)["\']?\s+(?:defined|used)',
|
||||
# Quoted or backticked symbols
|
||||
r'["\'](\w+)["\']',
|
||||
r'`(\w+)`',
|
||||
# "X is defined/used"
|
||||
r'(\w+)\s+(?:is\s+)?(?:defined|used)',
|
||||
# Generic "find/show X" - but filter common words
|
||||
r'(?:find|show)\s+["\']?(\w+)["\']?',
|
||||
]
|
||||
|
||||
# Words to filter out
|
||||
filter_words = {'the', 'a', 'an', 'is', 'are', 'in', 'of', 'to', 'for',
|
||||
'all', 'any', 'some', 'this', 'that', 'where', 'what',
|
||||
'definition', 'references', 'reference', 'symbol', 'symbols'}
|
||||
|
||||
for pattern in patterns:
|
||||
match = re.search(pattern, query, re.IGNORECASE)
|
||||
if match:
|
||||
symbol = match.group(1)
|
||||
# Filter out common words
|
||||
if symbol.lower() not in ['the', 'a', 'an', 'is', 'are', 'in', 'of', 'to', 'for']:
|
||||
if symbol.lower() not in filter_words:
|
||||
return symbol
|
||||
|
||||
return None
|
||||
|
||||
@@ -40,7 +40,7 @@ class RuntimeConfig:
|
||||
workspace: str = "."
|
||||
lsp_enabled: bool = True
|
||||
acp_enabled: bool = True
|
||||
approval_mode: str = "manual" # manual, auto, scoped
|
||||
approval_mode: str = "auto" # auto (full privileges), manual, scoped
|
||||
trace_enabled: bool = False
|
||||
trace_file: Optional[str] = None
|
||||
json_output: bool = False
|
||||
@@ -146,15 +146,21 @@ class InteractiveRuntime:
|
||||
def read_only(self) -> bool:
|
||||
"""Check if runtime is in read-only mode.
|
||||
|
||||
Note: When PRAISON_APPROVAL_MODE=auto, we allow writes even without ACP
|
||||
to support non-interactive automation and testing scenarios.
|
||||
Note: When approval_mode=auto (via config or env), we allow writes even
|
||||
without ACP to support non-interactive automation and testing scenarios.
|
||||
"""
|
||||
# Auto-approval mode bypasses read-only for automation
|
||||
import os as _os
|
||||
approval_mode = _os.environ.get("PRAISON_APPROVAL_MODE", "").lower()
|
||||
if approval_mode == "auto":
|
||||
# Check config approval_mode first (takes precedence)
|
||||
if self.config.approval_mode == "auto":
|
||||
return False
|
||||
return self._read_only or not self.acp_ready
|
||||
|
||||
# Then check environment variable as fallback
|
||||
import os as _os
|
||||
env_approval_mode = _os.environ.get("PRAISON_APPROVAL_MODE", "").lower()
|
||||
if env_approval_mode == "auto":
|
||||
return False
|
||||
|
||||
# Only enforce read-only if explicitly set or ACP not ready
|
||||
return self._read_only
|
||||
|
||||
def get_status(self) -> Dict[str, Any]:
|
||||
"""Get runtime status."""
|
||||
|
||||
@@ -72,7 +72,7 @@ class ToolConfig:
|
||||
enable_acp: bool = True
|
||||
enable_lsp: bool = True
|
||||
enable_basic: bool = True
|
||||
approval_mode: str = "auto" # auto, manual, scoped
|
||||
approval_mode: str = "auto" # auto (full privileges), manual, scoped
|
||||
lsp_enabled: bool = True
|
||||
acp_enabled: bool = True
|
||||
|
||||
|
||||
File diff suppressed because it is too large.
Load diff
@@ -50,8 +50,9 @@ class InteractiveConfig:
|
||||
autonomy: bool = True # Enable autonomy by default for complex tasks
|
||||
autonomy_config: Optional[dict] = None # Custom autonomy config
|
||||
|
||||
# Approval mode
|
||||
approval_mode: Union[str, ApprovalMode] = "prompt"
|
||||
# Approval mode - default to "auto" for full privileges in interactive mode
|
||||
# Use "prompt" for safer mode that asks before each action
|
||||
approval_mode: Union[str, ApprovalMode] = "auto"
|
||||
|
||||
# File attachments
|
||||
files: List[str] = field(default_factory=list)
|
||||
|
||||
@@ -24,6 +24,9 @@ class InteractiveEventType(Enum):
|
||||
TOOL_START = "tool.start"
|
||||
TOOL_END = "tool.end"
|
||||
|
||||
# Stage transitions (PLAN → EXPLORE → BUILD → REVIEW)
|
||||
STAGE_CHANGE = "stage.change"
|
||||
|
||||
# Approval/permission flow
|
||||
APPROVAL_ASKED = "approval.asked"
|
||||
APPROVAL_ANSWERED = "approval.answered"
|
||||
|
||||
@@ -31,14 +31,21 @@ class RichFrontend:
|
||||
- `praisonai chat`
|
||||
"""
|
||||
|
||||
def __init__(self, core: Optional[InteractiveCore] = None, config: Optional[InteractiveConfig] = None):
|
||||
def __init__(
|
||||
self,
|
||||
core: Optional[InteractiveCore] = None,
|
||||
config: Optional[InteractiveConfig] = None,
|
||||
ui_config: Optional['UIConfig'] = None,
|
||||
):
|
||||
"""Initialize the Rich frontend.
|
||||
|
||||
Args:
|
||||
core: InteractiveCore instance. If None, creates one.
|
||||
config: Configuration. Used if core is None.
|
||||
ui_config: UI backend configuration for rendering options.
|
||||
"""
|
||||
self.core = core or InteractiveCore(config=config)
|
||||
self._ui_config = ui_config
|
||||
self._running = False
|
||||
self._current_response = ""
|
||||
self._pending_approval: Optional[ApprovalRequest] = None
|
||||
|
||||
@@ -0,0 +1,502 @@
|
||||
"""
|
||||
PraisonIO - Interactive CLI I/O handler inspired by Aider.
|
||||
|
||||
Key design principles:
|
||||
1. prompt_toolkit used SYNCHRONOUSLY (never inside asyncio.run)
|
||||
2. Rich for output rendering
|
||||
3. MarkdownStream for flicker-free streaming
|
||||
4. Clean separation of input/output concerns
|
||||
"""
|
||||
|
||||
import sys
|
||||
import time
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Set
|
||||
|
||||
# Lazy imports for performance
|
||||
_PROMPT_TOOLKIT_AVAILABLE = None
|
||||
_RICH_AVAILABLE = None
|
||||
|
||||
|
||||
def _check_prompt_toolkit():
|
||||
global _PROMPT_TOOLKIT_AVAILABLE
|
||||
if _PROMPT_TOOLKIT_AVAILABLE is None:
|
||||
try:
|
||||
import prompt_toolkit # noqa: F401
|
||||
_PROMPT_TOOLKIT_AVAILABLE = True
|
||||
except ImportError:
|
||||
_PROMPT_TOOLKIT_AVAILABLE = False
|
||||
return _PROMPT_TOOLKIT_AVAILABLE
|
||||
|
||||
|
||||
def _check_rich():
|
||||
global _RICH_AVAILABLE
|
||||
if _RICH_AVAILABLE is None:
|
||||
try:
|
||||
import rich # noqa: F401
|
||||
_RICH_AVAILABLE = True
|
||||
except ImportError:
|
||||
_RICH_AVAILABLE = False
|
||||
return _RICH_AVAILABLE
|
||||
|
||||
|
||||
@dataclass
|
||||
class IOConfig:
|
||||
"""Configuration for PraisonIO."""
|
||||
# Appearance
|
||||
pretty: bool = True
|
||||
user_input_color: str = "#00cc00"
|
||||
tool_output_color: str = "#0088ff"
|
||||
tool_error_color: str = "#ff0000"
|
||||
tool_warning_color: str = "#ffaa00"
|
||||
assistant_color: str = "#00aaff"
|
||||
|
||||
# Input settings
|
||||
multiline_mode: bool = False
|
||||
vi_mode: bool = False
|
||||
|
||||
# History
|
||||
input_history_file: Optional[str] = None
|
||||
|
||||
# Completion
|
||||
enable_completions: bool = True
|
||||
|
||||
# Streaming
|
||||
stream_delay: float = 0.05 # 20fps default
|
||||
|
||||
|
||||
class PraisonCompleter:
|
||||
"""Auto-completer for commands, files, and symbols."""
|
||||
|
||||
def __init__(self, commands: Optional[Dict[str, str]] = None):
|
||||
self.commands = commands or {}
|
||||
self.files: Set[str] = set()
|
||||
self.symbols: Set[str] = set()
|
||||
|
||||
def add_files(self, files: List[str]) -> None:
|
||||
"""Add files to completion."""
|
||||
self.files.update(files)
|
||||
|
||||
def add_symbols(self, symbols: List[str]) -> None:
|
||||
"""Add symbols to completion."""
|
||||
self.symbols.update(symbols)
|
||||
|
||||
def get_completions(self, text: str, cursor_pos: int) -> List[tuple]:
|
||||
"""Get completions for current input."""
|
||||
before_cursor = text[:cursor_pos]
|
||||
words = before_cursor.split()
|
||||
current_word = words[-1] if words else ""
|
||||
|
||||
completions = []
|
||||
|
||||
# Slash commands
|
||||
if current_word.startswith("/"):
|
||||
cmd_part = current_word[1:].lower()
|
||||
for cmd, desc in self.commands.items():
|
||||
if cmd.lower().startswith(cmd_part):
|
||||
completions.append((f"/{cmd}", desc))
|
||||
|
||||
# @ file mentions
|
||||
elif current_word.startswith("@"):
|
||||
file_part = current_word[1:].lower()
|
||||
for f in self.files:
|
||||
if file_part in f.lower():
|
||||
completions.append((f"@{f}", "file"))
|
||||
|
||||
# General word completion
|
||||
elif current_word:
|
||||
word_lower = current_word.lower()
|
||||
for symbol in self.symbols:
|
||||
if symbol.lower().startswith(word_lower):
|
||||
completions.append((symbol, "symbol"))
|
||||
|
||||
return completions[:20]
|
||||
|
||||
def create_prompt_toolkit_completer(self):
|
||||
"""Create prompt_toolkit Completer."""
|
||||
if not _check_prompt_toolkit():
|
||||
return None
|
||||
|
||||
from prompt_toolkit.completion import Completer, Completion
|
||||
|
||||
outer = self
|
||||
|
||||
class PTCompleter(Completer):
|
||||
def get_completions(self, document, complete_event):
|
||||
text = document.text
|
||||
cursor_pos = document.cursor_position
|
||||
|
||||
for completion, meta in outer.get_completions(text, cursor_pos):
|
||||
words = text[:cursor_pos].split()
|
||||
current_word = words[-1] if words else ""
|
||||
start_pos = -len(current_word)
|
||||
yield Completion(completion, start_position=start_pos, display_meta=meta)
|
||||
|
||||
return PTCompleter()
|
||||
|
||||
|
||||
class MarkdownStream:
|
||||
"""Flicker-free streaming markdown renderer.
|
||||
|
||||
Uses Rich Live with a sliding window approach:
|
||||
- Stable lines print above the live area
|
||||
- Unstable lines (last N) render in the live window
|
||||
"""
|
||||
|
||||
def __init__(self, live_window: int = 6):
|
||||
self.live_window = live_window
|
||||
self.printed: List[str] = []
|
||||
self.live = None
|
||||
self._live_started = False
|
||||
self.min_delay = 1.0 / 20 # 20fps
|
||||
self.when = 0
|
||||
|
||||
def _render_to_lines(self, text: str) -> List[str]:
|
||||
"""Render markdown to lines."""
|
||||
if not _check_rich():
|
||||
return text.splitlines(keepends=True)
|
||||
|
||||
import io
|
||||
from rich.console import Console
|
||||
from rich.markdown import Markdown
|
||||
|
||||
string_io = io.StringIO()
|
||||
console = Console(file=string_io, force_terminal=True, width=100)
|
||||
console.print(Markdown(text))
|
||||
return string_io.getvalue().splitlines(keepends=True)
|
||||
|
||||
def update(self, text: str, final: bool = False) -> None:
|
||||
"""Update the streaming display."""
|
||||
if not _check_rich():
|
||||
# Fallback: just print
|
||||
print(text, end="" if not final else "\n", flush=True)
|
||||
return
|
||||
|
||||
from rich.live import Live
|
||||
from rich.text import Text
|
||||
|
||||
# Start live on first update
|
||||
if not self._live_started:
|
||||
self.live = Live(Text(""), refresh_per_second=20)
|
||||
self.live.start()
|
||||
self._live_started = True
|
||||
|
||||
# Throttle updates
|
||||
now = time.time()
|
||||
if not final and now - self.when < self.min_delay:
|
||||
return
|
||||
self.when = now
|
||||
|
||||
lines = self._render_to_lines(text)
|
||||
num_lines = len(lines)
|
||||
|
||||
# Calculate stable lines
|
||||
if not final:
|
||||
num_lines -= self.live_window
|
||||
|
||||
if final or num_lines > 0:
|
||||
num_printed = len(self.printed)
|
||||
show_count = num_lines - num_printed
|
||||
|
||||
if show_count > 0:
|
||||
show = lines[num_printed:num_lines]
|
||||
show_text = "".join(show)
|
||||
self.live.console.print(Text.from_ansi(show_text), end="")
|
||||
self.printed = lines[:num_lines]
|
||||
|
||||
if final:
|
||||
self.live.update(Text(""))
|
||||
self.live.stop()
|
||||
self.live = None
|
||||
return
|
||||
|
||||
# Update live window
|
||||
rest = lines[num_lines:]
|
||||
rest_text = "".join(rest)
|
||||
self.live.update(Text.from_ansi(rest_text))
|
||||
|
||||
def __del__(self):
|
||||
if self.live:
|
||||
try:
|
||||
self.live.stop()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
class PraisonIO:
|
||||
"""
|
||||
Main I/O handler for PraisonAI interactive CLI.
|
||||
|
||||
Inspired by Aider's io.py - handles all terminal I/O with:
|
||||
- Rich formatting for output
|
||||
- prompt_toolkit for input (with completions, history)
|
||||
- Streaming markdown rendering
|
||||
"""
|
||||
|
||||
def __init__(self, config: Optional[IOConfig] = None):
|
||||
self.config = config or IOConfig()
|
||||
self.completer = PraisonCompleter()
|
||||
self._console = None
|
||||
self._prompt_session = None
|
||||
self._history_file = None
|
||||
|
||||
# Setup history file
|
||||
if self.config.input_history_file:
|
||||
self._history_file = Path(self.config.input_history_file)
|
||||
else:
|
||||
self._history_file = Path.home() / ".praison" / "input_history"
|
||||
|
||||
self._history_file.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
@property
|
||||
def console(self):
|
||||
"""Lazy-load Rich console."""
|
||||
if self._console is None and _check_rich():
|
||||
from rich.console import Console
|
||||
self._console = Console()
|
||||
return self._console
|
||||
|
||||
def _create_prompt_session(self):
|
||||
"""Create prompt_toolkit session."""
|
||||
if not _check_prompt_toolkit():
|
||||
return None
|
||||
|
||||
from prompt_toolkit import PromptSession
|
||||
from prompt_toolkit.history import FileHistory
|
||||
from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
|
||||
from prompt_toolkit.key_binding import KeyBindings
|
||||
|
||||
kb = KeyBindings()
|
||||
|
||||
# Ctrl+C to cancel current input
|
||||
@kb.add("c-c")
|
||||
def _(event):
|
||||
event.current_buffer.reset()
|
||||
|
||||
# Alt+Enter for newline in multiline mode
|
||||
@kb.add("escape", "enter")
|
||||
def _(event):
|
||||
event.current_buffer.insert_text("\n")
|
||||
|
||||
# Enter to submit (unless in multiline mode)
|
||||
@kb.add("enter")
|
||||
def _(event):
|
||||
if self.config.multiline_mode:
|
||||
event.current_buffer.insert_text("\n")
|
||||
else:
|
||||
event.current_buffer.validate_and_handle()
|
||||
|
||||
# Ctrl+D to submit in multiline mode
|
||||
@kb.add("c-d")
|
||||
def _(event):
|
||||
event.current_buffer.validate_and_handle()
|
||||
|
||||
session_kwargs = {
|
||||
"history": FileHistory(str(self._history_file)),
|
||||
"auto_suggest": AutoSuggestFromHistory(),
|
||||
"key_bindings": kb,
|
||||
"multiline": self.config.multiline_mode,
|
||||
}
|
||||
|
||||
if self.config.enable_completions:
|
||||
completer = self.completer.create_prompt_toolkit_completer()
|
||||
if completer:
|
||||
from prompt_toolkit.completion import ThreadedCompleter
|
||||
session_kwargs["completer"] = ThreadedCompleter(completer)
|
||||
|
||||
if self.config.vi_mode:
|
||||
from prompt_toolkit.enums import EditingMode
|
||||
session_kwargs["editing_mode"] = EditingMode.VI
|
||||
|
||||
return PromptSession(**session_kwargs)
|
||||
|
||||
def _get_style(self):
|
||||
"""Get prompt_toolkit style."""
|
||||
if not _check_prompt_toolkit() or not self.config.pretty:
|
||||
return None
|
||||
|
||||
from prompt_toolkit.styles import Style
|
||||
|
||||
style_dict = {}
|
||||
if self.config.user_input_color:
|
||||
style_dict[""] = self.config.user_input_color
|
||||
|
||||
return Style.from_dict(style_dict) if style_dict else None
|
||||
|
||||
def get_input(self, prompt: str = "You: ") -> str:
|
||||
"""
|
||||
Get input from user.
|
||||
|
||||
This is SYNCHRONOUS - never call from inside asyncio.run().
|
||||
"""
|
||||
if self._prompt_session is None:
|
||||
self._prompt_session = self._create_prompt_session()
|
||||
|
||||
if self._prompt_session:
|
||||
try:
|
||||
style = self._get_style()
|
||||
return self._prompt_session.prompt(prompt, style=style)
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
except EOFError:
|
||||
return "/exit"
|
||||
else:
|
||||
# Fallback to basic input
|
||||
try:
|
||||
return input(prompt)
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
except EOFError:
|
||||
return "/exit"
|
||||
|
||||
def rule(self) -> None:
|
||||
"""Print a horizontal rule."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.rule(style=self.config.user_input_color)
|
||||
else:
|
||||
print()
|
||||
|
||||
def print_welcome(self, model: str = "gpt-4o-mini", tools_count: int = 0, session_id: str = "") -> None:
|
||||
"""Print welcome message."""
|
||||
if self.console and self.config.pretty:
|
||||
from rich.panel import Panel
|
||||
from rich.text import Text
|
||||
|
||||
welcome = Text()
|
||||
welcome.append("PraisonAI Interactive Mode\n", style="bold cyan")
|
||||
welcome.append("Type your prompt, use ", style="dim")
|
||||
welcome.append("/help", style="bold green")
|
||||
welcome.append(" for commands, ", style="dim")
|
||||
welcome.append("/exit", style="bold yellow")
|
||||
welcome.append(" to quit\n", style="dim")
|
||||
welcome.append(f"Model: {model}", style="dim cyan")
|
||||
if tools_count:
|
||||
welcome.append(f" | Tools: {tools_count}", style="dim")
|
||||
if session_id:
|
||||
welcome.append(f" | Session: {session_id[:8]}", style="dim")
|
||||
|
||||
self.console.print(Panel(welcome, border_style="blue", padding=(0, 1)))
|
||||
else:
|
||||
print("PraisonAI Interactive Mode")
|
||||
print("Type your prompt, use /help for commands, /exit to quit")
|
||||
print(f"Model: {model} | Tools: {tools_count}")
|
||||
|
||||
def print_user_input(self, text: str) -> None:
|
||||
"""Echo user input with styling."""
|
||||
if self.console and self.config.pretty:
|
||||
from rich.text import Text
|
||||
self.console.print(Text(text, style=self.config.user_input_color))
|
||||
|
||||
def print_assistant_start(self) -> None:
|
||||
"""Print assistant response start marker."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print("\n[bold cyan]Assistant:[/bold cyan]")
|
||||
else:
|
||||
print("\nAssistant:")
|
||||
|
||||
def print_assistant_response(self, response: str) -> None:
|
||||
"""Print assistant response with markdown formatting."""
|
||||
if self.console and self.config.pretty:
|
||||
from rich.markdown import Markdown
|
||||
from rich.panel import Panel
|
||||
|
||||
try:
|
||||
md = Markdown(response)
|
||||
self.console.print(Panel(md, border_style="cyan", padding=(0, 1)))
|
||||
except Exception:
|
||||
self.console.print(response)
|
||||
else:
|
||||
print(response)
|
||||
|
||||
def stream_response(self, text: str, final: bool = False) -> MarkdownStream:
|
||||
"""Get or update streaming response."""
|
||||
if not hasattr(self, '_current_stream') or self._current_stream is None:
|
||||
self._current_stream = MarkdownStream()
|
||||
|
||||
self._current_stream.update(text, final=final)
|
||||
|
||||
if final:
|
||||
self._current_stream = None
|
||||
|
||||
return self._current_stream
|
||||
|
||||
def tool_output(self, message: str) -> None:
|
||||
"""Print tool output."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print(f"[{self.config.tool_output_color}]⚙ {message}[/]")
|
||||
else:
|
||||
print(f"⚙ {message}")
|
||||
|
||||
def tool_error(self, message: str) -> None:
|
||||
"""Print tool error."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print(f"[{self.config.tool_error_color}]✗ {message}[/]")
|
||||
else:
|
||||
print(f"✗ {message}", file=sys.stderr)
|
||||
|
||||
def tool_warning(self, message: str) -> None:
|
||||
"""Print tool warning."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print(f"[{self.config.tool_warning_color}]⚠ {message}[/]")
|
||||
else:
|
||||
print(f"⚠ {message}", file=sys.stderr)
|
||||
|
||||
def info(self, message: str) -> None:
|
||||
"""Print info message."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print(f"[dim]ℹ {message}[/dim]")
|
||||
else:
|
||||
print(f"ℹ {message}")
|
||||
|
||||
def success(self, message: str) -> None:
|
||||
"""Print success message."""
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print(f"[green]✓ {message}[/green]")
|
||||
else:
|
||||
print(f"✓ {message}")
|
||||
|
||||
def print_help(self, commands: Dict[str, str]) -> None:
|
||||
"""Print help for available commands."""
|
||||
if self.console and self.config.pretty:
|
||||
from rich.table import Table
|
||||
|
||||
table = Table(title="Available Commands", border_style="blue")
|
||||
table.add_column("Command", style="green")
|
||||
table.add_column("Description", style="dim")
|
||||
|
||||
for cmd, desc in sorted(commands.items()):
|
||||
table.add_row(f"/{cmd}", desc)
|
||||
|
||||
self.console.print(table)
|
||||
else:
|
||||
print("\nAvailable Commands:")
|
||||
for cmd, desc in sorted(commands.items()):
|
||||
print(f" /{cmd:<12} - {desc}")
|
||||
|
||||
def confirm(self, message: str, default: bool = False) -> bool:
|
||||
"""Ask for confirmation."""
|
||||
suffix = " [Y/n]: " if default else " [y/N]: "
|
||||
|
||||
if self.console and self.config.pretty:
|
||||
self.console.print(f"[yellow]? {message}[/yellow]", end="")
|
||||
|
||||
try:
|
||||
response = input(suffix).strip().lower()
|
||||
if not response:
|
||||
return default
|
||||
return response in ("y", "yes")
|
||||
except (EOFError, KeyboardInterrupt):
|
||||
return False
|
||||
|
||||
def add_commands(self, commands: Dict[str, str]) -> None:
|
||||
"""Add commands for completion."""
|
||||
self.completer.commands.update(commands)
|
||||
|
||||
def add_files(self, files: List[str]) -> None:
|
||||
"""Add files for completion."""
|
||||
self.completer.add_files(files)
|
||||
|
||||
def add_symbols(self, symbols: List[str]) -> None:
|
||||
"""Add symbols for completion."""
|
||||
self.completer.add_symbols(symbols)
|
||||
@@ -0,0 +1,297 @@
|
||||
"""
|
||||
Interactive REPL for PraisonAI.
|
||||
|
||||
This is the main entry point for interactive chat mode.
|
||||
Uses PraisonIO for input/output (prompt_toolkit is used SYNCHRONOUSLY).
|
||||
"""
|
||||
|
||||
import logging
|
||||
from dataclasses import dataclass
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from .praison_io import PraisonIO, IOConfig
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class REPLConfig:
|
||||
"""Configuration for the interactive REPL."""
|
||||
model: str = "gpt-4o-mini"
|
||||
verbose: bool = False
|
||||
memory: bool = False
|
||||
tools: Optional[List] = None
|
||||
session_id: Optional[str] = None
|
||||
continue_session: bool = False
|
||||
workspace: Optional[str] = None
|
||||
autonomy: bool = True
|
||||
|
||||
|
||||
# Default slash commands
|
||||
DEFAULT_COMMANDS: Dict[str, str] = {
|
||||
"help": "Show available commands",
|
||||
"exit": "Exit interactive mode",
|
||||
"quit": "Exit interactive mode",
|
||||
"clear": "Clear conversation history",
|
||||
"session": "Show current session info",
|
||||
"model": "Show or change model",
|
||||
"cost": "Show token usage and cost",
|
||||
"history": "Show conversation history",
|
||||
"export": "Export conversation to file",
|
||||
"compact": "Toggle compact output mode",
|
||||
"multiline": "Toggle multiline input mode",
|
||||
}
|
||||
|
||||
|
||||
class InteractiveREPL:
|
||||
"""
|
||||
Interactive REPL for PraisonAI chat.
|
||||
|
||||
Key design:
|
||||
- Uses PraisonIO for all I/O (prompt_toolkit used synchronously)
|
||||
- Agent execution is async but input is sync
|
||||
- Clean separation between I/O and agent logic
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config: Optional[REPLConfig] = None,
|
||||
io_config: Optional[IOConfig] = None,
|
||||
):
|
||||
self.config = config or REPLConfig()
|
||||
self.io = PraisonIO(io_config)
|
||||
self._agent = None
|
||||
self._running = False
|
||||
self._conversation_history: List[Dict] = []
|
||||
self._session_id: Optional[str] = None
|
||||
self._total_tokens = 0
|
||||
self._total_cost = 0.0
|
||||
|
||||
# Setup commands
|
||||
self.io.add_commands(DEFAULT_COMMANDS)
|
||||
|
||||
def _get_agent(self):
|
||||
"""Lazy-load the agent."""
|
||||
if self._agent is None:
|
||||
try:
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent_kwargs = {
|
||||
"name": "InteractiveAgent",
|
||||
"role": "Assistant",
|
||||
"goal": "Help the user with their requests",
|
||||
"instructions": "You are a helpful AI assistant. Be concise and helpful.",
|
||||
}
|
||||
|
||||
if self.config.model:
|
||||
agent_kwargs["llm"] = self.config.model
|
||||
|
||||
if self.config.memory:
|
||||
agent_kwargs["memory"] = True
|
||||
|
||||
if self.config.tools:
|
||||
agent_kwargs["tools"] = self.config.tools
|
||||
|
||||
self._agent = Agent(**agent_kwargs)
|
||||
|
||||
except ImportError as e:
|
||||
self.io.tool_error(f"Failed to import praisonaiagents: {e}")
|
||||
raise
|
||||
|
||||
return self._agent
|
||||
|
||||
def _handle_command(self, command: str) -> bool:
|
||||
"""
|
||||
Handle slash commands.
|
||||
|
||||
Returns True if command was handled, False otherwise.
|
||||
"""
|
||||
parts = command.split(maxsplit=1)
|
||||
cmd = parts[0].lower().lstrip("/")
|
||||
args = parts[1] if len(parts) > 1 else ""
|
||||
|
||||
if cmd in ("exit", "quit", "q"):
|
||||
self._running = False
|
||||
self.io.info("Goodbye!")
|
||||
return True
|
||||
|
||||
elif cmd == "help":
|
||||
self.io.print_help(DEFAULT_COMMANDS)
|
||||
return True
|
||||
|
||||
elif cmd == "clear":
|
||||
self._conversation_history.clear()
|
||||
self.io.success("Conversation cleared.")
|
||||
return True
|
||||
|
||||
elif cmd == "session":
|
||||
if self._session_id:
|
||||
self.io.info(f"Session: {self._session_id}")
|
||||
else:
|
||||
self.io.info("No active session")
|
||||
return True
|
||||
|
||||
elif cmd == "model":
|
||||
if args:
|
||||
self.config.model = args
|
||||
self._agent = None # Reset agent to use new model
|
||||
self.io.success(f"Model changed to: {args}")
|
||||
else:
|
||||
self.io.info(f"Current model: {self.config.model}")
|
||||
return True
|
||||
|
||||
elif cmd == "cost":
|
||||
self.io.info(f"Total tokens: {self._total_tokens}")
|
||||
self.io.info(f"Estimated cost: ${self._total_cost:.4f}")
|
||||
return True
|
||||
|
||||
elif cmd == "history":
|
||||
if not self._conversation_history:
|
||||
self.io.info("No conversation history")
|
||||
else:
|
||||
for i, msg in enumerate(self._conversation_history[-10:], 1):
|
||||
role = msg.get("role", "unknown")
|
||||
content = msg.get("content", "")[:100]
|
||||
self.io.info(f"{i}. [{role}] {content}...")
