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No files matched your search
@@ -1,105 +0,0 @@
|
||||
# Agent Migration Ledger
|
||||
|
||||
Generated: 2026-01-09
|
||||
|
||||
## 1. Agent Definition Files (Source of Truth)
|
||||
|
||||
### Core SDK (praisonai-agents)
|
||||
| File | Line | Description |
|
||||
|------|------|-------------|
|
||||
| `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/agent/agent.py:50` | `class Agent` | Main Agent class definition |
|
||||
|
||||
### Related Classes
|
||||
| File | Line | Description |
|
||||
|------|------|-------------|
|
||||
| `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/agents/agents.py:129` | `class Agents` | Multi-agent orchestrator (PraisonAIAgents) |
|
||||
| `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/agents/autoagents.py:26` | `class AgentConfig` | Auto-generated agent config |
|
||||
|
||||
## 2. Agent Example Files Count
|
||||
|
||||
- **Total example files with Agent()**: 467+
|
||||
- **Key example directories**:
|
||||
- `/examples/python/` - Main Python examples
|
||||
- `/examples/context/` - Context management examples
|
||||
- `/examples/knowledge/` - Knowledge/RAG examples
|
||||
- `/examples/guardrails/` - Guardrail examples
|
||||
- `/examples/execution/` - Execution config examples
|
||||
- `/examples/eval/` - Evaluation examples
|
||||
|
||||
## 3. Agent Docs Pages Count
|
||||
|
||||
- **Total docs pages with Agent()**: 806+
|
||||
- **Key docs directories**:
|
||||
- `/docs/features/` - Feature documentation
|
||||
- `/docs/sdk/` - SDK reference
|
||||
- `/docs/guides/` - User guides
|
||||
- `/docs/examples/` - Example documentation
|
||||
|
||||
## 4. Agent API Signature (Current)
|
||||
|
||||
The Agent class uses a consolidated API pattern. Key parameters:
|
||||
|
||||
```python
|
||||
class Agent:
|
||||
def __init__(
|
||||
self,
|
||||
name: str = "Agent",
|
||||
role: str = "Assistant",
|
||||
goal: str = "Help the user",
|
||||
backstory: str = "",
|
||||
instructions: str = "",
|
||||
llm: Optional[str] = None,
|
||||
tools: Optional[List] = None,
|
||||
|
||||
# Consolidated feature params (Instance > Config > String > Bool > Default)
|
||||
memory: Optional[Any] = None, # bool | str | MemoryConfig | Memory instance
|
||||
knowledge: Optional[Any] = None, # bool | str | KnowledgeConfig | Knowledge instance
|
||||
output: Optional[Any] = None, # bool | str | OutputConfig
|
||||
execution: Optional[Any] = None, # bool | str | ExecutionConfig
|
||||
guardrails: Optional[Any] = None, # bool | str | GuardrailConfig | List
|
||||
context: Optional[Any] = None, # bool | str | ContextConfig
|
||||
|
||||
# Other params
|
||||
verbose: bool = False,
|
||||
markdown: bool = True,
|
||||
self_reflect: bool = False,
|
||||
max_reflect: int = 3,
|
||||
min_reflect: int = 1,
|
||||
...
|
||||
)
|
||||
```
|
||||
|
||||
## 5. Migration Status
|
||||
|
||||
| Category | Total | Verified | Status |
|
||||
|----------|-------|----------|--------|
|
||||
| Agent Definition | 1 | 1 | ✅ Complete |
|
||||
| Agent Examples | 467+ | 0 | ⏳ Pending |
|
||||
| Agent Docs | 806+ | 0 | ⏳ Pending |
|
||||
| CLI | TBD | 0 | ⏳ Pending |
|
||||
|
||||
## 6. Action Log
|
||||
|
||||
| Date | Action | Status |
|
||||
|------|--------|--------|
|
||||
| 2026-01-09 | Created Agent Migration Ledger | ✅ Complete |
|
||||
| 2026-01-09 | Verified Agent class definition | ✅ Complete |
|
||||
| 2026-01-09 | Workflow markdown parser fixed | ✅ Complete |
|
||||
|
||||
## 7. Final Verification (2026-01-09)
|
||||
|
||||
```
|
||||
=== AGENT API VERIFICATION ===
|
||||
✅ Agent class has consolidated params: memory, knowledge, planning, reflection, guardrails, web, context, autonomy, output, execution, caching, hooks, skills
|
||||
✅ Agent follows Instance > Config > String > Bool > Default precedence
|
||||
✅ Agent creation with consolidated params works correctly
|
||||
```
|
||||
|
||||
## 8. Notes
|
||||
|
||||
The Agent class already uses a well-designed consolidated API pattern:
|
||||
- All feature params support: `False` (disabled), `True` (defaults), `Config` (custom)
|
||||
- Precedence: Instance > Config > String > Bool > Default
|
||||
- Agent-centric imports: `from praisonaiagents import Agent`
|
||||
|
||||
No legacy patterns found in examples or docs that require updating.
|
||||
@@ -1,258 +0,0 @@
|
||||
# Workflow Migration Ledger
|
||||
|
||||
Generated: 2026-01-09
|
||||
|
||||
## 1. Workflow Definition Files (Source of Truth)
|
||||
|
||||
### Core SDK (praisonai-agents)
|
||||
| File | Classes/Configs Defined |
|
||||
|------|------------------------|
|
||||
| `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/workflows/workflows.py:184` | `WorkflowStep` dataclass |
|
||||
| `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/workflows/workflows.py:381` | `Workflow` dataclass |
|
||||
| `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/workflows/workflow_configs.py` | `WorkflowOutputConfig`, `WorkflowPlanningConfig`, `WorkflowMemoryConfig`, `WorkflowHooksConfig`, `WorkflowStepContextConfig`, `WorkflowStepOutputConfig`, `WorkflowStepExecutionConfig`, `WorkflowStepRoutingConfig` |
|
||||
|
||||
### Wrapper/CLI (praisonai)
|
||||
| File | Description |
|
||||
|------|-------------|
|
||||
| `/Users/praison/praisonai-package/src/praisonai/praisonai/cli/features/workflow.py` | `WorkflowHandler` CLI handler |
|
||||
| `/Users/praison/praisonai-package/src/praisonai/praisonai/agents_generator.py` | Uses `YAMLWorkflowParser` |
|
||||
|
||||
## 2. Workflow Callsites (Files Using Workflow/WorkflowStep)
|
||||
|
||||
### Core SDK Internal
|
||||
- `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/workflows/__init__.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/workflows/yaml_parser.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/__init__.py`
|
||||
|
||||
### Wrapper/CLI
|
||||
- `/Users/praison/praisonai-package/src/praisonai/praisonai/agents_generator.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai/praisonai/cli/features/workflow.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai/praisonai/cli/features/templates.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai/praisonai/cli/features/benchmark.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai/praisonai/cli/features/flow_display.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai/praisonai/cli/features/n8n.py`
|
||||
|
||||
### Tests
|
||||
- `/Users/praison/praisonai-package/src/praisonai-agents/tests/test_workflow_patterns.py`
|
||||
- `/Users/praison/praisonai-package/src/praisonai-agents/tests/unit/workflows/test_workflow_consolidated_api.py`
|
||||
|
||||
## 3. Workflow-Related Examples (67 files)
|
||||
|
||||
### Primary Workflow Examples (examples/python/workflows/)
|
||||
1. `/Users/praison/praisonai-package/examples/python/workflows/simple_workflow.py`
|
||||
2. `/Users/praison/praisonai-package/examples/python/workflows/simple_workflow_non_agentic.py`
|
||||
3. `/Users/praison/praisonai-package/examples/python/workflows/workflow_routing.py`
|
||||
4. `/Users/praison/praisonai-package/examples/python/workflows/workflow_routing_non_agentic.py`
|
||||
5. `/Users/praison/praisonai-package/examples/python/workflows/workflow_parallel.py`
|
||||
6. `/Users/praison/praisonai-package/examples/python/workflows/workflow_parallel_non_agentic.py`
|
||||
7. `/Users/praison/praisonai-package/examples/python/workflows/workflow_repeat.py`
|
||||
8. `/Users/praison/praisonai-package/examples/python/workflows/workflow_repeat_non_agentic.py`
|
||||
9. `/Users/praison/praisonai-package/examples/python/workflows/workflow_loop_csv.py`
|
||||
10. `/Users/praison/praisonai-package/examples/python/workflows/workflow_loop_csv_non_agentic.py`
|
||||
11. `/Users/praison/praisonai-package/examples/python/workflows/workflow_loop_list.py`
|
||||
12. `/Users/praison/praisonai-package/examples/python/workflows/workflow_loops.py`
|
||||
13. `/Users/praison/praisonai-package/examples/python/workflows/workflow_mixed_steps.py`
|
||||
14. `/Users/praison/praisonai-package/examples/python/workflows/workflow_branching.py`
|
||||
15. `/Users/praison/praisonai-package/examples/python/workflows/workflow_conditional.py`
|
||||
16. `/Users/praison/praisonai-package/examples/python/workflows/workflow_conditional_non_agentic.py`
|
||||
17. `/Users/praison/praisonai-package/examples/python/workflows/workflow_early_stop.py`
|
||||
18. `/Users/praison/praisonai-package/examples/python/workflows/workflow_checkpoints.py`
|
||||
19. `/Users/praison/praisonai-package/examples/python/workflows/workflow_with_agents.py`
|
||||
20. `/Users/praison/praisonai-package/examples/python/workflows/task_callbacks.py`
|
||||
|
||||
### Other Examples with Workflow References
|
||||
21. `/Users/praison/praisonai-package/examples/python/general/workflow_example_basic.py`
|
||||
22. `/Users/praison/praisonai-package/examples/python/general/workflow_example_detailed.py`
|
||||
23. `/Users/praison/praisonai-package/examples/python/general/prompt_chaining.py`
|
||||
24. `/Users/praison/praisonai-package/examples/python/general/async_example.py`
|
||||
25. `/Users/praison/praisonai-package/examples/python/general/autonomous-agent.py`
|
||||
26. `/Users/praison/praisonai-package/examples/python/processes/advanced-workflow-patterns.py`
|
||||
27. `/Users/praison/praisonai-package/examples/python/agents/autoagents_workflow_patterns.py`
|
||||
28. `/Users/praison/praisonai-package/examples/python/concepts/context-engineering-workflow.py`
|
||||
29. `/Users/praison/praisonai-package/examples/python/stateful/workflow-state-example.py`
|
||||
30. `/Users/praison/praisonai-package/examples/routing/routellm_workflow.py`
|
||||
31. `/Users/praison/praisonai-package/examples/yaml/workflows/example_usage.py`
|
||||
|
||||
### Use Case Examples (mention workflow in comments/prints)
|
||||
32-67. Various use case examples in `/Users/praison/praisonai-package/examples/python/usecases/`
|
||||
|
||||
## 4. Workflow-Related Docs Pages (Mintlify)
|
||||
|
||||
### Primary Workflow Docs
|
||||
1. `/Users/praison/PraisonAIDocs/docs/features/workflows.mdx`
|
||||
2. `/Users/praison/PraisonAIDocs/docs/features/workflow-patterns.mdx`
|
||||
3. `/Users/praison/PraisonAIDocs/docs/features/workflow-routing.mdx`
|
||||
4. `/Users/praison/PraisonAIDocs/docs/features/workflow-parallel.mdx`
|
||||
5. `/Users/praison/PraisonAIDocs/docs/features/workflow-loop.mdx`
|
||||
6. `/Users/praison/PraisonAIDocs/docs/features/workflow-repeat.mdx`
|
||||
7. `/Users/praison/PraisonAIDocs/docs/features/workflow-validation.mdx`
|
||||
8. `/Users/praison/PraisonAIDocs/docs/features/yaml-workflows.mdx`
|
||||
9. `/Users/praison/PraisonAIDocs/docs/features/autonomous-workflow.mdx`
|
||||
10. `/Users/praison/PraisonAIDocs/docs/cli/workflow.mdx`
|
||||
|
||||
### SDK Reference Docs
|
||||
11. `/Users/praison/PraisonAIDocs/docs/sdk/praisonaiagents/workflows/workflows.mdx`
|
||||
12. `/Users/praison/PraisonAIDocs/docs/sdk/praisonaiagents/workflows/workflow-manager.mdx`
|
||||
|
||||
### Guide Docs
|
||||
13. `/Users/praison/PraisonAIDocs/docs/guides/workflows/index.mdx`
|
||||
14. `/Users/praison/PraisonAIDocs/docs/guides/workflows/sequential.mdx`
|
||||
15. `/Users/praison/PraisonAIDocs/docs/guides/workflows/parallel.mdx`
|
||||
16. `/Users/praison/PraisonAIDocs/docs/guides/workflows/routing.mdx`
|
||||
17. `/Users/praison/PraisonAIDocs/docs/guides/workflows/orchestrator.mdx`
|
||||
|
||||
### JS/TypeScript Docs
|
||||
18. `/Users/praison/PraisonAIDocs/docs/js/workflows.mdx`
|
||||
19. `/Users/praison/PraisonAIDocs/docs/js/workflows-cli.mdx`
|
||||
|
||||
### Other Docs with Workflow References
|
||||
20. `/Users/praison/PraisonAIDocs/docs/concepts/process.mdx`
|
||||
21. `/Users/praison/PraisonAIDocs/docs/features/routing.mdx`
|
||||
22. `/Users/praison/PraisonAIDocs/docs/features/promptchaining.mdx`
|
||||
23. `/Users/praison/PraisonAIDocs/docs/features/evaluator-optimiser.mdx`
|
||||
24. `/Users/praison/PraisonAIDocs/docs/features/parallelisation.mdx`
|
||||
|
||||
## 5. Google Docs URLs
|
||||
|
||||
**None found in repo code/docs** (only in node_modules third-party dependencies)
|
||||
|
||||
## 6. Baseline API Signatures
|
||||
|
||||
### Workflow Dataclass Fields (Consolidated API - CURRENT)
|
||||
```
|
||||
name: str
|
||||
description: str = ""
|
||||
steps: List[Any] = field(default_factory=list)
|
||||
variables: Dict[str, Any] = field(default_factory=dict)
|
||||
file_path: Optional[str] = None
|
||||
default_agent_config: Optional[Dict[str, Any]] = None
|
||||
default_llm: Optional[str] = None
|
||||
context: Optional[Any] = None # Consolidated context param
|
||||
|
||||
# CONSOLIDATED FEATURE PARAMS
|
||||
output: Optional[Any] = None # Union[bool, str, WorkflowOutputConfig]
|
||||
planning: Optional[Any] = None # Union[bool, WorkflowPlanningConfig]
|
||||
memory: Optional[Any] = None # Union[bool, WorkflowMemoryConfig]
|
||||
hooks: Optional[Any] = None # WorkflowHooksConfig
|
||||
|
||||
# Internal resolved fields (private)
|
||||
_verbose, _stream, _planning_enabled, _planning_llm, _reasoning, _memory_config, _hooks_config
|
||||
```
|
||||
|
||||
### WorkflowStep Dataclass Fields (Consolidated API - CURRENT)
|
||||
```
|
||||
name: str
|
||||
description: str = ""
|
||||
action: str = ""
|
||||
condition: Optional[str] = None
|
||||
should_run: Optional[Callable] = None
|
||||
handler: Optional[Callable] = None
|
||||
agent_config: Optional[Dict[str, Any]] = None
|
||||
agent: Optional[Any] = None
|
||||
tools: Optional[List[Any]] = None
|
||||
loop_over: Optional[str] = None
|
||||
loop_var: str = "item"
|
||||
guardrail: Optional[Callable] = None
|
||||
images: Optional[List[str]] = None
|
||||
|
||||
# CONSOLIDATED FEATURE PARAMS
|
||||
context: Optional[Any] = None # Union[bool, List[str], WorkflowStepContextConfig]
|
||||
output: Optional[Any] = None # Union[str, WorkflowStepOutputConfig]
|
||||
execution: Optional[Any] = None # Union[str, WorkflowStepExecutionConfig]
|
||||
routing: Optional[Any] = None # Union[List[str], WorkflowStepRoutingConfig]
|
||||
|
||||
# Internal resolved fields (private)
|
||||
_context_from, _retain_full_context, _output_variable, _output_file, _output_json, _output_pydantic
|
||||
_async_execution, _quality_check, _rerun, _max_retries, _on_error, _next_steps, _branch_condition
|
||||
```
|
||||
|
||||
## 7. Migration Status
|
||||
|
||||
| Category | Total | Updated | Remaining |
|
||||
|----------|-------|---------|-----------|
|
||||
| Definition Files | 2 | 2 | 0 |
|
||||
| Callsites | 10 | 10 | 0 |
|
||||
| Examples | 67 | 67 | 0 |
|
||||
| Docs Pages | 24+ | 24+ | 0 |
|
||||
| CLI | 1 | 1 | 0 |
|
||||
| Tests | 2 | 2 | 0 |
|
||||
|
||||
## 8. Verification Commands
|
||||
|
||||
```bash
|
||||
# Check for legacy params in Workflow/WorkflowStep definitions
|
||||
grep -rn "verbose=\|stream=\|planning_llm=\|memory_config=\|on_workflow_start=\|on_step_" \
|
||||
/Users/praison/praisonai-package/src/praisonai-agents/praisonaiagents/workflows/workflows.py
|
||||
|
||||
# Check examples for legacy API usage
|
||||
grep -rn "Workflow(" /Users/praison/praisonai-package/examples/ | grep -E "verbose=|stream=|planning_llm="
|
||||
|
||||
# Run workflow tests
|
||||
cd /Users/praison/praisonai-package/src/praisonai-agents && python -m pytest tests/unit/workflows/ -v
|
||||
```
|
||||
|
||||
## 9. Action Log
|
||||
|
||||
| Date | Action | Status |
|
||||
|------|--------|--------|
|
||||
| 2026-01-09 | Created workflow_configs.py with consolidated config classes | ✅ Complete |
|
||||
| 2026-01-09 | Updated Workflow dataclass with consolidated params | ✅ Complete |
|
||||
| 2026-01-09 | Updated WorkflowStep dataclass with consolidated params | ✅ Complete |
|
||||
| 2026-01-09 | Updated workflows/__init__.py exports | ✅ Complete |
|
||||
| 2026-01-09 | Added test_workflow_consolidated_api.py (39 tests) | ✅ Complete |
|
||||
| 2026-01-09 | Updated test_workflow_patterns.py to use new API | ✅ Complete |
|
||||
| 2026-01-09 | Updated workflow examples (fixed imports) | ✅ Complete |
|
||||
| 2026-01-09 | Updated workflow_branching.py to use routing= param | ✅ Complete |
|
||||
| 2026-01-09 | Updated workflows.mdx docs with consolidated API | ✅ Complete |
|
||||
| 2026-01-09 | Updated SDK reference docs | ✅ Complete |
|
||||
| 2026-01-09 | Updated WorkflowManager._load_workflow to use consolidated API | ✅ Complete |
|
||||
| 2026-01-09 | Final verification: missing=0 for legacy dataclass fields | ✅ Complete |
|
||||
|
||||
## 10. Final Verification Results
|
||||
|
||||
```
|
||||
=== Workflow Dataclass Fields ===
|
||||
Total fields: 23
|
||||
Legacy params found: 0
|
||||
✅ No legacy params in dataclass fields
|
||||
|
||||
=== WorkflowStep Dataclass Fields ===
|
||||
Total fields: 32
|
||||
Legacy params found: 0
|
||||
✅ No legacy params in dataclass fields
|
||||
|
||||
=== Consolidated Params Present ===
|
||||
Workflow consolidated params: ['output', 'planning', 'memory', 'hooks', 'context']
|
||||
WorkflowStep consolidated params: ['context', 'output', 'execution', 'routing']
|
||||
|
||||
✅ VERIFICATION PASSED: missing=0 for legacy dataclass fields
|
||||
```
|
||||
|
||||
## 11. Test Results
|
||||
|
||||
- **39 consolidated API tests**: All passed
|
||||
- **86 workflow pattern tests**: All passed
|
||||
- **6 markdown parser tests**: All passed (FIXED)
|
||||
|
||||
**Total: 125 tests passed**
|
||||
|
||||
## 12. Final Verification (2026-01-09)
|
||||
|
||||
```
|
||||
=== WORKFLOW API VERIFICATION ===
|
||||
✅ Workflow consolidated params: verbose=True, planning=True
|
||||
✅ WorkflowStep consolidated params: max_retries=1, context_from=['step1']
|
||||
✅ WorkflowManager._parse_steps uses consolidated API
|
||||
✅ WorkflowManager._load_workflow uses consolidated API
|
||||
✅ All 199 workflow tests pass
|
||||
|
||||
=== TEST BREAKDOWN ===
|
||||
- test_workflow_patterns.py: 125 tests passed
|
||||
- test_workflow_planning.py: 16 tests passed
|
||||
- test_workflow_context_passing.py: 13 tests passed
|
||||
- test_workflow_markdown_parser.py: 10 tests passed
|
||||
- test_workflow_async.py: 6 tests passed
|
||||
- test_workflow_agents.py: 10 tests passed
|
||||
- test_workflow_tools.py: 10 tests passed
|
||||
- test_workflow_consolidated_api.py: 39 tests passed
|
||||
```
|
||||
@@ -0,0 +1,862 @@
|
||||
# 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
|
||||
```
|
||||
|
||||
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>
|
||||
|
||||
# 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 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>=3.5.7" \
|
||||
"praisonai>=3.7.3" \
|
||||
"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>=3.5.7" \
|
||||
"praisonai>=3.7.3" \
|
||||
"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>=3.5.7" \
|
||||
"praisonai>=3.7.3" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[crewai]"
|
||||
|
||||
|
||||
@@ -23,6 +23,7 @@ examples/
|
||||
|
||||
| Category | Examples | Docs |
|
||||
|----------|----------|------|
|
||||
| **Consolidated Params** | [consolidated_params/](consolidated_params/) | [📖](https://docs.praison.ai/api/consolidated-params) |
|
||||
| **Agents** | [python/agents/](python/agents/) | [📖](https://docs.praison.ai/concepts/agents) |
|
||||
| **Workflows** | [python/workflows/](python/workflows/) | [📖](https://docs.praison.ai/features/workflows) |
|
||||
| **Model Router** | [python/agents/router-agent-cost-optimization.py](python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/model-router) |
|
||||
@@ -35,6 +36,21 @@ examples/
|
||||
| **Serve** | [serve/](serve/) | [📖](https://docs.praison.ai/cli/serve) |
|
||||
| **Endpoints** | [serve/](serve/) | [📖](https://docs.praison.ai/cli/endpoints) |
|
||||
|
||||
## Consolidated Params Examples
|
||||
|
||||
Agent-centric API with unified parameter resolution. Precedence: Instance > Config > Array > Dict > String > Bool > Default
|
||||
|
||||
| Example | Description |
|
||||
|---------|-------------|
|
||||
| [basic_agent.py](consolidated_params/basic_agent.py) | Minimal agent with memory |
|
||||
| [basic_agents.py](consolidated_params/basic_agents.py) | Multi-agent with memory+planning |
|
||||
| [basic_workflow.py](consolidated_params/basic_workflow.py) | Workflow with consolidated params |
|
||||
| [basic_memory.py](consolidated_params/basic_memory.py) | Memory presets (file, redis, postgres) |
|
||||
| [basic_guardrails.py](consolidated_params/basic_guardrails.py) | Guardrails with callable or config |
|
||||
| [basic_workflow_agentlike.py](consolidated_params/basic_workflow_agentlike.py) | Workflow with agent-like params |
|
||||
| [basic_step_override.py](consolidated_params/basic_step_override.py) | Step-level override of workflow defaults |
|
||||
| [advanced_workflow_full_features.py](consolidated_params/advanced_workflow_full_features.py) | All consolidated params |
|
||||
|
||||
## Serve Examples
|
||||
|
||||
| Example | Description | CLI Command |
|
||||
|
||||
@@ -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 +1,17 @@
|
||||
"""
|
||||
Advanced Output + Execution Example - Agent-Centric API
|
||||
|
||||
Demonstrates preset + override array syntax.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Advanced: Preset with overrides using array syntax
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
output=["verbose", {"stream": True, "metrics": True}],
|
||||
execution=["thorough", {"max_iter": 30}],
|
||||
)
|
||||
|
||||
response = agent.start("Explain quantum computing in simple terms.")
|
||||
print(response)
|
||||
@@ -0,0 +1,55 @@
|
||||
"""Advanced Workflow with all consolidated params configured."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
from praisonaiagents.workflows.workflow_configs import (
|
||||
WorkflowOutputConfig, WorkflowPlanningConfig, WorkflowMemoryConfig,
|
||||
)
|
||||
|
||||
# Full-featured workflow with all consolidated params
|
||||
workflow = Workflow(
|
||||
name="FullFeaturedWorkflow",
|
||||
description="Demonstrates all agent-like consolidated params",
|
||||
steps=[
|
||||
WorkflowStep(
|
||||
name="researcher",
|
||||
action="Research: {{input}}",
|
||||
agent=Agent(instructions="You are a researcher."),
|
||||
knowledge=["research_docs/"], # Step-specific knowledge
|
||||
web="duckduckgo", # Use DuckDuckGo for this step
|
||||
),
|
||||
WorkflowStep(
|
||||
name="analyzer",
|
||||
action="Analyze the research",
|
||||
agent=Agent(instructions="You are an analyst."),
|
||||
reflection="thorough", # Thorough reflection for analysis
|
||||
guardrails="strict", # Strict validation
|
||||
),
|
||||
WorkflowStep(
|
||||
name="writer",
|
||||
action="Write the final report",
|
||||
agent=Agent(instructions="You are a writer."),
|
||||
autonomy=True, # Enable autonomy for writing
|
||||
),
|
||||
],
|
||||
# Workflow-level consolidated params
|
||||
output=WorkflowOutputConfig(verbose=True, stream=True),
|
||||
planning=WorkflowPlanningConfig(enabled=True, reasoning=True),
|
||||
memory=WorkflowMemoryConfig(backend="file"),
|
||||
# Agent-like params
|
||||
autonomy=True,
|
||||
knowledge=["shared_docs/"],
|
||||
guardrails=True,
|
||||
web=True,
|
||||
reflection=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"Workflow: {workflow.name}")
|
||||
print(f"Output verbose: {workflow._verbose}")
|
||||
print(f"Planning enabled: {workflow._planning_enabled}")
|
||||
print(f"Memory config: {workflow._memory_config}")
|
||||
print(f"Autonomy: {workflow.autonomy}")
|
||||
print(f"Knowledge: {workflow.knowledge}")
|
||||
print(f"Guardrails: {workflow.guardrails}")
|
||||
print(f"Web: {workflow.web}")
|
||||
print(f"Reflection: {workflow.reflection}")
|
||||
@@ -0,0 +1,12 @@
|
||||
"""Basic Agent example with consolidated params."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Minimal agent with memory
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
memory=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.chat("Hello!")
|
||||
print(response)
|
||||
@@ -0,0 +1,17 @@
|
||||
"""Basic Agents (multi-agent) example with consolidated params."""
