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+4
-1
@@ -77,4 +77,7 @@ agents/praisonaiagents/praisonaiagents.egg-info
|
||||
.qodo
|
||||
CopilotKit*
|
||||
.gemini
|
||||
issue_details.json
|
||||
issue_details.json
|
||||
|
||||
# MCP Registry tokens
|
||||
.mcpregistry_*
|
||||
@@ -6,10 +6,13 @@
|
||||
</picture>
|
||||
</p>
|
||||
|
||||
<!-- mcp-name: io.github.MervinPraison/praisonai -->
|
||||
|
||||
<p align="center">
|
||||
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://static.pepy.tech/badge/PraisonAI" alt="Total Downloads" /></a>
|
||||
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/github/v/release/MervinPraison/PraisonAI" alt="Latest Stable Version" /></a>
|
||||
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License" /></a>
|
||||
<a href="https://registry.modelcontextprotocol.io/servers/io.github.MervinPraison/praisonai"><img src="https://img.shields.io/badge/MCP-Registry-blue" alt="MCP Registry" /></a>
|
||||
</p>
|
||||
|
||||
<div align="center">
|
||||
@@ -60,6 +63,7 @@ PraisonAI is a production-ready Multi-AI Agents framework with self-reflection,
|
||||
- [Planning & Workflows](#planning--workflows)
|
||||
- [Specialised Agents](#specialised-agents)
|
||||
- [MCP Protocol](#mcp-protocol)
|
||||
- [A2A & A2UI Protocols](#a2a--a2ui-protocols)
|
||||
- [Safety & Control](#safety--control)
|
||||
- [Developer Tools](#developer-tools)
|
||||
- [📊 Process Types & Patterns](#-process-types--patterns)
|
||||
@@ -187,7 +191,14 @@ npm install praisonai
|
||||
| 📚 Add Custom Knowledge | [Example](examples/python/concepts/knowledge-agents.py) | [📖](https://docs.praison.ai/features/knowledge) |
|
||||
| 🧠 Memory (Short & Long Term) | [Example](examples/python/general/memory_example.py) | [📖](https://docs.praison.ai/concepts/memory) |
|
||||
| 📄 Chat with PDF Agents | [Example](examples/python/concepts/chat-with-pdf.py) | [📖](https://docs.praison.ai/features/chat-with-pdf) |
|
||||
| 💻 Code Interpreter Agents | [Example](examples/python/agents/code-agent.py) | [📖](https://docs.praison.ai/features/codeagent) |
|
||||
| **💻 Code** | | |
|
||||
| ↳ Code Interpreter Agents | [Example](examples/python/agents/code-agent.py) | [📖](https://docs.praison.ai/features/codeagent) |
|
||||
| ↳ AI Code Editing Tools | [Example](examples/python/code/code_editing_example.py) | [📖](https://docs.praison.ai/code/editing) |
|
||||
| ↳ External Agents (All) | [Example](examples/python/code/external_agents_example.py) | [📖](https://docs.praison.ai/code/external-agents) |
|
||||
| ↳ Claude Code CLI | [Example](examples/python/code/claude_code_example.py) | [📖](https://docs.praison.ai/code/claude-code) |
|
||||
| ↳ Gemini CLI | [Example](examples/python/code/gemini_cli_example.py) | [📖](https://docs.praison.ai/code/gemini-cli) |
|
||||
| ↳ Codex CLI | [Example](examples/python/code/codex_cli_example.py) | [📖](https://docs.praison.ai/code/codex-cli) |
|
||||
| ↳ Cursor CLI | [Example](examples/python/code/cursor_cli_example.py) | [📖](https://docs.praison.ai/code/cursor-cli) |
|
||||
| 📚 RAG Agents | [Example](examples/python/concepts/rag-agents.py) | [📖](https://docs.praison.ai/features/rag) |
|
||||
| 🤔 Async & Parallel Processing | [Example](examples/python/general/async_example.py) | [📖](https://docs.praison.ai/features/async) |
|
||||
| 🔢 Math Agents | [Example](examples/python/agents/math-agent.py) | [📖](https://docs.praison.ai/features/mathagent) |
|
||||
@@ -205,6 +216,7 @@ npm install praisonai
|
||||
| 🧠 Claude Memory Tool | [Example](#claude-memory-tool-cli) | [📖](https://docs.praison.ai/features/claude-memory-tool) |
|
||||
| 💾 File-Based Memory | [Example](examples/python/general/memory_example.py) | [📖](https://docs.praison.ai/concepts/memory) |
|
||||
| 🔍 Built-in Search Tools | [Example](examples/python/agents/websearch-agent.py) | [📖](https://docs.praison.ai/tools/tavily) |
|
||||
| 🔎 Unified Web Search | [Example](src/praisonai-agents/examples/web_search_example.py) | [📖](https://docs.praison.ai/tools/web-search) |
|
||||
| 📋 Planning Mode | [Example](examples/python/agents/planning-agent.py) | [📖](https://docs.praison.ai/features/planning-mode) |
|
||||
| 🔧 Planning Tools | [Example](#3-agent-with-planning-mode) | [📖](https://docs.praison.ai/features/planning-mode) |
|
||||
| 🧠 Planning Reasoning | [Example](#3-agent-with-planning-mode) | [📖](https://docs.praison.ai/features/planning-mode) |
|
||||
@@ -224,7 +236,7 @@ npm install praisonai
|
||||
| 💻 Programming Agent | [Example](examples/python/agents/programming-agent.py) | [📖](https://docs.praison.ai/agents/programming) |
|
||||
| 📝 Markdown Agent | [Example](examples/python/agents/markdown-agent.py) | [📖](https://docs.praison.ai/agents/markdown) |