|
||||
return True
|
||||
|
||||
elif cmd == "export":
|
||||
filename = args or "conversation.txt"
|
||||
try:
|
||||
with open(filename, "w") as f:
|
||||
for msg in self._conversation_history:
|
||||
f.write(f"[{msg.get('role', 'unknown')}]\n")
|
||||
f.write(f"{msg.get('content', '')}\n\n")
|
||||
self.io.success(f"Exported to {filename}")
|
||||
except Exception as e:
|
||||
self.io.tool_error(f"Export failed: {e}")
|
||||
return True
|
||||
|
||||
elif cmd == "compact":
|
||||
self.io.config.pretty = not self.io.config.pretty
|
||||
mode = "disabled" if self.io.config.pretty else "enabled"
|
||||
self.io.info(f"Compact mode {mode}")
|
||||
return True
|
||||
|
||||
elif cmd == "multiline":
|
||||
self.io.config.multiline_mode = not self.io.config.multiline_mode
|
||||
mode = "enabled" if self.io.config.multiline_mode else "disabled"
|
||||
self.io.info(f"Multiline mode {mode}")
|
||||
return True
|
||||
|
||||
else:
|
||||
self.io.tool_warning(f"Unknown command: /{cmd}")
|
||||
self.io.info("Type /help for available commands")
|
||||
return True
|
||||
|
||||
def _execute_prompt(self, prompt: str) -> Optional[str]:
|
||||
"""Execute a prompt and return the response."""
|
||||
try:
|
||||
agent = self._get_agent()
|
||||
|
||||
# Add to history
|
||||
self._conversation_history.append({
|
||||
"role": "user",
|
||||
"content": prompt
|
||||
})
|
||||
|
||||
# Execute
|
||||
response = agent.start(prompt)
|
||||
|
||||
# Add response to history
|
||||
if response:
|
||||
self._conversation_history.append({
|
||||
"role": "assistant",
|
||||
"content": str(response)
|
||||
})
|
||||
|
||||
return str(response) if response else None
|
||||
|
||||
except Exception as e:
|
||||
logger.exception("Error executing prompt")
|
||||
self.io.tool_error(f"Error: {e}")
|
||||
return None
|
||||
|
||||
def run(self) -> None:
|
||||
"""
|
||||
Run the interactive REPL.
|
||||
|
||||
This is the main entry point. It runs synchronously,
|
||||
using prompt_toolkit for input (which must be sync).
|
||||
"""
|
||||
self._running = True
|
||||
|
||||
# Get tools count for display
|
||||
tools_count = len(self.config.tools) if self.config.tools else 0
|
||||
|
||||
# Generate session ID
|
||||
import uuid
|
||||
self._session_id = self.config.session_id or str(uuid.uuid4())
|
||||
|
||||
# Print welcome
|
||||
self.io.print_welcome(
|
||||
model=self.config.model,
|
||||
tools_count=tools_count,
|
||||
session_id=self._session_id
|
||||
)
|
||||
|
||||
while self._running:
|
||||
try:
|
||||
# Get input (SYNC - this is the key!)
|
||||
user_input = self.io.get_input("You: ").strip()
|
||||
|
||||
if not user_input:
|
||||
continue
|
||||
|
||||
# Handle slash commands
|
||||
if user_input.startswith("/"):
|
||||
self._handle_command(user_input)
|
||||
continue
|
||||
|
||||
# Show thinking indicator
|
||||
self.io.print_assistant_start()
|
||||
|
||||
# Execute prompt
|
||||
response = self._execute_prompt(user_input)
|
||||
|
||||
# Display response
|
||||
if response:
|
||||
self.io.print_assistant_response(response)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
self.io.info("\nUse /exit to quit")
|
||||
except EOFError:
|
||||
self._running = False
|
||||
self.io.info("Goodbye!")
|
||||
except Exception as e:
|
||||
logger.exception("Error in REPL loop")
|
||||
self.io.tool_error(f"Error: {e}")
|
||||
|
||||
def run_single(self, prompt: str) -> Optional[str]:
|
||||
"""Run a single prompt and return the response."""
|
||||
return self._execute_prompt(prompt)
|
||||
|
||||
|
||||
def start_interactive(
|
||||
model: str = "gpt-4o-mini",
|
||||
verbose: bool = False,
|
||||
memory: bool = False,
|
||||
tools: Optional[List] = None,
|
||||
session_id: Optional[str] = None,
|
||||
**kwargs
|
||||
) -> None:
|
||||
"""
|
||||
Start the interactive REPL.
|
||||
|
||||
This is the main entry point for `praisonai chat` and `praisonai` (no args).
|
||||
"""
|
||||
config = REPLConfig(
|
||||
model=model,
|
||||
verbose=verbose,
|
||||
memory=memory,
|
||||
tools=tools,
|
||||
session_id=session_id,
|
||||
)
|
||||
|
||||
repl = InteractiveREPL(config=config)
|
||||
repl.run()
|
||||
@@ -0,0 +1,456 @@
|
||||
"""
|
||||
PraisonAI Split-Pane TUI Application.
|
||||
|
||||
Full-screen terminal UI with:
|
||||
- Fixed bottom input pane (always visible)
|
||||
- Scrollable top output pane
|
||||
- Direct response (no streaming - faster)
|
||||
- Activity indicators showing agent status
|
||||
|
||||
Uses prompt_toolkit Application for true split-pane layout.
|
||||
"""
|
||||
|
||||
import shutil
|
||||
import threading
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import List, Optional
|
||||
from datetime import datetime
|
||||
|
||||
# ============================================================================
|
||||
# Branding - Import from unified source
|
||||
# ============================================================================
|
||||
|
||||
from praisonai.cli.branding import get_logo, get_version
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Configuration
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class SplitTUIConfig:
|
||||
"""Configuration for the Split TUI application."""
|
||||
model: str = "gpt-4o-mini"
|
||||
show_logo: bool = True
|
||||
show_status_bar: bool = True
|
||||
session_id: Optional[str] = None
|
||||
workspace: Optional[str] = None
|
||||
history_file: Optional[str] = None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Message Types
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class ChatMessage:
|
||||
"""A chat message."""
|
||||
role: str # "user", "assistant", "system", "status"
|
||||
content: str
|
||||
timestamp: datetime = field(default_factory=datetime.now)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Split TUI Application
|
||||
# ============================================================================
|
||||
|
||||
class SplitTUI:
|
||||
"""
|
||||
Split-pane TUI with fixed bottom input and scrollable top output.
|
||||
|
||||
Key features:
|
||||
- Input box ALWAYS visible at bottom
|
||||
- Output scrolls above independently
|
||||
- Direct response (no streaming) for speed
|
||||
- Activity indicators during processing
|
||||
"""
|
||||
|
||||
def __init__(self, config: Optional[SplitTUIConfig] = None):
|
||||
self.config = config or SplitTUIConfig()
|
||||
self.messages: List[ChatMessage] = []
|
||||
self._running = False
|
||||
self._agent = None
|
||||
self._processing = False
|
||||
self._status_text = ""
|
||||
|
||||
# Terminal size
|
||||
self.term_width, self.term_height = shutil.get_terminal_size((80, 24))
|
||||
|
||||
# Session ID
|
||||
import uuid
|
||||
self.session_id = self.config.session_id or str(uuid.uuid4())[:8]
|
||||
|
||||
def _get_agent(self):
|
||||
"""Lazy-load the agent with verbose=False for no streaming."""
|
||||
if self._agent is None:
|
||||
try:
|
||||
from praisonaiagents import Agent
|
||||
|
||||
self._agent = Agent(
|
||||
name="Praison",
|
||||
role="AI Assistant",
|
||||
goal="Help the user with their requests",
|
||||
instructions="You are Praison AI, a helpful assistant. Be concise and helpful.",
|
||||
llm=self.config.model,
|
||||
)
|
||||
except ImportError as e:
|
||||
raise RuntimeError(f"Failed to import praisonaiagents: {e}")
|
||||
|
||||
return self._agent
|
||||
|
||||
def _format_output(self) -> str:
|
||||
"""Format all messages for the output pane."""
|
||||
lines = []
|
||||
|
||||
# Logo
|
||||
if self.config.show_logo and not self.messages:
|
||||
logo = get_logo(self.term_width)
|
||||
lines.append(logo.strip())
|
||||
lines.append("")
|
||||
lines.append(f" v{get_version()} · Model: {self.config.model}")
|
||||
lines.append("")
|
||||
lines.append(" Type your message and press Enter. Use /help for commands.")
|
||||
lines.append("")
|
||||
|
||||
# Messages
|
||||
for msg in self.messages:
|
||||
if msg.role == "user":
|
||||
lines.append(f"› {msg.content}")
|
||||
lines.append("")
|
||||
elif msg.role == "assistant":
|
||||
lines.append(f"● {msg.content}")
|
||||
lines.append("")
|
||||
elif msg.role == "system":
|
||||
lines.append(f" {msg.content}")
|
||||
lines.append("")
|
||||
elif msg.role == "status":
|
||||
lines.append(f" ⏳ {msg.content}")
|
||||
|
||||
# Processing indicator
|
||||
if self._processing:
|
||||
lines.append(f" ⏳ {self._status_text}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def _handle_command(self, command: str) -> bool:
|
||||
"""Handle slash commands. Returns True if handled."""
|
||||
parts = command.split(maxsplit=1)
|
||||
cmd = parts[0].lower().lstrip("/")
|
||||
args = parts[1] if len(parts) > 1 else ""
|
||||
|
||||
if cmd in ("exit", "quit", "q"):
|
||||
self._running = False
|
||||
return True
|
||||
|
||||
elif cmd == "help":
|
||||
help_text = """Available Commands:
|
||||
/help Show this help
|
||||
/exit, /quit Exit Praison AI
|
||||
/clear Clear conversation
|
||||
/model [name] Show or change model
|
||||
/new Start new conversation"""
|
||||
self.messages.append(ChatMessage(role="system", content=help_text))
|
||||
return True
|
||||
|
||||
elif cmd == "clear":
|
||||
self.messages.clear()
|
||||
return True
|
||||
|
||||
elif cmd == "new":
|
||||
self.messages.clear()
|
||||
import uuid
|
||||
self.session_id = str(uuid.uuid4())[:8]
|
||||
self.messages.append(ChatMessage(role="system", content=f"New session: {self.session_id}"))
|
||||
return True
|
||||
|
||||
elif cmd == "model":
|
||||
if args:
|
||||
self.config.model = args
|
||||
self._agent = None
|
||||
self.messages.append(ChatMessage(role="system", content=f"Model changed to: {args}"))
|
||||
else:
|
||||
self.messages.append(ChatMessage(role="system", content=f"Current model: {self.config.model}"))
|
||||
return True
|
||||
|
||||
else:
|
||||
self.messages.append(ChatMessage(role="system", content=f"Unknown command: /{cmd}. Use /help for available commands."))
|
||||
return True
|
||||
|
||||
def _execute_prompt(self, prompt: str) -> Optional[str]:
|
||||
"""Execute a prompt and return the response (direct, no streaming)."""
|
||||
import sys
|
||||
import io
|
||||
|
||||
try:
|
||||
agent = self._get_agent()
|
||||
|
||||
# Suppress agent's Rich output by redirecting stdout/stderr
|
||||
old_stdout = sys.stdout
|
||||
old_stderr = sys.stderr
|
||||
sys.stdout = io.StringIO()
|
||||
sys.stderr = io.StringIO()
|
||||
|
||||
try:
|
||||
response = agent.start(prompt)
|
||||
finally:
|
||||
# Restore stdout/stderr
|
||||
sys.stdout = old_stdout
|
||||
sys.stderr = old_stderr
|
||||
|
||||
return str(response) if response else None
|
||||
except Exception as e:
|
||||
return f"Error: {e}"
|
||||
|
||||
def _run_with_status(self, prompt: str) -> Optional[str]:
|
||||
"""Run prompt with status updates."""
|
||||
self._processing = True
|
||||
self._status_text = "Praison AI is thinking..."
|
||||
|
||||
# Execute in background
|
||||
result = [None]
|
||||
error = [None]
|
||||
|
||||
def execute():
|
||||
try:
|
||||
result[0] = self._execute_prompt(prompt)
|
||||
except Exception as e:
|
||||
error[0] = str(e)
|
||||
|
||||
thread = threading.Thread(target=execute)
|
||||
thread.start()
|
||||
|
||||
# Update status while waiting
|
||||
start_time = time.time()
|
||||
spinner = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"]
|
||||
idx = 0
|
||||
|
||||
while thread.is_alive():
|
||||
elapsed = time.time() - start_time
|
||||
self._status_text = f"{spinner[idx]} Praison AI is thinking... ({elapsed:.1f}s)"
|
||||
idx = (idx + 1) % len(spinner)
|
||||
time.sleep(0.1)
|
||||
|
||||
thread.join()
|
||||
self._processing = False
|
||||
self._status_text = ""
|
||||
|
||||
if error[0]:
|
||||
return f"Error: {error[0]}"
|
||||
return result[0]
|
||||
|
||||
def run(self) -> None:
|
||||
"""Run the split-pane TUI."""
|
||||
self._running = True
|
||||
|
||||
# Try to use prompt_toolkit for better experience
|
||||
try:
|
||||
self._run_with_prompt_toolkit()
|
||||
except ImportError:
|
||||
# Fallback to simple mode
|
||||
self._run_simple()
|
||||
|
||||
def _run_simple(self) -> None:
|
||||
"""Simple fallback mode without prompt_toolkit."""
|
||||
# Print welcome
|
||||
print(self._format_output())
|
||||
|
||||
while self._running:
|
||||
try:
|
||||
# Status bar
|
||||
if self.config.show_status_bar:
|
||||
status = f" ? for help | {self.config.model} | Session: {self.session_id} "
|
||||
print(f"\033[90m{status}\033[0m")
|
||||
|
||||
# Get input
|
||||
user_input = input("› ").strip()
|
||||
|
||||
if not user_input:
|
||||
continue
|
||||
|
||||
# Handle commands
|
||||
if user_input.startswith("/"):
|
||||
self._handle_command(user_input)
|
||||
# Print system messages
|
||||
for msg in self.messages:
|
||||
if msg.role == "system":
|
||||
print(f" {msg.content}")
|
||||
self.messages = [m for m in self.messages if m.role != "system"]
|
||||
continue
|
||||
|
||||
# Add user message
|
||||
self.messages.append(ChatMessage(role="user", content=user_input))
|
||||
|
||||
# Execute with status
|
||||
print(" ⏳ Praison AI is thinking...")
|
||||
response = self._execute_prompt(user_input)
|
||||
|
||||
if response:
|
||||
self.messages.append(ChatMessage(role="assistant", content=response))
|
||||
print(f"\n● {response}\n")
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\n Use /exit to quit")
|
||||
except EOFError:
|
||||
self._running = False
|
||||
|
||||
print("\n Goodbye from Praison AI!")
|
||||
|
||||
def _run_with_prompt_toolkit(self) -> None:
|
||||
"""Run with prompt_toolkit for split-pane layout."""
|
||||
from prompt_toolkit import Application
|
||||
from prompt_toolkit.buffer import Buffer
|
||||
from prompt_toolkit.layout.containers import HSplit, VSplit, Window
|
||||
from prompt_toolkit.layout.controls import BufferControl, FormattedTextControl
|
||||
from prompt_toolkit.layout.layout import Layout
|
||||
from prompt_toolkit.key_binding import KeyBindings
|
||||
from prompt_toolkit.styles import Style
|
||||
from prompt_toolkit.history import FileHistory
|
||||
|
||||
# Setup history
|
||||
history_file = self.config.history_file or str(Path.home() / ".praison" / "history")
|
||||
Path(history_file).parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Output buffer (read-only, for displaying conversation)
|
||||
output_text = [self._format_output()]
|
||||
|
||||
def get_output_text():
|
||||
return output_text[0]
|
||||
|
||||
# Input buffer
|
||||
input_buffer = Buffer(
|
||||
multiline=False,
|
||||
history=FileHistory(history_file),
|
||||
)
|
||||
|
||||
# Key bindings
|
||||
kb = KeyBindings()
|
||||
|
||||
@kb.add("enter")
|
||||
def handle_enter(event):
|
||||
user_input = input_buffer.text.strip()
|
||||
if not user_input:
|
||||
return
|
||||
|
||||
input_buffer.reset()
|
||||
|
||||
# Handle commands
|
||||
if user_input.startswith("/"):
|
||||
self._handle_command(user_input)
|
||||
output_text[0] = self._format_output()
|
||||
return
|
||||
|
||||
# Add user message
|
||||
self.messages.append(ChatMessage(role="user", content=user_input))
|
||||
|
||||
# Show processing status
|
||||
self.messages.append(ChatMessage(role="status", content="Praison AI is thinking..."))
|
||||
output_text[0] = self._format_output()
|
||||
|
||||
# Execute (this blocks but that's OK for direct response)
|
||||
response = self._execute_prompt(user_input)
|
||||
|
||||
# Remove status message
|
||||
self.messages = [m for m in self.messages if m.role != "status"]
|
||||
|
||||
if response:
|
||||
self.messages.append(ChatMessage(role="assistant", content=response))
|
||||
|
||||
output_text[0] = self._format_output()
|
||||
|
||||
@kb.add("c-c")
|
||||
def handle_ctrl_c(event):
|
||||
input_buffer.reset()
|
||||
|
||||
@kb.add("c-d")
|
||||
def handle_ctrl_d(event):
|
||||
if not input_buffer.text:
|
||||
self._running = False
|
||||
event.app.exit()
|
||||
|
||||
@kb.add("c-q")
|
||||
def handle_ctrl_q(event):
|
||||
self._running = False
|
||||
event.app.exit()
|
||||
|
||||
# Style
|
||||
style = Style.from_dict({
|
||||
"output-area": "bg:#0d0d0d",
|
||||
"input-area": "bg:#1a1a1a",
|
||||
"status-bar": "bg:#333333 #888888",
|
||||
"prompt": "#00aaff bold",
|
||||
})
|
||||
|
||||
# Status bar text
|
||||
def get_status_bar():
|
||||
left = "? for help"
|
||||
center = self.config.model
|
||||
right = f"Session: {self.session_id}"
|
||||
return f" {left} | {center} | {right} "
|
||||
|
||||
# Layout: Output (top, scrollable) + Status bar + Input (bottom, fixed)
|
||||
layout = Layout(
|
||||
HSplit([
|
||||
# Output area (takes remaining space)
|
||||
Window(
|
||||
content=FormattedTextControl(get_output_text),
|
||||
wrap_lines=True,
|
||||
style="class:output-area",
|
||||
),
|
||||
# Status bar (1 line)
|
||||
Window(
|
||||
content=FormattedTextControl(get_status_bar),
|
||||
height=1,
|
||||
style="class:status-bar",
|
||||
),
|
||||
# Input area (fixed at bottom, 3 lines for visibility)
|
||||
HSplit([
|
||||
Window(height=1), # Spacer
|
||||
VSplit([
|
||||
Window(
|
||||
content=FormattedTextControl([("class:prompt", "› ")]),
|
||||
width=2,
|
||||
),
|
||||
Window(
|
||||
content=BufferControl(buffer=input_buffer),
|
||||
wrap_lines=True,
|
||||
),
|
||||
]),
|
||||
Window(height=1), # Spacer
|
||||
], height=3, style="class:input-area"),
|
||||
])
|
||||
)
|
||||
|
||||
# Create application
|
||||
app = Application(
|
||||
layout=layout,
|
||||
key_bindings=kb,
|
||||
style=style,
|
||||
full_screen=True,
|
||||
mouse_support=True,
|
||||
)
|
||||
|
||||
# Run
|
||||
app.run()
|
||||
|
||||
print("\n Goodbye from Praison AI!")
|
||||
|
||||
def run_single(self, prompt: str) -> Optional[str]:
|
||||
"""Run a single prompt (non-interactive)."""
|
||||
return self._execute_prompt(prompt)
|
||||
|
||||
|
||||
def start_split_tui(
|
||||
model: str = "gpt-4o-mini",
|
||||
show_logo: bool = True,
|
||||
**kwargs
|
||||
) -> None:
|
||||
"""Start the split-pane TUI application."""
|
||||
config = SplitTUIConfig(
|
||||
model=model,
|
||||
show_logo=show_logo,
|
||||
)
|
||||
|
||||
tui = SplitTUI(config=config)
|
||||
tui.run()
|
||||
@@ -0,0 +1,457 @@
|
||||
"""
|
||||
PraisonAI Interactive TUI Application.
|
||||
|
||||
Full-screen terminal UI with:
|
||||
- Sticky bottom input box (like Aider/Codex/Claude Code)
|
||||
- Scrollable output area above
|
||||
- ASCII art logo banner
|
||||
- Status bar with model/context info
|
||||
- Clean, spacious design inspired by Claude Code
|
||||
|
||||
Uses prompt_toolkit for the full-screen application.
|
||||
"""
|
||||
|
||||
import shutil
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional
|
||||
from datetime import datetime
|
||||
|
||||
# Lazy imports for performance
|
||||
_PT_AVAILABLE = None
|
||||
_RICH_AVAILABLE = None
|
||||
|
||||
|
||||
def _check_prompt_toolkit():
|
||||
global _PT_AVAILABLE
|
||||
if _PT_AVAILABLE is None:
|
||||
try:
|
||||
import prompt_toolkit # noqa: F401
|
||||
_PT_AVAILABLE = True
|
||||
except ImportError:
|
||||
_PT_AVAILABLE = False
|
||||
return _PT_AVAILABLE
|
||||
|
||||
|
||||
def _check_rich():
|
||||
global _RICH_AVAILABLE
|
||||
if _RICH_AVAILABLE is None:
|
||||
try:
|
||||
import rich # noqa: F401
|
||||
_RICH_AVAILABLE = True
|
||||
except ImportError:
|
||||
_RICH_AVAILABLE = False
|
||||
return _RICH_AVAILABLE
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Branding - Import from unified source
|
||||
# ============================================================================
|
||||
|
||||
from praisonai.cli.branding import get_logo, get_version
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Color Scheme
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class ColorScheme:
|
||||
"""Color scheme for the TUI."""
|
||||
# Primary colors
|
||||
primary: str = "#00aaff" # Cyan-blue (PraisonAI brand)
|
||||
secondary: str = "#888888" # Gray
|
||||
accent: str = "#00cc00" # Green
|
||||
|
||||
# Text colors
|
||||
text: str = "#ffffff" # White
|
||||
text_dim: str = "#666666" # Dim gray
|
||||
text_muted: str = "#444444" # Very dim
|
||||
|
||||
# Status colors
|
||||
success: str = "#00cc00" # Green
|
||||
warning: str = "#ffaa00" # Orange
|
||||
error: str = "#ff4444" # Red
|
||||
info: str = "#00aaff" # Blue
|
||||
|
||||
# UI elements
|
||||
border: str = "#333333" # Dark gray
|
||||
input_bg: str = "#1a1a1a" # Very dark
|
||||
output_bg: str = "#0d0d0d" # Almost black
|
||||
|
||||
|
||||
DEFAULT_COLORS = ColorScheme()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# TUI Configuration
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class TUIConfig:
|
||||
"""Configuration for the TUI application."""
|
||||
# Model settings
|
||||
model: str = "gpt-4o-mini"
|
||||
|
||||
# Display settings
|
||||
show_logo: bool = True
|
||||
show_tips: bool = True
|
||||
show_status_bar: bool = True
|
||||
compact_mode: bool = False
|
||||
|
||||
# Colors
|
||||
colors: ColorScheme = field(default_factory=ColorScheme)
|
||||
|
||||
# Input settings
|
||||
multiline: bool = False
|
||||
vi_mode: bool = False
|
||||
|
||||
# History
|
||||
history_file: Optional[str] = None
|
||||
|
||||
# Session
|
||||
session_id: Optional[str] = None
|
||||
workspace: Optional[str] = None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Message Types
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class Message:
|
||||
"""A chat message."""
|
||||
role: str # "user", "assistant", "system", "tool"
|
||||
content: str
|
||||
timestamp: datetime = field(default_factory=datetime.now)
|
||||
metadata: Dict = field(default_factory=dict)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# TUI Application
|
||||
# ============================================================================
|
||||
|
||||
class PraisonTUI:
|
||||
"""
|
||||
Full-screen TUI application for PraisonAI.
|
||||
|
||||
Features:
|
||||
- Sticky bottom input box
|
||||
- Scrollable output area
|
||||
- ASCII art logo
|
||||
- Status bar
|
||||
- Clean, spacious design
|
||||
"""
|
||||
|
||||
def __init__(self, config: Optional[TUIConfig] = None):
|
||||
self.config = config or TUIConfig()
|
||||
self.messages: List[Message] = []
|
||||
self._running = False
|
||||
self._agent = None
|
||||
self._total_tokens = 0
|
||||
self._total_cost = 0.0
|
||||
|
||||
# Get terminal size
|
||||
self.term_width, self.term_height = shutil.get_terminal_size((80, 24))
|
||||
|
||||
# Generate session ID
|
||||
import uuid
|
||||
self.session_id = self.config.session_id or str(uuid.uuid4())[:8]
|
||||
|
||||
def _get_agent(self):
|
||||
"""Lazy-load the agent."""
|
||||
if self._agent is None:
|
||||
try:
|
||||
from praisonaiagents import Agent
|
||||
|
||||
self._agent = Agent(
|
||||
name="PraisonAgent",
|
||||
role="Assistant",
|
||||
goal="Help the user with their requests",
|
||||
instructions="You are a helpful AI assistant. Be concise and helpful.",
|
||||
llm=self.config.model,
|
||||
)
|
||||
except ImportError as e:
|
||||
raise RuntimeError(f"Failed to import praisonaiagents: {e}")
|
||||
|
||||
return self._agent
|
||||
|
||||
def _render_logo(self) -> str:
|
||||
"""Render the ASCII logo with colors."""
|
||||
if not self.config.show_logo:
|
||||
return ""
|
||||
|
||||
logo = get_logo(self.term_width)
|
||||
version = get_version()
|
||||
|
||||
info_line = f"v{version} · Model: {self.config.model} · Session: {self.session_id}"
|
||||
return logo.strip() + "\n" + info_line
|
||||
|
||||
def _render_welcome(self) -> str:
|
||||
"""Render welcome message."""
|
||||
lines = []
|
||||
|
||||
# Logo
|
||||
if self.config.show_logo:
|
||||
lines.append(self._render_logo())
|
||||
lines.append("")
|
||||
|
||||
# Tips
|
||||
if self.config.show_tips:
|
||||
tips = [
|
||||
"Type your message and press Enter to send",
|
||||
"Use /help for commands, /exit to quit",
|
||||
"Press ? for keyboard shortcuts",
|
||||
]
|
||||
lines.append(" " + tips[0])
|
||||
|
||||
lines.append("")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def _render_status_bar(self) -> str:
|
||||
"""Render the status bar."""
|
||||
if not self.config.show_status_bar:
|
||||
return ""
|
||||
|
||||
left = f"? for shortcuts"
|
||||
center = f"{self.config.model}"
|
||||
right = f"Session: {self.session_id}"
|
||||
|
||||
# Calculate spacing
|
||||
total_len = len(left) + len(center) + len(right)
|
||||
available = self.term_width - total_len - 4
|
||||
|
||||
if available > 0:
|
||||
left_space = available // 2
|
||||
right_space = available - left_space
|
||||
return f" {left}{' ' * left_space}{center}{' ' * right_space}{right} "
|
||||
else:
|
||||
return f" {center} "
|
||||
|
||||
def _format_message(self, msg: Message) -> str:
|
||||
"""Format a message for display."""
|
||||
if msg.role == "user":
|
||||
prefix = "› "
|
||||
return f"{prefix}{msg.content}"
|
||||
elif msg.role == "assistant":
|
||||
prefix = "● "
|
||||
return f"{prefix}{msg.content}"
|
||||
elif msg.role == "tool":
|
||||
prefix = "⚙ "
|
||||
return f"{prefix}{msg.content}"
|
||||
else:
|
||||
return msg.content
|
||||
|
||||
def _handle_command(self, command: str) -> bool:
|
||||
"""Handle slash commands. Returns True if handled."""
|
||||
parts = command.split(maxsplit=1)
|
||||
cmd = parts[0].lower().lstrip("/")
|
||||
args = parts[1] if len(parts) > 1 else ""
|
||||
|
||||
if cmd in ("exit", "quit", "q"):
|
||||
self._running = False
|
||||
return True
|
||||
|
||||
elif cmd == "help":
|
||||
help_text = """
|
||||
Available Commands:
|
||||
/help Show this help
|
||||
/exit, /quit Exit interactive mode
|
||||
/clear Clear conversation
|
||||
/model [name] Show or change model
|
||||
/cost Show token usage
|
||||
/compact Toggle compact mode
|
||||
/multiline Toggle multiline input
|
||||
"""
|
||||
self.messages.append(Message(role="system", content=help_text.strip()))
|
||||
return True
|
||||
|
||||
elif cmd == "clear":
|
||||
self.messages.clear()
|
||||
return True
|
||||
|
||||
elif cmd == "model":
|
||||
if args:
|
||||
self.config.model = args
|
||||
self._agent = None
|
||||
self.messages.append(Message(role="system", content=f"Model changed to: {args}"))
|
||||
else:
|
||||
self.messages.append(Message(role="system", content=f"Current model: {self.config.model}"))
|
||||
return True
|
||||
|
||||
elif cmd == "cost":
|
||||
self.messages.append(Message(
|
||||
role="system",
|
||||
content=f"Tokens: {self._total_tokens} | Cost: ${self._total_cost:.4f}"
|
||||
))
|
||||
return True
|
||||
|
||||
elif cmd == "compact":
|
||||
self.config.compact_mode = not self.config.compact_mode
|
||||
mode = "enabled" if self.config.compact_mode else "disabled"
|
||||
self.messages.append(Message(role="system", content=f"Compact mode {mode}"))
|
||||
return True
|
||||
|
||||
elif cmd == "multiline":
|
||||
self.config.multiline = not self.config.multiline
|
||||
mode = "enabled" if self.config.multiline else "disabled"
|
||||
self.messages.append(Message(role="system", content=f"Multiline mode {mode}"))
|
||||
return True
|
||||
|
||||
else:
|
||||
self.messages.append(Message(role="system", content=f"Unknown command: /{cmd}"))
|
||||
return True
|
||||
|
||||
def _execute_prompt(self, prompt: str) -> Optional[str]:
|
||||
"""Execute a prompt and return the response."""