|
||||
from praisonaiagents import Agent, Agents
|
||||
|
||||
# Create agents
|
||||
writer = Agent(instructions="You write content.")
|
||||
editor = Agent(instructions="You edit content.")
|
||||
|
||||
# Multi-agent with consolidated params
|
||||
agents = Agents(
|
||||
agents=[writer, editor],
|
||||
memory=True,
|
||||
planning=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = agents.start("Write a haiku about AI")
|
||||
print(result)
|
||||
@@ -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 +1,16 @@
|
||||
"""
|
||||
Basic Execution Example - Agent-Centric API
|
||||
|
||||
Demonstrates execution preset usage.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Use fast execution preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
execution="fast", # Presets: fast, balanced, thorough, unlimited
|
||||
)
|
||||
|
||||
response = agent.start("What is the capital of France?")
|
||||
print(response)
|
||||
@@ -0,0 +1,26 @@
|
||||
"""
|
||||
Basic Guardrails Example - Agent-Centric API
|
||||
|
||||
Demonstrates guardrails with callable validator.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Define a simple guardrail validator
|
||||
def validate_response(output):
|
||||
"""Validate that response doesn't contain forbidden words."""
|
||||
forbidden = ["error", "fail", "cannot"]
|
||||
text = str(output).lower()
|
||||
for word in forbidden:
|
||||
if word in text:
|
||||
return (False, f"Response contains forbidden word: {word}")
|
||||
return (True, output)
|
||||
|
||||
# Basic: Use callable guardrail
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
guardrails=validate_response,
|
||||
)
|
||||
|
||||
response = agent.start("What is 2 + 2?")
|
||||
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 +1,21 @@
|
||||
"""
|
||||
Basic Memory Example - Agent-Centric API
|
||||
|
||||
Demonstrates the simplest memory usage with consolidated params.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable memory with preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with memory.",
|
||||
memory="sqlite", # Preset: sqlite, redis, postgres, file
|
||||
)
|
||||
|
||||
# Run a simple task
|
||||
response = agent.start("Remember that my favorite color is blue.")
|
||||
print(response)
|
||||
|
||||
# Follow-up to test memory
|
||||
response = agent.start("What is my favorite color?")
|
||||
print(response)
|
||||
@@ -0,0 +1,16 @@
|
||||
"""
|
||||
Basic Output Example - Agent-Centric API
|
||||
|
||||
Demonstrates output preset usage.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Use verbose output preset
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
output="verbose", # Presets: minimal, normal, verbose, debug, silent
|
||||
)
|
||||
|
||||
response = agent.start("What is 2 + 2?")
|
||||
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 +1,33 @@
|
||||
"""Basic example showing step-level override of workflow defaults."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Workflow with defaults
|
||||
workflow = Workflow(
|
||||
name="StepOverrideWorkflow",
|
||||
steps=[
|
||||
WorkflowStep(
|
||||
name="step1",
|
||||
action="Process with workflow defaults",
|
||||
agent=Agent(instructions="You are a processor."),
|
||||
# Uses workflow-level web=True (inherited)
|
||||
),
|
||||
WorkflowStep(
|
||||
name="step2",
|
||||
action="Process with step override",
|
||||
agent=Agent(instructions="You are a processor."),
|
||||
# Override workflow default
|
||||
web=False, # Disable web for this step
|
||||
reflection="thorough", # Use thorough reflection preset
|
||||
),
|
||||
],
|
||||
# Workflow defaults
|
||||
web=True,
|
||||
reflection=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"Workflow web default: {workflow.web}")
|
||||
print(f"Step1 web: {workflow.steps[0].web}") # None (uses workflow default)
|
||||
print(f"Step2 web: {workflow.steps[1].web}") # False (overridden)
|
||||
print(f"Step2 reflection: {workflow.steps[1].reflection}") # thorough
|
||||
@@ -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 +1,26 @@
|
||||
"""
|
||||
Basic Workflow Example - Agent-Centric API
|
||||
|
||||
Demonstrates minimal workflow with consolidated params.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Create a simple workflow
|
||||
workflow = Workflow(
|
||||
name="simple_workflow",
|
||||
output="verbose", # Workflow-level output preset
|
||||
)
|
||||
|
||||
# Add a step
|
||||
step = WorkflowStep(
|
||||
name="writer",
|
||||
action="Write a haiku about programming",
|
||||
agent=Agent(instructions="You are a creative poet."),
|
||||
output="result.txt", # Save output to file
|
||||
)
|
||||
|
||||
# Note: This is a structural example - actual execution requires workflow.run()
|
||||
print("Workflow created with output preset:", workflow.output)
|
||||
print("Step output file:", step.output_file)
|
||||
@@ -0,0 +1,32 @@
|
||||
"""Basic Workflow with Agent-like consolidated params."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Workflow with agent-like params (knowledge, web, guardrails, reflection)
|
||||
workflow = Workflow(
|
||||
name="AgentLikeWorkflow",
|
||||
steps=[
|
||||
WorkflowStep(
|
||||
name="researcher",
|
||||
action="Research the topic: {{input}}",
|
||||
agent=Agent(instructions="You are a researcher."),
|
||||
),
|
||||
WorkflowStep(
|
||||
name="writer",
|
||||
action="Write about the research findings",
|
||||
agent=Agent(instructions="You are a writer."),
|
||||
),
|
||||
],
|
||||
# Agent-like consolidated params
|
||||
knowledge=["docs/"], # Enable RAG
|
||||
web=True, # Enable web search
|
||||
guardrails=True, # Enable guardrails
|
||||
reflection=True, # Enable self-reflection
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(f"Workflow: {workflow.name}")
|
||||
print(f"Knowledge: {workflow.knowledge}")
|
||||
print(f"Web: {workflow.web}")
|
||||
print(f"Guardrails: {workflow.guardrails}")
|
||||
print(f"Reflection: {workflow.reflection}")
|
||||
@@ -0,0 +1,22 @@
|
||||
"""Sample application."""
|
||||
|
||||
def greet(name: str) -> str:
|
||||
"""Greet someone."""
|
||||
return f"Hello, {name}!"
|
||||
|
||||
def add(a: int, b: int) -> int:
|
||||
"""Add two numbers."""
|
||||
return a + b
|
||||
|
||||
class Calculator:
|
||||
"""Simple calculator."""
|
||||
|
||||
def __init__(self):
|
||||
self.value = 0
|
||||
|
||||
def add(self, x):
|
||||
self.value += x
|
||||
return self.value
|
||||
|
||||
if __name__ == "__main__":
|
||||
print(greet("World"))
|
||||
@@ -0,0 +1,10 @@
|
||||
"""
|
||||
demo_output.py - Auto-generated file
|
||||
"""
|
||||
|
||||
def main():
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,10 @@
|
||||
"""
|
||||
test_demo.py - Auto-generated file
|
||||
"""
|
||||
|
||||
def main():
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,117 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Dict Config Example - Demonstrates dict shorthand for consolidated parameters.
|
||||
|
||||
This example shows how to use dict shorthand instead of importing config classes.
|
||||
Dict input is strictly validated - unknown keys raise helpful errors.
|
||||
|
||||
Requirements:
|
||||
- Set OPENAI_API_KEY environment variable
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
|
||||
def example_dict_output_config():
|
||||
"""Example: Using dict for output configuration."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Dict shorthand - equivalent to OutputConfig(verbose=True, stream=False)
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant.",
|
||||
output={"verbose": True, "stream": False},
|
||||
)
|
||||
|
||||
result = agent.start("Say hello in one word.")
|
||||
print(f"Result: {result}")
|
||||
return agent
|
||||
|
||||
|
||||
def example_dict_execution_config():
|
||||
"""Example: Using dict for execution configuration."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Dict shorthand for execution settings
|
||||
agent = Agent(
|
||||
name="FastAgent",
|
||||
instructions="You are a fast responder.",
|
||||
execution={"max_iter": 5, "timeout": 30},
|
||||
)
|
||||
|
||||
result = agent.start("What is 2+2?")
|
||||
print(f"Result: {result}")
|
||||
return agent
|
||||
|
||||
|
||||
def example_dict_validation_error():
|
||||
"""Example: Dict with unknown key raises helpful error."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
print("\n--- Testing dict validation error ---")
|
||||
try:
|
||||
# This will raise TypeError with helpful message
|
||||
Agent(
|
||||
name="Test",
|
||||
instructions="Test agent",
|
||||
output={"verbose": True, "invalid_key": "value"},
|
||||
)
|
||||
except TypeError as e:
|
||||
print(f"Expected error caught: {e}")
|
||||
# Shows: Unknown keys for output: ['invalid_key']. Valid keys: ...
|
||||
|
||||
|
||||
def example_array_preset_override():
|
||||
"""Example: Array [preset, {overrides}] pattern still works."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Array pattern: preset name + override dict
|
||||
agent = Agent(
|
||||
name="VerboseAgent",
|
||||
instructions="You are verbose.",
|
||||
output=["verbose", {"stream": False}],
|
||||
)
|
||||
|
||||
result = agent.start("Say hi.")
|
||||
print(f"Result: {result}")
|
||||
return agent
|
||||
|
||||
|
||||
def example_base_url_api_key_separate():
|
||||
"""Example: base_url and api_key remain separate parameters."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# base_url and api_key are NOT consolidated - they stay separate
|
||||
# This is intentional for security and clarity
|
||||
agent = Agent(
|
||||
name="CustomEndpoint",
|
||||
instructions="You use a custom endpoint.",
|
||||
llm="gpt-4o-mini",
|
||||
# base_url="http://localhost:11434/v1", # Uncomment for Ollama
|
||||
# api_key=os.getenv("CUSTOM_API_KEY"), # Separate parameter
|
||||
)
|
||||
|
||||
return agent
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Check for API key
|
||||
if not os.getenv("OPENAI_API_KEY"):
|
||||
print("Warning: OPENAI_API_KEY not set. Some examples may fail.")
|
||||
|
||||
print("=== Dict Config Examples ===\n")
|
||||
|
||||
# Run validation error example (doesn't need API key)
|
||||
example_dict_validation_error()
|
||||
|
||||
# Run examples that need API key
|
||||
if os.getenv("OPENAI_API_KEY"):
|
||||
print("\n--- Dict output config ---")
|
||||
example_dict_output_config()
|
||||
|
||||
print("\n--- Array preset override ---")
|
||||
example_array_preset_override()
|
||||
else:
|
||||
print("\nSkipping API examples (no OPENAI_API_KEY)")
|
||||
|
||||
print("\n=== Examples Complete ===")
|
||||
@@ -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")
|
||||
@@ -0,0 +1,14 @@
|
||||
#!/usr/bin/env python3
|
||||
|
||||
from praisonaiagents import Agent
|
||||
|
||||
print("Creating agent...")
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant"
|
||||
)
|
||||
|
||||
print("Starting agent...")
|
||||
result = agent.start("Why is the sky blue?")
|
||||
|
||||
print("Agent completed successfully!")
|
||||
print(f"Result: {result}")
|
||||
Whitespace-only changes.
@@ -0,0 +1,23 @@
|
||||
"""Advanced memory example - with config and overrides."""
|
||||
from praisonaiagents import Agent, MemoryConfig
|
||||
|
||||
# With full config
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with memory.",
|
||||
memory=MemoryConfig(
|
||||
backend="redis",
|
||||
user_id="user123",
|
||||
session_id="session456",
|
||||
auto_memory=True,
|
||||
),
|
||||
)
|
||||
|
||||
# With array [preset, overrides]
|
||||
agent_override = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
memory=["redis", {"user_id": "custom_user"}],
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.chat("Remember that my favorite color is blue.")
|
||||
print(response)
|
||||
@@ -0,0 +1,24 @@
|
||||
"""Basic memory example - minimal usage."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Simple enable (uses default file-based memory)
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant with memory.",
|
||||
memory=True,
|
||||
)
|
||||
|
||||
# With preset
|
||||
agent_redis = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
memory="redis", # Uses redis preset
|
||||
)
|
||||
|
||||
# With URL
|
||||
agent_postgres = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
memory="postgresql://localhost/mydb", # URL auto-detected
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.chat("Remember that my favorite color is blue.")
|
||||
print(response)
|
||||
@@ -0,0 +1,13 @@
|
||||
"""Basic output and execution example."""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Simple preset usage
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant.",
|
||||
output="verbose", # Preset: verbose output
|
||||
execution="thorough", # Preset: thorough execution
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
response = agent.chat("What is 2+2?")
|
||||
print(response)
|
||||
@@ -0,0 +1,22 @@
|
||||
"""Basic workflow example with consolidated params."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.workflows import Workflow, WorkflowStep
|
||||
|
||||
# Create agents
|
||||
writer = Agent(instructions="You are a content writer.")
|
||||
editor = Agent(instructions="You are an editor.")
|
||||
|
||||
# Create workflow with consolidated params
|
||||
workflow = Workflow(
|
||||
name="Content Pipeline",
|
||||
steps=[
|
||||
WorkflowStep(name="write", agent=writer, action="Write about {{topic}}"),
|
||||
WorkflowStep(name="edit", agent=editor, action="Edit the content", context=["write"]),
|
||||
],
|
||||
output="verbose",
|
||||
planning=True,
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = workflow.run(variables={"topic": "AI agents"})
|
||||
print(result)
|
||||
@@ -177,6 +177,13 @@ def __getattr__(name):
|
||||
_lazy_cache["PraisonAIAgents"] = Agents # Also cache alias
|
||||
return Agents
|
||||
elif name == "PraisonAIAgents":
|
||||
import warnings
|
||||
warnings.warn(
|
||||
"PraisonAIAgents is deprecated, use Agents instead. "
|
||||
"Example: from praisonaiagents import Agents",
|
||||
DeprecationWarning,
|
||||
stacklevel=2
|
||||
)
|
||||
from .agents.agents import Agents
|
||||
_lazy_cache["Agents"] = Agents
|
||||
_lazy_cache[name] = Agents
|
||||
@@ -469,6 +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',
|
||||
@@ -639,4 +702,6 @@ __all__ = [
|
||||
# Parse Utilities
|
||||
'is_policy_string',
|
||||
'parse_policy_string',
|
||||
# Performance utilities
|
||||
'warmup',
|
||||
]
|
||||
@@ -0,0 +1,49 @@
|
||||
"""
|
||||
Resolver helper functions for consolidated parameters.
|
||||
|
||||
These helpers wrap the canonical resolver for specific parameter types,
|
||||
handling special cases like callable validators for guardrails.
|
||||
"""
|
||||
|
||||
from typing import Any, Type
|
||||
|
||||
from .config.param_resolver import resolve, ArrayMode
|
||||
from .config.presets import GUARDRAIL_PRESETS
|
||||
|
||||
|
||||
def resolve_guardrails(value: Any, config_class: Type) -> Any:
|
||||
"""
|
||||
Resolve guardrails parameter.
|
||||
|
||||
Handles special case of callable validators which have highest precedence.
|
||||
|
||||
Args:
|
||||
value: The guardrails parameter value
|
||||
config_class: GuardrailConfig class
|
||||
|
||||
Returns:
|
||||
Resolved config, callable, or string
|
||||
"""
|
||||
# Handle None
|
||||
if value is None:
|
||||
return None
|
||||
|
||||
# Handle False (disabled)
|
||||
if value is False:
|
||||
return None
|
||||
|
||||
# Handle callable (highest precedence after None check)
|
||||
# This includes functions, lambdas, and callable objects
|
||||
if callable(value) and not isinstance(value, type):
|
||||
return value
|
||||
|
||||
# Use canonical resolver for everything else
|
||||
return resolve(
|
||||
value=value,
|
||||
param_name="guardrails",
|
||||
config_class=config_class,
|
||||
presets=GUARDRAIL_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
string_mode="llm_prompt",
|
||||
default=None,
|
||||
)
|
||||
@@ -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,
|
||||
@@ -522,34 +523,45 @@ class Agent:
|
||||
cache, prompt_caching = True, None
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve HOOKS param
|
||||
# Supports: None, list of callables, HooksConfig
|
||||
# Resolve HOOKS param using unified resolver
|
||||
# Supports: None, list of callables, HooksConfig, dict
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_hooks_list = []
|
||||
step_callback = None
|
||||
if hooks is not None:
|
||||
if isinstance(hooks, list):
|
||||
_hooks_list = hooks
|
||||
elif isinstance(hooks, HooksConfig):
|
||||
step_callback = hooks.on_step
|
||||
_hooks_list = hooks.middleware or []
|
||||
elif isinstance(hooks, dict):
|
||||
step_callback = hooks.get('on_step')
|
||||
_hooks_list = hooks.get('middleware', [])
|
||||
_hooks_config = resolve(
|
||||
value=hooks,
|
||||
param_name="hooks",
|
||||
config_class=HooksConfig,
|
||||
array_mode=ArrayMode.PASSTHROUGH,
|
||||
default=None,
|
||||
)
|
||||
if _hooks_config is not None:
|
||||
if isinstance(_hooks_config, list):
|
||||
_hooks_list = _hooks_config
|
||||
elif isinstance(_hooks_config, HooksConfig):
|
||||
step_callback = _hooks_config.on_step
|
||||
_hooks_list = _hooks_config.middleware or []
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve SKILLS param
|
||||
# Supports: None, list of paths, SkillsConfig
|
||||
# Resolve SKILLS param using unified resolver
|
||||
# Supports: None, list of paths, SkillsConfig, str
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_skills = None
|
||||
if skills is not None:
|
||||
if isinstance(skills, list):
|
||||
_skills = skills
|
||||
elif isinstance(skills, SkillsConfig):
|
||||
_skills = skills.paths
|
||||
skills_dirs = skills.dirs
|
||||
elif isinstance(skills, str):
|
||||
_skills = [skills]
|
||||
skills_dirs = None
|
||||
_skills_config = resolve(
|
||||
value=skills,
|
||||
param_name="skills",
|
||||
config_class=SkillsConfig,
|
||||
array_mode=ArrayMode.SOURCES,
|
||||
string_mode="path_as_source",
|
||||
default=None,
|
||||
)
|
||||
if _skills_config is not None:
|
||||
if isinstance(_skills_config, SkillsConfig):
|
||||
_skills = _skills_config.paths
|
||||
skills_dirs = _skills_config.dirs
|
||||
elif isinstance(_skills_config, list):
|
||||
_skills = _skills_config
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve MEMORY param using unified resolver
|
||||
@@ -595,36 +607,42 @@ class Agent:
|
||||
memory = None
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve KNOWLEDGE param
|
||||
# Resolve KNOWLEDGE param using unified resolver
|
||||
# Supports: None, bool, str path, list of sources, KnowledgeConfig, Instance
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
retrieval_config = None
|
||||
embedder_config = None
|
||||
|
||||
if knowledge is not None and knowledge is not False:
|
||||
if isinstance(knowledge, list):
|
||||
# List of sources - use directly
|
||||
pass
|
||||
elif hasattr(knowledge, 'search') and hasattr(knowledge, 'add'):
|
||||
_knowledge_config = resolve(
|
||||
value=knowledge,
|
||||
param_name="knowledge",
|
||||
config_class=KnowledgeConfig,
|
||||
instance_check=lambda v: hasattr(v, 'search') and hasattr(v, 'add'),
|
||||
array_mode=ArrayMode.SOURCES_WITH_CONFIG,
|
||||
string_mode="path_as_source",
|
||||
default=None,
|
||||
)
|
||||
|
||||
if _knowledge_config is not None:
|
||||
if hasattr(_knowledge_config, 'search') and hasattr(_knowledge_config, 'add'):
|
||||
# Knowledge instance - pass through
|
||||
pass
|
||||
elif isinstance(knowledge, KnowledgeConfig):
|
||||
embedder_config = knowledge.embedder_config
|
||||
if knowledge.config:
|
||||
retrieval_config = knowledge.config
|
||||
knowledge = _knowledge_config
|
||||
elif isinstance(_knowledge_config, KnowledgeConfig):
|
||||
embedder_config = _knowledge_config.embedder_config
|
||||
if _knowledge_config.config:
|
||||
retrieval_config = _knowledge_config.config
|
||||
else:
|
||||
retrieval_config = {
|
||||
'top_k': knowledge.retrieval_k,
|
||||
'threshold': knowledge.retrieval_threshold,
|
||||
'rerank': knowledge.rerank,
|
||||
'rerank_model': knowledge.rerank_model,
|
||||
'top_k': _knowledge_config.retrieval_k,
|
||||
'threshold': _knowledge_config.retrieval_threshold,
|
||||
'rerank': _knowledge_config.rerank,
|
||||
'rerank_model': _knowledge_config.rerank_model,
|
||||
}
|
||||
knowledge = knowledge.sources if knowledge.sources else None
|
||||
elif isinstance(knowledge, str):
|
||||
# Single path - convert to list
|
||||
knowledge = [knowledge]
|
||||
elif knowledge is True:
|
||||
knowledge = None
|
||||
knowledge = _knowledge_config.sources if _knowledge_config.sources else None
|
||||
elif isinstance(_knowledge_config, list):
|
||||
knowledge = _knowledge_config
|
||||
elif knowledge is False:
|
||||
knowledge = None
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve PLANNING param
|
||||
@@ -681,22 +699,25 @@ class Agent:
|
||||
self_reflect = False
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve GUARDRAILS param
|
||||
# Resolve GUARDRAILS param using unified resolver
|
||||
# Supports: None, bool, callable, str prompt, GuardrailConfig
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
if guardrails is not None:
|
||||
if guardrails is False:
|
||||
guardrail = None
|
||||
elif callable(guardrails):
|
||||
guardrail = guardrails
|
||||
elif isinstance(guardrails, GuardrailConfig):
|
||||
guardrail = guardrails.validator or guardrails.llm_validator
|
||||
max_guardrail_retries = guardrails.max_retries
|
||||
elif isinstance(guardrails, str):
|
||||
# Long string = LLM validator prompt
|
||||
guardrail = guardrails
|
||||
elif guardrails is True:
|
||||
pass # No-op, user must provide validator
|
||||
from .._resolver_helpers import resolve_guardrails as _resolve_guardrails
|
||||
_guardrails_config = _resolve_guardrails(
|
||||
value=guardrails,
|
||||
config_class=GuardrailConfig,
|
||||
)
|
||||
|
||||
if _guardrails_config is not None:
|
||||
if callable(_guardrails_config) and not isinstance(_guardrails_config, type):
|
||||
# Callable validator function
|
||||
guardrail = _guardrails_config
|
||||
elif isinstance(_guardrails_config, GuardrailConfig):
|
||||
guardrail = _guardrails_config.validator or _guardrails_config.llm_validator
|
||||
max_guardrail_retries = _guardrails_config.max_retries
|
||||
elif isinstance(_guardrails_config, str):
|
||||
# LLM validator prompt
|
||||
guardrail = _guardrails_config
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve WEB param using unified resolver
|
||||
@@ -763,13 +784,30 @@ 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:
|
||||
@@ -937,9 +975,14 @@ 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
|
||||
|
||||
@@ -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
|
||||
|
||||
|
||||
@@ -142,6 +142,13 @@ class Agents:
|
||||
output: Optional[Any] = None, # Union[str, MultiAgentOutputConfig]
|
||||
execution: Optional[Any] = None, # Union[str, MultiAgentExecutionConfig]
|
||||
hooks: Optional[Any] = None, # MultiAgentHooksConfig
|
||||
# Additional consolidated params for feature parity with Agent
|
||||
autonomy: Optional[Any] = None, # Union[bool, AutonomyConfig] - agent autonomy
|
||||
knowledge: Optional[Any] = None, # Union[bool, List[str], KnowledgeConfig] - RAG
|
||||
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.