|
||||
try:
|
||||
agent = self._get_agent()
|
||||
response = agent.start(prompt)
|
||||
return str(response) if response else None
|
||||
except Exception as e:
|
||||
return f"Error: {e}"
|
||||
|
||||
def run(self) -> None:
|
||||
"""Run the TUI application."""
|
||||
self._running = True
|
||||
|
||||
# Print welcome
|
||||
print(self._render_welcome())
|
||||
|
||||
# Setup history
|
||||
history_file = self.config.history_file or str(Path.home() / ".praison" / "history")
|
||||
Path(history_file).parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Create prompt session
|
||||
if _check_prompt_toolkit():
|
||||
from prompt_toolkit import PromptSession
|
||||
from prompt_toolkit.history import FileHistory
|
||||
from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
|
||||
from prompt_toolkit.key_binding import KeyBindings
|
||||
from prompt_toolkit.styles import Style
|
||||
|
||||
# Key bindings
|
||||
kb = KeyBindings()
|
||||
|
||||
@kb.add("c-c")
|
||||
def _(event):
|
||||
event.current_buffer.reset()
|
||||
|
||||
@kb.add("c-d")
|
||||
def _(event):
|
||||
if not event.current_buffer.text:
|
||||
event.app.exit()
|
||||
|
||||
# Style
|
||||
style = Style.from_dict({
|
||||
"": self.config.colors.accent,
|
||||
"prompt": self.config.colors.primary,
|
||||
})
|
||||
|
||||
session = PromptSession(
|
||||
history=FileHistory(history_file),
|
||||
auto_suggest=AutoSuggestFromHistory(),
|
||||
key_bindings=kb,
|
||||
style=style,
|
||||
multiline=self.config.multiline,
|
||||
)
|
||||
|
||||
def get_input():
|
||||
return session.prompt(
|
||||
[("class:prompt", "› ")],
|
||||
placeholder="Type your message or @path/to/file"
|
||||
)
|
||||
else:
|
||||
def get_input():
|
||||
return input("› ")
|
||||
|
||||
# Main loop
|
||||
while self._running:
|
||||
try:
|
||||
# Print status bar
|
||||
if self.config.show_status_bar and not self.config.compact_mode:
|
||||
status = self._render_status_bar()
|
||||
if _check_rich():
|
||||
from rich.console import Console
|
||||
Console().print(f"[dim]{status}[/dim]")
|
||||
else:
|
||||
print(f"\033[90m{status}\033[0m")
|
||||
|
||||
# Get input
|
||||
user_input = get_input().strip()
|
||||
|
||||
if not user_input:
|
||||
continue
|
||||
|
||||
# Handle commands
|
||||
if user_input.startswith("/"):
|
||||
self._handle_command(user_input)
|
||||
# Print system messages
|
||||
for msg in self.messages:
|
||||
if msg.role == "system":
|
||||
print(self._format_message(msg))
|
||||
self.messages = [m for m in self.messages if m.role != "system"]
|
||||
continue
|
||||
|
||||
# Add user message
|
||||
self.messages.append(Message(role="user", content=user_input))
|
||||
|
||||
# Show thinking indicator
|
||||
if _check_rich():
|
||||
from rich.console import Console
|
||||
Console().print("[dim]Thinking...[/dim]")
|
||||
|
||||
# Execute
|
||||
response = self._execute_prompt(user_input)
|
||||
|
||||
if response:
|
||||
self.messages.append(Message(role="assistant", content=response))
|
||||
|
||||
# Display response
|
||||
if _check_rich():
|
||||
from rich.console import Console
|
||||
from rich.markdown import Markdown
|
||||
from rich.panel import Panel
|
||||
|
||||
console = Console()
|
||||
try:
|
||||
md = Markdown(response)
|
||||
console.print(Panel(md, border_style="cyan", padding=(0, 1)))
|
||||
except Exception:
|
||||
console.print(f"● {response}")
|
||||
else:
|
||||
print(f"● {response}")
|
||||
|
||||
print() # Spacing
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\nUse /exit to quit")
|
||||
except EOFError:
|
||||
self._running = False
|
||||
print("\nGoodbye!")
|
||||
except Exception as e:
|
||||
print(f"Error: {e}")
|
||||
|
||||
print("Goodbye!")
|
||||
|
||||
def run_single(self, prompt: str) -> Optional[str]:
|
||||
"""Run a single prompt."""
|
||||
return self._execute_prompt(prompt)
|
||||
|
||||
|
||||
def start_tui(
|
||||
model: str = "gpt-4o-mini",
|
||||
show_logo: bool = True,
|
||||
compact: bool = False,
|
||||
**kwargs
|
||||
) -> None:
|
||||
"""Start the TUI application."""
|
||||
config = TUIConfig(
|
||||
model=model,
|
||||
show_logo=show_logo,
|
||||
compact_mode=compact,
|
||||
)
|
||||
|
||||
tui = PraisonTUI(config=config)
|
||||
tui.run()
|
||||
@@ -34,6 +34,8 @@ TYPER_COMMANDS = {
|
||||
'memory', 'workflow', 'tools', 'knowledge', 'deploy', 'agents', 'skills',
|
||||
'eval', 'templates', 'recipe', 'todo', 'docs', 'commit', 'hooks', 'rules',
|
||||
'registry', 'package', 'endpoints',
|
||||
# Standardisation commands
|
||||
'standardise', 'standardize',
|
||||
}
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,162 @@
|
||||
"""
|
||||
UI Backend system for PraisonAI CLI.
|
||||
|
||||
Provides multiple rendering backends for interactive mode:
|
||||
- PlainBackend: No dependencies, works everywhere
|
||||
- RichBackend: Rich-based rendering (current default)
|
||||
- MiddleGroundBackend: Enhanced Rich + prompt_toolkit (new default when deps available)
|
||||
|
||||
All backends implement the UIBackend protocol and are selected automatically
|
||||
based on environment, or explicitly via --ui flag.
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
from typing import Optional
|
||||
|
||||
__all__ = [
|
||||
'UIConfig',
|
||||
'UIEventType',
|
||||
'select_backend',
|
||||
'PlainBackend',
|
||||
'RichBackend',
|
||||
'MiddleGroundBackend',
|
||||
]
|
||||
|
||||
_lazy_cache = {}
|
||||
|
||||
|
||||
def __getattr__(name: str):
|
||||
"""Lazy load UI components."""
|
||||
if name in _lazy_cache:
|
||||
return _lazy_cache[name]
|
||||
|
||||
if name == 'UIConfig':
|
||||
from .config import UIConfig
|
||||
_lazy_cache[name] = UIConfig
|
||||
return UIConfig
|
||||
|
||||
if name == 'UIEventType':
|
||||
from .events import UIEventType
|
||||
_lazy_cache[name] = UIEventType
|
||||
return UIEventType
|
||||
|
||||
if name == 'PlainBackend':
|
||||
from .plain import PlainBackend
|
||||
_lazy_cache[name] = PlainBackend
|
||||
return PlainBackend
|
||||
|
||||
if name == 'RichBackend':
|
||||
from .rich_backend import RichBackend
|
||||
_lazy_cache[name] = RichBackend
|
||||
return RichBackend
|
||||
|
||||
if name == 'MiddleGroundBackend':
|
||||
from .mg_backend import MiddleGroundBackend
|
||||
_lazy_cache[name] = MiddleGroundBackend
|
||||
return MiddleGroundBackend
|
||||
|
||||
if name == 'select_backend':
|
||||
from .selector import select_backend
|
||||
_lazy_cache[name] = select_backend
|
||||
return select_backend
|
||||
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
|
||||
|
||||
def select_backend(config: Optional['UIConfig'] = None):
|
||||
"""
|
||||
Select the appropriate UI backend based on config and environment.
|
||||
|
||||
Selection priority:
|
||||
1. Explicit config.ui_backend override
|
||||
2. PRAISONAI_UI_SAFE=1 → PlainBackend
|
||||
3. config.json_output=True → PlainBackend
|
||||
4. Non-TTY stdout → PlainBackend
|
||||
5. Auto-detect based on available deps:
|
||||
- MiddleGroundBackend if rich + prompt_toolkit available
|
||||
- RichBackend if rich available
|
||||
- PlainBackend otherwise
|
||||
|
||||
Args:
|
||||
config: UIConfig instance with settings
|
||||
|
||||
Returns:
|
||||
UIBackend instance
|
||||
"""
|
||||
from .config import UIConfig
|
||||
from .plain import PlainBackend
|
||||
|
||||
if config is None:
|
||||
config = UIConfig()
|
||||
|
||||
# Explicit override
|
||||
if config.ui_backend and config.ui_backend != 'auto':
|
||||
return _get_backend_by_name(config.ui_backend, config)
|
||||
|
||||
# Environment override for safe mode
|
||||
if os.environ.get('PRAISONAI_UI_SAFE') == '1':
|
||||
return PlainBackend(config)
|
||||
|
||||
# JSON output forces plain
|
||||
if config.json_output:
|
||||
return PlainBackend(config)
|
||||
|
||||
# Non-TTY forces plain
|
||||
if not sys.stdout.isatty():
|
||||
return PlainBackend(config)
|
||||
|
||||
# Auto-detect based on available deps
|
||||
return _auto_select_backend(config)
|
||||
|
||||
|
||||
def _get_backend_by_name(name: str, config: 'UIConfig'):
|
||||
"""Get backend by name."""
|
||||
from .plain import PlainBackend
|
||||
|
||||
if name == 'plain':
|
||||
return PlainBackend(config)
|
||||
|
||||
if name == 'rich':
|
||||
try:
|
||||
from .rich_backend import RichBackend
|
||||
return RichBackend(config)
|
||||
except ImportError:
|
||||
return PlainBackend(config)
|
||||
|
||||
if name == 'mg':
|
||||
try:
|
||||
from .mg_backend import MiddleGroundBackend
|
||||
return MiddleGroundBackend(config)
|
||||
except ImportError:
|
||||
# Fallback to rich, then plain
|
||||
try:
|
||||
from .rich_backend import RichBackend
|
||||
return RichBackend(config)
|
||||
except ImportError:
|
||||
return PlainBackend(config)
|
||||
|
||||
# Unknown backend, use plain
|
||||
return PlainBackend(config)
|
||||
|
||||
|
||||
def _auto_select_backend(config: 'UIConfig'):
|
||||
"""Auto-select best available backend."""
|
||||
from .plain import PlainBackend
|
||||
|
||||
# Try MiddleGroundBackend first (requires rich + prompt_toolkit)
|
||||
try:
|
||||
from .mg_backend import MiddleGroundBackend
|
||||
return MiddleGroundBackend(config)
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
# Try RichBackend (requires rich)
|
||||
try:
|
||||
from .rich_backend import RichBackend
|
||||
return RichBackend(config)
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
# Fallback to PlainBackend
|
||||
return PlainBackend(config)
|
||||
@@ -0,0 +1,46 @@
|
||||
"""
|
||||
UI Configuration for PraisonAI CLI.
|
||||
|
||||
Provides unified configuration for all UI backends.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Dict, Any
|
||||
|
||||
|
||||
@dataclass
|
||||
class UIConfig:
|
||||
"""Configuration for UI backends."""
|
||||
|
||||
# Backend selection
|
||||
ui_backend: str = 'auto' # auto, plain, rich, mg
|
||||
|
||||
# Output modes
|
||||
json_output: bool = False
|
||||
compact: bool = False
|
||||
verbose: bool = False
|
||||
|
||||
# Styling
|
||||
no_color: bool = False
|
||||
no_unicode: bool = False
|
||||
theme: str = 'default'
|
||||
|
||||
# Behavior
|
||||
no_fullscreen: bool = False
|
||||
|
||||
# Additional settings
|
||||
extra: Dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
@classmethod
|
||||
def from_cli_args(cls, **kwargs) -> 'UIConfig':
|
||||
"""Create UIConfig from CLI arguments."""
|
||||
return cls(
|
||||
ui_backend=kwargs.get('ui', 'auto'),
|
||||
json_output=kwargs.get('json', False),
|
||||
compact=kwargs.get('compact', False),
|
||||
verbose=kwargs.get('verbose', False),
|
||||
no_color=kwargs.get('no_color', False),
|
||||
no_unicode=kwargs.get('no_unicode', False),
|
||||
theme=kwargs.get('theme', 'default'),
|
||||
no_fullscreen=kwargs.get('no_fullscreen', False),
|
||||
)
|
||||
@@ -0,0 +1,61 @@
|
||||
"""
|
||||
UI Event types for backend communication.
|
||||
|
||||
Events flow from InteractiveCore to UI backends for rendering.
|
||||
"""
|
||||
|
||||
from enum import Enum
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
|
||||
class UIEventType(Enum):
|
||||
"""Event types emitted by InteractiveCore to UI backends."""
|
||||
|
||||
# Message lifecycle
|
||||
MESSAGE_START = "message.start"
|
||||
MESSAGE_CHUNK = "message.chunk"
|
||||
MESSAGE_END = "message.end"
|
||||
|
||||
# Tool lifecycle
|
||||
TOOL_START = "tool.start"
|
||||
TOOL_PROGRESS = "tool.progress"
|
||||
TOOL_END = "tool.end"
|
||||
|
||||
# Approval flow
|
||||
APPROVAL_REQUEST = "approval.request"
|
||||
APPROVAL_RESPONSE = "approval.response"
|
||||
|
||||
# Status updates
|
||||
STATUS_UPDATE = "status.update"
|
||||
STATUS_CLEAR = "status.clear"
|
||||
|
||||
# Errors
|
||||
ERROR = "error"
|
||||
WARNING = "warning"
|
||||
|
||||
# Session events
|
||||
SESSION_START = "session.start"
|
||||
SESSION_END = "session.end"
|
||||
|
||||
# Agent events (multi-agent)
|
||||
AGENT_SWITCH = "agent.switch"
|
||||
|
||||
# Input events
|
||||
INPUT_REQUEST = "input.request"
|
||||
INPUT_RECEIVED = "input.received"
|
||||
|
||||
|
||||
@dataclass
|
||||
class UIEvent:
|
||||
"""A UI event with type and data payload."""
|
||||
|
||||
event_type: UIEventType
|
||||
data: Dict[str, Any] = field(default_factory=dict)
|
||||
agent_name: Optional[str] = None
|
||||
timestamp: Optional[float] = None
|
||||
|
||||
def __post_init__(self):
|
||||
if self.timestamp is None:
|
||||
import time
|
||||
self.timestamp = time.time()
|
||||
@@ -0,0 +1,342 @@
|
||||
"""
|
||||
MiddleGroundBackend - Enhanced Rich + prompt_toolkit UI backend.
|
||||
|
||||
The "middle ground" between plain text and full TUI:
|
||||
- Rich for formatted output (panels, markdown, syntax highlighting)
|
||||
- prompt_toolkit for advanced input (history, completion, key bindings)
|
||||
- Streaming markdown with no-flicker approach (stable lines + live window)
|
||||
- Terminal cleanup on exit/crash
|
||||
|
||||
Key design: Uses Aider-style streaming where stable lines go to console
|
||||
above a small Live window, preserving terminal scrollback.
|
||||
"""
|
||||
|
||||
import sys
|
||||
import time
|
||||
import atexit
|
||||
import signal
|
||||
from typing import Dict, Any, Optional, List, TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .config import UIConfig
|
||||
|
||||
from .events import UIEventType
|
||||
|
||||
try:
|
||||
from rich.console import Console
|
||||
from rich.markdown import Markdown
|
||||
from rich.panel import Panel
|
||||
from rich.live import Live
|
||||
from rich.text import Text
|
||||
RICH_AVAILABLE = True
|
||||
except ImportError:
|
||||
RICH_AVAILABLE = False
|
||||
|
||||
try:
|
||||
from prompt_toolkit import PromptSession
|
||||
from prompt_toolkit.history import InMemoryHistory
|
||||
PROMPT_TOOLKIT_AVAILABLE = True
|
||||
except ImportError:
|
||||
PROMPT_TOOLKIT_AVAILABLE = False
|
||||
|
||||
|
||||
class MarkdownStreamer:
|
||||
"""Streaming markdown renderer with no-flicker approach.
|
||||
|
||||
Splits output into stable lines (printed above) and unstable lines
|
||||
(in Live window). This preserves terminal scrollback while allowing
|
||||
smooth streaming updates.
|
||||
"""
|
||||
|
||||
def __init__(self, console: 'Console', live_window: int = 6):
|
||||
"""Initialize streamer.
|
||||
|
||||
Args:
|
||||
console: Rich Console instance
|
||||
live_window: Number of lines to keep in live area
|
||||
"""
|
||||
self._console = console
|
||||
self._live_window = live_window
|
||||
self._live: Optional[Live] = None
|
||||
self._printed_lines: List[str] = []
|
||||
self._current_text = ""
|
||||
self._min_delay = 1.0 / 20 # 20 FPS max
|
||||
self._last_update = 0.0
|
||||
|
||||
def start(self) -> None:
|
||||
"""Start the streaming display."""
|
||||
self._live = Live(Text(""), console=self._console, refresh_per_second=20)
|
||||
self._live.start()
|
||||
self._printed_lines = []
|
||||
self._current_text = ""
|
||||
|
||||
def update(self, text: str, final: bool = False) -> None:
|
||||
"""Update the displayed content.
|
||||
|
||||
Args:
|
||||
text: Full markdown text so far
|
||||
final: If True, this is the final update
|
||||
"""
|
||||
if not self._live:
|
||||
return
|
||||
|
||||
now = time.time()
|
||||
if not final and now - self._last_update < self._min_delay:
|
||||
return
|
||||
self._last_update = now
|
||||
|
||||
self._current_text = text
|
||||
lines = text.splitlines(keepends=True)
|
||||
num_lines = len(lines)
|
||||
|
||||
# How many lines are stable (not in live window)?
|
||||
stable_count = num_lines - self._live_window if not final else num_lines
|
||||
|
||||
if stable_count > len(self._printed_lines):
|
||||
# Print new stable lines above live area
|
||||
new_lines = lines[len(self._printed_lines):stable_count]
|
||||
for line in new_lines:
|
||||
self._console.print(line.rstrip('\n'))
|
||||
self._printed_lines = lines[:stable_count]
|
||||
|
||||
if final:
|
||||
self._live.update(Text(""))
|
||||
self._live.stop()
|
||||
self._live = None
|
||||
else:
|
||||
# Update live window with remaining lines
|
||||
rest = lines[stable_count:]
|
||||
rest_text = "".join(rest)
|
||||
self._live.update(Text(rest_text))
|
||||
|
||||
def stop(self) -> None:
|
||||
"""Stop the streaming display."""
|
||||
if self._live:
|
||||
self._live.stop()
|
||||
self._live = None
|
||||
|
||||
|
||||
class MiddleGroundBackend:
|
||||
"""Enhanced Rich + prompt_toolkit UI backend."""
|
||||
|
||||
def __init__(self, config: Optional['UIConfig'] = None):
|
||||
"""Initialize MiddleGroundBackend.
|
||||
|
||||
Args:
|
||||
config: Optional UIConfig instance
|
||||
|
||||
Raises:
|
||||
ImportError: If required deps not installed
|
||||
"""
|
||||
if not RICH_AVAILABLE:
|
||||
raise ImportError("Rich is required. Install with: pip install rich")
|
||||
if not PROMPT_TOOLKIT_AVAILABLE:
|
||||
raise ImportError("prompt_toolkit is required. Install with: pip install prompt_toolkit")
|
||||
|
||||
self._config = config
|
||||
self._current_message = ""
|
||||
self._in_stream = False
|
||||
|
||||
# Configure console
|
||||
no_color = config.no_color if config else False
|
||||
self._console = Console(
|
||||
force_terminal=True,
|
||||
no_color=no_color,
|
||||
highlight=not no_color,
|
||||
)
|
||||
|
||||
# Markdown streamer for no-flicker streaming
|
||||
self._streamer: Optional[MarkdownStreamer] = None
|
||||
|
||||
# prompt_toolkit session
|
||||
self._prompt_session: Optional[PromptSession] = None
|
||||
self._history = InMemoryHistory()
|
||||
|
||||
# Register cleanup handlers
|
||||
self._register_cleanup()
|
||||
|
||||
def _register_cleanup(self) -> None:
|
||||
"""Register terminal cleanup handlers."""
|
||||
def cleanup():
|
||||
self._cleanup_terminal()
|
||||
|
||||
atexit.register(cleanup)
|
||||
|
||||
# Handle signals
|
||||
def signal_handler(signum, frame):
|
||||
self._cleanup_terminal()
|
||||
sys.exit(128 + signum)
|
||||
|
||||
try:
|
||||
signal.signal(signal.SIGINT, signal_handler)
|
||||
signal.signal(signal.SIGTERM, signal_handler)
|
||||
except (ValueError, OSError):
|
||||
# Can't set signal handlers in some contexts
|
||||
pass
|
||||
|
||||
def _cleanup_terminal(self) -> None:
|
||||
"""Restore terminal state."""
|
||||
try:
|
||||
# Stop any active streaming
|
||||
if self._streamer:
|
||||
self._streamer.stop()
|
||||
|
||||
# Restore cursor
|
||||
sys.stdout.write("\033[?25h") # Show cursor
|
||||
sys.stdout.write("\033[0m") # Reset colors
|
||||
sys.stdout.flush()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
def emit(self, event_type: UIEventType, data: Dict[str, Any]) -> None:
|
||||
"""Emit an event to the UI.
|
||||
|
||||
Args:
|
||||
event_type: Type of event
|
||||
data: Event data payload
|
||||
"""
|
||||
if event_type == UIEventType.MESSAGE_START:
|
||||
self._in_stream = True
|
||||
self._current_message = ""
|
||||
agent_name = data.get('agent_name', '')
|
||||
if agent_name:
|
||||
self._console.print(f"[bold cyan][{agent_name}][/bold cyan]")
|
||||
|
||||
# Start streaming display
|
||||
self._streamer = MarkdownStreamer(self._console)
|
||||
self._streamer.start()
|
||||
|
||||
elif event_type == UIEventType.MESSAGE_CHUNK:
|
||||
content = data.get('content', '')
|
||||
self._current_message += content
|
||||
|
||||
if self._streamer:
|
||||
self._streamer.update(self._current_message)
|
||||
|
||||
elif event_type == UIEventType.MESSAGE_END:
|
||||
self._in_stream = False
|
||||
|
||||
if self._streamer:
|
||||
self._streamer.update(self._current_message, final=True)
|
||||
self._streamer = None
|
||||
|
||||
self._current_message = ""
|
||||
|
||||
elif event_type == UIEventType.TOOL_START:
|
||||
tool_name = data.get('tool_name', 'tool')
|
||||
args = data.get('args', '')
|
||||
self._console.print(f"\n[dim]▶ {tool_name}[/dim]", end="")
|
||||
if args and self._config and self._config.verbose:
|
||||
self._console.print(f" [dim]{args}[/dim]")
|
||||
else:
|
||||
self._console.print()
|
||||
|
||||
elif event_type == UIEventType.TOOL_END:
|
||||
result = data.get('result', '')
|
||||
success = data.get('success', True)
|
||||
if result:
|
||||
style = "green" if success else "red"
|
||||
# Truncate long results
|
||||
if len(result) > 200 and not (self._config and self._config.verbose):
|
||||
result = result[:200] + "..."
|
||||
self._console.print(f"[{style}]{result}[/{style}]")
|
||||
|
||||
elif event_type == UIEventType.ERROR:
|
||||
message = data.get('message', 'Unknown error')
|
||||
self._console.print(Panel(
|
||||
f"[bold red]{message}[/bold red]",
|
||||
title="Error",
|
||||
border_style="red",
|
||||
))
|
||||
|
||||
elif event_type == UIEventType.WARNING:
|
||||
message = data.get('message', '')
|
||||
self._console.print(f"[yellow]⚠ {message}[/yellow]")
|
||||
|
||||
elif event_type == UIEventType.STATUS_UPDATE:
|
||||
status = data.get('status', '')
|
||||
if status:
|
||||
# Use transient status (overwrite with \r)
|
||||
sys.stdout.write(f"\r[{status}]")
|
||||
sys.stdout.flush()
|
||||
|
||||
elif event_type == UIEventType.STATUS_CLEAR:
|
||||
sys.stdout.write("\r" + " " * 40 + "\r")
|
||||
sys.stdout.flush()
|
||||
|
||||
elif event_type == UIEventType.APPROVAL_REQUEST:
|
||||
prompt = data.get('prompt', 'Approve?')
|
||||
action = data.get('action', '')
|
||||
|
||||
self._console.print()
|
||||
self._console.print(Panel(
|
||||
f"{prompt}\n\n[dim]{action}[/dim]" if action else prompt,
|
||||
title="[bold yellow]Approval Required[/bold yellow]",
|
||||
border_style="yellow",
|
||||
))
|
||||
self._console.print("[bold][y][/bold]es / [bold][n][/bold]o / [bold][a][/bold]lways: ", end="")
|
||||
|
||||
def prompt(self, message: str = "") -> str:
|
||||
"""Get user input with prompt_toolkit.
|
||||
|
||||
Args:
|
||||
message: Optional prompt message
|
||||
|
||||
Returns:
|
||||
User input string
|
||||
"""
|
||||
if not self._prompt_session:
|
||||
self._prompt_session = PromptSession(
|
||||
history=self._history,
|
||||
enable_history_search=True,
|
||||
)
|
||||
|
||||
try:
|
||||
return self._prompt_session.prompt(message)
|
||||
except EOFError:
|
||||
return ""
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
|
||||
async def prompt_async(self, message: str = "") -> str:
|
||||
"""Get user input asynchronously.
|
||||
|
||||
Args:
|
||||
message: Optional prompt message
|
||||
|
||||
Returns:
|
||||
User input string
|
||||
"""
|
||||
if not self._prompt_session:
|
||||
self._prompt_session = PromptSession(
|
||||
history=self._history,
|
||||
enable_history_search=True,
|
||||
)
|
||||
|
||||
try:
|
||||
return await self._prompt_session.prompt_async(message)
|
||||
except EOFError:
|
||||
return ""
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
|
||||
def is_tty(self) -> bool:
|
||||
"""Check if running in a TTY.
|
||||
|
||||
Returns:
|
||||
True if stdout is a TTY
|
||||
"""
|
||||
return sys.stdout.isatty()
|
||||
|
||||
def render_markdown(self, text: str) -> None:
|
||||
"""Render markdown text.
|
||||
|
||||
Args:
|
||||
text: Markdown text to render
|
||||
"""
|
||||
md = Markdown(text)
|
||||
self._console.print(md)
|
||||
|
||||
def cleanup(self) -> None:
|
||||
"""Cleanup resources."""
|
||||
self._cleanup_terminal()
|
||||
@@ -0,0 +1,133 @@
|
||||
"""
|
||||
PlainBackend - Zero-dependency UI backend.
|
||||
|
||||
Works in any environment: non-TTY, piped output, dumb terminals.
|
||||
No colors, no formatting, just plain text output.
|
||||
"""
|
||||
|
||||
import sys
|
||||
from typing import Dict, Any, Optional, TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .config import UIConfig
|
||||
|
||||
from .events import UIEventType
|
||||
|
||||
|
||||
class PlainBackend:
|
||||
"""Plain text UI backend with no dependencies."""
|
||||
|
||||
def __init__(self, config: Optional['UIConfig'] = None):
|
||||
"""Initialize PlainBackend.
|
||||
|
||||
Args:
|
||||
config: Optional UIConfig instance
|
||||
"""
|
||||
self._config = config
|
||||
self._current_message = ""
|
||||
self._in_stream = False
|
||||
|
||||
def emit(self, event_type: UIEventType, data: Dict[str, Any]) -> None:
|
||||
"""Emit an event to the UI.
|
||||
|
||||
Args:
|
||||
event_type: Type of event
|
||||
data: Event data payload
|
||||
"""
|
||||
if event_type == UIEventType.MESSAGE_START:
|
||||
self._in_stream = True
|
||||
self._current_message = ""
|
||||
agent_name = data.get('agent_name', '')
|
||||
if agent_name:
|
||||
sys.stdout.write(f"[{agent_name}] ")
|
||||
sys.stdout.flush()
|
||||
|
||||
elif event_type == UIEventType.MESSAGE_CHUNK:
|
||||
content = data.get('content', '')
|
||||
sys.stdout.write(content)
|
||||
sys.stdout.flush()
|
||||
self._current_message += content
|
||||
|
||||
elif event_type == UIEventType.MESSAGE_END:
|
||||
self._in_stream = False
|
||||
if not self._current_message.endswith('\n'):
|
||||
sys.stdout.write('\n')
|
||||
sys.stdout.flush()
|
||||
self._current_message = ""
|
||||
|
||||
elif event_type == UIEventType.TOOL_START:
|
||||
tool_name = data.get('tool_name', 'tool')
|
||||
sys.stdout.write(f"\n[Tool: {tool_name}]\n")
|
||||
sys.stdout.flush()
|
||||
|
||||
elif event_type == UIEventType.TOOL_END:
|
||||
result = data.get('result', '')
|
||||
if result:
|
||||
sys.stdout.write(f"{result}\n")
|
||||
sys.stdout.flush()
|
||||
|
||||
elif event_type == UIEventType.ERROR:
|
||||
message = data.get('message', 'Unknown error')
|
||||
sys.stderr.write(f"Error: {message}\n")
|
||||
sys.stderr.flush()
|
||||
|
||||
elif event_type == UIEventType.WARNING:
|
||||
message = data.get('message', '')
|
||||
sys.stderr.write(f"Warning: {message}\n")
|
||||
sys.stderr.flush()
|
||||
|
||||
elif event_type == UIEventType.STATUS_UPDATE:
|
||||
status = data.get('status', '')
|
||||
if status and self._config and self._config.verbose:
|
||||
sys.stderr.write(f"[{status}]\n")
|
||||
sys.stderr.flush()
|
||||
|
||||
elif event_type == UIEventType.APPROVAL_REQUEST:
|
||||
prompt = data.get('prompt', 'Approve?')