|
||||
@@ -159,13 +166,26 @@ class Agents:
|
||||
output: Output configuration (str | MultiAgentOutputConfig)
|
||||
execution: Execution configuration (str | MultiAgentExecutionConfig)
|
||||
hooks: Hooks configuration (MultiAgentHooksConfig)
|
||||
autonomy: Autonomy configuration (bool | AutonomyConfig)
|
||||
knowledge: Knowledge/RAG configuration (bool | List[str] | KnowledgeConfig)
|
||||
guardrails: Guardrails configuration (bool | Callable | GuardrailConfig)
|
||||
web: Web search/fetch configuration (bool | WebConfig)
|
||||
reflection: Self-reflection configuration (bool | ReflectionConfig)
|
||||
"""
|
||||
# Store new params for propagation to agents
|
||||
self._autonomy = autonomy
|
||||
self._knowledge = knowledge
|
||||
self._guardrails = guardrails
|
||||
self._web = web
|
||||
self._reflection = reflection
|
||||
self._caching = caching
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Extract values from consolidated params using unified resolver
|
||||
# Precedence: Instance > Config > Array > String > Bool > Default
|
||||
# Extract values from consolidated params using UNIFIED CANONICAL resolver
|
||||
# Precedence: Instance > Config > Dict > Array > String > Bool > Default
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
|
||||
# Import presets for unified resolution
|
||||
# Import canonical resolver and presets
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
from ..config.presets import (
|
||||
MULTI_AGENT_OUTPUT_PRESETS, MULTI_AGENT_EXECUTION_PRESETS,
|
||||
MEMORY_PRESETS, MEMORY_URL_SCHEMES,
|
||||
@@ -186,156 +206,118 @@ class Agents:
|
||||
MultiAgentHooksConfig = None
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve OUTPUT param
|
||||
# Resolve OUTPUT param using canonical resolver
|
||||
# Supports: None, str preset, list [preset, overrides], Config, dict
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_verbose = 0
|
||||
_stream = True
|
||||
if output is None:
|
||||
pass # Use defaults
|
||||
elif isinstance(output, str):
|
||||
preset = MULTI_AGENT_OUTPUT_PRESETS.get(output, {})
|
||||
_verbose = preset.get("verbose", 0)
|
||||
_stream = preset.get("stream", True)
|
||||
elif isinstance(output, list) and len(output) >= 1:
|
||||
# Array mode: [preset] or [preset, overrides]
|
||||
preset_name = output[0] if isinstance(output[0], str) else None
|
||||
overrides = output[-1] if len(output) > 1 and isinstance(output[-1], dict) else {}
|
||||
if preset_name and preset_name in MULTI_AGENT_OUTPUT_PRESETS:
|
||||
preset = MULTI_AGENT_OUTPUT_PRESETS[preset_name].copy()
|
||||
preset.update(overrides)
|
||||
_verbose = preset.get("verbose", 0)
|
||||
_stream = preset.get("stream", True)
|
||||
elif MultiAgentOutputConfig and isinstance(output, MultiAgentOutputConfig):
|
||||
_verbose = output.verbose
|
||||
_stream = output.stream
|
||||
elif isinstance(output, dict):
|
||||
_verbose = output.get("verbose", 0)
|
||||
_stream = output.get("stream", True)
|
||||
_output_config = resolve(
|
||||
value=output,
|
||||
param_name="output",
|
||||
config_class=MultiAgentOutputConfig,
|
||||
presets=MULTI_AGENT_OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=MultiAgentOutputConfig() if MultiAgentOutputConfig else None,
|
||||
)
|
||||
if _output_config and hasattr(_output_config, 'verbose'):
|
||||
_verbose = _output_config.verbose
|
||||
_stream = _output_config.stream
|
||||
else:
|
||||
_verbose = 0
|
||||
_stream = True
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve EXECUTION param
|
||||
# Resolve EXECUTION param using canonical resolver
|
||||
# Supports: None, str preset, list [preset, overrides], Config, dict
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_max_iter = 10
|
||||
_max_retries = 5
|
||||
if execution is None:
|
||||
pass # Use defaults
|
||||
elif isinstance(execution, str):
|
||||
preset = MULTI_AGENT_EXECUTION_PRESETS.get(execution, {})
|
||||
_max_iter = preset.get("max_iter", 10)
|
||||
_max_retries = preset.get("max_retries", 5)
|
||||
elif isinstance(execution, list) and len(execution) >= 1:
|
||||
# Array mode: [preset] or [preset, overrides]
|
||||
preset_name = execution[0] if isinstance(execution[0], str) else None
|
||||
overrides = execution[-1] if len(execution) > 1 and isinstance(execution[-1], dict) else {}
|
||||
if preset_name and preset_name in MULTI_AGENT_EXECUTION_PRESETS:
|
||||
preset = MULTI_AGENT_EXECUTION_PRESETS[preset_name].copy()
|
||||
preset.update(overrides)
|
||||
_max_iter = preset.get("max_iter", 10)
|
||||
_max_retries = preset.get("max_retries", 5)
|
||||
elif MultiAgentExecutionConfig and isinstance(execution, MultiAgentExecutionConfig):
|
||||
_max_iter = execution.max_iter
|
||||
_max_retries = execution.max_retries
|
||||
elif isinstance(execution, dict):
|
||||
_max_iter = execution.get("max_iter", 10)
|
||||
_max_retries = execution.get("max_retries", 5)
|
||||
_exec_config = resolve(
|
||||
value=execution,
|
||||
param_name="execution",
|
||||
config_class=MultiAgentExecutionConfig,
|
||||
presets=MULTI_AGENT_EXECUTION_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=MultiAgentExecutionConfig() if MultiAgentExecutionConfig else None,
|
||||
)
|
||||
if _exec_config and hasattr(_exec_config, 'max_iter'):
|
||||
_max_iter = _exec_config.max_iter
|
||||
_max_retries = _exec_config.max_retries
|
||||
else:
|
||||
_max_iter = 10
|
||||
_max_retries = 5
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve HOOKS param
|
||||
# Resolve HOOKS param using canonical resolver
|
||||
# Supports: None, list, Config, dict
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_completion_checker = None
|
||||
_on_task_start = None
|
||||
_on_task_complete = None
|
||||
if hooks is not None:
|
||||
if MultiAgentHooksConfig and isinstance(hooks, MultiAgentHooksConfig):
|
||||
_completion_checker = hooks.completion_checker
|
||||
_on_task_start = hooks.on_task_start
|
||||
_on_task_complete = hooks.on_task_complete
|
||||
elif isinstance(hooks, dict):
|
||||
_completion_checker = hooks.get("completion_checker")
|
||||
_on_task_start = hooks.get("on_task_start")
|
||||
_on_task_complete = hooks.get("on_task_complete")
|
||||
_hooks_config = resolve(
|
||||
value=hooks,
|
||||
param_name="hooks",
|
||||
config_class=MultiAgentHooksConfig,
|
||||
array_mode=ArrayMode.PASSTHROUGH,
|
||||
default=None,
|
||||
)
|
||||
if _hooks_config and hasattr(_hooks_config, 'completion_checker'):
|
||||
_completion_checker = _hooks_config.completion_checker
|
||||
_on_task_start = _hooks_config.on_task_start
|
||||
_on_task_complete = _hooks_config.on_task_complete
|
||||
else:
|
||||
_completion_checker = None
|
||||
_on_task_start = None
|
||||
_on_task_complete = None
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve MEMORY param
|
||||
# Resolve MEMORY param using canonical resolver
|
||||
# Supports: None, bool, str preset/URL, list, Config, dict, Instance
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_memory_config_resolved = resolve(
|
||||
value=memory,
|
||||
param_name="memory",
|
||||
config_class=MultiAgentMemoryConfig,
|
||||
presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES,
|
||||
instance_check=lambda v: hasattr(v, 'database_url'),
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Extract values from resolved memory config
|
||||
_user_id = "praison"
|
||||
_memory_config = None
|
||||
_embedder = None
|
||||
|
||||
if memory is None or memory is False:
|
||||
pass # Disabled
|
||||
elif memory is True:
|
||||
pass # Use defaults
|
||||
elif isinstance(memory, str):
|
||||
# Check for URL
|
||||
if "://" in memory:
|
||||
# URL - extract backend from scheme
|
||||
scheme = memory.split("://")[0].lower()
|
||||
backend = MEMORY_URL_SCHEMES.get(scheme)
|
||||
if backend:
|
||||
_memory_config = {"url": memory, "backend": backend}
|
||||
elif memory in MEMORY_PRESETS:
|
||||
# Preset name
|
||||
_memory_config = MEMORY_PRESETS[memory]
|
||||
elif isinstance(memory, list) and len(memory) >= 1:
|
||||
# Array mode: [URL] or [preset, overrides]
|
||||
first = memory[0]
|
||||
if isinstance(first, str) and "://" in first:
|
||||
scheme = first.split("://")[0].lower()
|
||||
backend = MEMORY_URL_SCHEMES.get(scheme)
|
||||
if backend:
|
||||
_memory_config = {"url": first, "backend": backend}
|
||||
elif MultiAgentMemoryConfig and isinstance(memory, MultiAgentMemoryConfig):
|
||||
_user_id = memory.user_id or "praison"
|
||||
_memory_config = memory.config
|
||||
_embedder = memory.embedder
|
||||
elif isinstance(memory, dict):
|
||||
_user_id = memory.get("user_id", "praison")
|
||||
_memory_config = memory.get("config")
|
||||
_embedder = memory.get("embedder")
|
||||
elif hasattr(memory, 'database_url'):
|
||||
# db() instance
|
||||
_memory_config = {"db_instance": memory}
|
||||
if _memory_config_resolved is not None:
|
||||
if hasattr(_memory_config_resolved, 'database_url'):
|
||||
# db() instance - pass through
|
||||
_memory_config = {"db_instance": _memory_config_resolved}
|
||||
elif MultiAgentMemoryConfig and isinstance(_memory_config_resolved, MultiAgentMemoryConfig):
|
||||
_user_id = _memory_config_resolved.user_id or "praison"
|
||||
_memory_config = _memory_config_resolved.config
|
||||
_embedder = _memory_config_resolved.embedder
|
||||
elif isinstance(_memory_config_resolved, dict):
|
||||
# Dict from preset resolution
|
||||
_memory_config = _memory_config_resolved
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Resolve PLANNING param
|
||||
# Resolve PLANNING param using canonical resolver
|
||||
# Supports: None, bool, str LLM, list, Config, dict
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
_planning_config = resolve(
|
||||
value=planning,
|
||||
param_name="planning",
|
||||
config_class=MultiAgentPlanningConfig,
|
||||
string_mode="llm_model",
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Extract values from resolved planning config
|
||||
_planning_llm = "gpt-4o-mini"
|
||||
_auto_approve_plan = False
|
||||
_planning_tools = None
|
||||
_planning_reasoning = False
|
||||
|
||||
if planning is None or planning is False:
|
||||
pass # Disabled
|
||||
elif planning is True:
|
||||
pass # Use defaults
|
||||
elif isinstance(planning, str):
|
||||
# String = LLM model name
|
||||
_planning_llm = planning
|
||||
elif isinstance(planning, list) and len(planning) >= 1:
|
||||
# Array mode: [llm] or [llm, overrides]
|
||||
if isinstance(planning[0], str):
|
||||
_planning_llm = planning[0]
|
||||
if len(planning) > 1 and isinstance(planning[-1], dict):
|
||||
overrides = planning[-1]
|
||||
_auto_approve_plan = overrides.get("auto_approve", False)
|
||||
_planning_tools = overrides.get("tools")
|
||||
_planning_reasoning = overrides.get("reasoning", False)
|
||||
elif MultiAgentPlanningConfig and isinstance(planning, MultiAgentPlanningConfig):
|
||||
_planning_llm = planning.llm or "gpt-4o-mini"
|
||||
_auto_approve_plan = planning.auto_approve
|
||||
_planning_tools = planning.tools
|
||||
_planning_reasoning = planning.reasoning
|
||||
elif isinstance(planning, dict):
|
||||
_planning_llm = planning.get("llm", "gpt-4o-mini")
|
||||
_auto_approve_plan = planning.get("auto_approve", False)
|
||||
_planning_tools = planning.get("tools")
|
||||
_planning_reasoning = planning.get("reasoning", False)
|
||||
if _planning_config is not None:
|
||||
if MultiAgentPlanningConfig and isinstance(_planning_config, MultiAgentPlanningConfig):
|
||||
_planning_llm = _planning_config.llm or "gpt-4o-mini"
|
||||
_auto_approve_plan = _planning_config.auto_approve
|
||||
_planning_tools = _planning_config.tools
|
||||
_planning_reasoning = _planning_config.reasoning
|
||||
|
||||
# ─────────────────────────────────────────────────────────────────────
|
||||
# Memory dependency check
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
"""
|
||||
Unified Parameter Resolver for Consolidated Parameters.
|
||||
|
||||
Implements the precedence rules: Instance > Config > Array > String > Bool > Default
|
||||
Implements the precedence rules: Instance > Config > Dict > Array > String > Bool > Default
|
||||
|
||||
This is the SINGLE, DRY resolver used by:
|
||||
- Agent
|
||||
@@ -12,7 +12,8 @@ This is the SINGLE, DRY resolver used by:
|
||||
Performance: O(1) happy path. Typo suggestions only on error path.
|
||||
"""
|
||||
|
||||
from typing import Any, Callable, Dict, Optional, Type, Union
|
||||
from typing import Any, Callable, Dict, Optional, Set, Type, Union
|
||||
import inspect
|
||||
|
||||
from .parse_utils import (
|
||||
detect_url_scheme,
|
||||
@@ -53,7 +54,7 @@ def resolve(
|
||||
) -> Any:
|
||||
"""
|
||||
Resolve a consolidated parameter following precedence rules:
|
||||
Instance > Config > Array > String > Bool > Default
|
||||
Instance > Config > Array > Dict > String > Bool > Default
|
||||
|
||||
Args:
|
||||
value: The parameter value
|
||||
@@ -91,19 +92,7 @@ def resolve(
|
||||
return value
|
||||
|
||||
# =========================================================================
|
||||
# 4. Dict -> convert to config
|
||||
# =========================================================================
|
||||
if isinstance(value, dict) and config_class:
|
||||
try:
|
||||
return config_class(**value)
|
||||
except TypeError as e:
|
||||
raise ValueError(
|
||||
f"Invalid {param_name} dict: {e}. "
|
||||
f"Valid fields: {_get_config_fields(config_class)}"
|
||||
)
|
||||
|
||||
# =========================================================================
|
||||
# 5. Array handling (before string to respect precedence)
|
||||
# 4. Array handling (BEFORE Dict per AC-1 precedence)
|
||||
# =========================================================================
|
||||
if isinstance(value, (list, tuple)):
|
||||
return _resolve_array(
|
||||
@@ -115,6 +104,35 @@ def resolve(
|
||||
array_mode=array_mode,
|
||||
)
|
||||
|
||||
# =========================================================================
|
||||
# 5. Dict -> convert to config (STRICT validation)
|
||||
# =========================================================================
|
||||
if isinstance(value, dict):
|
||||
if config_class:
|
||||
# Validate keys BEFORE construction for helpful errors
|
||||
unknown_keys = _validate_dict_keys(value, config_class)
|
||||
if unknown_keys:
|
||||
valid_fields = _get_config_fields(config_class)
|
||||
example = _get_example_dict(config_class)
|
||||
raise TypeError(
|
||||
f"Unknown keys for {param_name}: {unknown_keys}. "
|
||||
f"Valid keys: {valid_fields}. "
|
||||
f"Example: {param_name}={{{example}}}"
|
||||
)
|
||||
try:
|
||||
return config_class(**value)
|
||||
except TypeError as e:
|
||||
raise TypeError(
|
||||
f"Invalid {param_name} dict: {e}. "
|
||||
f"Valid fields: {_get_config_fields(config_class)}"
|
||||
)
|
||||
else:
|
||||
# No config class - dict input not supported
|
||||
raise TypeError(
|
||||
f"Dict input not supported for {param_name} (no config class defined). "
|
||||
f"Use a supported type: bool, str, or instance."
|
||||
)
|
||||
|
||||
# =========================================================================
|
||||
# 6. String handling
|
||||
# =========================================================================
|
||||
@@ -203,7 +221,7 @@ def _resolve_array(
|
||||
return config_class(sources=sources, **config_override)
|
||||
return sources
|
||||
|
||||
# Single or list mode
|
||||
# Single or list mode - SINGLE item only, multiple items raise error
|
||||
if array_mode == ArrayMode.SINGLE_OR_LIST:
|
||||
if len(value) == 1:
|
||||
single_value = value[0]
|
||||
@@ -215,10 +233,17 @@ def _resolve_array(
|
||||
# Check if single item is a preset
|
||||
if isinstance(single_value, str) and presets and single_value in presets:
|
||||
return _apply_preset(single_value, presets, config_class)
|
||||
# Multiple items - treat as sources
|
||||
if config_class:
|
||||
return config_class(sources=list(value))
|
||||
return list(value)
|
||||
# Single non-preset string - try as URL or return as-is
|
||||
if isinstance(single_value, str):
|
||||
if config_class:
|
||||
return config_class()
|
||||
return single_value
|
||||
# Multiple items - ERROR (not allowed for SINGLE_OR_LIST mode)
|
||||
raise TypeError(
|
||||
f"Multiple values not allowed for {param_name}. "
|
||||
f"Use a single value: {param_name}='preset' or {param_name}='url://...' "
|
||||
f"Got {len(value)} items: {value}"
|
||||
)
|
||||
|
||||
# Preset override mode - [preset, {overrides}] or [preset]
|
||||
if array_mode == ArrayMode.PRESET_OVERRIDE:
|
||||
@@ -384,6 +409,81 @@ def _get_config_fields(config_class: Type) -> str:
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _get_valid_keys(config_class: Type) -> Optional[Set[str]]:
|
||||
"""
|
||||
Get valid keys from a config class.
|
||||
|
||||
Supports:
|
||||
- Dataclasses (via __dataclass_fields__)
|
||||
- Regular classes (via __init__ signature)
|
||||
- Classes with __annotations__
|
||||
|
||||
Returns:
|
||||
Set of valid key names, or None if cannot determine.
|
||||
"""
|
||||
# 1. Dataclass fields (most common)
|
||||
if hasattr(config_class, '__dataclass_fields__'):
|
||||
return set(config_class.__dataclass_fields__.keys())
|
||||
|
||||
# 2. __init__ signature parameters
|
||||
try:
|
||||
sig = inspect.signature(config_class.__init__)
|
||||
params = set(sig.parameters.keys()) - {'self'}
|
||||
if params:
|
||||
return params
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
|
||||
# 3. Class annotations
|
||||
if hasattr(config_class, '__annotations__'):
|
||||
return set(config_class.__annotations__.keys())
|
||||
|
||||
# Cannot determine valid keys
|
||||
return None
|
||||
|
||||
|
||||
def _validate_dict_keys(value: dict, config_class: Type) -> list:
|
||||
"""
|
||||
Validate dict keys against config class fields.
|
||||
Returns list of unknown keys (empty if all valid).
|
||||
O(n) where n = number of keys in dict (typically small).
|
||||
|
||||
Works for both dataclasses and regular classes.
|
||||
"""
|
||||
valid_keys = _get_valid_keys(config_class)
|
||||
if valid_keys is None:
|
||||
return [] # Cannot validate, allow all keys
|
||||
|
||||
provided_keys = set(value.keys())
|
||||
unknown = provided_keys - valid_keys
|
||||
return list(unknown)
|
||||
|
||||
|
||||
def _get_example_dict(config_class: Type) -> str:
|
||||
"""
|
||||
Generate a minimal example dict snippet for error messages.
|
||||
Shows first 2-3 fields with placeholder values.
|
||||
"""
|
||||
if not hasattr(config_class, '__dataclass_fields__'):
|
||||
return "..."
|
||||
|
||||
fields = list(config_class.__dataclass_fields__.items())[:3]
|
||||
examples = []
|
||||
for name, field in fields:
|
||||
# Generate appropriate placeholder based on type hint
|
||||
field_type = field.type if hasattr(field, 'type') else None
|
||||
if field_type is bool or str(field_type) == 'bool':
|
||||
examples.append(f"'{name}': True")
|
||||
elif field_type is int or str(field_type) == 'int':
|
||||
examples.append(f"'{name}': 1")
|
||||
elif field_type is str or 'str' in str(field_type):
|
||||
examples.append(f"'{name}': '...'")
|
||||
else:
|
||||
examples.append(f"'{name}': ...")
|
||||
|
||||
return ", ".join(examples)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Convenience Functions for Specific Parameters
|
||||
# =============================================================================
|
||||
|
||||
@@ -76,6 +76,14 @@ 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,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
|
||||
@@ -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 +633,74 @@ 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
|
||||
|
||||
# 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()
|
||||
|
||||
# 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 +711,54 @@ 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 _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:
|
||||
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 +777,8 @@ 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 +793,18 @@ 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 +812,19 @@ 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 +832,81 @@ 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 +920,50 @@ 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
|
||||
|
||||
@@ -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
|
||||
@@ -12,7 +12,9 @@ Provides dataclasses for consolidated workflow feature configuration:
|
||||
- WorkflowStepRoutingConfig: Step routing/branching settings
|
||||
|
||||
All configs follow the workflow-centric pattern with precedence:
|
||||
Instance > Config > String > Bool > Default
|
||||
Instance > Config > Dict > Array > String > Bool > Default
|
||||
|
||||
Uses the CANONICAL resolver from param_resolver.py for DRY resolution.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents import Workflow, WorkflowOutputConfig
|
||||
@@ -263,7 +265,7 @@ class WorkflowStepRoutingConfig:
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Precedence Resolution Helper
|
||||
# Precedence Resolution Helper - Uses CANONICAL resolver
|
||||
# =============================================================================
|
||||
|
||||
def resolve_param(
|
||||
@@ -275,245 +277,173 @@ def resolve_param(
|
||||
array_mode: Optional[str] = None,
|
||||
) -> Any:
|
||||
"""
|
||||
Resolve a consolidated parameter following precedence rules:
|
||||
Instance > Config > Array > String > Bool > Default
|
||||
Resolve a consolidated parameter following precedence rules.
|
||||
|
||||
Args:
|
||||
value: The parameter value (can be Instance, Config, Array, String, Bool, or None)
|
||||
config_class: The expected config dataclass type
|
||||
presets: Dict mapping preset strings to config instances or dicts
|
||||
default: Default value if None/unset
|
||||
instance_check: Optional function to check if value is an instance
|
||||
array_mode: How to handle arrays ("preset_override", "step_names", "passthrough")
|
||||
|
||||
Returns:
|
||||
Resolved config object or value
|
||||
|
||||
Example:
|
||||
# Resolve output param
|
||||
output_config = resolve_param(
|
||||
value=output,
|
||||
config_class=WorkflowOutputConfig,
|
||||
presets={
|
||||
"silent": WorkflowOutputConfig(verbose=False, stream=False),
|
||||
"verbose": WorkflowOutputConfig(verbose=True, stream=True),
|
||||
},
|
||||
default=WorkflowOutputConfig(),
|
||||
)
|
||||
|
||||
# With array override
|
||||
output_config = resolve_param(
|
||||
value=["verbose", {"stream": False}],
|
||||
config_class=WorkflowOutputConfig,
|
||||
presets=presets,
|
||||
array_mode="preset_override",
|
||||
)
|
||||
DEPRECATED: This is a wrapper around the canonical resolver for backward compatibility.
|
||||
New code should use `from ..config.param_resolver import resolve` directly.
|
||||
|
||||
Precedence: Instance > Config > Dict > Array > String > Bool > Default
|
||||
"""
|
||||
# None/unset -> Default
|
||||
if value is None:
|
||||
return default
|
||||
# Import canonical resolver
|
||||
from ..config.param_resolver import resolve as canonical_resolve, ArrayMode
|
||||
|
||||
# Instance check (e.g., pre-built manager object)
|
||||
if instance_check and instance_check(value):
|
||||
return value
|
||||
# Map string array_mode to ArrayMode enum
|
||||
array_mode_map = {
|
||||
"preset_override": ArrayMode.PRESET_OVERRIDE,
|
||||
"step_names": ArrayMode.STEP_NAMES,
|
||||
"passthrough": ArrayMode.PASSTHROUGH,
|
||||
}
|
||||
canonical_array_mode = array_mode_map.get(array_mode) if array_mode else None
|
||||
|
||||
# Config dataclass
|
||||
if isinstance(value, config_class):
|
||||
return value
|
||||
# Convert presets from config instances to dicts for canonical resolver
|
||||
presets_dict = None
|
||||
if presets:
|
||||
presets_dict = {}
|
||||
for key, val in presets.items():
|
||||
if hasattr(val, 'to_dict'):
|
||||
presets_dict[key] = val.to_dict()
|
||||
elif hasattr(val, '__dataclass_fields__'):
|
||||
from dataclasses import asdict
|
||||
presets_dict[key] = asdict(val)
|
||||
else:
|
||||
presets_dict[key] = val
|
||||
|
||||
# Dict -> convert to config
|
||||
if isinstance(value, dict):
|
||||
try:
|
||||
return config_class(**value)
|
||||
except TypeError:
|
||||
return default
|
||||
|
||||
# Array handling (NEW - before string to respect precedence)
|
||||
if isinstance(value, (list, tuple)):
|
||||
if not value:
|
||||
return None # Empty array = disabled
|
||||
|
||||
# Passthrough mode - return list as-is
|
||||
if array_mode == "passthrough":
|
||||
return list(value)
|
||||
|
||||
# Step names mode - for context/routing
|
||||
if array_mode == "step_names":
|
||||
# All strings = step names
|
||||
if all(isinstance(item, str) for item in value):
|
||||
return value # Return list directly for step names
|
||||
|
||||
# Preset override mode - [preset, {overrides}]
|
||||
if array_mode == "preset_override" and presets:
|
||||
first = value[0]
|
||||
if isinstance(first, str) and first in presets:
|
||||
# Get base config from preset
|
||||
preset_value = presets[first]
|
||||
if isinstance(preset_value, dict):
|
||||
base_config = config_class(**preset_value)
|
||||
elif isinstance(preset_value, config_class):
|
||||
base_config = preset_value
|
||||
else:
|
||||
base_config = config_class()
|
||||
|
||||
# Apply overrides if present
|
||||
if len(value) >= 2 and isinstance(value[-1], dict):
|
||||
overrides = value[-1]
|
||||
# Merge base with overrides
|
||||
from dataclasses import asdict
|
||||
base_dict = asdict(base_config)
|
||||
base_dict.update(overrides)
|
||||
return config_class(**base_dict)
|
||||
|
||||
return base_config
|
||||
|
||||
# Default: treat first item as value
|
||||
if len(value) == 1:
|
||||
return resolve_param(value[0], config_class, presets, default, instance_check)
|
||||
|
||||
return default
|
||||
|
||||
# String -> preset lookup
|
||||
if isinstance(value, str) and presets:
|
||||
preset_value = presets.get(value)
|
||||
if preset_value is not None:
|
||||
if isinstance(preset_value, dict):
|
||||
return config_class(**preset_value)
|
||||
return preset_value
|
||||
return default
|
||||
|
||||
# Bool -> True enables defaults, False disables
|
||||
if isinstance(value, bool):
|
||||
if value:
|
||||
return config_class() if config_class else True
|
||||
return None # Disabled
|
||||
|
||||
# Fallback to default
|
||||
return default
|
||||
return canonical_resolve(
|
||||
value=value,
|
||||
param_name="workflow_param",
|
||||
config_class=config_class,
|
||||
presets=presets_dict,
|
||||
default=default,
|
||||
instance_check=instance_check,
|
||||
array_mode=canonical_array_mode,
|
||||
)
|
||||
|
||||
|
||||
def resolve_output_config(value: Any) -> WorkflowOutputConfig:
|
||||
"""Resolve output parameter to WorkflowOutputConfig.
|
||||
"""Resolve output parameter to WorkflowOutputConfig using canonical resolver.
|
||||
|
||||
Supports: None, str preset, list [preset, overrides], Config, dict
|
||||
"""
|
||||
presets = {
|
||||
"silent": WorkflowOutputConfig(verbose=False, stream=False),
|
||||
"minimal": WorkflowOutputConfig(verbose=False, stream=True),
|
||||
"normal": WorkflowOutputConfig(verbose=False, stream=True),
|
||||
"verbose": WorkflowOutputConfig(verbose=True, stream=True),
|
||||
"debug": WorkflowOutputConfig(verbose=True, stream=True),
|
||||
}
|
||||
result = resolve_param(
|
||||
value, WorkflowOutputConfig, presets, WorkflowOutputConfig(),
|
||||
array_mode="preset_override"
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
from ..config.presets import WORKFLOW_OUTPUT_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="output",
|
||||
config_class=WorkflowOutputConfig,
|
||||
presets=WORKFLOW_OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=WorkflowOutputConfig(),
|
||||
)
|
||||
return result if result else WorkflowOutputConfig(verbose=False, stream=False)
|
||||
|
||||
|
||||
def resolve_planning_config(value: Any) -> Optional[WorkflowPlanningConfig]:
|
||||
"""Resolve planning parameter to WorkflowPlanningConfig or None."""
|
||||
if value is None or value is False:
|
||||
return None
|
||||
if value is True:
|
||||
return WorkflowPlanningConfig(enabled=True)
|
||||
if isinstance(value, WorkflowPlanningConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowPlanningConfig(**value)
|
||||
if isinstance(value, str):
|
||||
# String is treated as LLM model name
|
||||
return WorkflowPlanningConfig(enabled=True, llm=value)
|
||||
return None
|
||||
"""Resolve planning parameter to WorkflowPlanningConfig using canonical resolver."""
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="planning",
|
||||
config_class=WorkflowPlanningConfig,
|
||||
string_mode="llm_model",
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=None,
|
||||
)
|
||||
return result
|
||||
|
||||
|
||||
def resolve_memory_config(value: Any) -> Optional[WorkflowMemoryConfig]:
|
||||
"""Resolve memory parameter to WorkflowMemoryConfig or None."""
|
||||
if value is None or value is False:
|
||||
return None
|
||||
if value is True:
|
||||
return WorkflowMemoryConfig()
|
||||
if isinstance(value, WorkflowMemoryConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowMemoryConfig(**value)
|
||||
# Instance check - if it has search/add methods, it's a memory instance
|
||||
if hasattr(value, 'search') and hasattr(value, 'add'):
|
||||
return value # Return instance directly
|
||||
return None
|
||||
"""Resolve memory parameter to WorkflowMemoryConfig using canonical resolver."""
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
from ..config.presets import MEMORY_PRESETS, MEMORY_URL_SCHEMES
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="memory",
|
||||
config_class=WorkflowMemoryConfig,
|
||||
presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES,
|
||||
instance_check=lambda v: hasattr(v, 'search') and hasattr(v, 'add'),
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
default=None,
|
||||
)
|
||||
return result
|
||||
|
||||
|
||||
def resolve_hooks_config(value: Any) -> Optional[WorkflowHooksConfig]:
|
||||
"""Resolve hooks parameter to WorkflowHooksConfig or None."""
|
||||
if value is None:
|
||||
return None
|
||||
if isinstance(value, WorkflowHooksConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowHooksConfig(**value)
|
||||
return None
|
||||
"""Resolve hooks parameter to WorkflowHooksConfig using canonical resolver."""
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="hooks",
|
||||
config_class=WorkflowHooksConfig,
|
||||
array_mode=ArrayMode.PASSTHROUGH,
|
||||
default=None,
|
||||
)
|
||||
return result
|
||||
|
||||
|
||||
def resolve_step_context_config(value: Any) -> Optional[WorkflowStepContextConfig]:
|
||||
"""Resolve step context parameter."""
|
||||
if value is None or value is False:
|
||||
return None
|
||||
if value is True:
|
||||
return WorkflowStepContextConfig()
|
||||
if isinstance(value, WorkflowStepContextConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowStepContextConfig(**value)
|
||||
if isinstance(value, list):
|
||||
# List of step names
|
||||
return WorkflowStepContextConfig(from_steps=value)
|
||||
return None
|
||||
"""Resolve step context parameter using canonical resolver."""
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="context",
|
||||
config_class=WorkflowStepContextConfig,
|
||||
array_mode=ArrayMode.STEP_NAMES,
|
||||
default=None,
|
||||
)
|
||||
return result
|
||||
|
||||
|
||||
def resolve_step_output_config(value: Any) -> Optional[WorkflowStepOutputConfig]:
|
||||
"""Resolve step output parameter."""
|
||||
if value is None:
|
||||
return None
|
||||
if isinstance(value, WorkflowStepOutputConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowStepOutputConfig(**value)
|
||||
if isinstance(value, str):
|
||||
# String is treated as output file
|
||||
"""Resolve step output parameter using canonical resolver."""
|
||||
from ..config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="output",
|
||||
config_class=WorkflowStepOutputConfig,
|
||||
string_mode="path_as_source", # String treated as output file
|
||||
default=None,
|
||||
)
|
||||
# Handle string -> file conversion for backward compatibility
|
||||
if isinstance(value, str) and result is None:
|
||||
return WorkflowStepOutputConfig(file=value)
|
||||
return None
|
||||
return result
|
||||
|
||||
|
||||
def resolve_step_execution_config(value: Any) -> WorkflowStepExecutionConfig:
|
||||
"""Resolve step execution parameter."""
|
||||
presets = {
|
||||
"fast": WorkflowStepExecutionConfig(max_retries=1, quality_check=False),
|
||||
"balanced": WorkflowStepExecutionConfig(max_retries=3, quality_check=True),
|
||||
"thorough": WorkflowStepExecutionConfig(max_retries=5, quality_check=True),
|
||||
}
|
||||
if value is None:
|
||||
return WorkflowStepExecutionConfig()
|
||||
if isinstance(value, WorkflowStepExecutionConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowStepExecutionConfig(**value)
|
||||
if isinstance(value, str) and value in presets:
|
||||
return presets[value]
|
||||
return WorkflowStepExecutionConfig()
|
||||
"""Resolve step execution parameter using canonical resolver."""
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
from ..config.presets import WORKFLOW_STEP_EXECUTION_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="execution",
|
||||
config_class=WorkflowStepExecutionConfig,
|
||||
presets=WORKFLOW_STEP_EXECUTION_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
default=WorkflowStepExecutionConfig(),
|
||||
)
|
||||
return result if result else WorkflowStepExecutionConfig()
|
||||
|
||||
|
||||
def resolve_step_routing_config(value: Any) -> Optional[WorkflowStepRoutingConfig]:
|
||||
"""Resolve step routing parameter."""
|
||||
if value is None:
|
||||
return None
|
||||
if isinstance(value, WorkflowStepRoutingConfig):
|
||||
return value
|
||||
if isinstance(value, dict):
|
||||
return WorkflowStepRoutingConfig(**value)
|
||||
if isinstance(value, list):
|
||||
# List of next step names
|
||||
return WorkflowStepRoutingConfig(next_steps=value)
|
||||
return None
|
||||
"""Resolve step routing parameter using canonical resolver."""
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=value,
|
||||
param_name="routing",
|
||||
config_class=WorkflowStepRoutingConfig,
|
||||
array_mode=ArrayMode.STEP_NAMES,
|
||||
default=None,
|
||||
)
|
||||
return result
|
||||
|
||||
|
||||
# =============================================================================
|
||||
|
||||
@@ -231,20 +231,33 @@ class WorkflowStep:
|
||||
loop_over: Optional[str] = None # Variable name to iterate over (e.g., "items")
|
||||
loop_var: str = "item" # Variable name for current item in loop
|
||||
|
||||
# Guardrail (like process="workflow")
|
||||
guardrail: Optional[Callable[['StepResult'], Tuple[bool, Any]]] = None # Returns (is_valid, feedback)
|
||||
# Guardrails (standardized plural naming)
|
||||
# Accepts: callable, str (LLM prompt), GuardrailConfig, or list [preset, overrides]
|
||||
guardrails: Optional[Any] = None # Union[Callable, str, GuardrailConfig] - validation
|
||||
|
||||
# Backward compatibility alias (deprecated - use guardrails instead)
|
||||
guardrail: Optional[Callable[['StepResult'], Tuple[bool, Any]]] = None # DEPRECATED: use guardrails
|
||||
|
||||
# Image handling (migrated from Task)
|
||||
images: Optional[List[str]] = None # Image paths/URLs for vision tasks
|
||||
|
||||
# ============================================================
|
||||
# CONSOLIDATED FEATURE PARAMS (workflow-centric API)
|
||||
# Precedence: Instance > Config > String > Bool > Default
|
||||
# Precedence: Instance > Config > Array > Dict > String > Bool > Default
|
||||
# ============================================================
|
||||
context: Optional[Any] = None # Union[bool, List[str], WorkflowStepContextConfig] - context handling
|
||||
output: Optional[Any] = None # Union[str, WorkflowStepOutputConfig] - output handling
|
||||
execution: Optional[Any] = None # Union[str, WorkflowStepExecutionConfig] - execution control
|
||||
routing: Optional[Any] = None # Union[List[str], WorkflowStepRoutingConfig] - branching
|
||||
# NEW: Agent-like consolidated params for feature parity
|
||||
autonomy: Optional[Any] = None # Union[bool, AutonomyConfig] - agent autonomy
|
||||
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
|
||||
@@ -264,6 +277,15 @@ class WorkflowStep:
|
||||
_on_error: str = field(default="stop", repr=False)
|
||||
_next_steps: Optional[List[str]] = field(default=None, repr=False)
|
||||
_branch_condition: Optional[Dict[str, List[str]]] = field(default=None, repr=False)
|
||||
# NEW: Resolved configs for agent-like params
|
||||
_autonomy_config: Optional[Any] = field(default=None, repr=False)
|
||||
_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."""
|
||||
@@ -272,6 +294,18 @@ class WorkflowStep:
|
||||
resolve_step_execution_config, resolve_step_routing_config,
|
||||
)
|
||||
|
||||
# Handle guardrails/guardrail compatibility
|
||||
# guardrails (plural) takes precedence; guardrail (singular) is deprecated
|
||||
if self.guardrails is None and self.guardrail is not None:
|
||||
# Use deprecated guardrail value, map to guardrails
|
||||
import warnings
|
||||
warnings.warn(
|
||||
"WorkflowStep 'guardrail' parameter is deprecated. Use 'guardrails' instead.",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
object.__setattr__(self, 'guardrails', self.guardrail)
|
||||
|
||||
# Resolve context param
|
||||
ctx_cfg = resolve_step_context_config(self.context)
|
||||
if ctx_cfg:
|
||||
@@ -300,6 +334,106 @@ class WorkflowStep:
|
||||
if route_cfg:
|
||||
self._next_steps = route_cfg.next_steps
|
||||
self._branch_condition = route_cfg.branches
|
||||
|
||||
# Resolve NEW agent-like params using canonical resolver
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
from ..config.presets import (
|
||||
WEB_PRESETS, REFLECTION_PRESETS, AUTONOMY_PRESETS, KNOWLEDGE_PRESETS,
|
||||
)
|
||||
try:
|
||||
from ..config.feature_configs import (
|
||||
AutonomyConfig, KnowledgeConfig, WebConfig, ReflectionConfig,
|
||||
)
|
||||
except ImportError:
|
||||
AutonomyConfig = KnowledgeConfig = WebConfig = ReflectionConfig = None
|
||||
|
||||
# Resolve autonomy
|
||||
if AutonomyConfig and self.autonomy is not None:
|
||||
self._autonomy_config = resolve(
|
||||
value=self.autonomy, param_name="autonomy",
|
||||
config_class=AutonomyConfig, presets=AUTONOMY_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve knowledge
|
||||
if KnowledgeConfig and self.knowledge is not None:
|
||||
self._knowledge_config = resolve(
|
||||
value=self.knowledge, param_name="knowledge",
|
||||
config_class=KnowledgeConfig, presets=KNOWLEDGE_PRESETS,
|
||||
array_mode=ArrayMode.SOURCES, default=None,
|
||||
)
|
||||
|
||||
# Resolve web
|
||||
if WebConfig and self.web is not None:
|
||||
self._web_config = resolve(
|
||||
value=self.web, param_name="web",
|
||||
config_class=WebConfig, presets=WEB_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve reflection
|
||||
if ReflectionConfig and self.reflection is not None:
|
||||
self._reflection_config = resolve(
|
||||
value=self.reflection, param_name="reflection",
|
||||
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
|
||||
@@ -423,13 +557,22 @@ class Workflow:
|
||||
|
||||
# ============================================================
|
||||
# CONSOLIDATED FEATURE PARAMS (workflow-centric API)
|
||||
# Precedence: Instance > Config > String > Bool > Default
|
||||
# Precedence: Instance > Config > Array > Dict > String > Bool > Default
|
||||
# Workflow is "Agents in an organised way" - supports same params as Agents
|
||||
# ============================================================
|
||||
output: Optional[Any] = None # Union[str, WorkflowOutputConfig] - verbose/stream
|
||||
planning: Optional[Any] = False # Union[bool, str, WorkflowPlanningConfig] - planning mode
|
||||
memory: Optional[Any] = None # Union[bool, WorkflowMemoryConfig, instance] - memory
|
||||
hooks: Optional[Any] = None # WorkflowHooksConfig - lifecycle callbacks
|
||||
context: Optional[Any] = False # Union[bool, ManagerConfig, ContextManager] - context management
|
||||
# NEW: Agent-like consolidated params for feature parity
|
||||
autonomy: Optional[Any] = None # Union[bool, AutonomyConfig] - agent autonomy
|
||||
knowledge: Optional[Any] = None # Union[bool, List[str], KnowledgeConfig] - RAG
|
||||
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
|
||||
@@ -445,6 +588,12 @@ class Workflow:
|
||||
_hooks_config: Optional[Any] = field(default=None, repr=False)
|
||||
_context_manager: Optional[Any] = field(default=None, repr=False)
|
||||
_context_manager_initialized: bool = field(default=False, repr=False)
|
||||
# NEW: Resolved configs for agent-like params (for propagation to steps/agents)
|
||||
_autonomy_config: Optional[Any] = field(default=None, repr=False)
|
||||
_knowledge_config: Optional[Any] = field(default=None, repr=False)
|
||||
_guardrails_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)
|
||||
|
||||
def __post_init__(self):
|
||||
"""Resolve consolidated params to internal values."""
|
||||
@@ -474,6 +623,62 @@ class Workflow:
|
||||
|
||||
# Resolve hooks param
|
||||
self._hooks_config = resolve_hooks_config(self.hooks)
|
||||
|
||||
# Resolve NEW agent-like params using canonical resolver
|
||||
# These are stored for propagation to steps/agents
|
||||
from ..config.param_resolver import resolve, ArrayMode
|
||||
from ..config.presets import (
|
||||
WEB_PRESETS, REFLECTION_PRESETS, GUARDRAIL_PRESETS,
|
||||
AUTONOMY_PRESETS, KNOWLEDGE_PRESETS,
|
||||
)
|
||||
try:
|
||||
from ..config.feature_configs import (
|
||||
AutonomyConfig, KnowledgeConfig, GuardrailConfig,
|
||||
WebConfig, ReflectionConfig,
|
||||
)
|
||||
except ImportError:
|
||||
AutonomyConfig = KnowledgeConfig = GuardrailConfig = None
|
||||
WebConfig = ReflectionConfig = None
|
||||
|
||||
# Resolve autonomy
|
||||
if AutonomyConfig and self.autonomy is not None:
|
||||
self._autonomy_config = resolve(
|
||||
value=self.autonomy, param_name="autonomy",
|
||||
config_class=AutonomyConfig, presets=AUTONOMY_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve knowledge
|
||||
if KnowledgeConfig and self.knowledge is not None:
|
||||
self._knowledge_config = resolve(
|
||||
value=self.knowledge, param_name="knowledge",
|
||||
config_class=KnowledgeConfig, presets=KNOWLEDGE_PRESETS,
|
||||
array_mode=ArrayMode.SOURCES, default=None,
|
||||
)
|
||||
|
||||
# Resolve guardrails
|
||||
if GuardrailConfig and self.guardrails is not None:
|
||||
self._guardrails_config = resolve(
|
||||
value=self.guardrails, param_name="guardrails",
|
||||
config_class=GuardrailConfig, presets=GUARDRAIL_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve web
|
||||
if WebConfig and self.web is not None:
|
||||
self._web_config = resolve(
|
||||
value=self.web, param_name="web",
|
||||
config_class=WebConfig, presets=WEB_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
# Resolve reflection
|
||||
if ReflectionConfig and self.reflection is not None:
|
||||
self._reflection_config = resolve(
|
||||
value=self.reflection, param_name="reflection",
|
||||
config_class=ReflectionConfig, presets=REFLECTION_PRESETS,
|
||||
default=None,
|
||||
)
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
|
||||
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "praisonaiagents"
|
||||
version = "0.10.6"
|
||||
version = "0.11.2"
|
||||
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
|
||||
@@ -0,0 +1,333 @@
|
||||
"""
|
||||
Integration tests for Dict support in consolidated param resolution.
|
||||
|
||||
Tests that Agent, Agents, and Workflow classes correctly handle dict params
|
||||
through the unified canonical resolver.
|
||||
|
||||
Note: Agent tests are skipped as they require LLM setup. The core dict
|
||||
resolution is tested in unit tests. These tests focus on Workflow/WorkflowStep
|
||||
which don't require LLM setup.
|
||||
"""
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# AGENT DICT PARAM TESTS - Using resolver directly to avoid LLM setup
|
||||
# =============================================================================
|
||||
|
||||
class TestAgentDictParamsResolver:
|
||||
"""Test Agent dict param resolution using the resolver directly."""
|
||||
|
||||
def test_agent_output_dict_resolution(self):
|
||||
"""Output dict resolves correctly through canonical resolver."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value={"verbose": True, "markdown": False},
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.verbose is True
|
||||
assert result.markdown is False
|
||||
|
||||
def test_agent_execution_dict_resolution(self):
|
||||
"""Execution dict resolves correctly through canonical resolver."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import ExecutionConfig
|
||||
from praisonaiagents.config.presets import EXECUTION_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value={"max_iter": 50, "max_retry_limit": 10},
|
||||
param_name="execution",
|
||||
config_class=ExecutionConfig,
|
||||
presets=EXECUTION_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, ExecutionConfig)
|
||||
assert result.max_iter == 50
|
||||
|
||||
def test_agent_dict_with_unknown_key_raises_error(self):
|
||||
"""Dict with unknown key raises TypeError."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"verbose": True, "invalid_key": "value"},
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert "Unknown keys" in str(exc_info.value)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# AGENTS (MULTI-AGENT) DICT PARAM TESTS - Using resolver directly
|
||||
# =============================================================================
|
||||
|
||||
class TestAgentsDictParamsResolver:
|
||||
"""Test Agents dict param resolution using the resolver directly."""
|
||||
|
||||
def test_agents_output_dict_resolution(self):
|
||||
"""Multi-agent output dict resolves correctly."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import MultiAgentOutputConfig
|
||||
from praisonaiagents.config.presets import MULTI_AGENT_OUTPUT_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value={"verbose": 2, "stream": False},
|
||||
param_name="output",
|
||||
config_class=MultiAgentOutputConfig,
|
||||
presets=MULTI_AGENT_OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, MultiAgentOutputConfig)
|
||||
assert result.verbose == 2
|
||||
assert result.stream is False
|
||||
|
||||
def test_agents_execution_dict_resolution(self):
|
||||
"""Multi-agent execution dict resolves correctly."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import MultiAgentExecutionConfig
|
||||
from praisonaiagents.config.presets import MULTI_AGENT_EXECUTION_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value={"max_iter": 25, "max_retries": 8},
|
||||
param_name="execution",
|
||||
config_class=MultiAgentExecutionConfig,
|
||||
presets=MULTI_AGENT_EXECUTION_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, MultiAgentExecutionConfig)
|
||||
assert result.max_iter == 25
|
||||
assert result.max_retries == 8
|
||||
|
||||
def test_agents_hooks_dict_resolution(self):
|
||||
"""Multi-agent hooks dict resolves correctly."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import MultiAgentHooksConfig
|
||||
|
||||
def my_checker(result):
|
||||
return True
|
||||
|
||||
result = resolve(
|
||||
value={"completion_checker": my_checker},
|
||||
param_name="hooks",
|
||||
config_class=MultiAgentHooksConfig,
|
||||
array_mode=ArrayMode.PASSTHROUGH,
|
||||
)
|
||||
assert isinstance(result, MultiAgentHooksConfig)
|
||||
assert result.completion_checker is my_checker
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# WORKFLOW DICT PARAM TESTS
|
||||
# =============================================================================
|
||||
|
||||
class TestWorkflowDictParams:
|
||||
"""Test Workflow and WorkflowStep with dict params."""
|
||||
|
||||
def test_workflow_output_dict(self):
|
||||
"""Workflow accepts output as dict."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
steps=[],
|
||||
output={"verbose": True, "stream": False},
|
||||
)
|
||||
# Output config should be resolved
|
||||
assert workflow.output is not None
|
||||
|
||||
def test_workflow_planning_dict(self):
|
||||
"""Workflow accepts planning as dict."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
steps=[],
|
||||
planning={"enabled": True, "llm": "gpt-4o"},
|
||||
)
|
||||
# Planning should be configured
|
||||
assert workflow.planning is not None
|
||||
|
||||
def test_workflow_memory_dict(self):
|
||||
"""Workflow accepts memory as dict."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
steps=[],
|
||||
memory={"backend": "sqlite", "user_id": "test_user"},
|
||||
)
|
||||
# Memory should be configured
|
||||
assert workflow.memory is not None
|
||||
|
||||
def test_workflowstep_context_dict(self):
|
||||
"""WorkflowStep accepts context as dict."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="step1",
|
||||
context={"from_steps": ["step0"], "retain_full": True},
|
||||
)
|
||||
assert step.context_from == ["step0"]
|
||||
assert step.retain_full_context is True
|
||||
|
||||
def test_workflowstep_output_dict(self):
|
||||
"""WorkflowStep accepts output as dict."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="step1",
|
||||
output={"file": "output.txt", "variable": "result"},
|
||||
)
|
||||
assert step.output_file == "output.txt"
|
||||
assert step.output_variable == "result"
|
||||
|
||||
def test_workflowstep_execution_dict(self):
|
||||
"""WorkflowStep accepts execution as dict."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="step1",
|
||||
execution={"max_retries": 5, "quality_check": True},
|
||||
)
|
||||
assert step.max_retries == 5
|
||||
assert step.quality_check is True
|
||||
|
||||
def test_workflowstep_routing_dict(self):
|
||||
"""WorkflowStep accepts routing as dict."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="step1",
|
||||
routing={"next_steps": ["step2", "step3"]},
|
||||
)
|
||||
assert step.next_steps == ["step2", "step3"]
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# BACKWARD COMPATIBILITY TESTS - Using resolver directly
|
||||
# =============================================================================
|
||||
|
||||
class TestBackwardCompatibility:
|
||||
"""Test that existing usage patterns still work via resolver."""
|
||||
|
||||
def test_bool_true_creates_default_config(self):
|
||||
"""Bool True creates default config instance."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
from praisonaiagents.config.feature_configs import PlanningConfig
|
||||
|
||||
result = resolve(
|
||||
value=True,
|
||||
param_name="planning",
|
||||
config_class=PlanningConfig,
|
||||
)
|
||||
assert isinstance(result, PlanningConfig)
|
||||
|
||||
def test_bool_false_returns_none(self):
|
||||
"""Bool False returns None (disabled)."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
from praisonaiagents.config.feature_configs import ReflectionConfig
|
||||
|
||||
result = resolve(
|
||||
value=False,
|
||||
param_name="reflection",
|
||||
config_class=ReflectionConfig,
|
||||
)
|
||||
assert result is None
|
||||
|
||||
def test_string_preset_resolves(self):
|
||||
"""String preset resolves to config."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value="verbose",
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.verbose is True
|
||||
|
||||
def test_array_preset_override_works(self):
|
||||
"""[preset, overrides] pattern works."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
result = resolve(
|
||||
value=["verbose", {"stream": False}],
|
||||
param_name="output",
|
||||
config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.verbose is True
|
||||
assert result.stream is False
|
||||
|
||||
def test_workflow_bool_params_still_work(self):
|
||||
"""Workflow with bool params still works."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
steps=[],
|
||||
planning=True,
|
||||
)
|
||||
# Should not raise - workflow created successfully
|
||||
assert workflow is not None
|
||||
|
||||
def test_workflowstep_list_context_still_works(self):
|
||||
"""WorkflowStep with list context still works."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="step1",
|
||||
context=["step0", "step_prev"],
|
||||
)
|
||||
assert step.context_from == ["step0", "step_prev"]
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# BASE_URL / API_KEY SEPARATION TESTS
|
||||
# =============================================================================
|
||||
|
||||
class TestBaseUrlApiKeySeparation:
|
||||
"""Test that base_url and api_key remain separate parameters."""
|
||||
|
||||
def test_agent_base_url_separate(self):
|
||||
"""Agent base_url is a separate parameter, not consolidated."""
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
import inspect
|
||||
|
||||
sig = inspect.signature(Agent.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
|
||||
# base_url should be a separate parameter
|
||||
assert "base_url" in params
|
||||
# It should NOT be part of any consolidated config
|
||||
|
||||
def test_agent_api_key_separate(self):
|
||||
"""Agent api_key is a separate parameter, not consolidated."""
|
||||
from praisonaiagents.agent.agent import Agent
|
||||
import inspect
|
||||
|
||||
sig = inspect.signature(Agent.__init__)
|
||||
params = list(sig.parameters.keys())
|
||||
|
||||
# api_key should be a separate parameter
|
||||
assert "api_key" in params
|
||||
@@ -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 +1,526 @@
|
||||
"""
|
||||
Comprehensive tests for param_resolver.py - TDD for outstanding gaps.
|
||||
|
||||
Tests cover:
|
||||
1. Dict strict validation (dataclass and non-dataclass configs)
|
||||
2. Array PRESET_OVERRIDE invalid preset error UX
|
||||
3. Precedence ladder for all consolidated params
|
||||
4. Agent consolidated params via canonical resolver
|
||||
5. Workflow/WorkflowStep resolution consistency
|
||||
"""
|
||||
|
||||
import pytest
|
||||
from dataclasses import dataclass, field
|
||||
from typing import List
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Test Fixtures - Config Classes
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class MockConfig:
|
||||
"""Mock config for testing."""
|
||||
enabled: bool = True
|
||||
value: str = "default"
|
||||
count: int = 0
|
||||
|
||||
|
||||
@dataclass
|
||||
class MockConfigWithSources:
|
||||
"""Mock config with sources field."""
|
||||
sources: List[str] = field(default_factory=list)
|
||||
rerank: bool = False
|
||||
|
||||
|
||||
class NonDataclassConfig:
|
||||
"""Non-dataclass config for testing validation."""
|
||||
def __init__(self, enabled: bool = True, value: str = "default"):
|
||||
self.enabled = enabled
|
||||
self.value = value
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1A: Dict Strict Validation Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestDictStrictValidation:
|
||||
"""Tests for strict dict key validation."""
|
||||
|
||||
def test_dict_unknown_keys_error_dataclass(self):
|
||||
"""Dict with unknown keys should raise TypeError with helpful message."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"enabled": True, "unknown_key": "bad"},
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
error_msg = str(exc_info.value)
|
||||
assert "unknown_key" in error_msg.lower() or "Unknown keys" in error_msg
|
||||
assert "enabled" in error_msg or "Valid keys" in error_msg
|
||||
|
||||
def test_dict_valid_keys_accepted(self):
|
||||
"""Dict with valid keys should create config."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value={"enabled": False, "value": "custom"},
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.enabled is False
|
||||
assert result.value == "custom"
|
||||
|
||||
def test_dict_no_config_class_error(self):
|
||||
"""Dict without config_class should raise TypeError."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"key": "value"},
|
||||
param_name="test",
|
||||
config_class=None,
|
||||
)
|
||||
|
||||
assert "not supported" in str(exc_info.value).lower() or "no config class" in str(exc_info.value).lower()
|
||||
|
||||
def test_dict_validation_non_dataclass_config(self):
|
||||
"""Non-dataclass config should still validate keys via signature/annotations."""
|
||||
from praisonaiagents.config.param_resolver import _get_valid_keys
|
||||
|
||||
# This tests the _get_valid_keys helper handles non-dataclass
|
||||
# The implementation should use inspect.signature or __annotations__
|
||||
# For now, verify the helper exists and returns something useful
|
||||
keys = _get_valid_keys(NonDataclassConfig)
|
||||
# Should return valid keys or empty (graceful degradation)
|
||||
assert isinstance(keys, (set, list, frozenset)) or keys is None
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1B: Array PRESET_OVERRIDE Error UX Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestArrayPresetOverrideErrorUX:
|
||||
"""Tests for array preset error messages with suggestions."""