|
||||
sys.stdout.write(f"\n{prompt} [y/n]: ")
|
||||
sys.stdout.flush()
|
||||
|
||||
def prompt(self, message: str = "") -> str:
|
||||
"""Get user input.
|
||||
|
||||
Args:
|
||||
message: Optional prompt message
|
||||
|
||||
Returns:
|
||||
User input string
|
||||
"""
|
||||
if message:
|
||||
sys.stdout.write(message)
|
||||
sys.stdout.flush()
|
||||
|
||||
try:
|
||||
return input()
|
||||
except EOFError:
|
||||
return ""
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
|
||||
async def prompt_async(self, message: str = "") -> str:
|
||||
"""Get user input asynchronously.
|
||||
|
||||
For PlainBackend, this is just a sync call wrapped.
|
||||
|
||||
Args:
|
||||
message: Optional prompt message
|
||||
|
||||
Returns:
|
||||
User input string
|
||||
"""
|
||||
return self.prompt(message)
|
||||
|
||||
def is_tty(self) -> bool:
|
||||
"""Check if running in a TTY.
|
||||
|
||||
Returns:
|
||||
True if stdout is a TTY
|
||||
"""
|
||||
return sys.stdout.isatty()
|
||||
|
||||
def cleanup(self) -> None:
|
||||
"""Cleanup resources. No-op for PlainBackend."""
|
||||
pass
|
||||
@@ -0,0 +1,162 @@
|
||||
"""
|
||||
RichBackend - Rich-based UI backend.
|
||||
|
||||
Uses Rich library for formatted terminal output with colors,
|
||||
panels, markdown rendering, and syntax highlighting.
|
||||
"""
|
||||
|
||||
import sys
|
||||
from typing import Dict, Any, Optional, TYPE_CHECKING
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .config import UIConfig
|
||||
|
||||
from .events import UIEventType
|
||||
|
||||
try:
|
||||
from rich.console import Console
|
||||
from rich.markdown import Markdown
|
||||
from rich.panel import Panel
|
||||
RICH_AVAILABLE = True
|
||||
except ImportError:
|
||||
RICH_AVAILABLE = False
|
||||
|
||||
|
||||
class RichBackend:
|
||||
"""Rich-based UI backend with formatted output."""
|
||||
|
||||
def __init__(self, config: Optional['UIConfig'] = None):
|
||||
"""Initialize RichBackend.
|
||||
|
||||
Args:
|
||||
config: Optional UIConfig instance
|
||||
|
||||
Raises:
|
||||
ImportError: If rich is not installed
|
||||
"""
|
||||
if not RICH_AVAILABLE:
|
||||
raise ImportError("Rich is required for RichBackend. Install with: pip install rich")
|
||||
|
||||
self._config = config
|
||||
self._current_message = ""
|
||||
self._in_stream = False
|
||||
|
||||
# Configure console
|
||||
no_color = config.no_color if config else False
|
||||
self._console = Console(
|
||||
force_terminal=True,
|
||||
no_color=no_color,
|
||||
highlight=not no_color,
|
||||
)
|
||||
|
||||
def emit(self, event_type: UIEventType, data: Dict[str, Any]) -> None:
|
||||
"""Emit an event to the UI.
|
||||
|
||||
Args:
|
||||
event_type: Type of event
|
||||
data: Event data payload
|
||||
"""
|
||||
if event_type == UIEventType.MESSAGE_START:
|
||||
self._in_stream = True
|
||||
self._current_message = ""
|
||||
agent_name = data.get('agent_name', '')
|
||||
if agent_name:
|
||||
self._console.print(f"[bold cyan][{agent_name}][/bold cyan] ", end="")
|
||||
|
||||
elif event_type == UIEventType.MESSAGE_CHUNK:
|
||||
content = data.get('content', '')
|
||||
# For streaming, use raw print to avoid Rich overhead
|
||||
sys.stdout.write(content)
|
||||
sys.stdout.flush()
|
||||
self._current_message += content
|
||||
|
||||
elif event_type == UIEventType.MESSAGE_END:
|
||||
self._in_stream = False
|
||||
if not self._current_message.endswith('\n'):
|
||||
sys.stdout.write('\n')
|
||||
sys.stdout.flush()
|
||||
self._current_message = ""
|
||||
|
||||
elif event_type == UIEventType.TOOL_START:
|
||||
tool_name = data.get('tool_name', 'tool')
|
||||
self._console.print(f"\n[dim]▶ {tool_name}[/dim]")
|
||||
|
||||
elif event_type == UIEventType.TOOL_END:
|
||||
result = data.get('result', '')
|
||||
success = data.get('success', True)
|
||||
if result:
|
||||
style = "green" if success else "red"
|
||||
self._console.print(f"[{style}]{result}[/{style}]")
|
||||
|
||||
elif event_type == UIEventType.ERROR:
|
||||
message = data.get('message', 'Unknown error')
|
||||
self._console.print(f"[bold red]Error:[/bold red] {message}")
|
||||
|
||||
elif event_type == UIEventType.WARNING:
|
||||
message = data.get('message', '')
|
||||
self._console.print(f"[yellow]Warning:[/yellow] {message}")
|
||||
|
||||
elif event_type == UIEventType.STATUS_UPDATE:
|
||||
status = data.get('status', '')
|
||||
if status and self._config and self._config.verbose:
|
||||
self._console.print(f"[dim][{status}][/dim]")
|
||||
|
||||
elif event_type == UIEventType.APPROVAL_REQUEST:
|
||||
prompt = data.get('prompt', 'Approve?')
|
||||
self._console.print(Panel(
|
||||
prompt,
|
||||
title="[bold yellow]Approval Required[/bold yellow]",
|
||||
border_style="yellow",
|
||||
))
|
||||
self._console.print("[y]es / [n]o / [a]lways: ", end="")
|
||||
|
||||
def prompt(self, message: str = "") -> str:
|
||||
"""Get user input.
|
||||
|
||||
Args:
|
||||
message: Optional prompt message
|
||||
|
||||
Returns:
|
||||
User input string
|
||||
"""
|
||||
if message:
|
||||
self._console.print(message, end="")
|
||||
|
||||
try:
|
||||
return input()
|
||||
except EOFError:
|
||||
return ""
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
|
||||
async def prompt_async(self, message: str = "") -> str:
|
||||
"""Get user input asynchronously.
|
||||
|
||||
Args:
|
||||
message: Optional prompt message
|
||||
|
||||
Returns:
|
||||
User input string
|
||||
"""
|
||||
return self.prompt(message)
|
||||
|
||||
def is_tty(self) -> bool:
|
||||
"""Check if running in a TTY.
|
||||
|
||||
Returns:
|
||||
True if stdout is a TTY
|
||||
"""
|
||||
return sys.stdout.isatty()
|
||||
|
||||
def render_markdown(self, text: str) -> None:
|
||||
"""Render markdown text.
|
||||
|
||||
Args:
|
||||
text: Markdown text to render
|
||||
"""
|
||||
md = Markdown(text)
|
||||
self._console.print(md)
|
||||
|
||||
def cleanup(self) -> None:
|
||||
"""Cleanup resources."""
|
||||
pass
|
||||
@@ -57,7 +57,7 @@ class CloudDeployer:
|
||||
file.write("FROM python:3.11-slim\n")
|
||||
file.write("WORKDIR /app\n")
|
||||
file.write("COPY . .\n")
|
||||
file.write("RUN pip install flask praisonai==3.6.2 gunicorn markdown\n")
|
||||
file.write("RUN pip install flask praisonai==3.7.8 gunicorn markdown\n")
|
||||
file.write("EXPOSE 8080\n")
|
||||
file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
|
||||
|
||||
|
||||
@@ -0,0 +1,84 @@
|
||||
"""
|
||||
PraisonAI Standardise Module
|
||||
|
||||
Feature Docs/Examples Protocol (FDEP) implementation for standardising
|
||||
documentation and examples across the PraisonAI ecosystem.
|
||||
|
||||
All imports are lazy-loaded for zero performance impact.
|
||||
"""
|
||||
|
||||
__all__ = [
|
||||
# Models
|
||||
"FeatureSlug",
|
||||
"FeatureManifest",
|
||||
"ArtifactStatus",
|
||||
"ValidationResult",
|
||||
"DuplicateCluster",
|
||||
"DriftReport",
|
||||
# Engine
|
||||
"StandardiseEngine",
|
||||
"FeatureDiscovery",
|
||||
"ArtifactValidator",
|
||||
"DedupeDetector",
|
||||
"DriftDetector",
|
||||
"TemplateGenerator",
|
||||
"ReportGenerator",
|
||||
# Config
|
||||
"StandardiseConfig",
|
||||
# AI Generation
|
||||
"AIGenerator",
|
||||
"ExampleVerifier",
|
||||
]
|
||||
|
||||
|
||||
def __getattr__(name: str):
|
||||
"""Lazy loading of standardise components."""
|
||||
if name in ("FeatureSlug", "FeatureManifest", "ArtifactStatus",
|
||||
"ValidationResult", "DuplicateCluster", "DriftReport"):
|
||||
from .models import (
|
||||
FeatureSlug, FeatureManifest, ArtifactStatus,
|
||||
ValidationResult, DuplicateCluster, DriftReport
|
||||
)
|
||||
return locals()[name]
|
||||
|
||||
if name == "StandardiseEngine":
|
||||
from .engine import StandardiseEngine
|
||||
return StandardiseEngine
|
||||
|
||||
if name == "FeatureDiscovery":
|
||||
from .discovery import FeatureDiscovery
|
||||
return FeatureDiscovery
|
||||
|
||||
if name == "ArtifactValidator":
|
||||
from .validator import ArtifactValidator
|
||||
return ArtifactValidator
|
||||
|
||||
if name == "DedupeDetector":
|
||||
from .dedupe import DedupeDetector
|
||||
return DedupeDetector
|
||||
|
||||
if name == "DriftDetector":
|
||||
from .drift import DriftDetector
|
||||
return DriftDetector
|
||||
|
||||
if name == "TemplateGenerator":
|
||||
from .templates import TemplateGenerator
|
||||
return TemplateGenerator
|
||||
|
||||
if name == "ReportGenerator":
|
||||
from .reports import ReportGenerator
|
||||
return ReportGenerator
|
||||
|
||||
if name == "StandardiseConfig":
|
||||
from .config import StandardiseConfig
|
||||
return StandardiseConfig
|
||||
|
||||
if name == "AIGenerator":
|
||||
from .ai_generator import AIGenerator
|
||||
return AIGenerator
|
||||
|
||||
if name == "ExampleVerifier":
|
||||
from .example_verifier import ExampleVerifier
|
||||
return ExampleVerifier
|
||||
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
File diff suppressed because it is too large.
Load diff
@@ -0,0 +1,260 @@
|
||||
"""
|
||||
Configuration for the FDEP standardisation system.
|
||||
|
||||
Supports configuration via:
|
||||
1. CLI flags (highest priority)
|
||||
2. Config file (.praison/standardise.yaml)
|
||||
3. Environment variables
|
||||
4. Defaults (lowest priority)
|
||||
"""
|
||||
|
||||
import os
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
|
||||
@dataclass
|
||||
class StandardiseConfig:
|
||||
"""Configuration for the standardiser engine."""
|
||||
|
||||
# Root paths (auto-detected if not specified)
|
||||
project_root: Optional[Path] = None
|
||||
docs_root: Optional[Path] = None
|
||||
examples_root: Optional[Path] = None
|
||||
sdk_root: Optional[Path] = None
|
||||
cli_root: Optional[Path] = None
|
||||
|
||||
# Mintlify config
|
||||
mintlify_config: Optional[Path] = None
|
||||
|
||||
# Manifest storage
|
||||
manifest_dir: Optional[Path] = None
|
||||
|
||||
# Safety settings
|
||||
dry_run: bool = True
|
||||
backup: bool = True
|
||||
force: bool = False
|
||||
|
||||
# Scope settings
|
||||
scope: str = "all" # all, docs, examples, sdk, cli
|
||||
feature_filter: Optional[str] = None # Specific feature slug to check
|
||||
|
||||
# Dedupe settings
|
||||
dedupe_mode: str = "prompt" # prompt, auto, skip
|
||||
similarity_threshold: float = 0.8
|
||||
|
||||
# Report settings
|
||||
report_format: str = "text" # text, json, markdown
|
||||
|
||||
# CI settings
|
||||
ci_mode: bool = False
|
||||
|
||||
# Excluded paths (relative to project root)
|
||||
excluded_paths: List[str] = field(default_factory=lambda: [
|
||||
"node_modules",
|
||||
"__pycache__",
|
||||
".git",
|
||||
".venv",
|
||||
"venv",
|
||||
"dist",
|
||||
"build",
|
||||
])
|
||||
|
||||
# Required artifact types per feature
|
||||
required_artifacts: List[str] = field(default_factory=lambda: [
|
||||
"docs_concept",
|
||||
"docs_feature",
|
||||
"docs_cli",
|
||||
"docs_sdk",
|
||||
"example_basic",
|
||||
"example_advanced",
|
||||
])
|
||||
|
||||
def __post_init__(self):
|
||||
"""Auto-detect paths if not specified."""
|
||||
# Convert string paths to Path objects
|
||||
if isinstance(self.project_root, str):
|
||||
self.project_root = Path(self.project_root)
|
||||
if isinstance(self.docs_root, str):
|
||||
self.docs_root = Path(self.docs_root)
|
||||
if isinstance(self.examples_root, str):
|
||||
self.examples_root = Path(self.examples_root)
|
||||
if isinstance(self.sdk_root, str):
|
||||
self.sdk_root = Path(self.sdk_root)
|
||||
if isinstance(self.cli_root, str):
|
||||
self.cli_root = Path(self.cli_root)
|
||||
if isinstance(self.mintlify_config, str):
|
||||
self.mintlify_config = Path(self.mintlify_config)
|
||||
if isinstance(self.manifest_dir, str):
|
||||
self.manifest_dir = Path(self.manifest_dir)
|
||||
|
||||
if self.project_root is None:
|
||||
self.project_root = self._detect_project_root()
|
||||
|
||||
if self.project_root:
|
||||
self._auto_detect_paths()
|
||||
|
||||
def _detect_project_root(self) -> Optional[Path]:
|
||||
"""Detect project root by looking for common markers."""
|
||||
cwd = Path.cwd()
|
||||
|
||||
# Look for .praison directory or pyproject.toml
|
||||
for parent in [cwd] + list(cwd.parents):
|
||||
if (parent / ".praison").exists():
|
||||
return parent
|
||||
if (parent / "pyproject.toml").exists():
|
||||
return parent
|
||||
if (parent / "mint.json").exists():
|
||||
return parent
|
||||
|
||||
return cwd
|
||||
|
||||
def _auto_detect_paths(self):
|
||||
"""Auto-detect paths based on project root."""
|
||||
if not self.project_root:
|
||||
return
|
||||
|
||||
root = self.project_root
|
||||
|
||||
# Docs root detection - default: ~/PraisonAIDocs/docs
|
||||
if self.docs_root is None:
|
||||
# First check home directory for PraisonAIDocs
|
||||
home_docs = Path.home() / "PraisonAIDocs" / "docs"
|
||||
if home_docs.exists():
|
||||
self.docs_root = home_docs
|
||||
else:
|
||||
# Fallback to project-relative paths
|
||||
for candidate in ["docs", "PraisonAIDocs/docs"]:
|
||||
path = root / candidate
|
||||
if path.exists():
|
||||
self.docs_root = path
|
||||
break
|
||||
# Check parent for PraisonAIDocs
|
||||
parent_docs = root.parent / "PraisonAIDocs"
|
||||
if parent_docs.exists() and self.docs_root is None:
|
||||
self.docs_root = parent_docs / "docs"
|
||||
|
||||
# Examples root detection - default: ~/praisonai-package/examples
|
||||
if self.examples_root is None:
|
||||
# First check home directory for praisonai-package/examples
|
||||
home_examples = Path.home() / "praisonai-package" / "examples"
|
||||
if home_examples.exists():
|
||||
self.examples_root = home_examples
|
||||
else:
|
||||
# Fallback to project-relative paths
|
||||
for candidate in ["examples/python", "examples"]:
|
||||
path = root / candidate
|
||||
if path.exists():
|
||||
self.examples_root = path
|
||||
break
|
||||
|
||||
# SDK root detection
|
||||
if self.sdk_root is None:
|
||||
for candidate in [
|
||||
"src/praisonai-agents/praisonaiagents",
|
||||
"praisonaiagents",
|
||||
]:
|
||||
path = root / candidate
|
||||
if path.exists():
|
||||
self.sdk_root = path
|
||||
break
|
||||
|
||||
# CLI root detection
|
||||
if self.cli_root is None:
|
||||
for candidate in [
|
||||
"src/praisonai/praisonai/cli",
|
||||
"praisonai/cli",
|
||||
]:
|
||||
path = root / candidate
|
||||
if path.exists():
|
||||
self.cli_root = path
|
||||
break
|
||||
|
||||
# Mintlify config detection
|
||||
if self.mintlify_config is None:
|
||||
# Check docs root parent for mint.json
|
||||
if self.docs_root:
|
||||
mint_path = self.docs_root.parent / "mint.json"
|
||||
if mint_path.exists():
|
||||
self.mintlify_config = mint_path
|
||||
# Check project root
|
||||
if self.mintlify_config is None:
|
||||
for name in ["mint.json", "mintlify.json", "docs.json"]:
|
||||
path = root / name
|
||||
if path.exists():
|
||||
self.mintlify_config = path
|
||||
break
|
||||
|
||||
# Manifest directory
|
||||
if self.manifest_dir is None:
|
||||
self.manifest_dir = root / ".praison" / "features"
|
||||
|
||||
@classmethod
|
||||
def from_file(cls, path: Path) -> "StandardiseConfig":
|
||||
"""Load configuration from a YAML file."""
|
||||
try:
|
||||
import yaml
|
||||
except ImportError:
|
||||
# Fallback to basic parsing if PyYAML not available
|
||||
return cls()
|
||||
|
||||
if not path.exists():
|
||||
return cls()
|
||||
|
||||
with open(path, "r") as f:
|
||||
data = yaml.safe_load(f) or {}
|
||||
|
||||
return cls(
|
||||
project_root=Path(data["project_root"]) if data.get("project_root") else None,
|
||||
docs_root=Path(data["docs_root"]) if data.get("docs_root") else None,
|
||||
examples_root=Path(data["examples_root"]) if data.get("examples_root") else None,
|
||||
sdk_root=Path(data["sdk_root"]) if data.get("sdk_root") else None,
|
||||
cli_root=Path(data["cli_root"]) if data.get("cli_root") else None,
|
||||
mintlify_config=Path(data["mintlify_config"]) if data.get("mintlify_config") else None,
|
||||
manifest_dir=Path(data["manifest_dir"]) if data.get("manifest_dir") else None,
|
||||
dry_run=data.get("dry_run", True),
|
||||
backup=data.get("backup", True),
|
||||
force=data.get("force", False),
|
||||
scope=data.get("scope", "all"),
|
||||
feature_filter=data.get("feature_filter"),
|
||||
dedupe_mode=data.get("dedupe_mode", "prompt"),
|
||||
similarity_threshold=data.get("similarity_threshold", 0.8),
|
||||
report_format=data.get("report_format", "text"),
|
||||
ci_mode=data.get("ci_mode", False),
|
||||
excluded_paths=data.get("excluded_paths", cls.__dataclass_fields__["excluded_paths"].default_factory()),
|
||||
required_artifacts=data.get("required_artifacts", cls.__dataclass_fields__["required_artifacts"].default_factory()),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def from_env(cls) -> "StandardiseConfig":
|
||||
"""Load configuration from environment variables."""
|
||||
return cls(
|
||||
project_root=Path(os.environ["PRAISON_PROJECT_ROOT"]) if os.environ.get("PRAISON_PROJECT_ROOT") else None,
|
||||
docs_root=Path(os.environ["PRAISON_DOCS_ROOT"]) if os.environ.get("PRAISON_DOCS_ROOT") else None,
|
||||
dry_run=os.environ.get("PRAISON_DRY_RUN", "true").lower() == "true",
|
||||
ci_mode=os.environ.get("CI", "false").lower() == "true",
|
||||
)
|
||||
|
||||
def to_dict(self) -> Dict:
|
||||
"""Convert to dictionary for serialisation."""
|
||||
return {
|
||||
"project_root": str(self.project_root) if self.project_root else None,
|
||||
"docs_root": str(self.docs_root) if self.docs_root else None,
|
||||
"examples_root": str(self.examples_root) if self.examples_root else None,
|
||||
"sdk_root": str(self.sdk_root) if self.sdk_root else None,
|
||||
"cli_root": str(self.cli_root) if self.cli_root else None,
|
||||
"mintlify_config": str(self.mintlify_config) if self.mintlify_config else None,
|
||||
"manifest_dir": str(self.manifest_dir) if self.manifest_dir else None,
|
||||
"dry_run": self.dry_run,
|
||||
"backup": self.backup,
|
||||
"force": self.force,
|
||||
"scope": self.scope,
|
||||
"feature_filter": self.feature_filter,
|
||||
"dedupe_mode": self.dedupe_mode,
|
||||
"similarity_threshold": self.similarity_threshold,
|
||||
"report_format": self.report_format,
|
||||
"ci_mode": self.ci_mode,
|
||||
"excluded_paths": self.excluded_paths,
|
||||
"required_artifacts": self.required_artifacts,
|
||||
}
|
||||
@@ -0,0 +1,221 @@
|
||||
"""
|
||||
Duplicate detection for the FDEP standardisation system.
|
||||
|
||||
Detects duplicates via:
|
||||
- Same slug in multiple locations
|
||||
- High title similarity (>80%)
|
||||
- High code-block overlap (>40%)
|
||||
"""
|
||||
|
||||
import re
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
|
||||
from .config import StandardiseConfig
|
||||
from .discovery import FeatureDiscovery
|
||||
from .models import DuplicateCluster, FeatureSlug
|
||||
|
||||
|
||||
class DedupeDetector:
|
||||
"""Detects duplicate and near-duplicate content."""
|
||||
|
||||
def __init__(self, config: StandardiseConfig, discovery: FeatureDiscovery):
|
||||
self.config = config
|
||||
self.discovery = discovery
|
||||
self._frontmatter_cache: Dict[Path, Dict] = {}
|
||||
|
||||
def detect_all(self) -> List[DuplicateCluster]:
|
||||
"""Detect all duplicate clusters."""
|
||||
clusters = []
|
||||
|
||||
# Detect same-slug duplicates
|
||||
clusters.extend(self._detect_same_slug_duplicates())
|
||||
|
||||
# Detect title similarity duplicates
|
||||
clusters.extend(self._detect_title_duplicates())
|
||||
|
||||
return clusters
|
||||
|
||||
def _detect_same_slug_duplicates(self) -> List[DuplicateCluster]:
|
||||
"""Detect pages with the same slug in different locations."""
|
||||
clusters = []
|
||||
|
||||
all_features = self.discovery.get_all_features()
|
||||
|
||||
for slug in all_features:
|
||||
pages = self.discovery.find_docs_pages(slug)
|
||||
|
||||
if len(pages) > 1:
|
||||
# Determine primary page (prefer features > concepts > cli > sdk)
|
||||
primary = self._select_primary_page(pages)
|
||||
|
||||
clusters.append(DuplicateCluster(
|
||||
slug=slug,
|
||||
pages=pages,
|
||||
similarity_score=1.0, # Exact slug match
|
||||
issue_type="same_slug",
|
||||
recommendation="merge" if len(pages) <= 4 else "review",
|
||||
primary_page=primary,
|
||||
))
|
||||
|
||||
return clusters
|
||||
|
||||
def _detect_title_duplicates(self) -> List[DuplicateCluster]:
|
||||
"""Detect pages with similar titles."""
|
||||
clusters = []
|
||||
|
||||
if not self.config.docs_root or not self.config.docs_root.exists():
|
||||
return clusters
|
||||
|
||||
# Collect all page titles
|
||||
title_to_pages: Dict[str, List[Tuple[Path, str]]] = {}
|
||||
|
||||
for mdx_file in self.config.docs_root.rglob("*.mdx"):
|
||||
# Skip node_modules and other excluded paths
|
||||
if any(excluded in str(mdx_file) for excluded in self.config.excluded_paths):
|
||||
continue
|
||||
|
||||
title = self._extract_title(mdx_file)
|
||||
if title:
|
||||
normalised_title = self._normalise_title(title)
|
||||
if normalised_title not in title_to_pages:
|
||||
title_to_pages[normalised_title] = []
|
||||
title_to_pages[normalised_title].append((mdx_file, title))
|
||||
|
||||
# Find duplicates
|
||||
for normalised_title, pages in title_to_pages.items():
|
||||
if len(pages) > 1:
|
||||
# Check if these are already captured by same-slug detection
|
||||
slugs = set()
|
||||
for page, _ in pages:
|
||||
slug = FeatureSlug.from_path(page, "docs")
|
||||
slugs.add(slug.normalised)
|
||||
|
||||
if len(slugs) > 1:
|
||||
# Different slugs but same title - this is a title duplicate
|
||||
slug = FeatureSlug.from_string(normalised_title)
|
||||
clusters.append(DuplicateCluster(
|
||||
slug=slug,
|
||||
pages=[p for p, _ in pages],
|
||||
similarity_score=0.9,
|
||||
issue_type="title_similarity",
|
||||
recommendation="review",
|
||||
primary_page=pages[0][0],
|
||||
))
|
||||
|
||||
return clusters
|
||||
|
||||
def _extract_title(self, mdx_file: Path) -> Optional[str]:
|
||||
"""Extract title from MDX frontmatter."""
|
||||
if mdx_file in self._frontmatter_cache:
|
||||
return self._frontmatter_cache[mdx_file].get("title")
|
||||
|
||||
try:
|
||||
content = mdx_file.read_text(encoding="utf-8")
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
frontmatter = self._parse_frontmatter(content)
|
||||
self._frontmatter_cache[mdx_file] = frontmatter
|
||||
|
||||
return frontmatter.get("title")
|
||||
|
||||
def _parse_frontmatter(self, content: str) -> Dict:
|
||||
"""Parse YAML frontmatter from MDX content."""
|
||||
frontmatter = {}
|
||||
|
||||
# Check for frontmatter delimiters
|
||||
if not content.startswith("---"):
|
||||
return frontmatter
|
||||
|
||||
# Find end of frontmatter
|
||||
end_match = re.search(r"\n---\s*\n", content[3:])
|
||||
if not end_match:
|
||||
return frontmatter
|
||||
|
||||
frontmatter_text = content[3:end_match.start() + 3]
|
||||
|
||||
# Simple YAML parsing (avoid dependency on PyYAML)
|
||||
for line in frontmatter_text.split("\n"):
|
||||
line = line.strip()
|
||||
if ":" in line:
|
||||
key, value = line.split(":", 1)
|
||||
key = key.strip()
|
||||
value = value.strip().strip('"').strip("'")
|
||||
frontmatter[key] = value
|
||||
|
||||
return frontmatter
|
||||
|
||||
def _normalise_title(self, title: str) -> str:
|
||||
"""Normalise a title for comparison."""
|
||||
# Lowercase, remove special chars, collapse whitespace
|
||||
normalised = title.lower()
|
||||
normalised = re.sub(r"[^a-z0-9\s]", "", normalised)
|
||||
normalised = re.sub(r"\s+", " ", normalised).strip()
|
||||
return normalised
|
||||
|
||||
def _select_primary_page(self, pages: List[Path]) -> Optional[Path]:
|
||||
"""Select the primary page from a list of duplicates."""
|
||||
# Priority: features > concepts > cli > sdk
|
||||
priority_order = ["features", "concepts", "cli", "sdk"]
|
||||
|
||||
for priority_dir in priority_order:
|
||||
for page in pages:
|
||||
if f"/{priority_dir}/" in str(page) or f"\\{priority_dir}\\" in str(page):
|
||||
return page
|
||||
|
||||
# Default to first page
|
||||
return pages[0] if pages else None
|
||||
|
||||
def calculate_similarity(self, text1: str, text2: str) -> float:
|
||||
"""Calculate similarity between two texts using Levenshtein ratio."""
|
||||
if not text1 or not text2:
|
||||
return 0.0
|
||||
|
||||
# Simple character-level similarity
|
||||
len1, len2 = len(text1), len(text2)
|
||||
if len1 == 0 and len2 == 0:
|
||||
return 1.0
|
||||
if len1 == 0 or len2 == 0:
|
||||
return 0.0
|
||||
|
||||
# Use set-based similarity for efficiency
|
||||
set1 = set(text1.lower().split())
|
||||
set2 = set(text2.lower().split())
|
||||
|
||||
intersection = len(set1 & set2)
|
||||
union = len(set1 | set2)
|
||||
|
||||
if union == 0:
|
||||
return 0.0
|
||||
|
||||
return intersection / union
|
||||
|
||||
def get_naming_inconsistencies(self) -> List[Tuple[Path, Path, str]]:
|
||||
"""Find naming inconsistencies (e.g., handoff.mdx vs handoffs.mdx)."""