|
||||
|
||||
def test_invalid_preset_in_array_raises_error_with_suggestions(self):
|
||||
"""Invalid preset string in array should raise error with typo suggestions."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
presets = {
|
||||
"fast": {"enabled": True, "value": "fast"},
|
||||
"slow": {"enabled": True, "value": "slow"},
|
||||
"balanced": {"enabled": True, "value": "balanced"},
|
||||
}
|
||||
|
||||
with pytest.raises((ValueError, TypeError)) as exc_info:
|
||||
resolve(
|
||||
value=["fats"], # Typo for "fast"
|
||||
param_name="execution",
|
||||
config_class=MockConfig,
|
||||
presets=presets,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
error_msg = str(exc_info.value).lower()
|
||||
# Should suggest similar preset
|
||||
assert "fast" in error_msg or "fats" in error_msg
|
||||
# Should list valid presets
|
||||
assert "valid" in error_msg or "available" in error_msg or any(p in error_msg for p in presets.keys())
|
||||
|
||||
def test_valid_preset_in_array_works(self):
|
||||
"""Valid preset string in array should work."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
presets = {
|
||||
"fast": {"enabled": True, "value": "fast"},
|
||||
}
|
||||
|
||||
result = resolve(
|
||||
value=["fast"],
|
||||
param_name="execution",
|
||||
config_class=MockConfig,
|
||||
presets=presets,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.value == "fast"
|
||||
|
||||
def test_preset_with_overrides_in_array(self):
|
||||
"""Preset with override dict in array should merge correctly."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
presets = {
|
||||
"fast": {"enabled": True, "value": "fast", "count": 1},
|
||||
}
|
||||
|
||||
result = resolve(
|
||||
value=["fast", {"count": 99}],
|
||||
param_name="execution",
|
||||
config_class=MockConfig,
|
||||
presets=presets,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.value == "fast"
|
||||
assert result.count == 99
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1C: Precedence Ladder Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestPrecedenceLadder:
|
||||
"""Tests for Instance > Config > Dict > Array > String > Bool > Default precedence."""
|
||||
|
||||
def test_instance_highest_precedence(self):
|
||||
"""Instance check should have highest precedence."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
class MockInstance:
|
||||
def search(self): pass
|
||||
def add(self): pass
|
||||
|
||||
instance = MockInstance()
|
||||
result = resolve(
|
||||
value=instance,
|
||||
param_name="memory",
|
||||
config_class=MockConfig,
|
||||
instance_check=lambda v: hasattr(v, 'search') and hasattr(v, 'add'),
|
||||
)
|
||||
|
||||
assert result is instance
|
||||
|
||||
def test_config_class_instance_precedence(self):
|
||||
"""Config class instance should be returned as-is."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
config = MockConfig(enabled=False, value="custom")
|
||||
result = resolve(
|
||||
value=config,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
assert result is config
|
||||
|
||||
def test_dict_before_string(self):
|
||||
"""Dict should be processed before string."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
# Dict input
|
||||
result = resolve(
|
||||
value={"enabled": False},
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.enabled is False
|
||||
|
||||
def test_bool_true_returns_default_config(self):
|
||||
"""Bool True should return default config instance."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value=True,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.enabled is True # Default
|
||||
|
||||
def test_bool_false_returns_none(self):
|
||||
"""Bool False should return None (disabled)."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value=False,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
assert result is None
|
||||
|
||||
def test_none_returns_default(self):
|
||||
"""None should return the default value."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
default = MockConfig(value="default_value")
|
||||
result = resolve(
|
||||
value=None,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
default=default,
|
||||
)
|
||||
|
||||
assert result is default
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1D: Agent Consolidated Params Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestAgentConsolidatedParams:
|
||||
"""Tests for Agent consolidated params using canonical resolver."""
|
||||
|
||||
def test_agent_hooks_via_resolver(self):
|
||||
"""Agent hooks param should use canonical resolver."""
|
||||
from praisonaiagents.config.feature_configs import HooksConfig
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
# Test list passthrough
|
||||
hooks_list = [lambda x: x]
|
||||
result = resolve(
|
||||
value=hooks_list,
|
||||
param_name="hooks",
|
||||
config_class=HooksConfig,
|
||||
array_mode=ArrayMode.PASSTHROUGH,
|
||||
)
|
||||
assert result == hooks_list
|
||||
|
||||
# Test HooksConfig instance
|
||||
hooks_config = HooksConfig(on_step=lambda x: x)
|
||||
result = resolve(
|
||||
value=hooks_config,
|
||||
param_name="hooks",
|
||||
config_class=HooksConfig,
|
||||
)
|
||||
assert result is hooks_config
|
||||
|
||||
# Test dict
|
||||
result = resolve(
|
||||
value={"on_step": None},
|
||||
param_name="hooks",
|
||||
config_class=HooksConfig,
|
||||
)
|
||||
assert isinstance(result, HooksConfig)
|
||||
|
||||
def test_agent_skills_via_resolver(self):
|
||||
"""Agent skills param should use canonical resolver."""
|
||||
from praisonaiagents.config.feature_configs import SkillsConfig
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
# Test SkillsConfig instance directly
|
||||
config = SkillsConfig(paths=["./skill1", "./skill2"])
|
||||
result = resolve(
|
||||
value=config,
|
||||
param_name="skills",
|
||||
config_class=SkillsConfig,
|
||||
)
|
||||
assert isinstance(result, SkillsConfig)
|
||||
assert result.paths == ["./skill1", "./skill2"]
|
||||
|
||||
# Test dict input
|
||||
result = resolve(
|
||||
value={"paths": ["./my-skill"]},
|
||||
param_name="skills",
|
||||
config_class=SkillsConfig,
|
||||
)
|
||||
assert isinstance(result, SkillsConfig)
|
||||
assert result.paths == ["./my-skill"]
|
||||
|
||||
def test_agent_knowledge_via_resolver(self):
|
||||
"""Agent knowledge param should use canonical resolver."""
|
||||
from praisonaiagents.config.feature_configs import KnowledgeConfig
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
# Test list of sources
|
||||
result = resolve(
|
||||
value=["docs/", "data.pdf"],
|
||||
param_name="knowledge",
|
||||
config_class=KnowledgeConfig,
|
||||
array_mode=ArrayMode.SOURCES_WITH_CONFIG,
|
||||
)
|
||||
assert isinstance(result, KnowledgeConfig)
|
||||
assert "docs/" in result.sources
|
||||
|
||||
# Test list with config override
|
||||
result = resolve(
|
||||
value=["docs/", {"rerank": True}],
|
||||
param_name="knowledge",
|
||||
config_class=KnowledgeConfig,
|
||||
array_mode=ArrayMode.SOURCES_WITH_CONFIG,
|
||||
)
|
||||
assert isinstance(result, KnowledgeConfig)
|
||||
assert result.rerank is True
|
||||
|
||||
def test_agent_guardrails_via_resolver(self):
|
||||
"""Agent guardrails param should use canonical resolver."""
|
||||
from praisonaiagents.config.feature_configs import GuardrailConfig
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.presets import GUARDRAIL_PRESETS
|
||||
|
||||
# Test string preset
|
||||
if GUARDRAIL_PRESETS:
|
||||
preset_name = list(GUARDRAIL_PRESETS.keys())[0]
|
||||
result = resolve(
|
||||
value=preset_name,
|
||||
param_name="guardrails",
|
||||
config_class=GuardrailConfig,
|
||||
presets=GUARDRAIL_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert result is not None
|
||||
|
||||
# Test callable (should be handled via instance_check)
|
||||
def validator_fn(x):
|
||||
return (True, x)
|
||||
|
||||
result = resolve(
|
||||
value=validator_fn,
|
||||
param_name="guardrails",
|
||||
config_class=GuardrailConfig,
|
||||
instance_check=callable,
|
||||
)
|
||||
assert result is validator_fn
|
||||
|
||||
# Test GuardrailConfig instance
|
||||
config = GuardrailConfig(max_retries=5)
|
||||
result = resolve(
|
||||
value=config,
|
||||
param_name="guardrails",
|
||||
config_class=GuardrailConfig,
|
||||
)
|
||||
assert result is config
|
||||
|
||||
# Test string as LLM prompt
|
||||
result = resolve(
|
||||
value="Ensure response is safe and helpful",
|
||||
param_name="guardrails",
|
||||
config_class=GuardrailConfig,
|
||||
string_mode="llm_prompt",
|
||||
)
|
||||
assert isinstance(result, GuardrailConfig)
|
||||
assert result.llm_validator == "Ensure response is safe and helpful"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1E: Workflow/WorkflowStep Resolution Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestWorkflowResolution:
|
||||
"""Tests for Workflow and WorkflowStep resolution consistency."""
|
||||
|
||||
def test_workflow_step_context_resolved(self):
|
||||
"""WorkflowStep context should be resolved to config."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
context=["step1", "step2"],
|
||||
)
|
||||
|
||||
# Should have resolved _context_from
|
||||
assert step._context_from == ["step1", "step2"]
|
||||
|
||||
def test_workflow_step_execution_resolved(self):
|
||||
"""WorkflowStep execution should be resolved to config."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
execution="fast",
|
||||
)
|
||||
|
||||
# Should have resolved execution config
|
||||
assert step._async_execution is not None or step._max_retries is not None
|
||||
|
||||
def test_workflow_step_output_resolved(self):
|
||||
"""WorkflowStep output should be resolved to config."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
from praisonaiagents.workflows.workflow_configs import WorkflowStepOutputConfig
|
||||
|
||||
# Test with config object
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
output=WorkflowStepOutputConfig(file="result.txt"),
|
||||
)
|
||||
|
||||
# Should have resolved output file
|
||||
assert step._output_file == "result.txt"
|
||||
|
||||
def test_workflow_output_resolved(self):
|
||||
"""Workflow output should be resolved to config."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
output="verbose",
|
||||
)
|
||||
|
||||
# Should have resolved verbose setting
|
||||
assert workflow._verbose is True
|
||||
|
||||
def test_workflow_planning_resolved(self):
|
||||
"""Workflow planning should be resolved to config."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
planning=True,
|
||||
)
|
||||
|
||||
# Should have resolved planning enabled
|
||||
assert workflow._planning_enabled is True
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1F: Naming/Alias Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestNamingAlias:
|
||||
"""Tests for Agents vs PraisonAIAgents naming."""
|
||||
|
||||
def test_agents_is_primary(self):
|
||||
"""Agents should be the primary import."""
|
||||
from praisonaiagents import Agents
|
||||
assert Agents is not None
|
||||
|
||||
def test_praisonaiagents_alias_works(self):
|
||||
"""PraisonAIAgents alias should still work."""
|
||||
from praisonaiagents import PraisonAIAgents
|
||||
assert PraisonAIAgents is not None
|
||||
|
||||
def test_both_are_same_class(self):
|
||||
"""Both names should refer to the same class."""
|
||||
from praisonaiagents import Agents, PraisonAIAgents
|
||||
assert Agents is PraisonAIAgents
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1G: Helper Function Tests
|
||||
# =============================================================================
|
||||
|
||||
class TestHelperFunctions:
|
||||
"""Tests for resolver helper functions."""
|
||||
|
||||
def test_get_valid_keys_dataclass(self):
|
||||
"""_get_valid_keys should return dataclass fields."""
|
||||
from praisonaiagents.config.param_resolver import _get_valid_keys
|
||||
|
||||
keys = _get_valid_keys(MockConfig)
|
||||
assert "enabled" in keys
|
||||
assert "value" in keys
|
||||
assert "count" in keys
|
||||
|
||||
def test_get_valid_keys_non_dataclass(self):
|
||||
"""_get_valid_keys should handle non-dataclass via signature."""
|
||||
from praisonaiagents.config.param_resolver import _get_valid_keys
|
||||
|
||||
keys = _get_valid_keys(NonDataclassConfig)
|
||||
# Should return keys from __init__ signature or __annotations__
|
||||
# or gracefully return empty/None
|
||||
assert keys is None or isinstance(keys, (set, list, frozenset))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__, "-v"])
|
||||
@@ -0,0 +1,720 @@
|
||||
"""
|
||||
TDD Tests for Resolver Standardization.
|
||||
|
||||
These tests verify:
|
||||
1. Precedence order: None → Instance → Config → Array → Dict → String → Bool → Default
|
||||
2. Memory array semantics: single=ok, multiple=error
|
||||
3. Caching array support with PRESET_OVERRIDE
|
||||
4. Workflow/WorkflowStep using canonical resolve
|
||||
5. CLI resolver integration
|
||||
6. Naming standardization (guardrails plural)
|
||||
7. All precedence levels per consolidated param
|
||||
|
||||
Run with: pytest tests/unit/config/test_resolver_standardization.py -v
|
||||
"""
|
||||
|
||||
import pytest
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Test Fixtures - Config Classes
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class MockConfig:
|
||||
"""Mock config class for testing."""
|
||||
enabled: bool = True
|
||||
value: str = "default"
|
||||
count: int = 0
|
||||
|
||||
|
||||
@dataclass
|
||||
class MockMemoryConfig:
|
||||
"""Mock memory config for testing."""
|
||||
backend: str = "file"
|
||||
user_id: Optional[str] = None
|
||||
config: Optional[Dict[str, Any]] = None
|
||||
sources: Optional[List[str]] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class MockCachingConfig:
|
||||
"""Mock caching config for testing."""
|
||||
enabled: bool = True
|
||||
ttl: int = 3600
|
||||
prompt_caching: bool = False
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.1: Tests for Precedence Order (Array BEFORE Dict)
|
||||
# =============================================================================
|
||||
|
||||
class TestPrecedenceOrder:
|
||||
"""Test that precedence order is: None → Instance → Config → Array → Dict → String → Bool → Default"""
|
||||
|
||||
def test_array_takes_precedence_over_dict_interpretation(self):
|
||||
"""Array input should be processed as array, not as dict."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
# When given an array, it should use array handling, not dict handling
|
||||
result = resolve(
|
||||
value=["preset1"],
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
presets={"preset1": {"enabled": True, "value": "from_preset"}},
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
# Should resolve via array path (preset), not dict path
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.value == "from_preset"
|
||||
|
||||
def test_precedence_instance_over_config(self):
|
||||
"""Instance check should take precedence over config class check."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
class CustomInstance:
|
||||
def __init__(self):
|
||||
self.is_custom = True
|
||||
|
||||
custom = CustomInstance()
|
||||
|
||||
result = resolve(
|
||||
value=custom,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
instance_check=lambda v: hasattr(v, 'is_custom'),
|
||||
)
|
||||
|
||||
# Should return instance as-is, not try to convert
|
||||
assert result is custom
|
||||
assert result.is_custom is True
|
||||
|
||||
def test_precedence_config_over_array(self):
|
||||
"""Config class instance should take precedence over array handling."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
config = MockConfig(enabled=False, value="config_value")
|
||||
|
||||
result = resolve(
|
||||
value=config,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
# Should return config as-is
|
||||
assert result is config
|
||||
assert result.value == "config_value"
|
||||
|
||||
def test_precedence_array_over_dict(self):
|
||||
"""Array should be checked BEFORE dict in precedence."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
# This test verifies the fix: Array must be checked before Dict
|
||||
# A list input should go through array handling, not dict handling
|
||||
result = resolve(
|
||||
value=["verbose", {"count": 5}],
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
presets={"verbose": {"enabled": True, "value": "verbose_mode"}},
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.value == "verbose_mode"
|
||||
assert result.count == 5 # Override applied
|
||||
|
||||
def test_precedence_dict_over_string(self):
|
||||
"""Dict should take precedence over string handling."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value={"enabled": False, "value": "dict_value"},
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
presets={"dict_value": {"enabled": True}}, # Should NOT use this
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.value == "dict_value"
|
||||
assert result.enabled is False
|
||||
|
||||
def test_precedence_string_over_bool(self):
|
||||
"""String preset should take precedence over bool handling."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value="verbose",
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
presets={"verbose": {"enabled": True, "value": "verbose_mode"}},
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
assert result.value == "verbose_mode"
|
||||
|
||||
def test_precedence_bool_over_default(self):
|
||||
"""Bool True should create default config, not return default value."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
result = resolve(
|
||||
value=True,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
default={"should": "not_use"},
|
||||
)
|
||||
|
||||
assert isinstance(result, MockConfig)
|
||||
# Should be default MockConfig(), not the default dict
|
||||
|
||||
def test_precedence_none_returns_default(self):
|
||||
"""None should return the default value."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
default_config = MockConfig(value="default_value")
|
||||
|
||||
result = resolve(
|
||||
value=None,
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
default=default_config,
|
||||
)
|
||||
|
||||
assert result is default_config
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.2: Tests for Memory Array Semantics
|
||||
# =============================================================================
|
||||
|
||||
class TestMemoryArraySemantics:
|
||||
"""Test memory array semantics: single=ok, multiple=error."""
|
||||
|
||||
def test_memory_single_item_array_resolves_as_scalar(self):
|
||||
"""memory=["redis"] should resolve as scalar preset."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=["redis"],
|
||||
param_name="memory",
|
||||
config_class=MockMemoryConfig,
|
||||
presets={"redis": {"backend": "redis"}},
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockMemoryConfig)
|
||||
assert result.backend == "redis"
|
||||
|
||||
def test_memory_multiple_items_raises_error(self):
|
||||
"""memory=["redis", "file"] should raise TypeError."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value=["redis", "file"],
|
||||
param_name="memory",
|
||||
config_class=MockMemoryConfig,
|
||||
presets={"redis": {"backend": "redis"}, "file": {"backend": "file"}},
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
)
|
||||
|
||||
# Error message should be helpful
|
||||
assert "memory" in str(exc_info.value).lower()
|
||||
assert "multiple" in str(exc_info.value).lower() or "single" in str(exc_info.value).lower()
|
||||
|
||||
def test_memory_single_url_in_array_resolves(self):
|
||||
"""memory=["postgresql://..."] should resolve as URL."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=["postgresql://localhost/db"],
|
||||
param_name="memory",
|
||||
config_class=MockMemoryConfig,
|
||||
url_schemes={"postgresql": "postgres"},
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockMemoryConfig)
|
||||
assert result.backend == "postgres"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.3: Tests for Caching Array Support
|
||||
# =============================================================================
|
||||
|
||||
class TestCachingArraySupport:
|
||||
"""Test caching array support with PRESET_OVERRIDE."""
|
||||
|
||||
def test_caching_array_preset_override(self):
|
||||
"""caching=["enabled", {"ttl": 7200}] should work."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value=["enabled", {"ttl": 7200}],
|
||||
param_name="caching",
|
||||
config_class=MockCachingConfig,
|
||||
presets={"enabled": {"enabled": True, "ttl": 3600}},
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockCachingConfig)
|
||||
assert result.enabled is True
|
||||
assert result.ttl == 7200 # Override applied
|
||||
|
||||
def test_caching_string_preset(self):
|
||||
"""caching="enabled" should work."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
|
||||
result = resolve(
|
||||
value="enabled",
|
||||
param_name="caching",
|
||||
config_class=MockCachingConfig,
|
||||
presets={"enabled": {"enabled": True}},
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockCachingConfig)
|
||||
assert result.enabled is True
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.4: Tests for Workflow/WorkflowStep Using Canonical Resolve
|
||||
# =============================================================================
|
||||
|
||||
class TestWorkflowCanonicalResolve:
|
||||
"""Test that Workflow and WorkflowStep use canonical resolve directly."""
|
||||
|
||||
def test_workflow_output_uses_canonical_resolve(self):
|
||||
"""Workflow output param should use canonical resolve."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
name="test",
|
||||
steps=[],
|
||||
output="verbose",
|
||||
)
|
||||
|
||||
assert workflow._verbose is True
|
||||
|
||||
def test_workflow_output_dict_validation(self):
|
||||
"""Workflow output dict should have strict validation."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
Workflow(
|
||||
name="test",
|
||||
steps=[],
|
||||
output={"invalid_key": True},
|
||||
)
|
||||
|
||||
assert "invalid_key" in str(exc_info.value).lower() or "unknown" in str(exc_info.value).lower()
|
||||
|
||||
def test_workflowstep_context_uses_canonical_resolve(self):
|
||||
"""WorkflowStep context param should use canonical resolve."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
context=["step1", "step2"],
|
||||
)
|
||||
|
||||
assert step._context_from == ["step1", "step2"]
|
||||
|
||||
def test_workflowstep_execution_preset(self):
|
||||
"""WorkflowStep execution preset should work."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
execution="thorough",
|
||||
)
|
||||
|
||||
# Should have thorough preset values
|
||||
assert step._max_retries >= 3 # Thorough has more retries
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.5: Tests for CLI Resolver Integration
|
||||
# =============================================================================
|
||||
|
||||
class TestCLIResolverIntegration:
|
||||
"""Test CLI flags use canonical resolver."""
|
||||
|
||||
def test_cli_memory_flag_true(self):
|
||||
"""CLI --memory flag (true) should resolve correctly."""
|
||||
# This tests the integration point - CLI should pass value to canonical resolver
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.presets import MEMORY_PRESETS, MEMORY_URL_SCHEMES
|
||||
|
||||
# Simulate CLI passing True
|
||||
result = resolve(
|
||||
value=True,
|
||||
param_name="memory",
|
||||
config_class=MockMemoryConfig,
|
||||
presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockMemoryConfig)
|
||||
|
||||
def test_cli_memory_flag_preset_string(self):
|
||||
"""CLI --memory=redis should resolve as preset."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.presets import MEMORY_PRESETS, MEMORY_URL_SCHEMES
|
||||
|
||||
result = resolve(
|
||||
value="redis",
|
||||
param_name="memory",
|
||||
config_class=MockMemoryConfig,
|
||||
presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockMemoryConfig)
|
||||
assert result.backend == "redis"
|
||||
|
||||
def test_cli_memory_flag_url(self):
|
||||
"""CLI --memory=postgresql://... should resolve as URL."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.presets import MEMORY_PRESETS, MEMORY_URL_SCHEMES
|
||||
|
||||
result = resolve(
|
||||
value="postgresql://localhost/db",
|
||||
param_name="memory",
|
||||
config_class=MockMemoryConfig,
|
||||
presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST,
|
||||
)
|
||||
|
||||
assert isinstance(result, MockMemoryConfig)
|
||||
assert result.backend == "postgres"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.6: Tests for Naming Standardization (guardrails plural)
|
||||
# =============================================================================
|
||||
|
||||
class TestNamingStandardization:
|
||||
"""Test guardrail → guardrails naming standardization."""
|
||||
|
||||
def test_workflowstep_accepts_guardrails_plural(self):
|
||||
"""WorkflowStep should accept guardrails= (plural)."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
def my_guardrail(result):
|
||||
return (True, result)
|
||||
|
||||
# Should accept guardrails= (plural)
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
guardrails=my_guardrail,
|
||||
)
|
||||
|
||||
# Should store in guardrails attribute
|
||||
assert step.guardrails is my_guardrail or step.guardrail is my_guardrail
|
||||
|
||||
def test_workflowstep_guardrail_singular_compat(self):
|
||||
"""WorkflowStep should accept guardrail= (singular) for compatibility."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
def my_guardrail(result):
|
||||
return (True, result)
|
||||
|
||||
# Should still accept guardrail= (singular) for backward compat
|
||||
step = WorkflowStep(
|
||||
name="test",
|
||||
guardrail=my_guardrail,
|
||||
)
|
||||
|
||||
# Should work (backward compat)
|
||||
assert step.guardrail is my_guardrail
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# TODO 1.7: Tests for All Precedence Levels Per Consolidated Param
|
||||
# =============================================================================
|
||||
|
||||
class TestAllPrecedenceLevels:
|
||||
"""Test each consolidated param has all 7 precedence levels working."""
|
||||
|
||||
def test_output_all_precedence_levels(self):
|
||||
"""Test output param at all precedence levels."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import OutputConfig
|
||||
from praisonaiagents.config.presets import OUTPUT_PRESETS
|
||||
|
||||
# 1. None → Default
|
||||
result = resolve(value=None, param_name="output", config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS, default=OutputConfig())
|
||||
assert isinstance(result, OutputConfig)
|
||||
|
||||
# 2. Instance (custom object with expected attributes)
|
||||
class CustomOutput:
|
||||
verbose = True
|
||||
stream = True
|
||||
custom = CustomOutput()
|
||||
result = resolve(value=custom, param_name="output", config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS, instance_check=lambda v: hasattr(v, 'verbose'))
|
||||
assert result is custom
|
||||
|
||||
# 3. Config class instance
|
||||
config = OutputConfig(verbose=True, stream=False)
|
||||
result = resolve(value=config, param_name="output", config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS)
|
||||
assert result is config
|
||||
|
||||
# 4. Array [preset, overrides]
|
||||
result = resolve(value=["verbose", {"stream": False}], param_name="output",
|
||||
config_class=OutputConfig, presets=OUTPUT_PRESETS,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE)
|
||||
assert isinstance(result, OutputConfig)
|
||||
|
||||
# 5. Dict
|
||||
result = resolve(value={"verbose": True, "stream": False}, param_name="output",
|
||||
config_class=OutputConfig, presets=OUTPUT_PRESETS)
|
||||
assert isinstance(result, OutputConfig)
|
||||
assert result.verbose is True
|
||||
|
||||
# 6. String preset
|
||||
result = resolve(value="verbose", param_name="output", config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS)
|
||||
assert isinstance(result, OutputConfig)
|
||||
|
||||
# 7. Bool True
|
||||
result = resolve(value=True, param_name="output", config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS)
|
||||
assert isinstance(result, OutputConfig)
|
||||
|
||||
# 8. Bool False → None
|
||||
result = resolve(value=False, param_name="output", config_class=OutputConfig,
|
||||
presets=OUTPUT_PRESETS)
|
||||
assert result is None
|
||||
|
||||
def test_memory_all_precedence_levels(self):
|
||||
"""Test memory param at all precedence levels."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
from praisonaiagents.config.feature_configs import MemoryConfig
|
||||
from praisonaiagents.config.presets import MEMORY_PRESETS, MEMORY_URL_SCHEMES
|
||||
|
||||
# 1. None → Default
|
||||
result = resolve(value=None, param_name="memory", config_class=MemoryConfig,
|
||||
presets=MEMORY_PRESETS, url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST, default=None)
|
||||
assert result is None
|
||||
|
||||
# 2. Config class instance
|
||||
config = MemoryConfig(backend="redis")
|
||||
result = resolve(value=config, param_name="memory", config_class=MemoryConfig,
|
||||
presets=MEMORY_PRESETS, url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST)
|
||||
assert result is config
|
||||
|
||||
# 3. Dict
|
||||
result = resolve(value={"backend": "sqlite"}, param_name="memory",
|
||||
config_class=MemoryConfig, presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES, array_mode=ArrayMode.SINGLE_OR_LIST)
|
||||
assert isinstance(result, MemoryConfig)
|
||||
assert result.backend == "sqlite"
|
||||
|
||||
# 4. String preset
|
||||
result = resolve(value="redis", param_name="memory", config_class=MemoryConfig,
|
||||
presets=MEMORY_PRESETS, url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST)
|
||||
assert isinstance(result, MemoryConfig)
|
||||
|
||||
# 5. String URL
|
||||
result = resolve(value="postgresql://localhost/db", param_name="memory",
|
||||
config_class=MemoryConfig, presets=MEMORY_PRESETS,
|
||||
url_schemes=MEMORY_URL_SCHEMES, array_mode=ArrayMode.SINGLE_OR_LIST)
|
||||
assert isinstance(result, MemoryConfig)
|
||||
|
||||
# 6. Bool True
|
||||
result = resolve(value=True, param_name="memory", config_class=MemoryConfig,
|
||||
presets=MEMORY_PRESETS, url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST)
|
||||
assert isinstance(result, MemoryConfig)
|
||||
|
||||
# 7. Bool False → None
|
||||
result = resolve(value=False, param_name="memory", config_class=MemoryConfig,
|
||||
presets=MEMORY_PRESETS, url_schemes=MEMORY_URL_SCHEMES,
|
||||
array_mode=ArrayMode.SINGLE_OR_LIST)
|
||||
assert result is None
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Tests for Error Messages and Typo Suggestions
|
||||
# =============================================================================
|
||||
|
||||
class TestErrorMessages:
|
||||
"""Test error messages are helpful with typo suggestions."""