|
||||
inconsistencies = []
|
||||
|
||||
if not self.config.docs_root or not self.config.docs_root.exists():
|
||||
return inconsistencies
|
||||
|
||||
# Check each docs directory
|
||||
for doc_dir in ["concepts", "features", "cli"]:
|
||||
dir_path = self.config.docs_root / doc_dir
|
||||
if not dir_path.exists():
|
||||
continue
|
||||
|
||||
# Get all MDX files
|
||||
mdx_files = list(dir_path.glob("*.mdx"))
|
||||
file_stems = {f.stem.lower(): f for f in mdx_files}
|
||||
|
||||
# Check for singular/plural pairs
|
||||
from .models import SINGULAR_PLURAL_MAP
|
||||
for singular, plural in SINGULAR_PLURAL_MAP.items():
|
||||
if singular in file_stems and plural in file_stems:
|
||||
inconsistencies.append((
|
||||
file_stems[singular],
|
||||
file_stems[plural],
|
||||
f"Both {singular}.mdx and {plural}.mdx exist in {doc_dir}/",
|
||||
))
|
||||
|
||||
return inconsistencies
|
||||
@@ -0,0 +1,319 @@
|
||||
"""
|
||||
Feature discovery for the FDEP standardisation system.
|
||||
|
||||
Discovers features from:
|
||||
- SDK modules (praisonaiagents/*)
|
||||
- CLI features (praisonai/cli/features/*)
|
||||
- Docs pages (docs/**)
|
||||
- Examples (examples/python/**)
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Set
|
||||
|
||||
from .config import StandardiseConfig
|
||||
from .models import FeatureSlug
|
||||
|
||||
|
||||
class FeatureDiscovery:
|
||||
"""Discovers features from various sources in the codebase."""
|
||||
|
||||
# Directories to skip during discovery
|
||||
SKIP_DIRS = {
|
||||
"__pycache__", ".git", ".venv", "venv", "node_modules",
|
||||
"dist", "build", ".pytest_cache", ".mypy_cache",
|
||||
}
|
||||
|
||||
# Files to skip
|
||||
SKIP_FILES = {"__init__.py", "base.py", "utils.py", "helpers.py"}
|
||||
|
||||
def __init__(self, config: StandardiseConfig):
|
||||
self.config = config
|
||||
self._sdk_features: Optional[Set[FeatureSlug]] = None
|
||||
self._cli_features: Optional[Set[FeatureSlug]] = None
|
||||
self._docs_features: Optional[Set[FeatureSlug]] = None
|
||||
self._example_features: Optional[Set[FeatureSlug]] = None
|
||||
|
||||
def discover_all(self) -> Dict[str, Set[FeatureSlug]]:
|
||||
"""Discover features from all sources."""
|
||||
return {
|
||||
"sdk": self.discover_sdk_features(),
|
||||
"cli": self.discover_cli_features(),
|
||||
"docs": self.discover_docs_features(),
|
||||
"examples": self.discover_example_features(),
|
||||
}
|
||||
|
||||
def get_all_features(self) -> Set[FeatureSlug]:
|
||||
"""Get union of all discovered features."""
|
||||
all_sources = self.discover_all()
|
||||
result: Set[FeatureSlug] = set()
|
||||
for features in all_sources.values():
|
||||
result.update(features)
|
||||
return result
|
||||
|
||||
def discover_sdk_features(self) -> Set[FeatureSlug]:
|
||||
"""Discover features from SDK modules."""
|
||||
if self._sdk_features is not None:
|
||||
return self._sdk_features
|
||||
|
||||
self._sdk_features = set()
|
||||
|
||||
if not self.config.sdk_root or not self.config.sdk_root.exists():
|
||||
return self._sdk_features
|
||||
|
||||
# Each top-level directory in SDK is a feature module
|
||||
for item in self.config.sdk_root.iterdir():
|
||||
if not item.is_dir():
|
||||
continue
|
||||
if item.name in self.SKIP_DIRS:
|
||||
continue
|
||||
if item.name.startswith("."):
|
||||
continue
|
||||
|
||||
slug = FeatureSlug.from_path(item, "sdk")
|
||||
if slug.is_valid:
|
||||
self._sdk_features.add(slug)
|
||||
|
||||
return self._sdk_features
|
||||
|
||||
def discover_cli_features(self) -> Set[FeatureSlug]:
|
||||
"""Discover features from CLI feature files."""
|
||||
if self._cli_features is not None:
|
||||
return self._cli_features
|
||||
|
||||
self._cli_features = set()
|
||||
|
||||
if not self.config.cli_root or not self.config.cli_root.exists():
|
||||
return self._cli_features
|
||||
|
||||
# Check features directory
|
||||
features_dir = self.config.cli_root / "features"
|
||||
if features_dir.exists():
|
||||
for item in features_dir.iterdir():
|
||||
if not item.is_file():
|
||||
continue
|
||||
if item.suffix != ".py":
|
||||
continue
|
||||
if item.name in self.SKIP_FILES:
|
||||
continue
|
||||
|
||||
slug = FeatureSlug.from_path(item, "cli")
|
||||
if slug.is_valid:
|
||||
self._cli_features.add(slug)
|
||||
|
||||
# Check commands directory
|
||||
commands_dir = self.config.cli_root / "commands"
|
||||
if commands_dir.exists():
|
||||
for item in commands_dir.iterdir():
|
||||
if not item.is_file():
|
||||
continue
|
||||
if item.suffix != ".py":
|
||||
continue
|
||||
if item.name in self.SKIP_FILES:
|
||||
continue
|
||||
|
||||
slug = FeatureSlug.from_path(item, "cli")
|
||||
if slug.is_valid:
|
||||
self._cli_features.add(slug)
|
||||
|
||||
return self._cli_features
|
||||
|
||||
def discover_docs_features(self) -> Set[FeatureSlug]:
|
||||
"""Discover features from docs pages."""
|
||||
if self._docs_features is not None:
|
||||
return self._docs_features
|
||||
|
||||
self._docs_features = set()
|
||||
|
||||
if not self.config.docs_root or not self.config.docs_root.exists():
|
||||
return self._docs_features
|
||||
|
||||
# Scan key docs directories
|
||||
docs_dirs = ["concepts", "features", "cli", "sdk"]
|
||||
|
||||
for dir_name in docs_dirs:
|
||||
dir_path = self.config.docs_root / dir_name
|
||||
if not dir_path.exists():
|
||||
continue
|
||||
|
||||
self._scan_docs_directory(dir_path)
|
||||
|
||||
return self._docs_features
|
||||
|
||||
def _scan_docs_directory(self, directory: Path, depth: int = 0):
|
||||
"""Recursively scan a docs directory for feature slugs."""
|
||||
if depth > 3: # Limit recursion depth
|
||||
return
|
||||
|
||||
for item in directory.iterdir():
|
||||
if item.name in self.SKIP_DIRS:
|
||||
continue
|
||||
if item.name.startswith("."):
|
||||
continue
|
||||
|
||||
if item.is_file() and item.suffix == ".mdx":
|
||||
slug = FeatureSlug.from_path(item, "docs")
|
||||
if slug.is_valid:
|
||||
self._docs_features.add(slug)
|
||||
elif item.is_dir():
|
||||
# Directory name itself might be a feature
|
||||
slug = FeatureSlug.from_path(item, "docs")
|
||||
if slug.is_valid:
|
||||
self._docs_features.add(slug)
|
||||
# Recurse into subdirectory
|
||||
self._scan_docs_directory(item, depth + 1)
|
||||
|
||||
def discover_example_features(self) -> Set[FeatureSlug]:
|
||||
"""Discover features from examples."""
|
||||
if self._example_features is not None:
|
||||
return self._example_features
|
||||
|
||||
self._example_features = set()
|
||||
|
||||
if not self.config.examples_root or not self.config.examples_root.exists():
|
||||
return self._example_features
|
||||
|
||||
# Each top-level directory in examples is a feature
|
||||
for item in self.config.examples_root.iterdir():
|
||||
if not item.is_dir():
|
||||
continue
|
||||
if item.name in self.SKIP_DIRS:
|
||||
continue
|
||||
if item.name.startswith("."):
|
||||
continue
|
||||
|
||||
slug = FeatureSlug.from_path(item, "examples")
|
||||
if slug.is_valid:
|
||||
self._example_features.add(slug)
|
||||
|
||||
return self._example_features
|
||||
|
||||
def get_feature_sources(self, slug: FeatureSlug) -> Dict[str, bool]:
|
||||
"""Get which sources contain a given feature."""
|
||||
return {
|
||||
"sdk": slug in self.discover_sdk_features(),
|
||||
"cli": slug in self.discover_cli_features(),
|
||||
"docs": slug in self.discover_docs_features(),
|
||||
"examples": slug in self.discover_example_features(),
|
||||
}
|
||||
|
||||
def find_docs_pages(self, slug: FeatureSlug) -> List[Path]:
|
||||
"""Find all docs pages for a given feature slug."""
|
||||
pages = []
|
||||
|
||||
if not self.config.docs_root or not self.config.docs_root.exists():
|
||||
return pages
|
||||
|
||||
# Search in key directories
|
||||
search_dirs = [
|
||||
self.config.docs_root / "concepts",
|
||||
self.config.docs_root / "features",
|
||||
self.config.docs_root / "cli",
|
||||
]
|
||||
|
||||
# Also search SDK docs
|
||||
sdk_docs = self.config.docs_root / "sdk" / "praisonaiagents"
|
||||
if sdk_docs.exists():
|
||||
search_dirs.append(sdk_docs)
|
||||
|
||||
slug_str = slug.normalised
|
||||
slug_variants = {slug_str, slug_str.replace("-", "_")}
|
||||
|
||||
# Add singular/plural variants
|
||||
from .models import SINGULAR_PLURAL_MAP
|
||||
for singular, plural in SINGULAR_PLURAL_MAP.items():
|
||||
if slug_str == plural:
|
||||
slug_variants.add(singular)
|
||||
elif slug_str == singular:
|
||||
slug_variants.add(plural)
|
||||
|
||||
for search_dir in search_dirs:
|
||||
if not search_dir.exists():
|
||||
continue
|
||||
|
||||
self._find_pages_recursive(search_dir, slug_variants, pages)
|
||||
|
||||
return pages
|
||||
|
||||
def _find_pages_recursive(self, directory: Path, slug_variants: Set[str],
|
||||
pages: List[Path], depth: int = 0):
|
||||
"""Recursively find pages matching slug variants."""
|
||||
if depth > 4:
|
||||
return
|
||||
|
||||
for item in directory.iterdir():
|
||||
if item.name in self.SKIP_DIRS:
|
||||
continue
|
||||
|
||||
if item.is_file() and item.suffix == ".mdx":
|
||||
stem = item.stem.lower().replace("_", "-")
|
||||
if stem in slug_variants:
|
||||
pages.append(item)
|
||||
elif item.is_dir():
|
||||
dir_name = item.name.lower().replace("_", "-")
|
||||
if dir_name in slug_variants:
|
||||
# Check for index or main file in this directory
|
||||
for mdx_file in item.glob("*.mdx"):
|
||||
pages.append(mdx_file)
|
||||
else:
|
||||
self._find_pages_recursive(item, slug_variants, pages, depth + 1)
|
||||
|
||||
def find_examples(self, slug: FeatureSlug) -> List[Path]:
|
||||
"""Find all example files for a given feature slug."""
|
||||
examples = []
|
||||
|
||||
if not self.config.examples_root or not self.config.examples_root.exists():
|
||||
return examples
|
||||
|
||||
slug_str = slug.normalised
|
||||
slug_variants = {slug_str, slug_str.replace("-", "_")}
|
||||
|
||||
# Check for feature directory
|
||||
for variant in slug_variants:
|
||||
feature_dir = self.config.examples_root / variant
|
||||
if feature_dir.exists() and feature_dir.is_dir():
|
||||
for py_file in feature_dir.glob("*.py"):
|
||||
examples.append(py_file)
|
||||
|
||||
return examples
|
||||
|
||||
def get_sdk_module_path(self, slug: FeatureSlug) -> Optional[Path]:
|
||||
"""Get the SDK module path for a feature."""
|
||||
if not self.config.sdk_root or not self.config.sdk_root.exists():
|
||||
return None
|
||||
|
||||
slug_str = slug.normalised
|
||||
variants = [slug_str, slug_str.replace("-", "_")]
|
||||
|
||||
for variant in variants:
|
||||
module_path = self.config.sdk_root / variant
|
||||
if module_path.exists() and module_path.is_dir():
|
||||
return module_path
|
||||
|
||||
return None
|
||||
|
||||
def get_cli_feature_path(self, slug: FeatureSlug) -> Optional[Path]:
|
||||
"""Get the CLI feature file path for a feature."""
|
||||
if not self.config.cli_root or not self.config.cli_root.exists():
|
||||
return None
|
||||
|
||||
slug_str = slug.normalised
|
||||
variants = [slug_str, slug_str.replace("-", "_")]
|
||||
|
||||
# Check features directory
|
||||
features_dir = self.config.cli_root / "features"
|
||||
if features_dir.exists():
|
||||
for variant in variants:
|
||||
feature_path = features_dir / f"{variant}.py"
|
||||
if feature_path.exists():
|
||||
return feature_path
|
||||
|
||||
# Check commands directory
|
||||
commands_dir = self.config.cli_root / "commands"
|
||||
if commands_dir.exists():
|
||||
for variant in variants:
|
||||
command_path = commands_dir / f"{variant}.py"
|
||||
if command_path.exists():
|
||||
return command_path
|
||||
|
||||
return None
|
||||
@@ -0,0 +1,263 @@
|
||||
"""
|
||||
Drift detection for the FDEP standardisation system.
|
||||
|
||||
Detects drift between:
|
||||
- SDK exports vs SDK docs
|
||||
- CLI help/flags vs CLI docs
|
||||
"""
|
||||
|
||||
import ast
|
||||
import re
|
||||
from pathlib import Path
|
||||
from typing import List, Optional, Set
|
||||
|
||||
from .config import StandardiseConfig
|
||||
from .discovery import FeatureDiscovery
|
||||
from .models import DriftItem, DriftReport, FeatureSlug
|
||||
|
||||
|
||||
class DriftDetector:
|
||||
"""Detects drift between code and documentation."""
|
||||
|
||||
def __init__(self, config: StandardiseConfig, discovery: FeatureDiscovery):
|
||||
self.config = config
|
||||
self.discovery = discovery
|
||||
|
||||
def detect_all(self) -> List[DriftReport]:
|
||||
"""Detect drift for all features."""
|
||||
reports = []
|
||||
|
||||
all_features = self.discovery.get_all_features()
|
||||
|
||||
for slug in all_features:
|
||||
report = self.detect_feature_drift(slug)
|
||||
if report.has_drift:
|
||||
reports.append(report)
|
||||
|
||||
return reports
|
||||
|
||||
def detect_feature_drift(self, slug: FeatureSlug) -> DriftReport:
|
||||
"""Detect drift for a single feature."""
|
||||
sdk_drift = self._detect_sdk_drift(slug)
|
||||
cli_drift = self._detect_cli_drift(slug)
|
||||
|
||||
return DriftReport(
|
||||
slug=slug,
|
||||
sdk_drift=sdk_drift,
|
||||
cli_drift=cli_drift,
|
||||
)
|
||||
|
||||
def _detect_sdk_drift(self, slug: FeatureSlug) -> List[DriftItem]:
|
||||
"""Detect drift between SDK module and SDK docs."""
|
||||
drift_items = []
|
||||
|
||||
# Get SDK module path
|
||||
sdk_module = self.discovery.get_sdk_module_path(slug)
|
||||
if not sdk_module or not sdk_module.exists():
|
||||
return drift_items
|
||||
|
||||
# Extract public exports from SDK module
|
||||
sdk_exports = self._extract_sdk_exports(sdk_module)
|
||||
|
||||
# Extract documented items from SDK docs
|
||||
sdk_docs = self._get_sdk_docs_path(slug)
|
||||
if sdk_docs:
|
||||
documented_items = self._extract_documented_items(sdk_docs)
|
||||
else:
|
||||
documented_items = set()
|
||||
|
||||
# Find items in SDK but not in docs
|
||||
for export in sdk_exports:
|
||||
if export not in documented_items:
|
||||
drift_items.append(DriftItem(
|
||||
name=export,
|
||||
source="sdk",
|
||||
missing_in="docs",
|
||||
item_type="class" if export[0].isupper() else "function",
|
||||
))
|
||||
|
||||
# Find items in docs but not in SDK
|
||||
for item in documented_items:
|
||||
if item not in sdk_exports:
|
||||
drift_items.append(DriftItem(
|
||||
name=item,
|
||||
source="docs",
|
||||
missing_in="sdk",
|
||||
item_type="class" if item[0].isupper() else "function",
|
||||
))
|
||||
|
||||
return drift_items
|
||||
|
||||
def _detect_cli_drift(self, slug: FeatureSlug) -> List[DriftItem]:
|
||||
"""Detect drift between CLI feature and CLI docs."""
|
||||
drift_items = []
|
||||
|
||||
# Get CLI feature path
|
||||
cli_feature = self.discovery.get_cli_feature_path(slug)
|
||||
if not cli_feature or not cli_feature.exists():
|
||||
return drift_items
|
||||
|
||||
# Extract CLI flags/commands from code
|
||||
cli_flags = self._extract_cli_flags(cli_feature)
|
||||
|
||||
# Extract documented flags from CLI docs
|
||||
cli_docs = self._get_cli_docs_path(slug)
|
||||
if cli_docs:
|
||||
documented_flags = self._extract_documented_flags(cli_docs)
|
||||
else:
|
||||
documented_flags = set()
|
||||
|
||||
# Find flags in code but not in docs
|
||||
for flag in cli_flags:
|
||||
if flag not in documented_flags:
|
||||
drift_items.append(DriftItem(
|
||||
name=flag,
|
||||
source="cli",
|
||||
missing_in="docs",
|
||||
item_type="flag",
|
||||
))
|
||||
|
||||
return drift_items
|
||||
|
||||
def _extract_sdk_exports(self, module_path: Path) -> Set[str]:
|
||||
"""Extract public exports from an SDK module."""
|
||||
exports = set()
|
||||
|
||||
# Check __init__.py for __all__
|
||||
init_file = module_path / "__init__.py"
|
||||
if init_file.exists():
|
||||
try:
|
||||
content = init_file.read_text(encoding="utf-8")
|
||||
# Look for __all__ = [...]
|
||||
all_match = re.search(r"__all__\s*=\s*\[(.*?)\]", content, re.DOTALL)
|
||||
if all_match:
|
||||
items = re.findall(r'["\'](\w+)["\']', all_match.group(1))
|
||||
exports.update(items)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Also scan for public classes and functions
|
||||
for py_file in module_path.glob("*.py"):
|
||||
if py_file.name.startswith("_"):
|
||||
continue
|
||||
|
||||
try:
|
||||
content = py_file.read_text(encoding="utf-8")
|
||||
tree = ast.parse(content)
|
||||
|
||||
for node in ast.walk(tree):
|
||||
if isinstance(node, ast.ClassDef):
|
||||
if not node.name.startswith("_"):
|
||||
exports.add(node.name)
|
||||
elif isinstance(node, ast.FunctionDef):
|
||||
if not node.name.startswith("_"):
|
||||
exports.add(node.name)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return exports
|
||||
|
||||
def _extract_cli_flags(self, cli_file: Path) -> Set[str]:
|
||||
"""Extract CLI flags from a CLI feature file."""
|
||||
flags = set()
|
||||
|
||||
try:
|
||||
content = cli_file.read_text(encoding="utf-8")
|
||||
|
||||
# Look for click.option or argparse add_argument patterns
|
||||
# click: @click.option("--flag-name", ...)
|
||||
click_flags = re.findall(r'@click\.option\(["\'](-{1,2}[\w-]+)["\']', content)
|
||||
flags.update(click_flags)
|
||||
|
||||
# argparse: parser.add_argument("--flag-name", ...)
|
||||
argparse_flags = re.findall(r'add_argument\(["\'](-{1,2}[\w-]+)["\']', content)
|
||||
flags.update(argparse_flags)
|
||||
|
||||
# Also look for flag definitions in strings
|
||||
string_flags = re.findall(r'["\'](-{2}[\w-]+)["\']', content)
|
||||
flags.update(string_flags)
|
||||
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return flags
|
||||
|
||||
def _extract_documented_items(self, docs_path: Path) -> Set[str]:
|
||||
"""Extract documented class/function names from docs."""
|
||||
items = set()
|
||||
|
||||
try:
|
||||
content = docs_path.read_text(encoding="utf-8")
|
||||
|
||||
# Look for class/function references in code blocks
|
||||
# Pattern: `ClassName` or `function_name`
|
||||
backtick_items = re.findall(r'`(\w+)`', content)
|
||||
items.update(backtick_items)
|
||||
|
||||
# Look for headings that might be class/function names
|
||||
heading_items = re.findall(r'^#{1,3}\s+`?(\w+)`?', content, re.MULTILINE)
|
||||
items.update(heading_items)
|
||||
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return items
|
||||
|
||||
def _extract_documented_flags(self, docs_path: Path) -> Set[str]:
|
||||
"""Extract documented CLI flags from docs."""
|
||||
flags = set()
|
||||
|
||||
try:
|
||||
content = docs_path.read_text(encoding="utf-8")
|
||||
|
||||
# Look for flags in code blocks and inline code
|
||||
flag_patterns = re.findall(r'`(-{1,2}[\w-]+)`', content)
|
||||
flags.update(flag_patterns)
|
||||
|
||||
# Also look for flags in plain text
|
||||
text_flags = re.findall(r'\s(-{2}[\w-]+)\s', content)
|
||||
flags.update(text_flags)
|
||||
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return flags
|
||||
|
||||
def _get_sdk_docs_path(self, slug: FeatureSlug) -> Optional[Path]:
|
||||
"""Get the SDK docs path for a feature."""
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
|
||||
sdk_docs = self.config.docs_root / "sdk" / "praisonaiagents"
|
||||
if not sdk_docs.exists():
|
||||
return None
|
||||
|
||||
slug_str = slug.normalised
|
||||
variants = [slug_str, slug_str.replace("-", "_")]
|
||||
|
||||
for variant in variants:
|
||||
module_dir = sdk_docs / variant
|
||||
if module_dir.exists():
|
||||
for mdx_file in module_dir.glob("*.mdx"):
|
||||
return mdx_file
|
||||
|
||||
return None
|
||||
|
||||
def _get_cli_docs_path(self, slug: FeatureSlug) -> Optional[Path]:
|
||||
"""Get the CLI docs path for a feature."""
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
|
||||
cli_docs = self.config.docs_root / "cli"
|
||||
if not cli_docs.exists():
|
||||
return None
|
||||
|
||||
slug_str = slug.normalised
|
||||
variants = [slug_str, slug_str.replace("-", "_")]
|
||||
|
||||
for variant in variants:
|
||||
path = cli_docs / f"{variant}.mdx"
|
||||
if path.exists():
|
||||
return path
|
||||
|
||||
return None
|
||||
@@ -0,0 +1,270 @@
|
||||
"""
|
||||
Main standardisation engine for the FDEP system.
|
||||
|
||||
Orchestrates all standardisation operations:
|
||||
- Discovery
|
||||
- Validation
|
||||
- Dedupe detection
|
||||
- Drift detection
|
||||
- Report generation
|
||||
- Fix application
|
||||
"""
|
||||
|
||||
import shutil
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from .config import StandardiseConfig
|
||||
from .dedupe import DedupeDetector
|
||||
from .discovery import FeatureDiscovery
|
||||
from .drift import DriftDetector
|
||||
from .models import (
|
||||
ArtifactType,
|
||||
FeatureSlug,
|
||||
IssueType,
|
||||
StandardiseIssue,
|
||||
StandardiseReport,
|
||||
)
|
||||
from .reports import ReportGenerator
|
||||
from .templates import TemplateGenerator
|
||||
from .validator import ArtifactValidator
|
||||
|
||||
|
||||
class StandardiseEngine:
|
||||
"""Main engine for standardisation operations."""
|
||||
|
||||
def __init__(self, config: Optional[StandardiseConfig] = None):
|
||||
self.config = config or StandardiseConfig()
|
||||
self.discovery = FeatureDiscovery(self.config)
|
||||
self.validator = ArtifactValidator(self.config, self.discovery)
|
||||
self.dedupe = DedupeDetector(self.config, self.discovery)
|
||||
self.drift = DriftDetector(self.config, self.discovery)
|
||||
self.templates = TemplateGenerator()
|
||||
self.reports = ReportGenerator()
|
||||
|
||||
def check(self) -> StandardiseReport:
|
||||
"""Run a full standardisation check and return a report."""
|
||||
timestamp = datetime.now().isoformat()
|
||||
|
||||
# Discover features
|
||||
all_features = self.discovery.get_all_features()
|
||||
|
||||
# Count docs and examples
|
||||
docs_count = self._count_docs()
|
||||
examples_count = self._count_examples()
|
||||
|
||||
# Validate artifacts
|
||||
validation_results = self.validator.validate_all()
|
||||
missing_artifacts = self.validator.get_missing_artifacts()
|
||||
|
||||
# Detect duplicates
|
||||
duplicates = self.dedupe.detect_all()
|
||||
|
||||
# Detect naming inconsistencies
|
||||
naming_issues = self.dedupe.get_naming_inconsistencies()
|
||||
|
||||
# Detect drift
|
||||
drift_reports = self.drift.detect_all()
|
||||
|
||||
# Compile issues
|
||||
issues = []
|
||||
|
||||
# Add naming inconsistency issues
|
||||
for path1, path2, message in naming_issues:
|
||||
issues.append(StandardiseIssue(
|
||||
issue_type=IssueType.NAMING_INCONSISTENCY,
|
||||
slug=None,
|
||||
path=path1,
|
||||
message=message,
|
||||
severity="warning",
|
||||
auto_fixable=True,
|
||||
fix_action=f"rename {path1} or {path2}",
|
||||
))
|
||||
|
||||
# Add drift issues
|
||||
for drift_report in drift_reports:
|
||||
for item in drift_report.sdk_drift:
|
||||
issues.append(StandardiseIssue(
|
||||
issue_type=IssueType.DRIFT_SDK_DOCS,
|
||||
slug=drift_report.slug,
|
||||
path=None,
|
||||
message=f"{item.name} in {item.source} but missing in {item.missing_in}",
|
||||
severity="info",
|
||||
auto_fixable=False,
|
||||
))
|
||||
for item in drift_report.cli_drift:
|
||||
issues.append(StandardiseIssue(
|
||||
issue_type=IssueType.DRIFT_CLI_DOCS,
|
||||
slug=drift_report.slug,
|
||||
path=None,
|
||||
message=f"{item.name} in {item.source} but missing in {item.missing_in}",
|
||||
severity="info",
|
||||
auto_fixable=False,
|
||||
))
|
||||
|
||||
return StandardiseReport(
|
||||
timestamp=timestamp,
|
||||
features_scanned=len(all_features),
|
||||
docs_pages=docs_count,
|
||||
examples_count=examples_count,
|
||||
issues=issues,
|
||||
duplicates=duplicates,
|
||||
missing_artifacts=missing_artifacts,
|
||||
drift_reports=drift_reports,
|
||||
validation_results=list(validation_results.values()),
|
||||
)
|
||||
|
||||
def report(self, format: str = "text") -> str:
|
||||
"""Generate a report in the specified format."""
|
||||
report = self.check()
|
||||
return self.reports.generate(report, format)
|
||||
|
||||
def fix(self, feature: Optional[str] = None,
|
||||
apply: bool = False) -> Dict[str, List[str]]:
|
||||
"""
|
||||
Fix standardisation issues.
|
||||
|
||||
Args:
|
||||
feature: Specific feature slug to fix (None = all)
|
||||
apply: Actually apply changes (False = dry-run)
|
||||
|
||||
Returns:
|
||||
Dict with 'planned' and 'applied' actions
|
||||
"""
|
||||
actions = {"planned": [], "applied": []}
|
||||
|
||||
# Get current state
|
||||
report = self.check()
|
||||
|
||||
# Plan fixes for missing artifacts
|
||||
for slug_str, missing in report.missing_artifacts.items():
|
||||
if feature and slug_str != feature:
|
||||
continue
|
||||
|
||||
slug = FeatureSlug.from_string(slug_str)
|
||||
|
||||
for artifact_type in missing:
|
||||
path = self.templates.get_expected_path(
|
||||
slug, artifact_type,
|
||||
docs_root=self.config.docs_root,
|
||||
examples_root=self.config.examples_root,
|
||||
)
|
||||
|
||||
if path:
|
||||
action = f"CREATE {path}"
|
||||
actions["planned"].append(action)
|
||||
|
||||
if apply and not self.config.dry_run:
|
||||
self._create_artifact(slug, artifact_type, path)
|
||||
actions["applied"].append(action)
|
||||
|
||||
# Plan fixes for naming inconsistencies
|
||||
naming_issues = self.dedupe.get_naming_inconsistencies()
|
||||
for path1, path2, message in naming_issues:
|
||||
if feature:
|
||||
slug1 = FeatureSlug.from_path(path1, "docs")
|
||||
slug2 = FeatureSlug.from_path(path2, "docs")
|
||||
if slug1.normalised != feature and slug2.normalised != feature:
|
||||
continue
|
||||
|
||||
# Prefer plural form
|
||||
if "singular" in str(path1).lower() or len(path1.stem) < len(path2.stem):
|
||||
action = f"RENAME {path1} -> deprecated, keep {path2}"
|
||||
else:
|
||||
action = f"RENAME {path2} -> deprecated, keep {path1}"
|
||||
actions["planned"].append(action)
|
||||
|
||||
return actions
|
||||
|
||||
def init(self, feature: str) -> Dict[str, str]:
|
||||
"""
|
||||
Initialise a new feature with all required artifacts.
|
||||
|
||||
Args:
|
||||
feature: Feature slug to initialise
|
||||
|
||||
Returns:
|
||||
Dict mapping artifact type to created path
|
||||
"""
|
||||
created = {}
|
||||
slug = FeatureSlug.from_string(feature)
|
||||
|
||||
if not slug.is_valid:
|
||||
raise ValueError(f"Invalid feature slug: {slug.validation_error}")
|
||||
|
||||
for artifact_type in ArtifactType:
|
||||
if artifact_type == ArtifactType.MANIFEST:
|
||||
continue
|
||||
|
||||
path = self.templates.get_expected_path(
|
||||
slug, artifact_type,
|
||||
docs_root=self.config.docs_root,
|
||||
examples_root=self.config.examples_root,
|
||||
)
|
||||
|
||||
if path and not path.exists():
|
||||
if not self.config.dry_run:
|
||||
self._create_artifact(slug, artifact_type, path)
|
||||
created[artifact_type.value] = str(path)
|
||||
|
||||
return created
|
||||
|
||||
def _create_artifact(self, slug: FeatureSlug, artifact_type: ArtifactType,
|
||||
path: Path) -> None:
|
||||
"""Create an artifact file."""
|
||||
# Backup if exists
|
||||
if path.exists() and self.config.backup:
|
||||
self._backup_file(path)
|
||||
|
||||
# Create parent directories
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Generate content
|
||||
content = self.templates.generate(slug, artifact_type)
|
||||
|
||||
# Write file
|
||||
path.write_text(content, encoding="utf-8")
|
||||
|
||||
def _backup_file(self, path: Path) -> Path:
|
||||
"""Create a backup of a file."""
|
||||
if not self.config.project_root:
|
||||
return path
|
||||
|
||||
backup_dir = self.config.project_root / ".praison" / "backups"
|
||||
backup_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
backup_name = f"{path.stem}_{timestamp}{path.suffix}"
|
||||
backup_path = backup_dir / backup_name
|
||||
|
||||
shutil.copy2(path, backup_path)
|
||||
return backup_path
|
||||
|
||||
def _count_docs(self) -> int:
|
||||
"""Count total docs pages."""
|
||||
if not self.config.docs_root or not self.config.docs_root.exists():
|
||||
return 0
|
||||
|
||||
count = 0
|
||||
for mdx_file in self.config.docs_root.rglob("*.mdx"):
|
||||
if not any(excluded in str(mdx_file) for excluded in self.config.excluded_paths):
|
||||
count += 1
|
||||
return count
|
||||
|
||||
def _count_examples(self) -> int:
|
||||
"""Count total example files."""
|
||||
if not self.config.examples_root or not self.config.examples_root.exists():
|
||||
return 0
|
||||
|
||||
count = 0
|
||||
for py_file in self.config.examples_root.rglob("*.py"):
|
||||
if not any(excluded in str(py_file) for excluded in self.config.excluded_paths):
|
||||
count += 1
|
||||
return count
|
||||
|
||||
def get_exit_code(self, report: StandardiseReport) -> int:
|
||||
"""Get CI exit code based on report."""
|
||||
if report.has_issues:
|
||||
return 1 # Issues found
|
||||
return 0 # No issues
|
||||
@@ -0,0 +1,674 @@
|
||||
"""
|
||||
Enhanced templates for the FDEP standardisation system.
|
||||
|
||||
Based on analysis of existing PraisonAI documentation best practices:
|
||||
- Progressive disclosure (simple first, advanced later)
|
||||
- Mermaid diagrams for concepts
|
||||
- CodeGroup/Tabs for multiple examples
|
||||
- Consistent structure across page types
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from .models import ArtifactType, FeatureSlug
|
||||
|
||||
|
||||
# Template constants based on existing doc analysis
|
||||
CONCEPT_TEMPLATE = '''---
|
||||
title: "{name}"
|
||||
sidebarTitle: "{name}"
|
||||
description: "{description}"
|
||||
icon: "{icon}"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
{name} provides [brief description of what this feature does and why it exists].
|
||||
|
||||
```mermaid
|
||||
flowchart LR
|
||||
subgraph Input
|
||||
A[User Request]
|
||||
end
|
||||
|
||||
subgraph {name}
|
||||
B[Process] --> C[Validate]
|
||||
C --> D[Execute]
|
||||
end
|
||||
|
||||
subgraph Output
|
||||
E[Result]
|
||||
end
|
||||
|
||||
A --> B
|
||||
D --> E
|
||||
|
||||
style B fill:#189AB4,color:#fff
|
||||
style C fill:#2E8B57,color:#fff
|
||||
style D fill:#8B0000,color:#fff
|
||||
```
|
||||
|
||||
## Types of {name}
|
||||
|
||||
<CardGroup cols={{2}}>
|
||||
<Card title="Type 1" icon="code">
|
||||
Description of first type
|
||||
</Card>
|
||||
<Card title="Type 2" icon="brain">
|
||||
Description of second type
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent, Task
|
||||
|
||||
# Basic {slug} usage
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
# Configure {slug} here
|
||||
)
|
||||
|
||||
result = agent.start("Your prompt here")
|
||||
print(result)
|
||||
```
|
||||
|
||||
## When to Use
|
||||
|
||||
| Use Case | Recommendation |
|
||||
|----------|----------------|
|
||||
| Simple tasks | Use basic configuration |
|
||||
| Complex workflows | Use advanced patterns |
|
||||
| Production | Enable all safety features |
|
||||
|
||||
## Related Features
|
||||
|
||||
- [Related Feature 1](/docs/concepts/related1)
|
||||
- [Related Feature 2](/docs/concepts/related2)
|
||||
'''
|
||||
|
||||
FEATURE_TEMPLATE = '''---
|
||||
title: "{name}"
|
||||
description: "How to use {slug} in PraisonAI"
|
||||
icon: "code"
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
<CodeGroup>
|
||||
```python Basic Usage
|
||||
from praisonaiagents import Agent, Task
|
||||
|
||||
# Simple {slug} example
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
# {slug} configuration
|
||||
)
|
||||
|
||||
result = agent.start("Hello!")
|
||||
print(result)
|
||||
```
|
||||
|
||||
```python Advanced Usage
|
||||
from praisonaiagents import Agent, Task, Agents
|
||||
|
||||
# Advanced {slug} with multiple agents
|
||||
agent1 = Agent(name="Agent1", instructions="First agent")
|
||||
agent2 = Agent(name="Agent2", instructions="Second agent")
|
||||
|
||||
task = Task(
|
||||
description="Complex task using {slug}",
|
||||
agent=agent1,
|
||||
)
|
||||
|
||||
agents = Agents(agents=[agent1, agent2], tasks=[task])
|
||||
result = agents.start()
|
||||
```
|
||||
</CodeGroup>
|
||||
|
||||
## Configuration Options
|
||||
|
||||
<Tabs>
|
||||
<Tab title="Basic">
|
||||
```python
|
||||
# Minimal configuration
|
||||
agent = Agent(
|
||||
instructions="Your instructions",
|
||||
# {slug}=True, # Enable feature
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Advanced">
|
||||
```python
|
||||
# Full configuration
|
||||
agent = Agent(
|
||||
instructions="Your instructions",
|
||||
# {slug}={{
|
||||
# "option1": "value1",
|
||||
# "option2": "value2",
|
||||
# }},
|
||||
)
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
## API Reference
|
||||
|
||||
### Parameters
|
||||
|
||||
<ParamField body="param1" type="string" required>
|
||||
Description of the first parameter.
|
||||
</ParamField>
|
||||
|
||||
<ParamField body="param2" type="boolean" default="false">
|
||||
Description of the second parameter.
|
||||
</ParamField>
|
||||
|
||||
<ParamField body="param3" type="object">
|
||||
Advanced configuration object.
|
||||
</ParamField>
|
||||
|
||||
## Examples
|
||||
|
||||
### Example 1: Basic Usage
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(instructions="You are helpful")
|
||||
result = agent.start("Hello")
|
||||
```
|
||||
|
||||
### Example 2: With Callbacks
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent
|
||||
|
||||
def on_complete(result):
|
||||
print(f"Completed: {{result}}")
|
||||
|
||||
agent = Agent(
|
||||
instructions="You are helpful",
|
||||
# callbacks=[on_complete],
|
||||
)
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
<Accordion title="Common Issue 1">
|
||||
**Problem**: Description of the issue
|
||||
|
||||
**Solution**: How to fix it
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Common Issue 2">
|
||||
**Problem**: Another common issue
|
||||
|
||||
**Solution**: The fix for this issue
|
||||
</Accordion>
|
||||
|
||||
## See Also
|
||||
|
||||
- [Concept Guide](/docs/concepts/{slug})
|
||||
- [CLI Reference](/docs/cli/{slug})
|
||||
- [API Reference](/docs/sdk/praisonaiagents/{slug}/{slug})
|
||||
'''
|
||||
|
||||
CLI_TEMPLATE = '''---
|
||||
title: "{name}"
|
||||
sidebarTitle: "{name}"
|
||||
description: "CLI commands for {slug}"
|
||||
icon: "terminal"
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
praisonai {slug} [OPTIONS]
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
### Basic Command
|
||||
|
||||
```bash
|
||||
praisonai {slug}
|
||||
```
|
||||
|
||||
**Expected Output:**
|
||||
```
|
||||
[Output example here]
|
||||
```
|
||||
|
||||
### With Options
|
||||
|
||||
```bash
|
||||
praisonai {slug} --option value
|
||||
```
|
||||
|
||||
## Options
|
||||
|
||||
| Option | Type | Default | Description |
|
||||
|--------|------|---------|-------------|
|
||||
| `--help` | flag | - | Show help message |
|
||||
| `--verbose` | flag | false | Enable verbose output |
|
||||
| `--config` | string | - | Path to config file |
|
||||
|
||||
## Environment Variables
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `PRAISONAI_{slug_upper}` | Configure {slug} | None |
|
||||
|
||||
## Examples
|
||||
|
||||
### Example 1: Basic
|
||||
|
||||
```bash
|
||||
praisonai {slug}
|
||||
```
|
||||
|
||||
### Example 2: With Config
|
||||
|
||||
```bash
|
||||
praisonai {slug} --config config.yaml
|
||||
```
|
||||
|
||||
### Example 3: Verbose Mode
|
||||
|
||||
```bash
|
||||
praisonai {slug} --verbose
|
||||
```
|
||||
|
||||
## Integration with Python
|
||||
|
||||
You can also use {slug} programmatically:
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Equivalent to CLI command
|
||||
agent = Agent(instructions="Your instructions")
|
||||
result = agent.start("Your prompt")
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
<Accordion title="Command not found">
|
||||
Ensure PraisonAI is installed: `pip install praisonai`
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Permission denied">
|
||||
Check file permissions and try with `sudo` if needed.
|
||||
</Accordion>
|
||||
'''
|
||||
|
||||
SDK_TEMPLATE = '''---
|
||||
title: "{name} Module"
|
||||
description: "API reference for {slug}"
|
||||
icon: "code"
|
||||
---
|
||||
|
||||
# {name}
|
||||
|
||||
The {name} module provides [brief description].
|
||||
|
||||
## Installation
|
||||
|
||||
```bash
|
||||
pip install praisonaiagents
|
||||
```
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from praisonaiagents import {class_name}
|
||||
|
||||
# Basic usage
|
||||
instance = {class_name}()
|
||||
result = instance.execute()
|
||||
```
|
||||
|
||||
## Classes
|
||||
|
||||
### `{class_name}`
|
||||
|
||||
Main class for {slug} functionality.
|
||||
|
||||
#### Constructor
|
||||
|
||||
```python
|
||||
{class_name}(
|
||||
param1: str,
|
||||
param2: bool = False,
|
||||
**kwargs
|
||||
)
|
||||
```
|
||||
|
||||
#### Parameters
|
||||
|
||||
<ParamField body="param1" type="string" required>
|
||||
Primary configuration parameter.
|
||||
</ParamField>
|
||||
|
||||
<ParamField body="param2" type="boolean" default="false">
|
||||
Enable advanced features.
|
||||
</ParamField>
|
||||
|
||||
#### Methods
|
||||
|
||||
##### `execute()`
|
||||
|
||||
Execute the main functionality.
|
||||
|
||||
```python
|
||||
result = instance.execute(input_data)
|
||||
```
|
||||
|
||||
**Parameters:**
|
||||
- `input_data` (str): The input to process
|
||||
|
||||
**Returns:** `str` - The processed result
|
||||
|
||||
##### `configure()`
|
||||
|
||||
Update configuration.
|
||||
|
||||
```python
|
||||
instance.configure(option="value")
|
||||
```
|
||||
|
||||
## Type Definitions
|
||||
|
||||
```python
|
||||
from typing import TypedDict, Optional
|
||||
|
||||
class {class_name}Config(TypedDict):
|
||||
param1: str
|
||||
param2: Optional[bool]
|
||||
```
|
||||
|
||||
## Examples
|
||||
|
||||
### Basic Example
|
||||
|
||||
```python
|
||||
from praisonaiagents import {class_name}
|
||||
|
||||
instance = {class_name}(param1="value")
|
||||
result = instance.execute()
|
||||
print(result)
|
||||
```
|
||||
|
||||
### Advanced Example
|
||||
|
||||
```python
|
||||
from praisonaiagents import {class_name}
|
||||
|
||||
# With full configuration
|
||||
instance = {class_name}(
|
||||
param1="value",
|
||||
param2=True,
|
||||
)
|
||||
|
||||
# Custom processing
|
||||
result = instance.execute()
|
||||
```
|
||||
|
||||
## See Also
|
||||
|
||||
- [Concept Guide](/docs/concepts/{slug})
|
||||
- [Feature Guide](/docs/features/{slug})
|
||||
'''
|
||||
|
||||
EXAMPLE_BASIC_TEMPLATE = '''"""
|
||||
{name} - Basic Example
|
||||
|
||||
Demonstrates minimal usage of {slug} with a single agent.
|
||||
|
||||
Features:
|
||||
- Simple configuration
|
||||
- Single agent setup
|
||||
- Basic execution
|
||||
|
||||
Expected Output:
|
||||
Agent response demonstrating {slug} functionality.
|
||||
|
||||
Usage:
|
||||
python {slug}-basic.py
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# ============================================================
|
||||
# Basic {name} Configuration
|
||||
# ============================================================
|
||||
|
||||
# Create an agent with {slug} enabled
|
||||
agent = Agent(
|
||||
name="{name}Agent",
|
||||
role="{name} Specialist",
|
||||
goal="Demonstrate basic {slug} functionality",
|
||||
backstory="You are an expert in {slug} operations.",
|
||||
instructions="Provide clear, helpful responses demonstrating {slug}.",
|
||||
# {slug}=True, # Enable {slug} feature
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Execute
|
||||
# ============================================================
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Run the agent
|
||||
result = agent.start("Demonstrate {slug} functionality")
|
||||
print(result)
|
||||
'''
|
||||
|
||||
EXAMPLE_ADVANCED_TEMPLATE = '''"""
|
||||
{name} - Advanced Example
|
||||
|
||||
Demonstrates advanced {slug} patterns including:
|
||||
- Multi-agent configuration
|
||||
- Custom callbacks/handlers
|
||||
- Error handling
|
||||
- All available options
|
||||
|
||||
Features:
|
||||
- Multiple agents working together
|
||||
- Custom configuration
|
||||
- Production-ready patterns
|
||||
|
||||
Expected Output:
|
||||
Comprehensive demonstration of {slug} with multiple agents.
|
||||
|
||||
Usage:
|
||||
python {slug}-advanced.py
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, Task, Agents
|
||||
from typing import Any
|
||||
|
||||
# ============================================================
|
||||
# Section 1: Custom Configuration
|
||||
# ============================================================
|
||||
|
||||
# Define custom {slug} configuration
|
||||
# config = {{
|
||||
# "option1": "value1",
|
||||
# "option2": True,
|
||||
# }}
|
||||
|
||||
# ============================================================
|
||||
# Section 2: Custom Callbacks
|
||||
# ============================================================
|
||||
|
||||
def on_task_complete(task_output: Any) -> None:
|
||||
"""Callback when a task completes."""
|
||||
print(f"Task completed: {{task_output}}")
|
||||
|
||||
def on_error(error: Exception) -> None:
|
||||
"""Callback when an error occurs."""
|
||||
print(f"Error occurred: {{error}}")
|
||||
|
||||
# ============================================================
|
||||
# Section 3: Multi-Agent Setup
|
||||
# ============================================================
|
||||
|
||||
# Primary agent
|
||||
primary_agent = Agent(
|
||||
name="Primary{name}Agent",
|
||||
role="Primary {name} Handler",
|
||||
goal="Handle primary {slug} operations",
|
||||
backstory="You are the primary handler for {slug} tasks.",
|
||||
instructions="Process {slug} requests thoroughly and accurately.",
|
||||
# {slug}=config,
|
||||
)
|
||||
|
||||
# Secondary agent
|
||||
secondary_agent = Agent(
|
||||
name="Secondary{name}Agent",
|
||||
role="Secondary {name} Handler",
|
||||
goal="Support and verify {slug} operations",
|
||||
backstory="You verify and enhance {slug} results.",
|
||||
instructions="Review and improve {slug} outputs.",
|
||||
# {slug}=config,
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Section 4: Task Definition
|
||||
# ============================================================
|
||||
|
||||
primary_task = Task(
|
||||
description="Demonstrate advanced {slug} with primary processing",
|
||||
agent=primary_agent,
|
||||
expected_output="Detailed {slug} demonstration",
|
||||
)
|
||||
|
||||
verification_task = Task(
|
||||
description="Verify and enhance the {slug} results",
|
||||
agent=secondary_agent,
|
||||
expected_output="Verified and enhanced {slug} output",
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Section 5: Execution
|
||||
# ============================================================
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Create agents team
|
||||
agents = Agents(
|
||||
agents=[primary_agent, secondary_agent],
|
||||
tasks=[primary_task, verification_task],
|
||||
verbose=True,
|
||||
)
|
||||
|
||||
# Execute
|
||||
result = agents.start()
|
||||
print("\\n" + "=" * 60)
|
||||
print("FINAL RESULT:")
|
||||
print("=" * 60)
|
||||
print(result)
|
||||
|
||||
# ============================================================
|
||||
# Section 6: All Options Reference
|
||||
# ============================================================
|
||||
"""
|
||||
{name} Options:
|
||||
──────────────────────────────────────────────────────────────
|
||||
| Option | Type | Default | Description |
|
||||
|-----------------|----------|---------|----------------------|
|
||||
| option1 | str | None | Primary option |
|
||||
| option2 | bool | False | Enable advanced mode |
|
||||
| option3 | int | 10 | Iteration count |
|
||||
| option4 | list | [] | Additional handlers |
|
||||
──────────────────────────────────────────────────────────────
|
||||
"""
|
||||
'''
|
||||
|
||||
|
||||
class EnhancedTemplateGenerator:
|
||||
"""Enhanced template generator with best-practice templates."""
|
||||
|
||||
# Icon mapping for features
|
||||
ICON_MAP = {
|
||||
"guardrails": "shield-halved",
|
||||
"memory": "brain",
|
||||
"knowledge": "book",
|
||||
"tools": "wrench",
|
||||
"agents": "robot",
|
||||
"tasks": "list-check",
|
||||
"workflows": "diagram-project",
|
||||
"handoffs": "arrow-right-arrow-left",
|
||||
"sessions": "clock",
|
||||
"hooks": "plug",
|
||||
"callbacks": "phone",
|
||||
"telemetry": "chart-line",
|
||||
"default": "code",
|
||||
}
|
||||
|
||||
def get_icon(self, slug: str) -> str:
|
||||
"""Get appropriate icon for a feature."""
|
||||
return self.ICON_MAP.get(slug, self.ICON_MAP["default"])
|
||||
|
||||
def generate(self, slug: FeatureSlug, artifact_type: ArtifactType) -> str:
|
||||
"""Generate template content for an artifact type."""
|
||||
slug_str = slug.normalised
|
||||
name = slug_str.replace("-", " ").title()
|
||||
class_name = "".join(word.title() for word in slug_str.split("-"))
|
||||
icon = self.get_icon(slug_str)
|
||||
slug_upper = slug_str.upper().replace("-", "_")
|
||||
|
||||
# Select template
|
||||
if artifact_type == ArtifactType.DOCS_CONCEPT:
|
||||
template = CONCEPT_TEMPLATE
|
||||
elif artifact_type == ArtifactType.DOCS_FEATURE:
|
||||
template = FEATURE_TEMPLATE
|
||||
elif artifact_type == ArtifactType.DOCS_CLI:
|
||||
template = CLI_TEMPLATE
|
||||
elif artifact_type == ArtifactType.DOCS_SDK:
|
||||
template = SDK_TEMPLATE
|
||||
elif artifact_type == ArtifactType.EXAMPLE_BASIC:
|
||||
template = EXAMPLE_BASIC_TEMPLATE
|
||||
elif artifact_type == ArtifactType.EXAMPLE_ADVANCED:
|
||||
template = EXAMPLE_ADVANCED_TEMPLATE
|
||||
else:
|
||||
return ""
|
||||
|
||||
# Fill template
|
||||
return template.format(
|
||||
name=name,
|
||||
slug=slug_str,
|
||||
class_name=class_name,
|
||||
icon=icon,
|
||||
slug_upper=slug_upper,
|
||||
description=f"{name} functionality for PraisonAI agents",
|
||||
)
|
||||
|
||||
def get_expected_path(self, slug: FeatureSlug, artifact_type: ArtifactType,
|
||||
docs_root: Optional[Path] = None,
|
||||
examples_root: Optional[Path] = None) -> Optional[Path]:
|
||||
"""Get the expected path for an artifact."""
|
||||
slug_str = slug.normalised
|
||||
|
||||
if artifact_type == ArtifactType.EXAMPLE_BASIC:
|
||||
if examples_root:
|
||||
return examples_root / slug_str / f"{slug_str}-basic.py"
|
||||
elif artifact_type == ArtifactType.EXAMPLE_ADVANCED:
|
||||
if examples_root:
|
||||
return examples_root / slug_str / f"{slug_str}-advanced.py"
|
||||
elif artifact_type == ArtifactType.DOCS_CONCEPT:
|
||||
if docs_root:
|
||||
return docs_root / "concepts" / f"{slug_str}.mdx"
|
||||
elif artifact_type == ArtifactType.DOCS_FEATURE:
|
||||
if docs_root:
|
||||
return docs_root / "features" / f"{slug_str}.mdx"
|
||||
elif artifact_type == ArtifactType.DOCS_CLI:
|
||||
if docs_root:
|
||||
return docs_root / "cli" / f"{slug_str}.mdx"
|
||||
elif artifact_type == ArtifactType.DOCS_SDK:
|
||||
if docs_root:
|
||||
return docs_root / "sdk" / "praisonaiagents" / slug_str / f"{slug_str}.mdx"
|
||||
|
||||
return None
|
||||
@@ -0,0 +1,229 @@
|
||||
"""
|
||||
Example verification module for the FDEP standardisation system.
|
||||
|
||||
Verifies that generated Python examples are:
|
||||
1. Syntactically correct (can be parsed)
|
||||
2. Runnable (can be executed without errors)
|
||||
3. Handle external library dependencies gracefully
|
||||
|
||||
Features:
|
||||
- Syntax validation via ast.parse
|
||||
- Execution in subprocess with timeout
|
||||
- Detection of missing external libraries
|
||||
- Detailed error reporting
|
||||
"""
|
||||
|
||||
import ast
|
||||
import subprocess
|
||||
import sys
|
||||
import tempfile
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
from typing import List, Tuple
|
||||
|
||||
|
||||
@dataclass
|
||||
class VerificationResult:
|
||||
"""Result of example verification."""
|
||||
success: bool
|
||||
syntax_valid: bool
|
||||
execution_passed: bool
|
||||
output: str
|
||||
error: str
|
||||
missing_libraries: List[str]
|
||||
requires_external: bool
|
||||
|
||||
@property
|
||||
def can_write(self) -> bool:
|
||||
"""Whether the example is safe to write."""
|
||||
return self.syntax_valid and (self.execution_passed or self.requires_external)
|
||||
|
||||
|
||||
class ExampleVerifier:
|
||||
"""Verifies that generated examples are runnable."""
|
||||
|
||||
# Known external libraries that may not be installed
|
||||
EXTERNAL_LIBRARIES = {
|
||||
"requests", "httpx", "aiohttp", # HTTP
|
||||
"pandas", "numpy", "scipy", # Data science
|
||||
"torch", "tensorflow", "transformers", # ML
|
||||
"redis", "pymongo", "psycopg2", # Databases
|
||||
"boto3", "google-cloud", # Cloud
|
||||
"playwright", "selenium", # Browser automation
|
||||
"beautifulsoup4", "scrapy", # Web scraping
|
||||
}
|
||||
|
||||
# Imports that indicate external dependencies
|
||||
EXTERNAL_IMPORT_PATTERNS = [
|
||||
"import requests",
|
||||
"import httpx",
|
||||
"import pandas",
|
||||
"import numpy",
|
||||
"import torch",
|
||||
"import tensorflow",
|
||||
"from transformers",
|
||||
"import redis",
|
||||
"import pymongo",
|
||||
"import boto3",
|
||||
]
|
||||
|
||||
# Patterns that indicate LLM API calls (will timeout during verification)
|
||||
LLM_CALL_PATTERNS = [
|
||||
"agent.start(",
|
||||
"agents.start(",
|
||||
".chat(",
|
||||
".run(",
|
||||
]
|
||||
|
||||
def __init__(self, timeout: int = 30):
|
||||
self.timeout = timeout
|
||||
|
||||
def verify(self, code: str) -> VerificationResult:
|
||||
"""
|
||||
Verify that the code is valid and runnable.
|
||||
|
||||
Args:
|
||||
code: Python source code to verify
|
||||
|
||||
Returns:
|
||||
VerificationResult with details
|
||||
"""
|
||||
# Step 1: Syntax validation
|
||||
syntax_valid, syntax_error = self._check_syntax(code)
|
||||
if not syntax_valid:
|
||||
return VerificationResult(
|
||||
success=False,
|
||||
syntax_valid=False,
|
||||
execution_passed=False,
|
||||
output="",
|
||||
error=f"Syntax error: {syntax_error}",
|
||||
missing_libraries=[],
|
||||
requires_external=False,
|
||||
)
|
||||
|
||||
# Step 2: Check for external dependencies
|
||||
requires_external, external_libs = self._detect_external_deps(code)
|
||||
|
||||
# Step 3: Skip execution for examples with LLM calls (they will timeout)
|
||||
if "LLM_API_CALL" in external_libs:
|
||||
return VerificationResult(
|
||||
success=True,
|
||||
syntax_valid=True,
|
||||
execution_passed=False,
|
||||
output="",
|
||||
error="Skipped: Example makes LLM API calls",
|
||||
missing_libraries=["praisonaiagents (LLM API)"],
|
||||
requires_external=True,
|
||||
)
|
||||
|
||||
# Step 4: Execute the code
|
||||
execution_passed, output, error, missing_libs = self._execute(code)
|
||||
|
||||
# Combine missing libraries
|
||||
all_missing = list(set(missing_libs + external_libs))
|
||||
|
||||
return VerificationResult(
|
||||
success=execution_passed or requires_external,
|
||||
syntax_valid=True,
|
||||
execution_passed=execution_passed,
|
||||
output=output,
|
||||
error=error,
|
||||
missing_libraries=all_missing,
|
||||
requires_external=requires_external and not execution_passed,
|
||||
)
|
||||
|
||||
def _check_syntax(self, code: str) -> Tuple[bool, str]:
|
||||
"""Check if code is syntactically valid."""
|
||||
try:
|
||||
ast.parse(code)
|
||||
return True, ""
|
||||
except SyntaxError as e:
|
||||
return False, f"Line {e.lineno}: {e.msg}"
|
||||
|
||||
def _detect_external_deps(self, code: str) -> Tuple[bool, List[str]]:
|
||||
"""Detect if code requires external libraries or makes LLM calls."""
|
||||
external_libs = []
|
||||
|
||||
for pattern in self.EXTERNAL_IMPORT_PATTERNS:
|
||||
if pattern in code:
|
||||
lib_name = pattern.split()[-1]
|
||||
external_libs.append(lib_name)
|
||||
|
||||
# Check for LLM API calls that will timeout during verification
|
||||
for pattern in self.LLM_CALL_PATTERNS:
|
||||
if pattern in code:
|
||||
external_libs.append("LLM_API_CALL")
|
||||
break
|
||||
|
||||
return len(external_libs) > 0, external_libs
|
||||
|
||||
def _execute(self, code: str) -> Tuple[bool, str, str, List[str]]:
|
||||
"""Execute code in a subprocess."""
|
||||
missing_libs = []
|
||||
|
||||
# Write code to temp file
|
||||
with tempfile.NamedTemporaryFile(
|
||||
mode="w", suffix=".py", delete=False, encoding="utf-8"
|
||||
) as f:
|
||||
f.write(code)
|
||||
temp_path = f.name
|
||||
|
||||
try:
|
||||
# Run with timeout
|
||||
result = subprocess.run(
|
||||
[sys.executable, temp_path],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=self.timeout,
|
||||
env={**subprocess.os.environ, "PYTHONDONTWRITEBYTECODE": "1"},
|
||||
)
|
||||
|
||||
output = result.stdout
|
||||
error = result.stderr
|
||||
|
||||
# Check for import errors
|
||||
if result.returncode != 0:
|
||||
if "ModuleNotFoundError" in error or "ImportError" in error:
|
||||
# Extract module name
|
||||
for line in error.split("\n"):
|
||||
if "No module named" in line:
|
||||
# Extract module name from error
|
||||
parts = line.split("'")
|
||||
if len(parts) >= 2:
|
||||
missing_libs.append(parts[1].split(".")[0])
|
||||
|
||||
return False, output, error, missing_libs
|
||||
|
||||
return True, output, error, missing_libs
|
||||
|
||||
except subprocess.TimeoutExpired:
|
||||
return False, "", f"Execution timed out after {self.timeout}s", missing_libs
|
||||
except Exception as e:
|
||||
return False, "", str(e), missing_libs
|
||||
finally:
|
||||
# Clean up temp file
|
||||
Path(temp_path).unlink(missing_ok=True)
|
||||
|
||||
def format_result(self, result: VerificationResult) -> str:
|
||||
"""Format verification result for display."""