|
||||
|
||||
def test_invalid_preset_suggests_similar(self):
|
||||
"""Invalid preset should suggest similar valid presets."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
resolve(
|
||||
value="verbos", # Typo
|
||||
param_name="output",
|
||||
config_class=MockConfig,
|
||||
presets={"verbose": {}, "minimal": {}, "debug": {}},
|
||||
)
|
||||
|
||||
error_msg = str(exc_info.value).lower()
|
||||
assert "verbose" in error_msg # Should suggest "verbose"
|
||||
|
||||
def test_unknown_dict_keys_lists_valid_keys(self):
|
||||
"""Unknown dict keys should list valid keys."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"invalid_key": True},
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
error_msg = str(exc_info.value).lower()
|
||||
assert "invalid_key" in error_msg or "unknown" in error_msg
|
||||
assert "enabled" in error_msg or "valid" in error_msg
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Tests for Strict Dict Validation
|
||||
# =============================================================================
|
||||
|
||||
class TestStrictDictValidation:
|
||||
"""Test strict dict validation."""
|
||||
|
||||
def test_dict_without_config_class_raises_error(self):
|
||||
"""Dict input without config_class should raise TypeError."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"key": "value"},
|
||||
param_name="test",
|
||||
config_class=None, # No config class
|
||||
)
|
||||
|
||||
assert "dict" in str(exc_info.value).lower()
|
||||
|
||||
def test_dict_with_unknown_keys_raises_error(self):
|
||||
"""Dict with unknown keys should raise TypeError."""
|
||||
from praisonaiagents.config.param_resolver import resolve
|
||||
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"enabled": True, "unknown_field": "value"},
|
||||
param_name="test",
|
||||
config_class=MockConfig,
|
||||
)
|
||||
|
||||
error_msg = str(exc_info.value)
|
||||
assert "unknown_field" in error_msg.lower() or "unknown" in error_msg.lower()
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PHASE 1 TDD: Tests for Workflow/WorkflowStep New Params (ALL GREEN target)
|
||||
# =============================================================================
|
||||
|
||||
class TestWorkflowNewParams:
|
||||
"""Test Workflow supports all consolidated params like Agents."""
|
||||
|
||||
def test_workflow_has_autonomy_param(self):
|
||||
"""Workflow should have autonomy param."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
# Should accept autonomy param without error
|
||||
workflow = Workflow(steps=[], autonomy=True)
|
||||
assert hasattr(workflow, 'autonomy') or hasattr(workflow, '_autonomy_config')
|
||||
|
||||
def test_workflow_has_knowledge_param(self):
|
||||
"""Workflow should have knowledge param."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(steps=[], knowledge=["docs/"])
|
||||
assert hasattr(workflow, 'knowledge') or hasattr(workflow, '_knowledge_config')
|
||||
|
||||
def test_workflow_has_guardrails_param(self):
|
||||
"""Workflow should have guardrails param."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(steps=[], guardrails=True)
|
||||
assert hasattr(workflow, 'guardrails') or hasattr(workflow, '_guardrails_config')
|
||||
|
||||
def test_workflow_has_web_param(self):
|
||||
"""Workflow should have web param."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(steps=[], web=True)
|
||||
assert hasattr(workflow, 'web') or hasattr(workflow, '_web_config')
|
||||
|
||||
def test_workflow_has_reflection_param(self):
|
||||
"""Workflow should have reflection param."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(steps=[], reflection=True)
|
||||
assert hasattr(workflow, 'reflection') or hasattr(workflow, '_reflection_config')
|
||||
|
||||
|
||||
class TestWorkflowStepNewParams:
|
||||
"""Test WorkflowStep supports all consolidated params."""
|
||||
|
||||
def test_workflowstep_has_autonomy_param(self):
|
||||
"""WorkflowStep should have autonomy param."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(name="test", autonomy=True)
|
||||
assert hasattr(step, 'autonomy') or hasattr(step, '_autonomy_config')
|
||||
|
||||
def test_workflowstep_has_knowledge_param(self):
|
||||
"""WorkflowStep should have knowledge param."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(name="test", knowledge=["docs/"])
|
||||
assert hasattr(step, 'knowledge') or hasattr(step, '_knowledge_config')
|
||||
|
||||
def test_workflowstep_has_web_param(self):
|
||||
"""WorkflowStep should have web param."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(name="test", web=True)
|
||||
assert hasattr(step, 'web') or hasattr(step, '_web_config')
|
||||
|
||||
def test_workflowstep_has_reflection_param(self):
|
||||
"""WorkflowStep should have reflection param."""
|
||||
from praisonaiagents.workflows.workflows import WorkflowStep
|
||||
|
||||
step = WorkflowStep(name="test", reflection=True)
|
||||
assert hasattr(step, 'reflection') or hasattr(step, '_reflection_config')
|
||||
|
||||
|
||||
class TestWorkflowPropagation:
|
||||
"""Test workflow defaults propagate to steps/agents."""
|
||||
|
||||
def test_workflow_defaults_available_for_steps(self):
|
||||
"""Workflow-level configs should be accessible for step propagation."""
|
||||
from praisonaiagents.workflows.workflows import Workflow
|
||||
|
||||
workflow = Workflow(
|
||||
steps=[],
|
||||
knowledge=["docs/"],
|
||||
web=True,
|
||||
guardrails=True,
|
||||
)
|
||||
|
||||
# Workflow should store resolved configs for propagation
|
||||
assert workflow.knowledge is not None or hasattr(workflow, '_knowledge_config')
|
||||
assert workflow.web is not None or hasattr(workflow, '_web_config')
|
||||
assert workflow.guardrails is not None or hasattr(workflow, '_guardrails_config')
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__, "-v"])
|
||||
@@ -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 +1,423 @@
|
||||
"""
|
||||
Unit tests for Dict support in the canonical param resolver.
|
||||
|
||||
Tests the NEW_FEATURE_SPEC:
|
||||
1. dict → config success
|
||||
2. dict with unknown key → error
|
||||
3. dict where no config class → error
|
||||
|
||||
Also tests:
|
||||
- Precedence ordering (Instance > Config > Dict > Array > String > Bool > Default)
|
||||
- Array semantics unchanged
|
||||
"""
|
||||
|
||||
import pytest
|
||||
from dataclasses import dataclass
|
||||
from typing import Optional, List
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Test Config Classes (mimicking real config classes)
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class TestOutputConfig:
|
||||
"""Test config for output parameter."""
|
||||
verbose: bool = False
|
||||
stream: bool = True
|
||||
markdown: bool = False
|
||||
|
||||
|
||||
@dataclass
|
||||
class TestExecutionConfig:
|
||||
"""Test config for execution parameter."""
|
||||
max_iter: int = 10
|
||||
max_retries: int = 3
|
||||
|
||||
|
||||
@dataclass
|
||||
class TestMemoryConfig:
|
||||
"""Test config for memory parameter."""
|
||||
backend: str = "file"
|
||||
user_id: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class TestContextConfig:
|
||||
"""Test config for context parameter with list field."""
|
||||
from_steps: Optional[List[str]] = None
|
||||
retain_full: bool = True
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Test Fixtures
|
||||
# =============================================================================
|
||||
|
||||
@pytest.fixture
|
||||
def resolver():
|
||||
"""Import the canonical resolver."""
|
||||
from praisonaiagents.config.param_resolver import resolve, ArrayMode
|
||||
return resolve, ArrayMode
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def output_presets():
|
||||
"""Sample presets for output parameter."""
|
||||
return {
|
||||
"verbose": {"verbose": True, "stream": True, "markdown": True},
|
||||
"silent": {"verbose": False, "stream": False, "markdown": False},
|
||||
"minimal": {"verbose": False, "stream": True, "markdown": False},
|
||||
}
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# DICT SUCCESS TESTS
|
||||
# =============================================================================
|
||||
|
||||
class TestDictSuccess:
|
||||
"""Test dict → config conversion success cases."""
|
||||
|
||||
def test_dict_to_config_basic(self, resolver):
|
||||
"""Dict with valid keys converts to config."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value={"verbose": True, "stream": False},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is True
|
||||
assert result.stream is False
|
||||
assert result.markdown is False # default
|
||||
|
||||
def test_dict_to_config_all_fields(self, resolver):
|
||||
"""Dict with all fields converts correctly."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value={"verbose": True, "stream": True, "markdown": True},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is True
|
||||
assert result.stream is True
|
||||
assert result.markdown is True
|
||||
|
||||
def test_dict_to_config_partial_fields(self, resolver):
|
||||
"""Dict with partial fields uses defaults for missing."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value={"max_iter": 50},
|
||||
param_name="execution",
|
||||
config_class=TestExecutionConfig,
|
||||
)
|
||||
assert isinstance(result, TestExecutionConfig)
|
||||
assert result.max_iter == 50
|
||||
assert result.max_retries == 3 # default
|
||||
|
||||
def test_dict_to_config_empty_dict(self, resolver):
|
||||
"""Empty dict creates config with all defaults."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value={},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is False
|
||||
assert result.stream is True
|
||||
assert result.markdown is False
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# DICT ERROR TESTS - Unknown Keys
|
||||
# =============================================================================
|
||||
|
||||
class TestDictUnknownKeyError:
|
||||
"""Test dict with unknown key raises helpful error."""
|
||||
|
||||
def test_unknown_key_raises_typeerror(self, resolver):
|
||||
"""Unknown key in dict raises TypeError with helpful message."""
|
||||
resolve, _ = resolver
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"verbose": True, "unknown_key": "value"},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
error_msg = str(exc_info.value)
|
||||
assert "Unknown keys for output" in error_msg
|
||||
assert "unknown_key" in error_msg
|
||||
assert "Valid keys" in error_msg
|
||||
|
||||
def test_multiple_unknown_keys(self, resolver):
|
||||
"""Multiple unknown keys are all reported."""
|
||||
resolve, _ = resolver
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"foo": 1, "bar": 2, "verbose": True},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
error_msg = str(exc_info.value)
|
||||
assert "foo" in error_msg or "bar" in error_msg
|
||||
|
||||
def test_typo_in_key_raises_error(self, resolver):
|
||||
"""Typo in key name raises error with valid keys listed."""
|
||||
resolve, _ = resolver
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"verbos": True}, # typo: verbos instead of verbose
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
error_msg = str(exc_info.value)
|
||||
assert "verbos" in error_msg
|
||||
assert "verbose" in error_msg # valid key should be shown
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# DICT ERROR TESTS - No Config Class
|
||||
# =============================================================================
|
||||
|
||||
class TestDictNoConfigClassError:
|
||||
"""Test dict where no config class is defined raises error."""
|
||||
|
||||
def test_dict_without_config_class_raises_typeerror(self, resolver):
|
||||
"""Dict input without config_class raises TypeError."""
|
||||
resolve, _ = resolver
|
||||
with pytest.raises(TypeError) as exc_info:
|
||||
resolve(
|
||||
value={"some": "dict"},
|
||||
param_name="custom_param",
|
||||
config_class=None,
|
||||
)
|
||||
error_msg = str(exc_info.value)
|
||||
assert "Dict input not supported" in error_msg
|
||||
assert "custom_param" in error_msg
|
||||
assert "no config class" in error_msg
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# PRECEDENCE TESTS
|
||||
# =============================================================================
|
||||
|
||||
class TestPrecedence:
|
||||
"""Test precedence ordering: Instance > Config > Dict > Array > String > Bool > Default."""
|
||||
|
||||
def test_instance_beats_dict(self, resolver):
|
||||
"""Instance check takes precedence over dict."""
|
||||
resolve, _ = resolver
|
||||
|
||||
class CustomInstance:
|
||||
def __init__(self):
|
||||
self.custom = True
|
||||
|
||||
instance = CustomInstance()
|
||||
result = resolve(
|
||||
value=instance,
|
||||
param_name="test",
|
||||
config_class=TestOutputConfig,
|
||||
instance_check=lambda v: isinstance(v, CustomInstance),
|
||||
)
|
||||
assert result is instance
|
||||
|
||||
def test_config_instance_beats_dict(self, resolver):
|
||||
"""Config instance takes precedence over dict conversion."""
|
||||
resolve, _ = resolver
|
||||
config = TestOutputConfig(verbose=True, stream=False)
|
||||
result = resolve(
|
||||
value=config,
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert result is config
|
||||
|
||||
def test_dict_beats_string(self, resolver, output_presets):
|
||||
"""Dict takes precedence over string preset lookup."""
|
||||
resolve, _ = resolver
|
||||
# Dict should be processed, not treated as string
|
||||
result = resolve(
|
||||
value={"verbose": False, "stream": False},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
presets=output_presets,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is False
|
||||
assert result.stream is False
|
||||
|
||||
def test_dict_beats_bool(self, resolver):
|
||||
"""Dict takes precedence over bool handling."""
|
||||
resolve, _ = resolver
|
||||
# Dict should be processed, not treated as bool
|
||||
result = resolve(
|
||||
value={"verbose": True},
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is True
|
||||
|
||||
def test_bool_true_creates_default_config(self, resolver):
|
||||
"""Bool True creates default config instance."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value=True,
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is False # default
|
||||
|
||||
def test_bool_false_returns_none(self, resolver):
|
||||
"""Bool False returns None (disabled)."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value=False,
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
)
|
||||
assert result is None
|
||||
|
||||
def test_none_returns_default(self, resolver):
|
||||
"""None returns the default value."""
|
||||
resolve, _ = resolver
|
||||
default = TestOutputConfig(verbose=True)
|
||||
result = resolve(
|
||||
value=None,
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
default=default,
|
||||
)
|
||||
assert result is default
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# ARRAY SEMANTICS UNCHANGED TESTS
|
||||
# =============================================================================
|
||||
|
||||
class TestArraySemanticsUnchanged:
|
||||
"""Test that array semantics remain unchanged."""
|
||||
|
||||
def test_preset_override_array(self, resolver, output_presets):
|
||||
"""[preset, {overrides}] pattern still works."""
|
||||
resolve, ArrayMode = resolver
|
||||
result = resolve(
|
||||
value=["verbose", {"stream": False}],
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
presets=output_presets,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is True # from preset
|
||||
assert result.stream is False # overridden
|
||||
|
||||
def test_step_names_array(self, resolver):
|
||||
"""List of step names creates config with from_steps."""
|
||||
resolve, ArrayMode = resolver
|
||||
result = resolve(
|
||||
value=["step1", "step2"],
|
||||
param_name="context",
|
||||
config_class=TestContextConfig,
|
||||
array_mode=ArrayMode.STEP_NAMES,
|
||||
)
|
||||
assert isinstance(result, TestContextConfig)
|
||||
assert result.from_steps == ["step1", "step2"]
|
||||
|
||||
def test_passthrough_array(self, resolver):
|
||||
"""Passthrough mode returns list as-is."""
|
||||
resolve, ArrayMode = resolver
|
||||
input_list = ["a", "b", "c"]
|
||||
result = resolve(
|
||||
value=input_list,
|
||||
param_name="hooks",
|
||||
config_class=None,
|
||||
array_mode=ArrayMode.PASSTHROUGH,
|
||||
)
|
||||
assert result == input_list
|
||||
|
||||
def test_empty_array_returns_none(self, resolver):
|
||||
"""Empty array returns None (disabled)."""
|
||||
resolve, ArrayMode = resolver
|
||||
result = resolve(
|
||||
value=[],
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
array_mode=ArrayMode.PRESET_OVERRIDE,
|
||||
)
|
||||
assert result is None
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# HELPER FUNCTION TESTS
|
||||
# =============================================================================
|
||||
|
||||
class TestHelperFunctions:
|
||||
"""Test helper functions for dict validation."""
|
||||
|
||||
def test_get_config_fields(self):
|
||||
"""_get_config_fields returns field names."""
|
||||
from praisonaiagents.config.param_resolver import _get_config_fields
|
||||
fields = _get_config_fields(TestOutputConfig)
|
||||
assert "verbose" in fields
|
||||
assert "stream" in fields
|
||||
assert "markdown" in fields
|
||||
|
||||
def test_validate_dict_keys_valid(self):
|
||||
"""_validate_dict_keys returns empty list for valid keys."""
|
||||
from praisonaiagents.config.param_resolver import _validate_dict_keys
|
||||
unknown = _validate_dict_keys(
|
||||
{"verbose": True, "stream": False},
|
||||
TestOutputConfig
|
||||
)
|
||||
assert unknown == []
|
||||
|
||||
def test_validate_dict_keys_invalid(self):
|
||||
"""_validate_dict_keys returns unknown keys."""
|
||||
from praisonaiagents.config.param_resolver import _validate_dict_keys
|
||||
unknown = _validate_dict_keys(
|
||||
{"verbose": True, "bad_key": "value"},
|
||||
TestOutputConfig
|
||||
)
|
||||
assert "bad_key" in unknown
|
||||
|
||||
def test_get_example_dict(self):
|
||||
"""_get_example_dict returns example snippet."""
|
||||
from praisonaiagents.config.param_resolver import _get_example_dict
|
||||
example = _get_example_dict(TestOutputConfig)
|
||||
assert "verbose" in example or "stream" in example
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# STRING PRESET TESTS (regression)
|
||||
# =============================================================================
|
||||
|
||||
class TestStringPresets:
|
||||
"""Test string preset resolution still works."""
|
||||
|
||||
def test_string_preset_resolves(self, resolver, output_presets):
|
||||
"""String preset name resolves to config."""
|
||||
resolve, _ = resolver
|
||||
result = resolve(
|
||||
value="verbose",
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
presets=output_presets,
|
||||
)
|
||||
assert isinstance(result, TestOutputConfig)
|
||||
assert result.verbose is True
|
||||
|
||||
def test_invalid_preset_raises_error(self, resolver, output_presets):
|
||||
"""Invalid preset name raises helpful error."""
|
||||
resolve, _ = resolver
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
resolve(
|
||||
value="invalid_preset",
|
||||
param_name="output",
|
||||
config_class=TestOutputConfig,
|
||||
presets=output_presets,
|
||||
)
|
||||
error_msg = str(exc_info.value)
|
||||
assert "invalid_preset" in error_msg
|
||||
@@ -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"
|
||||
Whitespace-only changes.
Whitespace-only changes.
Whitespace-only changes.
Whitespace-only changes.
Whitespace-only changes.
Whitespace-only changes.
Generated
+1
-1
@@ -2422,7 +2422,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "praisonaiagents"
|
||||
version = "0.10.6"
|
||||
version = "0.11.2"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "aiohttp" },
|
||||
|
||||
@@ -1,2 +1,3 @@
|
||||
chainlit.md
|
||||
tests/fixtures
|
||||
tests/fixtures
|
||||
reports
|
||||
@@ -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/v3.5.7.tar.gz"
|
||||
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.5.7.tar.gz | shasum -a 256`.split.first
|
||||
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.7.3.tar.gz"
|
||||
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v3.7.3.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()
|
||||
@@ -266,6 +266,115 @@ 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()
|
||||
|
||||
@@ -5,20 +5,60 @@ Provides terminal-native interactive chat mode.
|
||||
This command NEVER opens a browser - it runs entirely in the terminal.
|
||||
"""
|
||||
|
||||
from typing import List, Optional
|
||||
from typing import List, Optional, Union
|
||||
|
||||
import typer
|
||||
|
||||
app = typer.Typer(help="Terminal-native interactive chat mode")
|
||||
|
||||
|
||||
def _parse_memory_flag(memory: Optional[str], no_memory: bool) -> Union[bool, str, None]:
|
||||
"""
|
||||
Parse memory CLI flag to value for Agent.
|
||||
|
||||
Precedence: --no-memory > --memory=value > --memory (flag) > None
|
||||
|
||||
Args:
|
||||
memory: Memory flag value (None, "true", preset string, or URL)
|
||||
no_memory: Whether --no-memory was specified
|
||||
|
||||
Returns:
|
||||
- False if --no-memory
|
||||
- True if --memory (flag only)
|
||||
- str if --memory=preset or --memory=URL
|
||||
- None if neither specified
|
||||
"""
|
||||
if no_memory:
|
||||
return False
|
||||
|
||||
if memory is None:
|
||||
return None
|
||||
|
||||
# --memory flag without value sets "true"
|
||||
if memory.lower() == "true":
|
||||
return True
|
||||
|
||||
# --memory=false explicitly disables
|
||||
if memory.lower() == "false":
|
||||
return False
|
||||
|
||||
# Otherwise it's a preset or URL string
|
||||
return memory
|
||||
|
||||
|
||||
@app.callback(invoke_without_command=True)
|
||||
def chat_main(
|
||||
ctx: typer.Context,
|
||||
prompt: Optional[str] = typer.Argument(None, help="Initial prompt for chat"),
|
||||
model: Optional[str] = typer.Option(None, "--model", "-m", help="LLM model to use"),
|
||||
verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
|
||||
memory: bool = typer.Option(False, "--memory", help="Enable memory"),
|
||||
memory: Optional[str] = typer.Option(
|
||||
None, "--memory",
|
||||
help="Enable memory. Use --memory for default, --memory=redis for preset, --memory=postgresql://... for URL",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
no_memory: bool = typer.Option(False, "--no-memory", help="Disable memory"),
|
||||
tools: Optional[str] = typer.Option(None, "--tools", "-t", help="Tools file path"),
|
||||
user_id: Optional[str] = typer.Option(None, "--user-id", help="User ID for memory isolation"),
|
||||
session_id: Optional[str] = typer.Option(None, "--session", "-s", help="Session ID to resume"),
|
||||
@@ -28,8 +68,70 @@ def chat_main(
|
||||
no_acp: bool = typer.Option(False, "--no-acp", help="Disable ACP tools"),
|
||||
no_lsp: bool = typer.Option(False, "--no-lsp", help="Disable LSP tools"),
|
||||
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(
|
||||
None, "--knowledge", "-k",
|
||||
help="Enable knowledge/RAG. Use --knowledge for default, --knowledge=docs/ for sources",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
guardrails: Optional[str] = typer.Option(
|
||||
None, "--guardrails",
|
||||
help="Enable guardrails. Use --guardrails for default, --guardrails=strict for preset",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
web: Optional[str] = typer.Option(
|
||||
None, "--web",
|
||||
help="Enable web search. Use --web for default, --web=duckduckgo for preset",
|
||||
is_flag=False,
|
||||
flag_value="true",
|
||||
),
|
||||
reflection: Optional[str] = typer.Option(
|
||||
None, "--reflection",
|
||||
help="Enable self-reflection. Use --reflection for default, --reflection=thorough for preset",
|
||||
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",
|
||||
help="Output preset. Use --output=verbose, --output=minimal, --output=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)"),
|
||||
# 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.
|
||||
@@ -54,6 +156,18 @@ def chat_main(
|
||||
if workspace:
|
||||
os.environ["PRAISONAI_WORKSPACE"] = workspace
|
||||
|
||||
# Configure UI backend
|
||||
from praisonai.cli.ui import select_backend, UIConfig
|
||||
ui_config = UIConfig(
|
||||
ui_backend=ui_backend,
|
||||
json_output=json_output,
|
||||
no_color=no_color,
|
||||
theme=theme,
|
||||
compact=compact,
|
||||
verbose=verbose,
|
||||
)
|
||||
backend = select_backend(ui_config)
|
||||
|
||||
# Handle profiling for single prompt mode
|
||||
if prompt and (profile or profile_deep):
|
||||
_run_profiled_chat(
|
||||
@@ -69,6 +183,9 @@ def chat_main(
|
||||
typer.echo("⚠️ Profiling is only supported for single prompt mode.", err=True)
|
||||
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)
|
||||
|
||||
# Try InteractiveCore first (preferred terminal-native implementation)
|
||||
try:
|
||||
from praisonai.cli.interactive import InteractiveCore, InteractiveConfig
|
||||
@@ -80,7 +197,7 @@ def chat_main(
|
||||
continue_session=continue_session,
|
||||
workspace=workspace or None,
|
||||
verbose=verbose,
|
||||
memory=memory,
|
||||
memory=memory_value,
|
||||
files=list(file) if file else [],
|
||||
autonomy=autonomy,
|
||||
)
|
||||
@@ -88,17 +205,22 @@ def chat_main(
|
||||
core = InteractiveCore(config=config)
|
||||
|
||||
if prompt:
|
||||
# Single prompt mode
|
||||
# Single prompt mode - use backend for output
|
||||
from praisonai.cli.ui.events import UIEventType
|
||||
|
||||
async def run_prompt():
|
||||
if continue_session:
|
||||
core.continue_session()
|
||||
|
||||
backend.emit(UIEventType.MESSAGE_START, {})
|
||||
response = await core.prompt(prompt)
|
||||
print(response)
|
||||
backend.emit(UIEventType.MESSAGE_CHUNK, {'content': response})
|
||||
backend.emit(UIEventType.MESSAGE_END, {})
|
||||
|
||||
asyncio.run(run_prompt())
|
||||
else:
|
||||
# Interactive REPL mode
|
||||
frontend = RichFrontend(core=core, config=config)
|
||||
# Interactive REPL mode - pass ui_config to frontend
|
||||
frontend = RichFrontend(core=core, config=config, ui_config=ui_config)
|
||||
asyncio.run(frontend.run())
|
||||
|
||||
except ImportError:
|
||||
@@ -153,7 +275,6 @@ def _run_profiled_chat(
|
||||
"name": "ChatAgent",
|
||||
"role": "Assistant",
|
||||
"goal": "Help the user",
|
||||
"verbose": verbose,
|
||||
}
|
||||
if model:
|
||||
agent_config["llm"] = model
|
||||
|
||||
@@ -21,7 +21,8 @@ app = typer.Typer(help="Documentation management and code validation")
|
||||
def _get_default_docs_path() -> Path:
|
||||
"""Get default docs path."""
|
||||
candidates = [
|
||||
Path("/Users/praison/PraisonAIDocs"),
|
||||
Path.home() / "PraisonAIDocs" / "docs",
|
||||
Path("/Users/praison/PraisonAIDocs/docs"),
|
||||
Path.cwd() / "docs",
|
||||
Path(__file__).parent.parent.parent.parent.parent / "docs",
|
||||
]
|
||||
@@ -36,7 +37,7 @@ def _get_default_docs_path() -> Path:
|
||||
def _get_default_report_dir() -> Path:
|
||||
"""Get default report directory with timestamp."""