|
||||
lines = []
|
||||
|
||||
if result.success:
|
||||
lines.append("✅ Verification PASSED")
|
||||
else:
|
||||
lines.append("❌ Verification FAILED")
|
||||
|
||||
lines.append(f" Syntax valid: {'✓' if result.syntax_valid else '✗'}")
|
||||
lines.append(f" Execution passed: {'✓' if result.execution_passed else '✗'}")
|
||||
|
||||
if result.requires_external:
|
||||
lines.append(f" ⚠️ Requires external libraries: {', '.join(result.missing_libraries)}")
|
||||
lines.append(" (Will be written with warning)")
|
||||
|
||||
if result.error and not result.requires_external:
|
||||
lines.append(f" Error: {result.error[:200]}")
|
||||
|
||||
if result.output:
|
||||
lines.append(f" Output preview: {result.output[:100]}...")
|
||||
|
||||
return "\n".join(lines)
|
||||
@@ -0,0 +1,201 @@
|
||||
"""
|
||||
Manifest schema and storage for the FDEP standardisation system.
|
||||
|
||||
Manifests are stored in .praison/features/{slug}.yaml
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
from typing import List, Optional
|
||||
|
||||
from .models import FeatureManifest, FeatureSlug
|
||||
|
||||
|
||||
class ManifestStorage:
|
||||
"""Manages feature manifest files."""
|
||||
|
||||
def __init__(self, manifest_dir: Optional[Path] = None):
|
||||
self.manifest_dir = manifest_dir or Path(".praison/features")
|
||||
|
||||
def get_manifest_path(self, slug: FeatureSlug) -> Path:
|
||||
"""Get the path to a manifest file."""
|
||||
return self.manifest_dir / f"{slug.normalised}.yaml"
|
||||
|
||||
def load(self, slug: FeatureSlug) -> Optional[FeatureManifest]:
|
||||
"""Load a manifest from disk."""
|
||||
path = self.get_manifest_path(slug)
|
||||
if not path.exists():
|
||||
return None
|
||||
|
||||
try:
|
||||
import yaml
|
||||
except ImportError:
|
||||
return self._load_simple(path, slug)
|
||||
|
||||
try:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
data = yaml.safe_load(f)
|
||||
return FeatureManifest.from_dict(data)
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
def _load_simple(self, path: Path, slug: FeatureSlug) -> Optional[FeatureManifest]:
|
||||
"""Simple YAML loading without PyYAML dependency."""
|
||||
try:
|
||||
content = path.read_text(encoding="utf-8")
|
||||
data = {}
|
||||
|
||||
for line in content.split("\n"):
|
||||
line = line.strip()
|
||||
if ":" in line and not line.startswith("#"):
|
||||
key, value = line.split(":", 1)
|
||||
key = key.strip()
|
||||
value = value.strip().strip('"').strip("'")
|
||||
data[key] = value
|
||||
|
||||
return FeatureManifest.from_dict(data)
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
def save(self, manifest: FeatureManifest) -> Path:
|
||||
"""Save a manifest to disk."""
|
||||
path = self.get_manifest_path(manifest.slug)
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
try:
|
||||
import yaml
|
||||
content = yaml.dump(manifest.to_dict(), default_flow_style=False, sort_keys=False)
|
||||
except ImportError:
|
||||
content = self._to_simple_yaml(manifest)
|
||||
|
||||
path.write_text(content, encoding="utf-8")
|
||||
return path
|
||||
|
||||
def _to_simple_yaml(self, manifest: FeatureManifest) -> str:
|
||||
"""Convert manifest to simple YAML without PyYAML."""
|
||||
lines = []
|
||||
data = manifest.to_dict()
|
||||
|
||||
for key, value in data.items():
|
||||
if value is None:
|
||||
continue
|
||||
if isinstance(value, list):
|
||||
if value:
|
||||
lines.append(f"{key}:")
|
||||
for item in value:
|
||||
lines.append(f" - {item}")
|
||||
elif isinstance(value, dict):
|
||||
if value:
|
||||
lines.append(f"{key}:")
|
||||
for k, v in value.items():
|
||||
lines.append(f" {k}: {v}")
|
||||
else:
|
||||
lines.append(f"{key}: {value}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def list_all(self) -> List[FeatureManifest]:
|
||||
"""List all manifests."""
|
||||
manifests = []
|
||||
|
||||
if not self.manifest_dir.exists():
|
||||
return manifests
|
||||
|
||||
for yaml_file in self.manifest_dir.glob("*.yaml"):
|
||||
slug = FeatureSlug.from_path(yaml_file, "manifest")
|
||||
manifest = self.load(slug)
|
||||
if manifest:
|
||||
manifests.append(manifest)
|
||||
|
||||
return manifests
|
||||
|
||||
def delete(self, slug: FeatureSlug) -> bool:
|
||||
"""Delete a manifest."""
|
||||
path = self.get_manifest_path(slug)
|
||||
if path.exists():
|
||||
path.unlink()
|
||||
return True
|
||||
return False
|
||||
|
||||
def exists(self, slug: FeatureSlug) -> bool:
|
||||
"""Check if a manifest exists."""
|
||||
return self.get_manifest_path(slug).exists()
|
||||
|
||||
def create_default(self, slug: FeatureSlug,
|
||||
sdk_module: Optional[str] = None,
|
||||
cli_commands: Optional[List[str]] = None) -> FeatureManifest:
|
||||
"""Create a default manifest for a feature."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
|
||||
return FeatureManifest(
|
||||
slug=slug,
|
||||
name=name,
|
||||
description=f"{name} feature for PraisonAI",
|
||||
status="stable",
|
||||
sdk_module=sdk_module or slug.normalised,
|
||||
cli_commands=cli_commands or [],
|
||||
)
|
||||
|
||||
|
||||
# Schema for manifest validation
|
||||
MANIFEST_SCHEMA = {
|
||||
"type": "object",
|
||||
"required": ["slug", "name", "description"],
|
||||
"properties": {
|
||||
"slug": {
|
||||
"type": "string",
|
||||
"pattern": "^[a-z][a-z0-9-]{0,62}[a-z0-9]$|^[a-z]$",
|
||||
"description": "Feature slug (lowercase alphanumeric + hyphens)",
|
||||
},
|
||||
"name": {
|
||||
"type": "string",
|
||||
"minLength": 1,
|
||||
"maxLength": 100,
|
||||
"description": "Human-readable feature name",
|
||||
},
|
||||
"description": {
|
||||
"type": "string",
|
||||
"minLength": 1,
|
||||
"maxLength": 500,
|
||||
"description": "Brief description of the feature",
|
||||
},
|
||||
"status": {
|
||||
"type": "string",
|
||||
"enum": ["stable", "beta", "experimental", "deprecated"],
|
||||
"default": "stable",
|
||||
},
|
||||
"min_version": {
|
||||
"type": "string",
|
||||
"pattern": "^\\d+\\.\\d+\\.\\d+$",
|
||||
"description": "Minimum PraisonAI version required",
|
||||
},
|
||||
"tags": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "Tags for categorisation",
|
||||
},
|
||||
"related_features": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "Related feature slugs",
|
||||
},
|
||||
"sdk_module": {
|
||||
"type": "string",
|
||||
"description": "SDK module name (e.g., 'guardrails')",
|
||||
},
|
||||
"cli_commands": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "CLI commands for this feature",
|
||||
},
|
||||
"api_classes": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
"description": "Public API classes",
|
||||
},
|
||||
"artifacts": {
|
||||
"type": "object",
|
||||
"description": "Paths to artifacts",
|
||||
"additionalProperties": {"type": "string"},
|
||||
},
|
||||
},
|
||||
}
|
||||
@@ -0,0 +1,355 @@
|
||||
"""
|
||||
Data models for the FDEP standardisation system.
|
||||
|
||||
All models use dataclasses for lightweight, stdlib-only implementation.
|
||||
"""
|
||||
|
||||
import re
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
|
||||
class ArtifactType(Enum):
|
||||
"""Types of required artifacts per feature."""
|
||||
DOCS_CONCEPT = "docs_concept"
|
||||
DOCS_FEATURE = "docs_feature"
|
||||
DOCS_CLI = "docs_cli"
|
||||
DOCS_SDK = "docs_sdk"
|
||||
EXAMPLE_BASIC = "example_basic"
|
||||
EXAMPLE_ADVANCED = "example_advanced"
|
||||
MANIFEST = "manifest"
|
||||
|
||||
|
||||
class ArtifactStatus(Enum):
|
||||
"""Status of an artifact."""
|
||||
PRESENT = "present"
|
||||
MISSING = "missing"
|
||||
DUPLICATE = "duplicate"
|
||||
OUTDATED = "outdated"
|
||||
|
||||
|
||||
class IssueType(Enum):
|
||||
"""Types of standardisation issues."""
|
||||
MISSING_ARTIFACT = "missing_artifact"
|
||||
DUPLICATE_CONTENT = "duplicate_content"
|
||||
NAMING_INCONSISTENCY = "naming_inconsistency"
|
||||
DRIFT_SDK_DOCS = "drift_sdk_docs"
|
||||
DRIFT_CLI_DOCS = "drift_cli_docs"
|
||||
INVALID_FRONTMATTER = "invalid_frontmatter"
|
||||
|
||||
|
||||
# Slug validation regex: lowercase alphanumeric + hyphens, 2-64 chars
|
||||
SLUG_PATTERN = re.compile(r"^[a-z][a-z0-9-]{0,62}[a-z0-9]$|^[a-z]$")
|
||||
|
||||
# Singular to plural mappings for normalisation
|
||||
SINGULAR_PLURAL_MAP = {
|
||||
"agent": "agents",
|
||||
"task": "tasks",
|
||||
"tool": "tools",
|
||||
"guardrail": "guardrails",
|
||||
"handoff": "handoffs",
|
||||
"workflow": "workflows",
|
||||
"checkpoint": "checkpoints",
|
||||
"hook": "hooks",
|
||||
"skill": "skills",
|
||||
"plugin": "plugins",
|
||||
"session": "sessions",
|
||||
"process": "processes",
|
||||
}
|
||||
|
||||
# Legacy alias mappings
|
||||
LEGACY_ALIASES = {
|
||||
"rag": "knowledge",
|
||||
"retrieval": "knowledge",
|
||||
"llm": "models",
|
||||
"model": "models",
|
||||
"db": "databases",
|
||||
"database": "databases",
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class FeatureSlug:
|
||||
"""
|
||||
Represents a normalised feature slug.
|
||||
|
||||
Slug rules:
|
||||
- Lowercase alphanumeric + hyphens only
|
||||
- 1-64 characters
|
||||
- Stable normalisation (singular/plural, legacy aliases)
|
||||
"""
|
||||
raw: str
|
||||
normalised: str
|
||||
is_valid: bool
|
||||
validation_error: Optional[str] = None
|
||||
|
||||
@classmethod
|
||||
def from_string(cls, value: str) -> "FeatureSlug":
|
||||
"""Create a FeatureSlug from a raw string."""
|
||||
raw = value.strip().lower()
|
||||
|
||||
# Replace underscores with hyphens
|
||||
normalised = raw.replace("_", "-")
|
||||
|
||||
# Remove .py, .mdx extensions if present
|
||||
for ext in (".py", ".mdx", ".md"):
|
||||
if normalised.endswith(ext):
|
||||
normalised = normalised[:-len(ext)]
|
||||
|
||||
# Apply legacy alias mapping
|
||||
if normalised in LEGACY_ALIASES:
|
||||
normalised = LEGACY_ALIASES[normalised]
|
||||
|
||||
# Apply singular to plural normalisation (prefer plural for collections)
|
||||
if normalised in SINGULAR_PLURAL_MAP:
|
||||
normalised = SINGULAR_PLURAL_MAP[normalised]
|
||||
|
||||
# Validate
|
||||
is_valid = bool(SLUG_PATTERN.match(normalised))
|
||||
validation_error = None
|
||||
|
||||
if not is_valid:
|
||||
if not normalised:
|
||||
validation_error = "Slug cannot be empty"
|
||||
elif not normalised[0].isalpha():
|
||||
validation_error = "Slug must start with a letter"
|
||||
elif len(normalised) > 64:
|
||||
validation_error = "Slug must be 64 characters or less"
|
||||
else:
|
||||
validation_error = "Slug must contain only lowercase letters, numbers, and hyphens"
|
||||
|
||||
return cls(raw=raw, normalised=normalised, is_valid=is_valid,
|
||||
validation_error=validation_error)
|
||||
|
||||
@classmethod
|
||||
def from_path(cls, path: Path, base_type: str = "unknown") -> "FeatureSlug":
|
||||
"""
|
||||
Derive a slug from a file or directory path.
|
||||
|
||||
Args:
|
||||
path: Path to derive slug from
|
||||
base_type: Type hint (sdk, cli, docs, examples)
|
||||
"""
|
||||
# Use the stem (filename without extension) or directory name
|
||||
name = path.stem if path.is_file() else path.name
|
||||
return cls.from_string(name)
|
||||
|
||||
def __str__(self) -> str:
|
||||
return self.normalised
|
||||
|
||||
def __hash__(self) -> int:
|
||||
return hash(self.normalised)
|
||||
|
||||
def __eq__(self, other) -> bool:
|
||||
if isinstance(other, FeatureSlug):
|
||||
return self.normalised == other.normalised
|
||||
if isinstance(other, str):
|
||||
return self.normalised == other.lower()
|
||||
return False
|
||||
|
||||
|
||||
@dataclass
|
||||
class ArtifactPath:
|
||||
"""Represents a path to a required artifact."""
|
||||
artifact_type: ArtifactType
|
||||
expected_path: Path
|
||||
actual_path: Optional[Path] = None
|
||||
status: ArtifactStatus = ArtifactStatus.MISSING
|
||||
|
||||
@property
|
||||
def exists(self) -> bool:
|
||||
return self.actual_path is not None and self.actual_path.exists()
|
||||
|
||||
|
||||
@dataclass
|
||||
class FeatureManifest:
|
||||
"""
|
||||
Manifest entry for a single feature.
|
||||
|
||||
This is the source of truth for what artifacts a feature should have.
|
||||
"""
|
||||
slug: FeatureSlug
|
||||
name: str
|
||||
description: str
|
||||
status: str = "stable" # stable, beta, experimental, deprecated
|
||||
min_version: Optional[str] = None
|
||||
tags: List[str] = field(default_factory=list)
|
||||
related_features: List[str] = field(default_factory=list)
|
||||
sdk_module: Optional[str] = None
|
||||
cli_commands: List[str] = field(default_factory=list)
|
||||
api_classes: List[str] = field(default_factory=list)
|
||||
artifacts: Dict[str, str] = field(default_factory=dict)
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""Convert to dictionary for YAML serialisation."""
|
||||
return {
|
||||
"slug": self.slug.normalised,
|
||||
"name": self.name,
|
||||
"description": self.description,
|
||||
"status": self.status,
|
||||
"min_version": self.min_version,
|
||||
"tags": self.tags,
|
||||
"related_features": self.related_features,
|
||||
"sdk_module": self.sdk_module,
|
||||
"cli_commands": self.cli_commands,
|
||||
"api_classes": self.api_classes,
|
||||
"artifacts": self.artifacts,
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, data: dict) -> "FeatureManifest":
|
||||
"""Create from dictionary."""
|
||||
slug = FeatureSlug.from_string(data.get("slug", ""))
|
||||
return cls(
|
||||
slug=slug,
|
||||
name=data.get("name", slug.normalised.replace("-", " ").title()),
|
||||
description=data.get("description", ""),
|
||||
status=data.get("status", "stable"),
|
||||
min_version=data.get("min_version"),
|
||||
tags=data.get("tags", []),
|
||||
related_features=data.get("related_features", []),
|
||||
sdk_module=data.get("sdk_module"),
|
||||
cli_commands=data.get("cli_commands", []),
|
||||
api_classes=data.get("api_classes", []),
|
||||
artifacts=data.get("artifacts", {}),
|
||||
)
|
||||
|
||||
|
||||
@dataclass
|
||||
class ValidationResult:
|
||||
"""Result of validating a feature's artifacts."""
|
||||
slug: FeatureSlug
|
||||
is_valid: bool
|
||||
missing_artifacts: List[ArtifactType] = field(default_factory=list)
|
||||
present_artifacts: List[ArtifactPath] = field(default_factory=list)
|
||||
issues: List[str] = field(default_factory=list)
|
||||
|
||||
@property
|
||||
def missing_count(self) -> int:
|
||||
return len(self.missing_artifacts)
|
||||
|
||||
@property
|
||||
def present_count(self) -> int:
|
||||
return len(self.present_artifacts)
|
||||
|
||||
|
||||
@dataclass
|
||||
class DuplicateCluster:
|
||||
"""A cluster of duplicate or near-duplicate content."""
|
||||
slug: FeatureSlug
|
||||
pages: List[Path]
|
||||
similarity_score: float # 0.0 to 1.0
|
||||
issue_type: str # "same_slug", "title_similarity", "content_overlap"
|
||||
recommendation: str # "merge", "keep_both", "review"
|
||||
primary_page: Optional[Path] = None # Recommended canonical page
|
||||
|
||||
def __str__(self) -> str:
|
||||
return f"DuplicateCluster({self.slug}, {len(self.pages)} pages, {self.issue_type})"
|
||||
|
||||
|
||||
@dataclass
|
||||
class DriftItem:
|
||||
"""A single drift item (SDK export or CLI flag not in docs, or vice versa)."""
|
||||
name: str
|
||||
source: str # "sdk", "cli", "docs"
|
||||
missing_in: str # Where it's missing
|
||||
item_type: str # "class", "function", "flag", "command"
|
||||
|
||||
|
||||
@dataclass
|
||||
class DriftReport:
|
||||
"""Report of drift between code and documentation."""
|
||||
slug: FeatureSlug
|
||||
sdk_drift: List[DriftItem] = field(default_factory=list)
|
||||
cli_drift: List[DriftItem] = field(default_factory=list)
|
||||
|
||||
@property
|
||||
def has_drift(self) -> bool:
|
||||
return bool(self.sdk_drift or self.cli_drift)
|
||||
|
||||
@property
|
||||
def total_drift_items(self) -> int:
|
||||
return len(self.sdk_drift) + len(self.cli_drift)
|
||||
|
||||
|
||||
@dataclass
|
||||
class StandardiseIssue:
|
||||
"""A single standardisation issue."""
|
||||
issue_type: IssueType
|
||||
slug: Optional[FeatureSlug]
|
||||
path: Optional[Path]
|
||||
message: str
|
||||
severity: str = "warning" # error, warning, info
|
||||
auto_fixable: bool = False
|
||||
fix_action: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class StandardiseReport:
|
||||
"""Complete standardisation report."""
|
||||
timestamp: str
|
||||
features_scanned: int
|
||||
docs_pages: int
|
||||
examples_count: int
|
||||
issues: List[StandardiseIssue] = field(default_factory=list)
|
||||
duplicates: List[DuplicateCluster] = field(default_factory=list)
|
||||
missing_artifacts: Dict[str, List[ArtifactType]] = field(default_factory=dict)
|
||||
drift_reports: List[DriftReport] = field(default_factory=list)
|
||||
validation_results: List[ValidationResult] = field(default_factory=list)
|
||||
|
||||
@property
|
||||
def total_issues(self) -> int:
|
||||
return len(self.issues)
|
||||
|
||||
@property
|
||||
def total_missing(self) -> int:
|
||||
return sum(len(v) for v in self.missing_artifacts.values())
|
||||
|
||||
@property
|
||||
def total_duplicates(self) -> int:
|
||||
return len(self.duplicates)
|
||||
|
||||
@property
|
||||
def has_issues(self) -> bool:
|
||||
return self.total_issues > 0 or self.total_missing > 0 or self.total_duplicates > 0
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""Convert to dictionary for JSON serialisation."""
|
||||
return {
|
||||
"timestamp": self.timestamp,
|
||||
"summary": {
|
||||
"features_scanned": self.features_scanned,
|
||||
"docs_pages": self.docs_pages,
|
||||
"examples_count": self.examples_count,
|
||||
"total_issues": self.total_issues,
|
||||
"total_missing": self.total_missing,
|
||||
"total_duplicates": self.total_duplicates,
|
||||
},
|
||||
"issues": [
|
||||
{
|
||||
"type": i.issue_type.value,
|
||||
"slug": str(i.slug) if i.slug else None,
|
||||
"path": str(i.path) if i.path else None,
|
||||
"message": i.message,
|
||||
"severity": i.severity,
|
||||
"auto_fixable": i.auto_fixable,
|
||||
}
|
||||
for i in self.issues
|
||||
],
|
||||
"duplicates": [
|
||||
{
|
||||
"slug": str(d.slug),
|
||||
"pages": [str(p) for p in d.pages],
|
||||
"similarity": d.similarity_score,
|
||||
"type": d.issue_type,
|
||||
"recommendation": d.recommendation,
|
||||
}
|
||||
for d in self.duplicates
|
||||
],
|
||||
"missing_artifacts": {
|
||||
slug: [a.value for a in artifacts]
|
||||
for slug, artifacts in self.missing_artifacts.items()
|
||||
},
|
||||
}
|
||||
@@ -0,0 +1,176 @@
|
||||
"""
|
||||
Report generators for the FDEP standardisation system.
|
||||
|
||||
Generates reports in:
|
||||
- Text (terminal-friendly)
|
||||
- JSON (machine-readable)
|
||||
- Markdown (documentation-friendly)
|
||||
"""
|
||||
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
from .models import StandardiseReport
|
||||
|
||||
|
||||
class ReportGenerator:
|
||||
"""Generates standardisation reports in various formats."""
|
||||
|
||||
def generate(self, report: StandardiseReport, format: str = "text") -> str:
|
||||
"""Generate a report in the specified format."""
|
||||
if format == "text":
|
||||
return self._generate_text(report)
|
||||
elif format == "json":
|
||||
return self._generate_json(report)
|
||||
elif format == "markdown":
|
||||
return self._generate_markdown(report)
|
||||
else:
|
||||
raise ValueError(f"Unknown format: {format}")
|
||||
|
||||
def _generate_text(self, report: StandardiseReport) -> str:
|
||||
"""Generate a text report for terminal output."""
|
||||
lines = []
|
||||
|
||||
# Header
|
||||
lines.append("")
|
||||
lines.append("🔍 PraisonAI Standardisation Check")
|
||||
lines.append("══════════════════════════════════")
|
||||
lines.append("")
|
||||
|
||||
# Summary
|
||||
lines.append("📊 Summary")
|
||||
lines.append("──────────")
|
||||
lines.append(f"Features scanned: {report.features_scanned}")
|
||||
lines.append(f"Docs pages: {report.docs_pages}")
|
||||
lines.append(f"Examples: {report.examples_count}")
|
||||
lines.append("")
|
||||
|
||||
if not report.has_issues:
|
||||
lines.append("✅ No issues found!")
|
||||
return "\n".join(lines)
|
||||
|
||||
lines.append(f"⚠️ Issues Found: {report.total_issues + report.total_missing + report.total_duplicates}")
|
||||
lines.append("──────────────────────")
|
||||
lines.append("")
|
||||
|
||||
# Duplicates
|
||||
if report.duplicates:
|
||||
lines.append(f"🔴 DUPLICATES ({len(report.duplicates)} clusters)")
|
||||
for cluster in report.duplicates:
|
||||
pages_str = ", ".join(self._short_path(p) for p in cluster.pages[:3])
|
||||
if len(cluster.pages) > 3:
|
||||
pages_str += f" (+{len(cluster.pages) - 3} more)"
|
||||
lines.append(f" • {cluster.slug}: {len(cluster.pages)} pages ({cluster.issue_type})")
|
||||
lines.append("")
|
||||
|
||||
# Missing artifacts
|
||||
if report.missing_artifacts:
|
||||
lines.append(f"🟡 MISSING ARTIFACTS ({len(report.missing_artifacts)} features)")
|
||||
for slug, artifacts in list(report.missing_artifacts.items())[:10]:
|
||||
artifact_names = [a.value.replace("_", " ") for a in artifacts]
|
||||
lines.append(f" • {slug}: missing {', '.join(artifact_names[:3])}")
|
||||
if len(artifact_names) > 3:
|
||||
lines.append(f" (+{len(artifact_names) - 3} more)")
|
||||
if len(report.missing_artifacts) > 10:
|
||||
lines.append(f" ... and {len(report.missing_artifacts) - 10} more features")
|
||||
lines.append("")
|
||||
|
||||
# Other issues
|
||||
if report.issues:
|
||||
naming_issues = [i for i in report.issues if "naming" in i.message.lower()]
|
||||
if naming_issues:
|
||||
lines.append(f"🟢 NAMING ISSUES ({len(naming_issues)})")
|
||||
for issue in naming_issues[:5]:
|
||||
lines.append(f" • {issue.message}")
|
||||
lines.append("")
|
||||
|
||||
# Next actions
|
||||
lines.append("📋 Next Actions")
|
||||
lines.append("───────────────")
|
||||
lines.append("1. Run `praisonai standardise report --format markdown` for details")
|
||||
if report.duplicates:
|
||||
lines.append("2. Run `praisonai standardise fix --feature <slug>` to consolidate")
|
||||
if report.missing_artifacts:
|
||||
lines.append("3. Run `praisonai standardise init --feature <slug>` to create missing")
|
||||
lines.append("")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def _generate_json(self, report: StandardiseReport) -> str:
|
||||
"""Generate a JSON report."""
|
||||
return json.dumps(report.to_dict(), indent=2)
|
||||
|
||||
def _generate_markdown(self, report: StandardiseReport) -> str:
|
||||
"""Generate a Markdown report."""
|
||||
lines = []
|
||||
|
||||
# Header
|
||||
lines.append("# PraisonAI Standardisation Report")
|
||||
lines.append("")
|
||||
lines.append(f"Generated: {report.timestamp}")
|
||||
lines.append("")
|
||||
|
||||
# Summary table
|
||||
lines.append("## Summary")
|
||||
lines.append("")
|
||||
lines.append("| Metric | Value |")
|
||||
lines.append("|--------|-------|")
|
||||
lines.append(f"| Features scanned | {report.features_scanned} |")
|
||||
lines.append(f"| Docs pages | {report.docs_pages} |")
|
||||
lines.append(f"| Examples | {report.examples_count} |")
|
||||
lines.append(f"| Total issues | {report.total_issues} |")
|
||||
lines.append(f"| Missing artifacts | {report.total_missing} |")
|
||||
lines.append(f"| Duplicate clusters | {report.total_duplicates} |")
|
||||
lines.append("")
|
||||
|
||||
# Duplicates section
|
||||
if report.duplicates:
|
||||
lines.append("## Duplicate Clusters")
|
||||
lines.append("")
|
||||
for cluster in report.duplicates:
|
||||
lines.append(f"### {cluster.slug}")
|
||||
lines.append("")
|
||||
lines.append(f"- **Type**: {cluster.issue_type}")
|
||||
lines.append(f"- **Similarity**: {cluster.similarity_score:.0%}")
|
||||
lines.append(f"- **Recommendation**: {cluster.recommendation}")
|
||||
lines.append("")
|
||||
lines.append("**Pages:**")
|
||||
for page in cluster.pages:
|
||||
lines.append(f"- `{page}`")
|
||||
lines.append("")
|
||||
|
||||
# Missing artifacts section
|
||||
if report.missing_artifacts:
|
||||
lines.append("## Missing Artifacts")
|
||||
lines.append("")
|
||||
lines.append("| Feature | Missing |")
|
||||
lines.append("|---------|---------|")
|
||||
for slug, artifacts in report.missing_artifacts.items():
|
||||
artifact_names = ", ".join(a.value for a in artifacts)
|
||||
lines.append(f"| {slug} | {artifact_names} |")
|
||||
lines.append("")
|
||||
|
||||
# Issues section
|
||||
if report.issues:
|
||||
lines.append("## Other Issues")
|
||||
lines.append("")
|
||||
for issue in report.issues:
|
||||
severity_icon = {"error": "🔴", "warning": "🟡", "info": "🔵"}.get(issue.severity, "⚪")
|
||||
lines.append(f"- {severity_icon} **{issue.issue_type.value}**: {issue.message}")
|
||||
lines.append("")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def _short_path(self, path: Path) -> str:
|
||||
"""Get a shortened path for display."""
|
||||
parts = path.parts
|
||||
if len(parts) > 3:
|
||||
return "/".join(parts[-3:])
|
||||
return str(path)
|
||||
|
||||
def save(self, report: StandardiseReport, output_path: Path,
|
||||
format: str = "text") -> None:
|
||||
"""Save a report to a file."""
|
||||
content = self.generate(report, format)
|
||||
output_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
output_path.write_text(content, encoding="utf-8")
|
||||
@@ -0,0 +1,399 @@
|
||||
"""
|
||||
Template generators for the FDEP standardisation system.
|
||||
|
||||
Generates:
|
||||
- Example files (basic and advanced)
|
||||
- Docs pages (concept, feature, cli, sdk)
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from .models import ArtifactType, FeatureSlug
|
||||
|
||||
|
||||
class TemplateGenerator:
|
||||
"""Generates template files for features."""
|
||||
|
||||
def generate(self, slug: FeatureSlug, artifact_type: ArtifactType,
|
||||
output_path: Optional[Path] = None) -> str:
|
||||
"""Generate template content for an artifact type."""
|
||||
if artifact_type == ArtifactType.EXAMPLE_BASIC:
|
||||
return self._generate_basic_example(slug)
|
||||
elif artifact_type == ArtifactType.EXAMPLE_ADVANCED:
|
||||
return self._generate_advanced_example(slug)
|
||||
elif artifact_type == ArtifactType.DOCS_CONCEPT:
|
||||
return self._generate_concept_doc(slug)
|
||||
elif artifact_type == ArtifactType.DOCS_FEATURE:
|
||||
return self._generate_feature_doc(slug)
|
||||
elif artifact_type == ArtifactType.DOCS_CLI:
|
||||
return self._generate_cli_doc(slug)
|
||||
elif artifact_type == ArtifactType.DOCS_SDK:
|
||||
return self._generate_sdk_doc(slug)
|
||||
else:
|
||||
raise ValueError(f"Unknown artifact type: {artifact_type}")
|
||||
|
||||
def _generate_basic_example(self, slug: FeatureSlug) -> str:
|
||||
"""Generate a basic example template."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
slug_str = slug.normalised
|
||||
|
||||
return f'''"""
|
||||
{name} - Basic Example
|
||||
|
||||
Demonstrates minimal usage of {slug_str} with a single agent.
|
||||
|
||||
Expected Output:
|
||||
Agent response demonstrating {slug_str} functionality.
|
||||
"""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic {slug_str} usage
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
# {slug_str}=... # Configure {slug_str} here
|
||||
)
|
||||
|
||||
# Run the agent
|
||||
result = agent.start("Hello! Demonstrate {slug_str} functionality.")
|
||||
print(result)
|
||||
'''
|
||||
|
||||
def _generate_advanced_example(self, slug: FeatureSlug) -> str:
|
||||
"""Generate an advanced example template."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
slug_str = slug.normalised
|
||||
|
||||
return f'''"""
|
||||
{name} - Advanced Example
|
||||
|
||||
Demonstrates advanced {slug_str} patterns including:
|
||||
- Multi-agent configuration
|
||||
- Custom callbacks/handlers
|
||||
- Error handling
|
||||
- All available options
|
||||
|
||||
Expected Output:
|
||||
Comprehensive demonstration of {slug_str} with multiple agents.
|
||||
"""
|
||||
from praisonaiagents import Agent, Task, PraisonAIAgents
|
||||
|
||||
# ============================================================
|
||||
# Section 1: Custom Configuration
|
||||
# ============================================================
|
||||
|
||||
# Define custom {slug_str} configuration
|
||||
# config = ...
|
||||
|
||||
# ============================================================
|
||||
# Section 2: Multi-Agent Setup
|
||||
# ============================================================
|
||||
|
||||
agent1 = Agent(
|
||||
name="Agent1",
|
||||
instructions="You are the first agent",
|
||||
# {slug_str}=config,
|
||||
)
|
||||
|
||||
agent2 = Agent(
|
||||
name="Agent2",
|
||||
instructions="You are the second agent",
|
||||
# {slug_str}=config,
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Section 3: Task Definition
|
||||
# ============================================================
|
||||
|
||||
task = Task(
|
||||
description="Demonstrate {slug_str} with multiple agents",
|
||||
agent=agent1,
|
||||
)
|
||||
|
||||
# ============================================================
|
||||
# Section 4: Execution
|
||||
# ============================================================
|
||||
|
||||
agents = PraisonAIAgents(agents=[agent1, agent2], tasks=[task])
|
||||
result = agents.start()
|
||||
print(result)
|
||||
|
||||
# ============================================================
|
||||
# Section 5: All Options Reference
|
||||
# ============================================================
|
||||
"""
|
||||
{name} Options:
|
||||
──────────────────
|
||||
| Option | Type | Default | Description |
|
||||
|-----------------|----------|---------|----------------------|
|
||||
| option1 | str | None | Description here |
|
||||
| option2 | bool | False | Description here |
|
||||
"""
|
||||
'''
|
||||
|
||||
def _generate_concept_doc(self, slug: FeatureSlug) -> str:
|
||||
"""Generate a concept documentation template."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
slug_str = slug.normalised
|
||||
|
||||
return f'''---
|
||||
title: "{name}"
|
||||
description: "Understanding {slug_str} in PraisonAI"
|
||||
icon: "lightbulb"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
{name} provides [brief description of what this feature does and why it exists].
|
||||
|
||||
```mermaid
|
||||
graph LR
|
||||
A[Input] --> B[{name}]
|
||||
B --> C[Output]
|
||||
```
|
||||
|
||||
## When to Use
|
||||
|
||||
<CardGroup cols={{2}}>
|
||||
<Card title="Use When" icon="check">
|
||||
- Use case 1
|
||||
- Use case 2
|
||||
</Card>
|
||||
<Card title="Don't Use When" icon="xmark">
|
||||
- Anti-pattern 1
|
||||
- Anti-pattern 2
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## How It Works
|
||||
|
||||
[Brief explanation of the mechanism, 3-5 sentences max.]
|
||||
|
||||
## Related Features
|
||||
|
||||
- [Related Feature 1](/docs/concepts/related1)
|
||||
- [Related Feature 2](/docs/concepts/related2)
|
||||
'''
|
||||
|
||||
def _generate_feature_doc(self, slug: FeatureSlug) -> str:
|
||||
"""Generate a feature documentation template."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
slug_str = slug.normalised
|
||||
|
||||
return f'''---
|
||||
title: "{name}"
|
||||
description: "How to use {slug_str} in PraisonAI"
|
||||
icon: "code"
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant",
|
||||
# {slug_str}=...
|
||||
)
|
||||
result = agent.start("Hello!")
|
||||
```
|
||||
|
||||
## Basic Usage
|
||||
|
||||
<Steps>
|
||||
<Step title="Step 1: Configure">
|
||||
Configure {slug_str} for your agent.
|
||||
```python
|
||||
# Configuration code
|
||||
```
|
||||
</Step>
|
||||
<Step title="Step 2: Run">
|
||||
Run the agent with {slug_str} enabled.
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
## Advanced Patterns
|
||||
|
||||
<Tabs>
|
||||
<Tab title="Pattern 1">
|
||||
```python
|
||||
# Pattern 1 code
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="Pattern 2">
|
||||
```python
|
||||
# Pattern 2 code
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
## All Options
|
||||
|
||||
<ParamField body="option1" type="string" required>
|
||||
Description of option1.
|
||||
</ParamField>
|
||||
|
||||
<ParamField body="option2" type="boolean" default="false">
|
||||
Description of option2.
|
||||
</ParamField>
|
||||
|
||||
## See Also
|
||||
|
||||
- [CLI Reference](/docs/cli/{slug_str})
|
||||
- [API Reference](/docs/sdk/praisonaiagents/{slug_str}/{slug_str})
|
||||
'''
|
||||
|
||||
def _generate_cli_doc(self, slug: FeatureSlug) -> str:
|
||||
"""Generate a CLI documentation template."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
slug_str = slug.normalised
|
||||
|
||||
return f'''---
|
||||
title: "{name}"
|
||||
description: "CLI commands for {slug_str}"
|
||||
icon: "terminal"
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
praisonai "Your prompt" --{slug_str}
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
### `--{slug_str}`
|
||||
|
||||
Enable {slug_str} functionality.
|
||||
|
||||
```bash
|
||||
praisonai "Your prompt" --{slug_str}
|
||||
```
|
||||
|
||||
**Expected Output:**
|
||||
```
|
||||
[Example output here]
|
||||
```
|
||||
|
||||
## Environment Variables
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `PRAISONAI_{slug_str.upper().replace("-", "_")}` | Configure {slug_str} | None |
|
||||
|
||||
## Examples
|
||||
|
||||
### Basic
|
||||
|
||||
```bash
|
||||
praisonai "Hello" --{slug_str}
|
||||
```
|
||||
|
||||
### With Other Flags
|
||||
|
||||
```bash
|
||||
praisonai "Hello" --{slug_str} --verbose
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
<Accordion title="Common Issue 1">
|
||||
Solution for common issue 1.
|
||||
</Accordion>
|
||||
'''
|
||||
|
||||
def _generate_sdk_doc(self, slug: FeatureSlug) -> str:
|
||||
"""Generate an SDK documentation template."""
|
||||
name = slug.normalised.replace("-", " ").title()
|
||||
slug_str = slug.normalised
|
||||
class_name = "".join(word.title() for word in slug_str.split("-"))
|
||||
|
||||
return f'''---
|
||||
title: "{name} Module"
|
||||
description: "API reference for {slug_str}"
|
||||
icon: "code"
|
||||
---
|
||||
|
||||
# {name}
|
||||
|
||||
{name} module provides [brief description].
|
||||
|
||||
## Quick Start
|
||||
|
||||
```python
|
||||
from praisonaiagents import {class_name}
|
||||
|
||||
# Basic usage
|
||||
instance = {class_name}()
|
||||
```
|
||||
|
||||
## Classes
|
||||
|
||||
### `{class_name}`
|
||||
|
||||
Main class for {slug_str} functionality.
|
||||
|
||||
#### Constructor
|
||||
|
||||
```python
|
||||
{class_name}(
|
||||
param1: str,
|
||||
param2: bool = False
|
||||
)
|
||||
```
|
||||
|
||||
#### Parameters
|
||||
|
||||
<ParamField body="param1" type="string" required>
|
||||
Description of param1.
|
||||
</ParamField>
|
||||
|
||||
<ParamField body="param2" type="boolean" default="false">
|
||||
Description of param2.
|
||||
</ParamField>
|
||||
|
||||
#### Methods
|
||||
|
||||
##### `method_name()`
|
||||
|
||||
Description of the method.
|
||||
|
||||
```python
|
||||
result = instance.method_name(args)
|
||||
```
|
||||
|
||||
**Returns:** `ReturnType` - Description of return value.
|
||||
|
||||
## Type Definitions
|
||||
|
||||
```python
|
||||
# Type aliases used in this module
|
||||
```
|
||||
'''
|
||||
|
||||
def get_expected_path(self, slug: FeatureSlug, artifact_type: ArtifactType,
|
||||
docs_root: Optional[Path] = None,
|
||||
examples_root: Optional[Path] = None) -> Optional[Path]:
|
||||
"""Get the expected path for an artifact."""
|
||||
slug_str = slug.normalised
|
||||
|
||||
if artifact_type == ArtifactType.EXAMPLE_BASIC:
|
||||
if examples_root:
|
||||
return examples_root / slug_str / f"{slug_str}-basic.py"
|
||||
elif artifact_type == ArtifactType.EXAMPLE_ADVANCED:
|
||||
if examples_root:
|
||||
return examples_root / slug_str / f"{slug_str}-advanced.py"
|
||||
elif artifact_type == ArtifactType.DOCS_CONCEPT:
|
||||
if docs_root:
|
||||
return docs_root / "concepts" / f"{slug_str}.mdx"
|
||||
elif artifact_type == ArtifactType.DOCS_FEATURE:
|
||||
if docs_root:
|
||||
return docs_root / "features" / f"{slug_str}.mdx"
|
||||
elif artifact_type == ArtifactType.DOCS_CLI:
|
||||
if docs_root:
|
||||
return docs_root / "cli" / f"{slug_str}.mdx"
|
||||
elif artifact_type == ArtifactType.DOCS_SDK:
|
||||
if docs_root:
|
||||
return docs_root / "sdk" / "praisonaiagents" / slug_str / f"{slug_str}.mdx"
|
||||
|
||||
return None
|
||||
@@ -0,0 +1,232 @@
|
||||
"""
|
||||
Git-based undo/redo system for the FDEP standardisation system.
|
||||
|
||||
Provides:
|
||||
- Checkpoint creation before changes
|
||||
- Undo to previous checkpoint
|
||||
- Redo to next checkpoint
|
||||
- List checkpoints
|
||||
"""
|
||||
|
||||
import subprocess
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import List, Optional, Tuple
|
||||
|
||||
|
||||
class UndoRedoManager:
|
||||
"""Git-based undo/redo for standardisation changes."""
|
||||
|
||||
CHECKPOINT_PREFIX = "standardise-checkpoint-"
|
||||
|
||||
def __init__(self, repo_path: Optional[Path] = None):
|
||||
self.repo_path = repo_path or Path.cwd()
|
||||
self._verify_git_repo()
|
||||
|
||||
def _verify_git_repo(self) -> bool:
|
||||
"""Verify we're in a git repository."""
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "rev-parse", "--git-dir"],
|
||||
cwd=self.repo_path,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
)
|
||||
return result.returncode == 0
|
||||
except Exception:
|
||||
return False
|
||||
|
||||
def _run_git(self, *args) -> Tuple[bool, str]:
|
||||
"""Run a git command."""
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git"] + list(args),
|
||||
cwd=self.repo_path,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
)
|
||||
return result.returncode == 0, result.stdout + result.stderr
|
||||
except Exception as e:
|
||||
return False, str(e)
|
||||
|
||||
def create_checkpoint(self, message: Optional[str] = None) -> Tuple[bool, str]:
|
||||
"""
|
||||
Create a checkpoint before making changes.
|
||||
|
||||
Returns:
|
||||
Tuple of (success, checkpoint_id or error message)
|
||||
"""
|
||||
timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
|
||||
checkpoint_id = f"{self.CHECKPOINT_PREFIX}{timestamp}"
|
||||
|
||||
# Stage all changes
|
||||
success, output = self._run_git("add", "-A")
|
||||
if not success:
|
||||
return False, f"Failed to stage changes: {output}"
|
||||
|
||||
# Check if there are changes to commit
|
||||
success, output = self._run_git("diff", "--cached", "--quiet")
|
||||
if success:
|
||||
# No changes to commit, just create a tag at current HEAD
|
||||
pass
|
||||
else:
|
||||
# Commit changes
|
||||
commit_msg = message or f"Standardise checkpoint: {timestamp}"
|
||||
success, output = self._run_git("commit", "-m", commit_msg)
|
||||
if not success and "nothing to commit" not in output:
|
||||
return False, f"Failed to commit: {output}"
|
||||
|
||||
# Create tag
|
||||
tag_msg = message or f"Standardise checkpoint at {timestamp}"
|
||||
success, output = self._run_git("tag", "-a", checkpoint_id, "-m", tag_msg)
|
||||
if not success:
|
||||
return False, f"Failed to create tag: {output}"
|
||||
|
||||
return True, checkpoint_id
|
||||
|
||||
def undo(self, checkpoint_id: Optional[str] = None) -> Tuple[bool, str]:
|
||||
"""
|
||||
Undo to a previous checkpoint.
|
||||
|
||||
Args:
|
||||
checkpoint_id: Specific checkpoint to restore (default: previous)
|
||||
|
||||
Returns:
|
||||
Tuple of (success, message)
|
||||
"""
|
||||
if checkpoint_id is None:
|
||||
# Find the most recent checkpoint
|
||||
checkpoints = self.list_checkpoints()
|
||||
if len(checkpoints) < 2:
|
||||
return False, "No previous checkpoint to undo to"
|
||||
checkpoint_id = checkpoints[1][0] # Second most recent
|
||||
|
||||
# Verify checkpoint exists
|
||||
success, output = self._run_git("rev-parse", checkpoint_id)
|
||||
if not success:
|
||||
return False, f"Checkpoint not found: {checkpoint_id}"
|
||||
|
||||
# Create a safety checkpoint before undoing
|
||||
self.create_checkpoint("Auto-checkpoint before undo")
|
||||
|
||||
# Reset to checkpoint
|
||||
success, output = self._run_git("reset", "--hard", checkpoint_id)
|
||||
if not success:
|
||||
return False, f"Failed to reset: {output}"
|
||||
|
||||
return True, f"Restored to checkpoint: {checkpoint_id}"
|
||||
|
||||
def redo(self) -> Tuple[bool, str]:
|
||||
"""
|
||||
Redo to the next checkpoint (after an undo).
|
||||
|
||||
Returns:
|
||||
Tuple of (success, message)
|
||||
"""
|
||||
# Get reflog to find the previous HEAD
|
||||
success, output = self._run_git("reflog", "-n", "10", "--format=%H %s")
|
||||
if not success:
|
||||
return False, "Failed to read reflog"
|
||||
|
||||
# Find the commit before the last reset
|
||||
lines = output.strip().split("\n")
|
||||
for i, line in enumerate(lines):
|
||||
if "reset: moving to" in line and i > 0:
|
||||
# The previous line has the commit we want to redo to
|
||||
target_hash = lines[i - 1].split()[0]
|
||||
success, output = self._run_git("reset", "--hard", target_hash)
|
||||
if success:
|
||||
return True, "Redo successful"
|
||||
return False, f"Failed to redo: {output}"
|
||||
|
||||
return False, "No redo available"
|
||||
|
||||
def list_checkpoints(self) -> List[Tuple[str, str, str]]:
|
||||
"""
|
||||
List all standardise checkpoints.
|
||||
|
||||
Returns:
|
||||
List of (checkpoint_id, date, message) tuples
|
||||
"""
|
||||
success, output = self._run_git(
|
||||
"tag", "-l", f"{self.CHECKPOINT_PREFIX}*",
|
||||
"--format=%(refname:short)|%(creatordate:short)|%(subject)"
|
||||
)
|
||||
|
||||
if not success:
|
||||
return []
|
||||
|
||||
checkpoints = []
|
||||
for line in output.strip().split("\n"):
|
||||
if line and "|" in line:
|
||||
parts = line.split("|", 2)
|
||||
if len(parts) >= 3:
|
||||
checkpoints.append((parts[0], parts[1], parts[2]))
|
||||
elif len(parts) == 2:
|
||||
checkpoints.append((parts[0], parts[1], ""))
|
||||
|
||||
# Sort by date descending
|
||||
checkpoints.sort(key=lambda x: x[1], reverse=True)
|
||||
return checkpoints
|
||||
|
||||
def delete_checkpoint(self, checkpoint_id: str) -> Tuple[bool, str]:
|
||||
"""Delete a checkpoint."""
|
||||
success, output = self._run_git("tag", "-d", checkpoint_id)
|
||||
if success:
|
||||
return True, f"Deleted checkpoint: {checkpoint_id}"
|
||||
return False, f"Failed to delete: {output}"
|
||||
|
||||
def get_changes_since(self, checkpoint_id: str) -> List[str]:
|
||||
"""Get list of files changed since a checkpoint."""
|
||||
success, output = self._run_git(
|
||||
"diff", "--name-only", checkpoint_id, "HEAD"
|
||||
)
|
||||
|
||||
if not success:
|
||||
return []
|
||||
|
||||
return [f for f in output.strip().split("\n") if f]
|
||||
|
||||
def preview_undo(self, checkpoint_id: str) -> List[str]:
|
||||
"""Preview what files would change if we undo to a checkpoint."""
|
||||
return self.get_changes_since(checkpoint_id)
|
||||
|
||||
|
||||
class FileBackupManager:
|
||||
"""Simple file-based backup for non-git scenarios."""
|
||||
|
||||
def __init__(self, backup_dir: Optional[Path] = None):
|
||||
self.backup_dir = backup_dir or Path(".praison/backups")
|
||||
self.backup_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
def backup_file(self, file_path: Path) -> Optional[Path]:
|
||||
"""Create a backup of a file."""
|
||||
if not file_path.exists():
|
||||
return None
|
||||
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
backup_name = f"{file_path.stem}_{timestamp}{file_path.suffix}"
|
||||
backup_path = self.backup_dir / backup_name
|
||||
|
||||
import shutil
|
||||
shutil.copy2(file_path, backup_path)
|
||||
return backup_path
|
||||
|
||||
def restore_file(self, backup_path: Path, target_path: Path) -> bool:
|
||||
"""Restore a file from backup."""
|
||||
if not backup_path.exists():
|
||||
return False
|
||||
|
||||
import shutil
|
||||
shutil.copy2(backup_path, target_path)
|
||||
return True
|
||||
|
||||
def list_backups(self, file_stem: Optional[str] = None) -> List[Path]:
|
||||
"""List all backups, optionally filtered by file stem."""
|
||||
backups = list(self.backup_dir.glob("*"))
|
||||
|
||||
if file_stem:
|
||||
backups = [b for b in backups if b.stem.startswith(file_stem)]
|
||||
|
||||
backups.sort(key=lambda x: x.stat().st_mtime, reverse=True)
|
||||
return backups
|
||||
@@ -0,0 +1,283 @@
|
||||
"""
|
||||
Artifact validation for the FDEP standardisation system.
|
||||
|
||||
Validates that features have all required artifacts:
|
||||
- docs/concepts/{slug}.mdx
|
||||
- docs/features/{slug}.mdx
|
||||
- docs/cli/{slug}.mdx
|
||||
- docs/sdk/praisonaiagents/{module}/{slug}.mdx
|
||||
- examples/python/{slug}/{slug}-basic.py
|
||||
- examples/python/{slug}/{slug}-advanced.py
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from .config import StandardiseConfig
|
||||
from .discovery import FeatureDiscovery
|
||||
from .models import (
|
||||
ArtifactPath,
|
||||
ArtifactStatus,
|
||||
ArtifactType,
|
||||
FeatureSlug,
|
||||
ValidationResult,
|
||||
)
|
||||
|
||||
|
||||
class ArtifactValidator:
|
||||
"""Validates that features have all required artifacts."""
|
||||
|
||||
def __init__(self, config: StandardiseConfig, discovery: FeatureDiscovery):
|
||||
self.config = config
|
||||
self.discovery = discovery
|
||||
|
||||
def validate_feature(self, slug: FeatureSlug) -> ValidationResult:
|
||||
"""Validate all artifacts for a single feature."""
|
||||
missing = []
|
||||
present = []
|
||||
issues = []
|
||||
|
||||
# Check each required artifact type
|
||||
for artifact_type in ArtifactType:
|
||||
if artifact_type == ArtifactType.MANIFEST:
|
||||
continue # Manifest is optional
|
||||
|
||||
artifact_path = self._get_expected_path(slug, artifact_type)
|
||||
if artifact_path is None:
|
||||
continue
|
||||
|
||||
if artifact_path.exists:
|
||||
present.append(ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=artifact_path.expected_path,
|
||||
actual_path=artifact_path.actual_path,
|
||||
status=ArtifactStatus.PRESENT,
|
||||
))
|
||||
else:
|
||||
missing.append(artifact_type)
|
||||
present.append(ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=artifact_path.expected_path,
|
||||
actual_path=None,
|
||||
status=ArtifactStatus.MISSING,
|
||||
))
|
||||
|
||||
is_valid = len(missing) == 0
|
||||
|
||||
return ValidationResult(
|
||||
slug=slug,
|
||||
is_valid=is_valid,
|
||||
missing_artifacts=missing,
|
||||
present_artifacts=present,
|
||||
issues=issues,
|
||||
)
|
||||
|
||||
def validate_all(self) -> Dict[str, ValidationResult]:
|
||||
"""Validate all discovered features."""
|
||||
results = {}
|
||||
|
||||
all_features = self.discovery.get_all_features()
|
||||
|
||||
for slug in all_features:
|
||||
if self.config.feature_filter:
|
||||
if slug.normalised != self.config.feature_filter:
|
||||
continue
|
||||
|
||||
results[slug.normalised] = self.validate_feature(slug)
|
||||
|
||||
return results
|
||||
|
||||
def get_missing_artifacts(self) -> Dict[str, List[ArtifactType]]:
|
||||
"""Get all missing artifacts across all features."""
|
||||
missing = {}
|
||||
|
||||
results = self.validate_all()
|
||||
for slug_str, result in results.items():
|
||||
if result.missing_artifacts:
|
||||
missing[slug_str] = result.missing_artifacts
|
||||
|
||||
return missing
|
||||
|
||||
def _get_expected_path(self, slug: FeatureSlug,
|
||||
artifact_type: ArtifactType) -> Optional[ArtifactPath]:
|
||||
"""Get the expected path for an artifact."""
|
||||
slug_str = slug.normalised
|
||||
|
||||
if artifact_type == ArtifactType.DOCS_CONCEPT:
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
expected = self.config.docs_root / "concepts" / f"{slug_str}.mdx"
|
||||
actual = self._find_actual_path(expected, slug, "concepts")
|
||||
return ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=expected,
|
||||
actual_path=actual,
|
||||
status=ArtifactStatus.PRESENT if actual else ArtifactStatus.MISSING,
|
||||
)
|
||||
|
||||
elif artifact_type == ArtifactType.DOCS_FEATURE:
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
expected = self.config.docs_root / "features" / f"{slug_str}.mdx"
|
||||
actual = self._find_actual_path(expected, slug, "features")
|
||||
return ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=expected,
|
||||
actual_path=actual,
|
||||
status=ArtifactStatus.PRESENT if actual else ArtifactStatus.MISSING,
|
||||
)
|
||||
|
||||
elif artifact_type == ArtifactType.DOCS_CLI:
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
expected = self.config.docs_root / "cli" / f"{slug_str}.mdx"
|
||||
actual = self._find_actual_path(expected, slug, "cli")
|
||||
return ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=expected,
|
||||
actual_path=actual,
|
||||
status=ArtifactStatus.PRESENT if actual else ArtifactStatus.MISSING,
|
||||
)
|
||||
|
||||
elif artifact_type == ArtifactType.DOCS_SDK:
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
# SDK docs are in docs/sdk/praisonaiagents/{module}/
|
||||
sdk_docs = self.config.docs_root / "sdk" / "praisonaiagents"
|
||||
expected = sdk_docs / slug_str / f"{slug_str}.mdx"
|
||||
actual = self._find_sdk_docs_path(slug, sdk_docs)
|
||||
return ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=expected,
|
||||
actual_path=actual,
|
||||
status=ArtifactStatus.PRESENT if actual else ArtifactStatus.MISSING,
|
||||
)
|
||||
|
||||
elif artifact_type == ArtifactType.EXAMPLE_BASIC:
|
||||
if not self.config.examples_root:
|
||||
return None
|
||||
expected = self.config.examples_root / slug_str / f"{slug_str}-basic.py"
|
||||
actual = self._find_example_path(slug, "basic")
|
||||
return ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=expected,
|
||||
actual_path=actual,
|
||||
status=ArtifactStatus.PRESENT if actual else ArtifactStatus.MISSING,
|
||||
)
|
||||
|
||||
elif artifact_type == ArtifactType.EXAMPLE_ADVANCED:
|
||||
if not self.config.examples_root:
|
||||
return None
|
||||
expected = self.config.examples_root / slug_str / f"{slug_str}-advanced.py"
|
||||
actual = self._find_example_path(slug, "advanced")
|
||||
return ArtifactPath(
|
||||
artifact_type=artifact_type,
|
||||
expected_path=expected,
|
||||
actual_path=actual,
|
||||
status=ArtifactStatus.PRESENT if actual else ArtifactStatus.MISSING,
|
||||
)
|
||||
|
||||
return None
|
||||
|
||||
def _find_actual_path(self, expected: Path, slug: FeatureSlug,
|
||||
doc_type: str) -> Optional[Path]:
|
||||
"""Find the actual path, checking variants."""
|
||||
if expected.exists():
|
||||
return expected
|
||||
|
||||
if not self.config.docs_root:
|
||||
return None
|
||||
|
||||
# Check variants
|
||||
slug_str = slug.normalised
|
||||
variants = [
|
||||
slug_str,
|
||||
slug_str.replace("-", "_"),
|
||||
slug_str.replace("-", ""),
|
||||
]
|
||||
|
||||
# Add singular/plural variants
|
||||
from .models import SINGULAR_PLURAL_MAP
|
||||
for singular, plural in SINGULAR_PLURAL_MAP.items():
|
||||
if slug_str == plural:
|
||||
variants.append(singular)
|
||||
elif slug_str == singular:
|
||||
variants.append(plural)
|
||||
|
||||
doc_dir = self.config.docs_root / doc_type
|
||||
if not doc_dir.exists():
|
||||
return None
|
||||
|
||||
for variant in variants:
|
||||
path = doc_dir / f"{variant}.mdx"
|
||||
if path.exists():
|
||||
return path
|
||||
|
||||
return None
|
||||
|
||||
def _find_sdk_docs_path(self, slug: FeatureSlug,
|
||||
sdk_docs: Path) -> Optional[Path]:
|
||||
"""Find SDK docs path, checking module directories."""
|
||||
if not sdk_docs.exists():
|
||||
return None
|
||||
|
||||
slug_str = slug.normalised
|
||||
variants = [
|
||||
slug_str,
|
||||
slug_str.replace("-", "_"),
|
||||
]
|
||||
|
||||
# Check for module directory
|
||||
for variant in variants:
|
||||
module_dir = sdk_docs / variant
|
||||
if module_dir.exists() and module_dir.is_dir():
|
||||
# Look for any .mdx file in the module directory
|
||||
for mdx_file in module_dir.glob("*.mdx"):
|
||||
return mdx_file
|
||||
|
||||
return None
|
||||
|
||||
def _find_example_path(self, slug: FeatureSlug,
|
||||
example_type: str) -> Optional[Path]:
|
||||
"""Find example path, checking variants."""
|
||||
if not self.config.examples_root:
|
||||
return None
|
||||
|
||||
slug_str = slug.normalised
|
||||
variants = [
|
||||
slug_str,
|
||||
slug_str.replace("-", "_"),
|
||||
]
|
||||
|
||||
for variant in variants:
|
||||
example_dir = self.config.examples_root / variant
|
||||
if not example_dir.exists():
|
||||
continue
|
||||
|
||||
# Check for basic/advanced files with various naming patterns
|
||||
patterns = [
|
||||
f"{variant}-{example_type}.py",
|
||||
f"{variant}_{example_type}.py",
|
||||
f"{example_type}.py",
|
||||
f"{example_type}_{variant}.py",
|
||||
]
|
||||
|
||||
for pattern in patterns:
|
||||
path = example_dir / pattern
|
||||
if path.exists():
|
||||
return path
|
||||
|
||||
# If looking for basic, any simple example file counts
|
||||
if example_type == "basic":
|
||||
for py_file in example_dir.glob("*.py"):
|
||||
if "advanced" not in py_file.name.lower():
|
||||
return py_file
|
||||
|
||||
# If looking for advanced, any advanced/complex example counts
|
||||
if example_type == "advanced":
|
||||
for py_file in example_dir.glob("*.py"):
|
||||
name_lower = py_file.name.lower()
|
||||
if any(x in name_lower for x in ["advanced", "complex", "multi"]):
|
||||
return py_file
|
||||
|
||||
return None
|
||||
Loaded 100 of 122 files, more files were not shown because too many files have changed in this diff.
Show more
Reference in new issue
Block a user