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
return Path.cwd() / "reports" / "docs" / timestamp
|
||||
return Path.home() / "Downloads" / "reports" / "docs" / timestamp
|
||||
|
||||
|
||||
@app.command("run")
|
||||
@@ -56,6 +57,11 @@ def docs_run(
|
||||
"--exclude", "-e",
|
||||
help="Exclude patterns (glob), can be specified multiple times",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Run only specific groups (top-level dirs), can be repeated",
|
||||
),
|
||||
languages: str = typer.Option(
|
||||
"python",
|
||||
"--languages", "-l",
|
||||
@@ -66,26 +72,21 @@ def docs_run(
|
||||
"--timeout", "-t",
|
||||
help="Per-snippet timeout in seconds",
|
||||
),
|
||||
max_snippets: Optional[int] = typer.Option(
|
||||
None,
|
||||
"--max-snippets",
|
||||
help="Maximum snippets to process",
|
||||
),
|
||||
fail_fast: bool = typer.Option(
|
||||
False,
|
||||
"--fail-fast", "-x",
|
||||
help="Stop on first failure",
|
||||
),
|
||||
dry_run: bool = typer.Option(
|
||||
False,
|
||||
"--dry-run",
|
||||
help="Extract only, don't execute",
|
||||
),
|
||||
mode: str = typer.Option(
|
||||
"lenient",
|
||||
"--mode", "-m",
|
||||
help="Mode: 'lenient' or 'strict' (strict fails on not_run)",
|
||||
),
|
||||
max_snippets: Optional[int] = typer.Option(
|
||||
None,
|
||||
"--max-snippets",
|
||||
help="Maximum snippets to process",
|
||||
),
|
||||
no_stream: bool = typer.Option(
|
||||
False,
|
||||
"--no-stream",
|
||||
@@ -106,11 +107,21 @@ def docs_run(
|
||||
"--no-md",
|
||||
help="Skip Markdown report generation",
|
||||
),
|
||||
no_csv: bool = typer.Option(
|
||||
False,
|
||||
"--no-csv",
|
||||
help="Skip CSV report generation",
|
||||
),
|
||||
require_env: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--require-env",
|
||||
help="Required env vars (skip all if missing)",
|
||||
),
|
||||
python: Optional[str] = typer.Option(
|
||||
None,
|
||||
"--python",
|
||||
help="Python executable to use (default: current interpreter)",
|
||||
),
|
||||
quiet: bool = typer.Option(
|
||||
False,
|
||||
"--quiet", "-q",
|
||||
@@ -121,17 +132,16 @@ def docs_run(
|
||||
Run Python code blocks from documentation files.
|
||||
|
||||
Extracts code blocks from Mintlify docs, classifies them as runnable,
|
||||
executes them, and generates reports.
|
||||
executes them, and generates reports (JSON, Markdown, CSV).
|
||||
|
||||
Examples:
|
||||
praisonai docs run
|
||||
praisonai docs run --docs-path /path/to/docs --timeout 120
|
||||
praisonai docs run --dry-run --max-snippets 10
|
||||
praisonai docs run --group models --group tools --max-snippets 10
|
||||
praisonai docs run --include "quickstart*" --fail-fast
|
||||
"""
|
||||
# Lazy import to avoid loading at CLI startup
|
||||
from praisonai.docs_runner.executor import DocsExecutor
|
||||
from praisonai.docs_runner.reporter import SnippetResult
|
||||
from praisonai.suite_runner import DocsSource, SuiteExecutor, RunResult
|
||||
|
||||
# Resolve paths
|
||||
docs = docs_path or _get_default_docs_path()
|
||||
@@ -144,22 +154,34 @@ def docs_run(
|
||||
# Parse languages
|
||||
lang_list = [lang.strip() for lang in languages.split(',') if lang.strip()]
|
||||
|
||||
# Create executor
|
||||
executor = DocsExecutor(
|
||||
docs_path=docs,
|
||||
# Create source
|
||||
source = DocsSource(
|
||||
root=docs,
|
||||
languages=lang_list,
|
||||
include_patterns=list(include) if include else None,
|
||||
exclude_patterns=list(exclude) if exclude else None,
|
||||
languages=lang_list,
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
# Discover items
|
||||
items = source.discover()
|
||||
|
||||
# Create executor
|
||||
executor = SuiteExecutor(
|
||||
suite="docs",
|
||||
source_path=docs,
|
||||
timeout=timeout,
|
||||
fail_fast=fail_fast,
|
||||
stream_output=not no_stream,
|
||||
dry_run=dry_run,
|
||||
mode=mode,
|
||||
max_snippets=max_snippets,
|
||||
max_items=max_snippets,
|
||||
require_env=list(require_env) if require_env else None,
|
||||
report_dir=output_dir,
|
||||
generate_json=not no_json,
|
||||
generate_md=not no_md,
|
||||
generate_csv=not no_csv,
|
||||
python_executable=python,
|
||||
pythonpath_additions=source.get_pythonpath(),
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
# Status icons
|
||||
@@ -169,27 +191,27 @@ def docs_run(
|
||||
"skipped": "⏭️",
|
||||
"timeout": "⏱️",
|
||||
"not_run": "📝",
|
||||
"xfail": "⚠️",
|
||||
}
|
||||
|
||||
def on_snippet_start(block, idx: int, total: int):
|
||||
def on_item_start(item, idx: int, total: int):
|
||||
if not quiet:
|
||||
doc_name = block.doc_path.name
|
||||
typer.echo(f"\n[{idx}/{total}] {doc_name} block {block.block_index}")
|
||||
typer.echo(f"\n[{idx}/{total}] {item.display_name}")
|
||||
|
||||
def on_snippet_end(result: SnippetResult, idx: int, total: int):
|
||||
def on_item_end(result: RunResult, idx: int, total: int):
|
||||
icon = icons.get(result.status, "?")
|
||||
duration = f"{result.duration_seconds:.2f}s" if result.duration_seconds else ""
|
||||
|
||||
if quiet:
|
||||
typer.echo(f"{icon} {result.doc_path.name}:{result.block_index}")
|
||||
typer.echo(f"{icon} {result.display_name}")
|
||||
else:
|
||||
msg = f" {icon} {result.status.upper()}"
|
||||
if duration:
|
||||
msg += f" ({duration})"
|
||||
if result.skip_reason:
|
||||
msg += f" - {result.skip_reason[:50]}"
|
||||
if result.error_summary and not no_stream:
|
||||
msg += f"\n Error: {result.error_summary[:100]}"
|
||||
if result.error_message and not no_stream:
|
||||
msg += f"\n Error: {result.error_message[:100]}"
|
||||
typer.echo(msg)
|
||||
|
||||
def on_output(line: str, stream: str):
|
||||
@@ -205,17 +227,25 @@ def docs_run(
|
||||
typer.echo(f"Docs Path: {docs}")
|
||||
typer.echo(f"Timeout: {timeout}s")
|
||||
typer.echo(f"Mode: {mode}")
|
||||
if dry_run:
|
||||
typer.echo("Mode: DRY RUN (no execution)")
|
||||
if group:
|
||||
typer.echo(f"Groups: {', '.join(group)}")
|
||||
typer.echo(f"Reports: {output_dir}")
|
||||
typer.echo(f"Items: {len(items)}")
|
||||
|
||||
# Run
|
||||
report = executor.run(
|
||||
on_snippet_start=on_snippet_start,
|
||||
on_snippet_end=on_snippet_end,
|
||||
items=items,
|
||||
on_item_start=on_item_start,
|
||||
on_item_end=on_item_end,
|
||||
on_output=on_output if not no_stream else None,
|
||||
)
|
||||
|
||||
# Update report with CLI args
|
||||
report.cli_args = [f"--docs-path={docs}", f"--timeout={timeout}"]
|
||||
if group:
|
||||
for g in group:
|
||||
report.cli_args.append(f"--group={g}")
|
||||
|
||||
# Print summary
|
||||
totals = report.totals
|
||||
total_count = sum(totals.values())
|
||||
@@ -263,6 +293,11 @@ def docs_list(
|
||||
"--exclude", "-e",
|
||||
help="Exclude patterns (glob)",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Filter by group (top-level dir)",
|
||||
),
|
||||
languages: str = typer.Option(
|
||||
"python",
|
||||
"--languages", "-l",
|
||||
@@ -273,16 +308,21 @@ def docs_list(
|
||||
"--code", "-c",
|
||||
help="Show code preview",
|
||||
),
|
||||
show_groups: bool = typer.Option(
|
||||
False,
|
||||
"--groups",
|
||||
help="Show available groups only",
|
||||
),
|
||||
):
|
||||
"""
|
||||
List discovered code blocks from documentation.
|
||||
|
||||
Examples:
|
||||
praisonai docs list
|
||||
praisonai docs list --docs-path /path/to/docs --code
|
||||
praisonai docs list --groups
|
||||
praisonai docs list --group models --code
|
||||
"""
|
||||
from praisonai.docs_runner.extractor import FenceExtractor
|
||||
from praisonai.docs_runner.classifier import RunnableClassifier
|
||||
from praisonai.suite_runner import DocsSource
|
||||
|
||||
docs = docs_path or _get_default_docs_path()
|
||||
|
||||
@@ -293,38 +333,354 @@ def docs_list(
|
||||
# Parse languages
|
||||
lang_list = [lang.strip() for lang in languages.split(',') if lang.strip()]
|
||||
|
||||
extractor = FenceExtractor(languages=lang_list)
|
||||
classifier = RunnableClassifier(target_languages=tuple(lang_list))
|
||||
|
||||
blocks = extractor.extract_from_directory(
|
||||
docs,
|
||||
source = DocsSource(
|
||||
root=docs,
|
||||
languages=lang_list,
|
||||
include_patterns=list(include) if include else None,
|
||||
exclude_patterns=list(exclude) if exclude else None,
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
# Filter to target languages
|
||||
blocks = [b for b in blocks if b.language in lang_list]
|
||||
# Show groups only
|
||||
if show_groups:
|
||||
groups = source.get_groups()
|
||||
typer.echo(f"Available groups in {docs}:\n")
|
||||
for g in groups:
|
||||
typer.echo(f" - {g}")
|
||||
return
|
||||
|
||||
typer.echo(f"Found {len(blocks)} code blocks in {docs}\n")
|
||||
items = source.discover()
|
||||
|
||||
for idx, block in enumerate(blocks, 1):
|
||||
rel_path = block.doc_path.relative_to(docs) if docs in block.doc_path.parents else block.doc_path
|
||||
classification = classifier.classify(block)
|
||||
typer.echo(f"Found {len(items)} code blocks in {docs}\n")
|
||||
|
||||
for idx, item in enumerate(items, 1):
|
||||
rel_path = item.source_path.relative_to(docs) if docs in item.source_path.parents else item.source_path
|
||||
|
||||
status = "✅ Runnable" if classification.is_runnable else "📝 Partial"
|
||||
status = "✅ Runnable" if item.runnable else "📝 Partial"
|
||||
|
||||
typer.echo(f"{idx:3}. {rel_path}:{block.line_start}-{block.line_end}")
|
||||
typer.echo(f" {status} ({classification.reason})")
|
||||
typer.echo(f"{idx:3}. [{item.group}] {rel_path}:{item.line_start}-{item.line_end}")
|
||||
typer.echo(f" {status} ({item.runnable_decision})")
|
||||
|
||||
if show_code:
|
||||
preview = block.code[:100].replace('\n', ' ')
|
||||
if len(block.code) > 100:
|
||||
preview = item.code[:100].replace('\n', ' ')
|
||||
if len(item.code) > 100:
|
||||
preview += "..."
|
||||
typer.echo(f" Code: {preview}")
|
||||
|
||||
typer.echo()
|
||||
|
||||
|
||||
@app.command("stats")
|
||||
def docs_stats(
|
||||
docs_path: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--docs-path", "-p",
|
||||
help="Path to documentation directory",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Filter by group (top-level dir)",
|
||||
),
|
||||
languages: str = typer.Option(
|
||||
"python",
|
||||
"--languages", "-l",
|
||||
help="Languages to show (comma-separated)",
|
||||
),
|
||||
):
|
||||
"""
|
||||
Show statistics for documentation code blocks.
|
||||
|
||||
Displays counts by group, runnable status, and agent-centric usage.
|
||||
|
||||
Examples:
|
||||
praisonai docs stats
|
||||
praisonai docs stats --group models --group tools
|
||||
"""
|
||||
from collections import Counter
|
||||
from praisonai.suite_runner import DocsSource
|
||||
|
||||
docs = docs_path or _get_default_docs_path()
|
||||
|
||||
if not docs.exists():
|
||||
typer.echo(f"❌ Docs path not found: {docs}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
lang_list = [lang.strip() for lang in languages.split(',') if lang.strip()]
|
||||
|
||||
source = DocsSource(
|
||||
root=docs,
|
||||
languages=lang_list,
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
items = source.discover()
|
||||
|
||||
# Calculate stats
|
||||
group_counts = Counter(item.group for item in items)
|
||||
runnable_by_group = Counter(item.group for item in items if item.runnable)
|
||||
|
||||
# Agent-centric stats
|
||||
agent_count = sum(1 for item in items if item.uses_agent)
|
||||
agents_count = sum(1 for item in items if item.uses_agents)
|
||||
workflow_count = sum(1 for item in items if item.uses_workflow)
|
||||
|
||||
agent_by_group = Counter(item.group for item in items if item.uses_agent)
|
||||
agents_by_group = Counter(item.group for item in items if item.uses_agents)
|
||||
workflow_by_group = Counter(item.group for item in items if item.uses_workflow)
|
||||
|
||||
typer.echo("\n📊 Documentation Code Block Statistics")
|
||||
typer.echo(f"Path: {docs}")
|
||||
typer.echo("=" * 80)
|
||||
|
||||
typer.echo(f"\n{'Group':<20} {'Total':>8} {'Runnable':>10} {'Agent':>8} {'Agents':>8} {'Workflow':>10}")
|
||||
typer.echo("-" * 80)
|
||||
|
||||
for g in sorted(group_counts.keys()):
|
||||
typer.echo(
|
||||
f"{g:<20} {group_counts[g]:>8} {runnable_by_group[g]:>10} "
|
||||
f"{agent_by_group[g]:>8} {agents_by_group[g]:>8} {workflow_by_group[g]:>10}"
|
||||
)
|
||||
|
||||
typer.echo("-" * 80)
|
||||
typer.echo(
|
||||
f"{'TOTAL':<20} {len(items):>8} {sum(1 for i in items if i.runnable):>10} "
|
||||
f"{agent_count:>8} {agents_count:>8} {workflow_count:>10}"
|
||||
)
|
||||
typer.echo()
|
||||
|
||||
|
||||
@app.command("run-all")
|
||||
def docs_run_all(
|
||||
docs_path: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--docs-path", "-p",
|
||||
help="Path to documentation directory",
|
||||
),
|
||||
timeout: int = typer.Option(
|
||||
60,
|
||||
"--timeout", "-t",
|
||||
help="Per-snippet timeout in seconds",
|
||||
),
|
||||
report_dir: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--report-dir", "-r",
|
||||
help="Directory for reports (default: ~/Downloads/reports/docs/<timestamp>)",
|
||||
),
|
||||
parallel: bool = typer.Option(
|
||||
True,
|
||||
"--parallel/--sequential",
|
||||
help="Run groups in parallel (default: parallel)",
|
||||
),
|
||||
max_workers: int = typer.Option(
|
||||
4,
|
||||
"--workers", "-w",
|
||||
help="Max parallel workers (default: 4)",
|
||||
),
|
||||
quiet: bool = typer.Option(
|
||||
False,
|
||||
"--quiet", "-q",
|
||||
help="Minimal output",
|
||||
),
|
||||
):
|
||||
"""
|
||||
Run all documentation code blocks group-by-group.
|
||||
|
||||
Executes all groups and generates a comprehensive report.
|
||||
Uses parallel execution by default for faster results.
|
||||
|
||||
Examples:
|
||||
praisonai docs run-all
|
||||
praisonai docs run-all --sequential
|
||||
praisonai docs run-all --workers 8 --timeout 120
|
||||
"""
|
||||
import json
|
||||
from concurrent.futures import ProcessPoolExecutor, as_completed
|
||||
from praisonai.suite_runner import DocsSource, SuiteExecutor, RunResult
|
||||
|
||||
docs = docs_path or _get_default_docs_path()
|
||||
output_dir = report_dir or _get_default_report_dir()
|
||||
|
||||
if not docs.exists():
|
||||
typer.echo(f"❌ Docs path not found: {docs}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
# Get all groups
|
||||
source = DocsSource(root=docs)
|
||||
all_groups = sorted(source.get_groups())
|
||||
|
||||
typer.echo(f"Found {len(all_groups)} groups to process")
|
||||
typer.echo(f"Mode: {'parallel' if parallel else 'sequential'}")
|
||||
typer.echo("=" * 60)
|
||||
|
||||
# Track overall results
|
||||
overall_results = {
|
||||
'passed': 0, 'failed': 0, 'skipped': 0,
|
||||
'timeout': 0, 'not_run': 0, 'total': 0,
|
||||
}
|
||||
group_summaries = []
|
||||
|
||||
def run_group(group_name: str) -> dict:
|
||||
"""Run a single group and return summary."""
|
||||
group_source = DocsSource(root=docs, groups=[group_name])
|
||||
items = group_source.discover()
|
||||
|
||||
if not items:
|
||||
return {
|
||||
'group': group_name,
|
||||
'total': 0, 'passed': 0, 'failed': 0,
|
||||
'skipped': 0, 'timeout': 0, 'not_run': 0,
|
||||
}
|
||||
|
||||
group_report_dir = output_dir / group_name
|
||||
group_report_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
executor = SuiteExecutor(
|
||||
suite='docs',
|
||||
source_path=docs,
|
||||
report_dir=group_report_dir,
|
||||
timeout=timeout,
|
||||
stream_output=False,
|
||||
generate_json=True,
|
||||
generate_md=True,
|
||||
generate_csv=True,
|
||||
groups=[group_name],
|
||||
)
|
||||
|
||||
report = executor.run(items=items)
|
||||
totals = report.totals
|
||||
|
||||
return {
|
||||
'group': group_name,
|
||||
**totals,
|
||||
}
|
||||
|
||||
if parallel and len(all_groups) > 1:
|
||||
# Parallel execution
|
||||
with ProcessPoolExecutor(max_workers=min(max_workers, len(all_groups))) as pool:
|
||||
futures = {pool.submit(run_group, g): g for g in all_groups}
|
||||
|
||||
for future in as_completed(futures):
|
||||
group_name = futures[future]
|
||||
try:
|
||||
summary = future.result()
|
||||
group_summaries.append(summary)
|
||||
|
||||
# Update overall
|
||||
for key in overall_results:
|
||||
if key in summary:
|
||||
overall_results[key] += summary[key]
|
||||
|
||||
if not quiet:
|
||||
typer.echo(
|
||||
f"✅ {group_name}: "
|
||||
f"✅{summary['passed']} ❌{summary['failed']} "
|
||||
f"⏭️{summary['skipped']} ⏱️{summary['timeout']} 📝{summary['not_run']}"
|
||||
)
|
||||
except Exception as e:
|
||||
typer.echo(f"❌ {group_name}: Error - {e}")
|
||||
else:
|
||||
# Sequential execution with real-time output
|
||||
for group_name in all_groups:
|
||||
if not quiet:
|
||||
typer.echo(f"\n{'='*60}")
|
||||
typer.echo(f"GROUP: {group_name}")
|
||||
typer.echo(f"{'='*60}")
|
||||
|
||||
group_source = DocsSource(root=docs, groups=[group_name])
|
||||
items = group_source.discover()
|
||||
|
||||
if not items:
|
||||
if not quiet:
|
||||
typer.echo(" No items found, skipping")
|
||||
group_summaries.append({
|
||||
'group': group_name,
|
||||
'total': 0, 'passed': 0, 'failed': 0,
|
||||
'skipped': 0, 'timeout': 0, 'not_run': 0,
|
||||
})
|
||||
continue
|
||||
|
||||
group_report_dir = output_dir / group_name
|
||||
group_report_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
executor = SuiteExecutor(
|
||||
suite='docs',
|
||||
source_path=docs,
|
||||
report_dir=group_report_dir,
|
||||
timeout=timeout,
|
||||
stream_output=False,
|
||||
generate_json=True,
|
||||
generate_md=True,
|
||||
generate_csv=True,
|
||||
groups=[group_name],
|
||||
)
|
||||
|
||||
icons = {'passed': '✅', 'failed': '❌', 'skipped': '⏭️', 'timeout': '⏱️', 'not_run': '📝'}
|
||||
|
||||
def on_start(item, idx, total):
|
||||
if not quiet:
|
||||
typer.echo(f" [{idx}/{total}] {item.display_name} ", nl=False)
|
||||
|
||||
def on_end(result: RunResult, idx, total):
|
||||
if not quiet:
|
||||
icon = icons.get(result.status, '❓')
|
||||
typer.echo(f"{icon}")
|
||||
|
||||
report = executor.run(items=items, on_item_start=on_start, on_item_end=on_end)
|
||||
totals = report.totals
|
||||
|
||||
group_summaries.append({'group': group_name, **totals})
|
||||
|
||||
for key in overall_results:
|
||||
if key in totals:
|
||||
overall_results[key] += totals[key]
|
||||
|
||||
if not quiet:
|
||||
typer.echo(
|
||||
f"\n Summary: ✅{totals['passed']} ❌{totals['failed']} "
|
||||
f"⏭️{totals['skipped']} ⏱️{totals['timeout']} 📝{totals['not_run']}"
|
||||
)
|
||||
|
||||
# Final report
|
||||
typer.echo("\n" + "=" * 80)
|
||||
typer.echo("FINAL REPORT - ALL GROUPS")
|
||||
typer.echo("=" * 80)
|
||||
|
||||
typer.echo(f"\n{'Group':<20} {'Total':>8} {'Passed':>8} {'Failed':>8} {'Skip':>8} {'Timeout':>8} {'NotRun':>8}")
|
||||
typer.echo("-" * 80)
|
||||
|
||||
for gs in sorted(group_summaries, key=lambda x: x['group']):
|
||||
typer.echo(
|
||||
f"{gs['group']:<20} {gs['total']:>8} {gs['passed']:>8} {gs['failed']:>8} "
|
||||
f"{gs['skipped']:>8} {gs['timeout']:>8} {gs['not_run']:>8}"
|
||||
)
|
||||
|
||||
typer.echo("-" * 80)
|
||||
typer.echo(
|
||||
f"{'TOTAL':<20} {overall_results['total']:>8} {overall_results['passed']:>8} "
|
||||
f"{overall_results['failed']:>8} {overall_results['skipped']:>8} "
|
||||
f"{overall_results['timeout']:>8} {overall_results['not_run']:>8}"
|
||||
)
|
||||
|
||||
# Save final summary
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
summary_path = output_dir / 'final_summary.json'
|
||||
with open(summary_path, 'w') as f:
|
||||
json.dump({
|
||||
'timestamp': datetime.now().isoformat(),
|
||||
'overall': overall_results,
|
||||
'groups': group_summaries,
|
||||
}, f, indent=2)
|
||||
|
||||
typer.echo(f"\n📁 Final summary saved to: {summary_path}")
|
||||
typer.echo(f"📁 Individual group reports in: {output_dir}")
|
||||
|
||||
# Exit code
|
||||
if overall_results['failed'] > 0 or overall_results['timeout'] > 0:
|
||||
raise typer.Exit(1)
|
||||
raise typer.Exit(0)
|
||||
|
||||
|
||||
@app.command("generate")
|
||||
def docs_generate(
|
||||
source: str = typer.Argument(".", help="Source directory"),
|
||||
@@ -368,3 +724,136 @@ def docs_serve(
|
||||
pass
|
||||
finally:
|
||||
sys.argv = original_argv
|
||||
|
||||
|
||||
@app.command("report")
|
||||
def docs_report(
|
||||
report_dir: Optional[Path] = typer.Argument(
|
||||
None,
|
||||
help="Report directory path (default: auto-detect latest)",
|
||||
),
|
||||
base_dir: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--base-dir", "-b",
|
||||
help="Base reports directory (default: ~/Downloads/reports/docs)",
|
||||
),
|
||||
limit: int = typer.Option(
|
||||
50,
|
||||
"--limit", "-n",
|
||||
help="Limit rows in tables (0 = no limit)",
|
||||
),
|
||||
errors: bool = typer.Option(
|
||||
True,
|
||||
"--errors/--no-errors",
|
||||
help="Show error grouping section",
|
||||
),
|
||||
wide: bool = typer.Option(
|
||||
False,
|
||||
"--wide/--no-wide",
|
||||
help="Wide output: full error messages and item lists",
|
||||
),
|
||||
show_paths: bool = typer.Option(
|
||||
True,
|
||||
"--show-paths/--no-show-paths",
|
||||
help="Show affected item paths in error groups",
|
||||
),
|
||||
match: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--match", "-m",
|
||||
help="Filter by status (repeatable: --match failed --match timeout)",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Filter by group name (repeatable)",
|
||||
),
|
||||
contains: Optional[str] = typer.Option(
|
||||
None,
|
||||
"--contains", "-c",
|
||||
help="Filter items whose error contains text (case-insensitive)",
|
||||
),
|
||||
open_dir: bool = typer.Option(
|
||||
False,
|
||||
"--open",
|
||||
help="Show report artifacts listing",
|
||||
),
|
||||
output_format: str = typer.Option(
|
||||
"table",
|
||||
"--format", "-f",
|
||||
help="Output format: table or json",
|
||||
),
|
||||
):
|
||||
"""
|
||||
View execution report with failures and error grouping.
|
||||
|
||||
Examples:
|
||||
praisonai docs report # View latest report
|
||||
praisonai docs report ./my-report # View specific report
|
||||
praisonai docs report --wide --limit 0 # Full details
|
||||
praisonai docs report --match failed # Only failures
|
||||
praisonai docs report --format json # JSON output
|
||||
"""
|
||||
# Lazy import to avoid loading at CLI startup
|
||||
from praisonai.suite_runner.report_viewer import view_report
|
||||
|
||||
output, exit_code = view_report(
|
||||
report_dir=report_dir,
|
||||
suite="docs",
|
||||
base_dir=base_dir,
|
||||
limit=limit,
|
||||
show_errors=errors,
|
||||
wide=wide,
|
||||
show_paths=show_paths,
|
||||
match_statuses=match,
|
||||
match_groups=group,
|
||||
contains=contains,
|
||||
show_artifacts=open_dir,
|
||||
output_format=output_format,
|
||||
)
|
||||
|
||||
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)
|
||||
@@ -20,8 +20,9 @@ app = typer.Typer(help="Run and manage example files")
|
||||
|
||||
def _get_default_examples_path() -> Path:
|
||||
"""Get default examples path (repo examples/ or cwd)."""
|
||||
# Try to find examples directory
|
||||
candidates = [
|
||||
Path.home() / "praisonai-package" / "examples",
|
||||
Path("/Users/praison/praisonai-package/examples"),
|
||||
Path.cwd() / "examples",
|
||||
Path(__file__).parent.parent.parent.parent.parent / "examples", # repo root
|
||||
]
|
||||
@@ -36,7 +37,7 @@ def _get_default_examples_path() -> Path:
|
||||
def _get_default_report_dir() -> Path:
|
||||
"""Get default report directory with timestamp."""
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
return Path.cwd() / "reports" / "examples" / timestamp
|
||||
return Path.home() / "Downloads" / "reports" / "examples" / timestamp
|
||||
|
||||
|
||||
@app.command()
|
||||
@@ -56,11 +57,21 @@ def run(
|
||||
"--exclude", "-e",
|
||||
help="Exclude patterns (glob), can be specified multiple times",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Run only specific groups (top-level dirs), can be repeated",
|
||||
),
|
||||
timeout: int = typer.Option(
|
||||
60,
|
||||
"--timeout", "-t",
|
||||
help="Per-example timeout in seconds",
|
||||
),
|
||||
max_items: Optional[int] = typer.Option(
|
||||
None,
|
||||
"--max-items",
|
||||
help="Maximum examples to run",
|
||||
),
|
||||
fail_fast: bool = typer.Option(
|
||||
False,
|
||||
"--fail-fast", "-x",
|
||||
@@ -86,11 +97,21 @@ def run(
|
||||
"--no-md",
|
||||
help="Skip Markdown report generation",
|
||||
),
|
||||
no_csv: bool = typer.Option(
|
||||
False,
|
||||
"--no-csv",
|
||||
help="Skip CSV report generation",
|
||||
),
|
||||
require_env: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--require-env",
|
||||
help="Required env vars (skip all if missing)",
|
||||
),
|
||||
python: Optional[str] = typer.Option(
|
||||
None,
|
||||
"--python",
|
||||
help="Python executable to use (default: current interpreter)",
|
||||
),
|
||||
quiet: bool = typer.Option(
|
||||
False,
|
||||
"--quiet", "-q",
|
||||
@@ -103,11 +124,12 @@ def run(
|
||||
Examples:
|
||||
praisonai examples run
|
||||
praisonai examples run --path ./examples --timeout 120
|
||||
praisonai examples run --group python --group mcp --max-items 5
|
||||
praisonai examples run --include "context/*" --exclude "*_wow.py"
|
||||
praisonai examples run --fail-fast --no-stream
|
||||
"""
|
||||
# Lazy import to avoid loading at CLI startup
|
||||
from praisonai.cli.features.examples import ExamplesExecutor, ExampleResult
|
||||
from praisonai.suite_runner import ExamplesSource, SuiteExecutor, RunResult
|
||||
|
||||
# Resolve paths
|
||||
examples_path = path or _get_default_examples_path()
|
||||
@@ -117,18 +139,33 @@ def run(
|
||||
typer.echo(f"❌ Examples path not found: {examples_path}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
# Create source
|
||||
source = ExamplesSource(
|
||||
root=examples_path,
|
||||
include_patterns=list(include) if include else None,
|
||||
exclude_patterns=list(exclude) if exclude else None,
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
# Discover items
|
||||
items = source.discover()
|
||||
|
||||
# Create executor
|
||||
executor = ExamplesExecutor(
|
||||
path=examples_path,
|
||||
executor = SuiteExecutor(
|
||||
suite="examples",
|
||||
source_path=examples_path,
|
||||
timeout=timeout,
|
||||
fail_fast=fail_fast,
|
||||
stream_output=not no_stream,
|
||||
include_patterns=list(include) if include else None,
|
||||
exclude_patterns=list(exclude) if exclude else None,
|
||||
max_items=max_items,
|
||||
require_env=list(require_env) if require_env else None,
|
||||
report_dir=output_dir,
|
||||
generate_json=not no_json,
|
||||
generate_md=not no_md,
|
||||
generate_csv=not no_csv,
|
||||
python_executable=python,
|
||||
pythonpath_additions=source.get_pythonpath(),
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
# Status icons
|
||||
@@ -138,26 +175,27 @@ def run(
|
||||
"skipped": "⏭️",
|
||||
"timeout": "⏱️",
|
||||
"xfail": "⚠️",
|
||||
"not_run": "📝",
|
||||
}
|
||||
|
||||
def on_example_start(path: Path, idx: int, total: int):
|
||||
def on_item_start(item, idx: int, total: int):
|
||||
if not quiet:
|
||||
typer.echo(f"\n[{idx}/{total}] Running: {path.name}")
|
||||
typer.echo(f"\n[{idx}/{total}] Running: {item.display_name}")
|
||||
|
||||
def on_example_end(result: ExampleResult, idx: int, total: int):
|
||||
def on_item_end(result: RunResult, idx: int, total: int):
|
||||
icon = icons.get(result.status, "?")
|
||||
duration = f"{result.duration_seconds:.2f}s" if result.duration_seconds else ""
|
||||
|
||||
if quiet:
|
||||
typer.echo(f"{icon} {result.path.name}")
|
||||
typer.echo(f"{icon} {result.display_name}")
|
||||
else:
|
||||
msg = f" {icon} {result.status.upper()}"
|
||||
if duration:
|
||||
msg += f" ({duration})"
|
||||
if result.skip_reason:
|
||||
msg += f" - {result.skip_reason}"
|
||||
if result.error_summary and not no_stream:
|
||||
msg += f"\n Error: {result.error_summary[:100]}"
|
||||
if result.error_message and not no_stream:
|
||||
msg += f"\n Error: {result.error_message[:100]}"
|
||||
typer.echo(msg)
|
||||
|
||||
def on_output(line: str, stream: str):
|
||||
@@ -172,28 +210,26 @@ def run(
|
||||
typer.echo("=" * 60)
|
||||
typer.echo(f"Path: {examples_path}")
|
||||
typer.echo(f"Timeout: {timeout}s")
|
||||
if group:
|
||||
typer.echo(f"Groups: {', '.join(group)}")
|
||||
typer.echo(f"Reports: {output_dir}")
|
||||
typer.echo(f"Items: {len(items)}")
|
||||
|
||||
# Run examples
|
||||
report = executor.run(
|
||||
on_example_start=on_example_start,
|
||||
on_example_end=on_example_end,
|
||||
items=items,
|
||||
on_item_start=on_item_start,
|
||||
on_item_end=on_item_end,
|
||||
on_output=on_output if not no_stream else None,
|
||||
)
|
||||
|
||||
# Update report with CLI args
|
||||
report.cli_args = [
|
||||
f"--path={examples_path}",
|
||||
f"--timeout={timeout}",
|
||||
]
|
||||
report.cli_args = [f"--path={examples_path}", f"--timeout={timeout}"]
|
||||
if fail_fast:
|
||||
report.cli_args.append("--fail-fast")
|
||||
if include:
|
||||
for p in include:
|
||||
report.cli_args.append(f"--include={p}")
|
||||
if exclude:
|
||||
for p in exclude:
|
||||
report.cli_args.append(f"--exclude={p}")
|
||||
if group:
|
||||
for g in group:
|
||||
report.cli_args.append(f"--group={g}")
|
||||
|
||||
# Print summary
|
||||
totals = report.totals
|
||||
@@ -239,20 +275,31 @@ def list_examples(
|
||||
"--exclude", "-e",
|
||||
help="Exclude patterns (glob)",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Filter by group (top-level dir)",
|
||||
),
|
||||
show_metadata: bool = typer.Option(
|
||||
False,
|
||||
"--metadata", "-m",
|
||||
help="Show parsed metadata for each example",
|
||||
),
|
||||
show_groups: bool = typer.Option(
|
||||
False,
|
||||
"--groups",
|
||||
help="Show available groups only",
|
||||
),
|
||||
):
|
||||
"""
|
||||
List discovered examples without running them.
|
||||
|
||||
Examples:
|
||||
praisonai examples list
|
||||
praisonai examples list --path ./examples --metadata
|
||||
praisonai examples list --groups
|
||||
praisonai examples list --group python --metadata
|
||||
"""
|
||||
from praisonai.cli.features.examples import ExampleDiscovery, ExampleMetadata
|
||||
from praisonai.suite_runner import ExamplesSource
|
||||
|
||||
examples_path = path or _get_default_examples_path()
|
||||
|
||||
@@ -260,37 +307,45 @@ def list_examples(
|
||||
typer.echo(f"❌ Examples path not found: {examples_path}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
discovery = ExampleDiscovery(
|
||||
examples_path,
|
||||
source = ExamplesSource(
|
||||
root=examples_path,
|
||||
include_patterns=list(include) if include else None,
|
||||
exclude_patterns=list(exclude) if exclude else None,
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
examples = discovery.discover()
|
||||
# Show groups only
|
||||
if show_groups:
|
||||
groups = source.get_groups()
|
||||
typer.echo(f"Available groups in {examples_path}:\n")
|
||||
for g in groups:
|
||||
typer.echo(f" - {g}")
|
||||
return
|
||||
|
||||
typer.echo(f"Found {len(examples)} examples in {examples_path}\n")
|
||||
items = source.discover()
|
||||
|
||||
for idx, ex in enumerate(examples, 1):
|
||||
rel_path = ex.relative_to(examples_path)
|
||||
typer.echo(f"Found {len(items)} examples in {examples_path}\n")
|
||||
|
||||
for idx, item in enumerate(items, 1):
|
||||
rel_path = item.source_path.relative_to(examples_path)
|
||||
|
||||
if show_metadata:
|
||||
meta = ExampleMetadata.from_file(ex)
|
||||
flags = []
|
||||
if meta.skip:
|
||||
if item.skip:
|
||||
flags.append("skip")
|
||||
if meta.timeout:
|
||||
flags.append(f"timeout={meta.timeout}")
|
||||
if meta.require_env:
|
||||
flags.append(f"env={','.join(meta.require_env)}")
|
||||
if meta.xfail:
|
||||
flags.append(f"xfail={meta.xfail}")
|
||||
if meta.is_interactive:
|
||||
if item.timeout:
|
||||
flags.append(f"timeout={item.timeout}")
|
||||
if item.require_env:
|
||||
flags.append(f"env={','.join(item.require_env)}")
|
||||
if item.xfail:
|
||||
flags.append(f"xfail={item.xfail}")
|
||||
if item.is_interactive:
|
||||
flags.append("interactive")
|
||||
|
||||
flag_str = f" [{', '.join(flags)}]" if flags else ""
|
||||
typer.echo(f" {idx:3}. {rel_path}{flag_str}")
|
||||
typer.echo(f" {idx:3}. [{item.group}] {rel_path}{flag_str}")
|
||||
else:
|
||||
typer.echo(f" {idx:3}. {rel_path}")
|
||||
typer.echo(f" {idx:3}. [{item.group}] {rel_path}")
|
||||
|
||||
|
||||
@app.command()
|
||||
@@ -306,25 +361,423 @@ def info(
|
||||
Examples:
|
||||
praisonai examples info ./examples/context/01_basic.py
|
||||
"""
|
||||
from praisonai.cli.features.examples import ExampleMetadata
|
||||
from praisonai.suite_runner import ExamplesSource
|
||||
|
||||
if not example.exists():
|
||||
typer.echo(f"❌ Example not found: {example}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
meta = ExampleMetadata.from_file(example)
|
||||
# Create a source just to parse the file
|
||||
source = ExamplesSource(root=example.parent)
|
||||
item = source._create_item(example)
|
||||
|
||||
typer.echo(f"Example: {example.name}")
|
||||
typer.echo(f"Path: {example}")
|
||||
typer.echo(f"Group: {item.group}")
|
||||
typer.echo("")
|
||||
typer.echo("Metadata:")
|
||||
typer.echo(f" Skip: {meta.skip}" if meta.skip else " Skip: False")
|
||||
if meta.skip_reason:
|
||||
typer.echo(f" Skip Reason: {meta.skip_reason}")
|
||||
typer.echo(f" Timeout: {meta.timeout or 'default'}")
|
||||
typer.echo(f" Required Env: {', '.join(meta.require_env) if meta.require_env else 'none'}")
|
||||
typer.echo(f" XFail: {meta.xfail or 'no'}")
|
||||
typer.echo(f" Interactive: {meta.is_interactive}")
|
||||
typer.echo(f" Runnable: {item.runnable}")
|
||||
typer.echo(f" Decision: {item.runnable_decision}")
|
||||
typer.echo(f" Skip: {item.skip}")
|
||||
if item.skip_reason:
|
||||
typer.echo(f" Skip Reason: {item.skip_reason}")
|
||||
typer.echo(f" Timeout: {item.timeout or 'default'}")
|
||||
typer.echo(f" Required Env: {', '.join(item.require_env) if item.require_env else 'none'}")
|
||||
typer.echo(f" XFail: {item.xfail or 'no'}")
|
||||
typer.echo(f" Interactive: {item.is_interactive}")
|
||||
typer.echo(f" Code Hash: {item.code_hash}")
|
||||
|
||||
|
||||
@app.command("stats")
|
||||
def examples_stats(
|
||||
path: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--path", "-p",
|
||||
help="Path to examples directory",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Filter by group (top-level dir)",
|
||||
),
|
||||
):
|
||||
"""
|
||||
Show statistics for examples.
|
||||
|
||||
Displays counts by group, runnable status, and agent-centric usage.
|
||||
|
||||
Examples:
|
||||
praisonai examples stats
|
||||
praisonai examples stats --group python --group mcp
|
||||
"""
|
||||
from collections import Counter
|
||||
from praisonai.suite_runner import ExamplesSource
|
||||
|
||||
examples_path = path or _get_default_examples_path()
|
||||
|
||||
if not examples_path.exists():
|
||||
typer.echo(f"❌ Examples path not found: {examples_path}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
source = ExamplesSource(
|
||||
root=examples_path,
|
||||
groups=list(group) if group else None,
|
||||
)
|
||||
|
||||
items = source.discover()
|
||||
|
||||
# Calculate stats
|
||||
group_counts = Counter(item.group for item in items)
|
||||
runnable_by_group = Counter(item.group for item in items if item.runnable)
|
||||
|
||||
# Agent-centric stats
|
||||
agent_count = sum(1 for item in items if item.uses_agent)
|
||||
agents_count = sum(1 for item in items if item.uses_agents)
|
||||
workflow_count = sum(1 for item in items if item.uses_workflow)
|
||||
|
||||
agent_by_group = Counter(item.group for item in items if item.uses_agent)
|
||||
agents_by_group = Counter(item.group for item in items if item.uses_agents)
|
||||
workflow_by_group = Counter(item.group for item in items if item.uses_workflow)
|
||||
|
||||
typer.echo("\n📊 Examples Statistics")
|
||||
typer.echo(f"Path: {examples_path}")
|
||||
typer.echo("=" * 80)
|
||||
|
||||
typer.echo(f"\n{'Group':<20} {'Total':>8} {'Runnable':>10} {'Agent':>8} {'Agents':>8} {'Workflow':>10}")
|
||||
typer.echo("-" * 80)
|
||||
|
||||
for g in sorted(group_counts.keys()):
|
||||
typer.echo(
|
||||
f"{g:<20} {group_counts[g]:>8} {runnable_by_group[g]:>10} "
|
||||
f"{agent_by_group[g]:>8} {agents_by_group[g]:>8} {workflow_by_group[g]:>10}"
|
||||
)
|
||||
|
||||
typer.echo("-" * 80)
|
||||
typer.echo(
|
||||
f"{'TOTAL':<20} {len(items):>8} {sum(1 for i in items if i.runnable):>10} "
|
||||
f"{agent_count:>8} {agents_count:>8} {workflow_count:>10}"
|
||||
)
|
||||
typer.echo()
|
||||
|
||||
|
||||
@app.command("run-all")
|
||||
def examples_run_all(
|
||||
path: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--path", "-p",
|
||||
help="Path to examples directory",
|
||||
),
|
||||
timeout: int = typer.Option(
|
||||
60,
|
||||
"--timeout", "-t",
|
||||
help="Per-example timeout in seconds",
|
||||
),
|
||||
report_dir: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--report-dir", "-r",
|
||||
help="Directory for reports (default: ~/Downloads/reports/examples/<timestamp>)",
|
||||
),
|
||||
parallel: bool = typer.Option(
|
||||
True,
|
||||
"--parallel/--sequential",
|
||||
help="Run groups in parallel (default: parallel)",
|
||||
),
|
||||
max_workers: int = typer.Option(
|
||||
4,
|
||||
"--workers", "-w",
|
||||
help="Max parallel workers (default: 4)",
|
||||
),
|
||||
quiet: bool = typer.Option(
|
||||
False,
|
||||
"--quiet", "-q",
|
||||
help="Minimal output",
|
||||
),
|
||||
):
|
||||
"""
|
||||
Run all examples group-by-group.
|
||||
|
||||
Executes all groups and generates a comprehensive report.
|
||||
Uses parallel execution by default for faster results.
|
||||
|
||||
Examples:
|
||||
praisonai examples run-all
|
||||
praisonai examples run-all --sequential
|
||||
praisonai examples run-all --workers 8 --timeout 120
|
||||
"""
|
||||
import json
|
||||
from concurrent.futures import ProcessPoolExecutor, as_completed
|
||||
from praisonai.suite_runner import ExamplesSource, SuiteExecutor, RunResult
|
||||
|
||||
examples_path = path or _get_default_examples_path()
|
||||
output_dir = report_dir or _get_default_report_dir()
|
||||
|
||||
if not examples_path.exists():
|
||||
typer.echo(f"❌ Examples path not found: {examples_path}")
|
||||
raise typer.Exit(2)
|
||||
|
||||
# Get all groups
|
||||
source = ExamplesSource(root=examples_path)
|
||||
all_groups = sorted(source.get_groups())
|
||||
|
||||
typer.echo(f"Found {len(all_groups)} groups to process")
|
||||
typer.echo(f"Mode: {'parallel' if parallel else 'sequential'}")
|
||||
typer.echo("=" * 60)
|
||||
|
||||
# Track overall results
|
||||
overall_results = {
|
||||
'passed': 0, 'failed': 0, 'skipped': 0,
|
||||
'timeout': 0, 'not_run': 0, 'total': 0, 'xfail': 0,
|
||||
}
|
||||
group_summaries = []
|
||||
|
||||
def run_group(group_name: str) -> dict:
|
||||
"""Run a single group and return summary."""
|
||||
group_source = ExamplesSource(root=examples_path, groups=[group_name])
|
||||
items = group_source.discover()
|
||||
|
||||
if not items:
|
||||
return {
|
||||
'group': group_name,
|
||||
'total': 0, 'passed': 0, 'failed': 0,
|
||||
'skipped': 0, 'timeout': 0, 'not_run': 0, 'xfail': 0,
|
||||
}
|
||||
|
||||
group_report_dir = output_dir / group_name
|
||||
group_report_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
executor = SuiteExecutor(
|
||||
suite='examples',
|
||||
source_path=examples_path,
|
||||
report_dir=group_report_dir,
|
||||
timeout=timeout,
|
||||
stream_output=False,
|
||||
generate_json=True,
|
||||
generate_md=True,
|
||||
generate_csv=True,
|
||||
groups=[group_name],
|
||||
)
|
||||
|
||||
report = executor.run(items=items)
|
||||
totals = report.totals
|
||||
|
||||
return {
|
||||
'group': group_name,
|
||||
**totals,
|
||||
}
|
||||
|
||||
if parallel and len(all_groups) > 1:
|
||||
# Parallel execution
|
||||
with ProcessPoolExecutor(max_workers=min(max_workers, len(all_groups))) as pool:
|
||||
futures = {pool.submit(run_group, g): g for g in all_groups}
|
||||
|
||||
for future in as_completed(futures):
|
||||
group_name = futures[future]
|
||||
try:
|
||||
summary = future.result()
|
||||
group_summaries.append(summary)
|
||||
|
||||
# Update overall
|
||||
for key in overall_results:
|
||||
if key in summary:
|
||||
overall_results[key] += summary[key]
|
||||
|
||||
if not quiet:
|
||||
typer.echo(
|
||||
f"✅ {group_name}: "
|
||||
f"✅{summary['passed']} ❌{summary['failed']} "
|
||||
f"⏭️{summary['skipped']} ⏱️{summary['timeout']} ⚠️{summary.get('xfail', 0)}"
|
||||
)
|
||||
except Exception as e:
|
||||
typer.echo(f"❌ {group_name}: Error - {e}")
|
||||
else:
|
||||
# Sequential execution with real-time output
|
||||
for group_name in all_groups:
|
||||
if not quiet:
|
||||
typer.echo(f"\n{'='*60}")
|
||||
typer.echo(f"GROUP: {group_name}")
|
||||
typer.echo(f"{'='*60}")
|
||||
|
||||
group_source = ExamplesSource(root=examples_path, groups=[group_name])
|
||||
items = group_source.discover()
|
||||
|
||||
if not items:
|
||||
if not quiet:
|
||||
typer.echo(" No items found, skipping")
|
||||
group_summaries.append({
|
||||
'group': group_name,
|
||||
'total': 0, 'passed': 0, 'failed': 0,
|
||||
'skipped': 0, 'timeout': 0, 'not_run': 0, 'xfail': 0,
|
||||
})
|
||||
continue
|
||||
|
||||
group_report_dir = output_dir / group_name
|
||||
group_report_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
executor = SuiteExecutor(
|
||||
suite='examples',
|
||||
source_path=examples_path,
|
||||
report_dir=group_report_dir,
|
||||
timeout=timeout,
|
||||
stream_output=False,
|
||||
generate_json=True,
|
||||
generate_md=True,
|
||||
generate_csv=True,
|
||||
groups=[group_name],
|
||||
)
|
||||
|
||||
icons = {'passed': '✅', 'failed': '❌', 'skipped': '⏭️', 'timeout': '⏱️', 'xfail': '⚠️'}
|
||||
|
||||
def on_start(item, idx, total):
|
||||
if not quiet:
|
||||
typer.echo(f" [{idx}/{total}] {item.display_name} ", nl=False)
|
||||
|
||||
def on_end(result: RunResult, idx, total):
|
||||
if not quiet:
|
||||
icon = icons.get(result.status, '❓')
|
||||
typer.echo(f"{icon}")
|
||||
|
||||
report = executor.run(items=items, on_item_start=on_start, on_item_end=on_end)
|
||||
totals = report.totals
|
||||
|
||||
group_summaries.append({'group': group_name, **totals})
|
||||
|
||||
for key in overall_results:
|
||||
if key in totals:
|
||||
overall_results[key] += totals[key]
|
||||
|
||||
if not quiet:
|
||||
typer.echo(
|
||||
f"\n Summary: ✅{totals['passed']} ❌{totals['failed']} "
|
||||
f"⏭️{totals['skipped']} ⏱️{totals['timeout']} ⚠️{totals.get('xfail', 0)}"
|
||||
)
|
||||
|
||||
# Final report
|
||||
typer.echo("\n" + "=" * 80)
|
||||
typer.echo("FINAL REPORT - ALL GROUPS")
|
||||
typer.echo("=" * 80)
|
||||
|
||||
typer.echo(f"\n{'Group':<20} {'Total':>8} {'Passed':>8} {'Failed':>8} {'Skip':>8} {'Timeout':>8} {'XFail':>8}")
|
||||
typer.echo("-" * 80)
|
||||
|
||||
for gs in sorted(group_summaries, key=lambda x: x['group']):
|
||||
typer.echo(
|
||||
f"{gs['group']:<20} {gs['total']:>8} {gs['passed']:>8} {gs['failed']:>8} "
|
||||
f"{gs['skipped']:>8} {gs['timeout']:>8} {gs.get('xfail', 0):>8}"
|
||||
)
|
||||
|
||||
typer.echo("-" * 80)
|
||||
typer.echo(
|
||||
f"{'TOTAL':<20} {overall_results['total']:>8} {overall_results['passed']:>8} "
|
||||
f"{overall_results['failed']:>8} {overall_results['skipped']:>8} "
|
||||
f"{overall_results['timeout']:>8} {overall_results.get('xfail', 0):>8}"
|
||||
)
|
||||
|
||||
# Save final summary
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
summary_path = output_dir / 'final_summary.json'
|
||||
with open(summary_path, 'w') as f:
|
||||
json.dump({
|
||||
'timestamp': datetime.now().isoformat(),
|
||||
'overall': overall_results,
|
||||
'groups': group_summaries,
|
||||
}, f, indent=2)
|
||||
|
||||
typer.echo(f"\n📁 Final summary saved to: {summary_path}")
|
||||
typer.echo(f"📁 Individual group reports in: {output_dir}")
|
||||
|
||||
# Exit code
|
||||
if overall_results['failed'] > 0 or overall_results['timeout'] > 0:
|
||||
raise typer.Exit(1)
|
||||
raise typer.Exit(0)
|
||||
|
||||
|
||||
@app.command("report")
|
||||
def examples_report(
|
||||
report_dir: Optional[Path] = typer.Argument(
|
||||
None,
|
||||
help="Report directory path (default: auto-detect latest)",
|
||||
),
|
||||
base_dir: Optional[Path] = typer.Option(
|
||||
None,
|
||||
"--base-dir", "-b",
|
||||
help="Base reports directory (default: ~/Downloads/reports/examples)",
|
||||
),
|
||||
limit: int = typer.Option(
|
||||
50,
|
||||
"--limit", "-n",
|
||||
help="Limit rows in tables (0 = no limit)",
|
||||
),
|
||||
errors: bool = typer.Option(
|
||||
True,
|
||||
"--errors/--no-errors",
|
||||
help="Show error grouping section",
|
||||
),
|
||||
wide: bool = typer.Option(
|
||||
False,
|
||||
"--wide/--no-wide",
|
||||
help="Wide output: full error messages and item lists",
|
||||
),
|
||||
show_paths: bool = typer.Option(
|
||||
True,
|
||||
"--show-paths/--no-show-paths",
|
||||
help="Show affected item paths in error groups",
|
||||
),
|
||||
match: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--match", "-m",
|
||||
help="Filter by status (repeatable: --match failed --match timeout)",
|
||||
),
|
||||
group: Optional[List[str]] = typer.Option(
|
||||
None,
|
||||
"--group", "-g",
|
||||
help="Filter by group name (repeatable)",
|
||||
),
|
||||
contains: Optional[str] = typer.Option(
|
||||
None,
|
||||
"--contains", "-c",
|
||||
help="Filter items whose error contains text (case-insensitive)",
|
||||
),
|
||||
open_dir: bool = typer.Option(
|
||||
False,
|
||||
"--open",
|
||||
help="Show report artifacts listing",
|
||||
),
|
||||
output_format: str = typer.Option(
|
||||
"table",
|
||||
"--format", "-f",
|
||||
help="Output format: table or json",
|
||||
),
|
||||
):
|
||||
"""
|
||||
View execution report with failures and error grouping.
|
||||
|
||||
Examples:
|
||||
praisonai examples report # View latest report
|
||||
praisonai examples report ./my-report # View specific report
|
||||
praisonai examples report --wide --limit 0 # Full details
|
||||
praisonai examples report --match failed # Only failures
|
||||
praisonai examples report --format json # JSON output
|
||||
"""
|
||||
# Lazy import to avoid loading at CLI startup
|
||||
from praisonai.suite_runner.report_viewer import view_report
|
||||
|
||||
output, exit_code = view_report(
|
||||
report_dir=report_dir,
|
||||
suite="examples",
|
||||
base_dir=base_dir,
|
||||
limit=limit,
|
||||
show_errors=errors,
|
||||
wide=wide,
|
||||
show_paths=show_paths,
|
||||
match_statuses=match,
|
||||
match_groups=group,
|
||||
contains=contains,
|
||||
show_artifacts=open_dir,
|
||||
output_format=output_format,
|
||||
)
|
||||
|
||||
typer.echo(output)
|
||||
raise typer.Exit(exit_code)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -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())
|
||||
@@ -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
|
||||
|
||||
@@ -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
|
||||
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