|
||||
| 📝 Prompt Expander Agent | [Example](#prompt-expansion) | [📖](https://docs.praison.ai/agents/prompt-expander) |
|
||||
| 🔀 Router Agent | [Example](examples/python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/routing) |
|
||||
| 🔀 Model Router | [Example](examples/python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/model-router) |
|
||||
| ⛓️ Prompt Chaining | [Example](examples/python/general/prompt_chaining.py) | [📖](https://docs.praison.ai/features/promptchaining) |
|
||||
| 🔍 Evaluator Optimiser | [Example](examples/python/general/evaluator-optimiser.py) | [📖](https://docs.praison.ai/features/evaluator-optimiser) |
|
||||
| 👷 Orchestrator Workers | [Example](examples/python/general/orchestrator-workers.py) | [📖](https://docs.praison.ai/features/orchestrator-worker) |
|
||||
@@ -240,12 +252,20 @@ npm install praisonai
|
||||
| 🪝 Hooks | [Example](#9-hooks) | [📖](https://docs.praison.ai/features/hooks) |
|
||||
| 📈 Telemetry | [Example](examples/python/telemetry/production-telemetry-example.py) | [📖](https://docs.praison.ai/features/telemetry) |
|
||||
| 📹 Camera Integration | [Example](examples/python/camera/) | [📖](https://docs.praison.ai/features/camera-integration) |
|
||||
| 📄 Project Docs (.praison/docs/) | [Example](#docs-cli) | [📖](https://docs.praison.ai/cli/docs) |
|
||||
| 🔌 MCP Config Management | [Example](#mcp-config-cli) | [📖](https://docs.praison.ai/cli/mcp) |
|
||||
| 💬 AI Commit Messages | [Example](#ai-commit-cli) | [📖](https://docs.praison.ai/cli/commit) |
|
||||
| @ @Mentions in Prompts | [Example](#mentions-in-prompts) | [📖](https://docs.praison.ai/cli/mentions) |
|
||||
| 💾 Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
|
||||
| 📜 History in Context | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
|
||||
| 📄 Project Docs (.praison/docs/) | [Example](#docs-cli) | [📖](https://docs.praison.ai/docs/cli/docs) |
|
||||
| 🔌 MCP Config Management | [Example](#mcp-config-cli) | [📖](https://docs.praison.ai/docs/cli/mcp) |
|
||||
| 💬 AI Commit Messages | [Example](#ai-commit-cli) | [📖](https://docs.praison.ai/docs/cli/commit) |
|
||||
| @ @Mentions in Prompts | [Example](#mentions-in-prompts) | [📖](https://docs.praison.ai/docs/cli/mentions) |
|
||||
| 💾 Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/docs/cli/session) |
|
||||
| 📜 History in Context | [Example](#session-management-python) | [📖](https://docs.praison.ai/docs/cli/session) |
|
||||
| **🖥️ CLI Features** | | |
|
||||
| ↳ Slash Commands | [Example](examples/python/cli/slash_commands_example.py) | [📖](https://docs.praison.ai/docs/cli/slash-commands) |
|
||||
| ↳ Autonomy Modes | [Example](examples/python/cli/autonomy_modes_example.py) | [📖](https://docs.praison.ai/docs/cli/autonomy-modes) |
|
||||
| ↳ Cost Tracking | [Example](examples/python/cli/cost_tracking_example.py) | [📖](https://docs.praison.ai/docs/cli/cost-tracking) |
|
||||
| ↳ Repository Map | [Example](examples/python/cli/repo_map_example.py) | [📖](https://docs.praison.ai/docs/cli/repo-map) |
|
||||
| ↳ Interactive TUI | [Example](examples/python/cli/interactive_tui_example.py) | [📖](https://docs.praison.ai/docs/cli/interactive-tui) |
|
||||
| ↳ Git Integration | [Example](examples/python/cli/git_integration_example.py) | [📖](https://docs.praison.ai/docs/cli/git-integration) |
|
||||
| ↳ Sandbox Execution | [Example](examples/python/cli/sandbox_execution_example.py) | [📖](https://docs.praison.ai/docs/cli/sandbox-execution) |
|
||||
|
||||
---
|
||||
|
||||
@@ -952,6 +972,32 @@ export OPENAI_API_KEY=xxxxxxxxxxxxxxxxxxxxxx
|
||||
praisonai --auto create a movie script about Robots in Mars
|
||||
```
|
||||
|
||||
### Interactive Mode CLI:
|
||||
```bash
|
||||
# Start interactive terminal mode (inspired by Gemini CLI, Codex CLI, Claude Code)
|
||||
praisonai --interactive
|
||||
praisonai -i
|
||||
|
||||
# Features:
|
||||
# - Streaming responses (no boxes)
|
||||
# - Built-in tools: read_file, write_file, list_files, execute_command, internet_search
|
||||
# - Slash commands: /help, /exit, /tools, /clear
|
||||
|
||||
# Chat mode - single prompt with interactive style (for testing/scripting)
|
||||
# Use --chat (or --chat-mode for backward compatibility)
|
||||
praisonai "list files in current folder" --chat
|
||||
praisonai "search the web for AI news" --chat
|
||||
praisonai "read README.md" --chat
|
||||
```
|
||||
|
||||
### Chat UI (Web Interface):
|
||||
```bash
|
||||
# Start web-based Chainlit chat interface (requires praisonai[chat])
|
||||
pip install "praisonai[chat]"
|
||||
praisonai chat
|
||||
# Opens browser at http://localhost:8084
|
||||
```
|
||||
|
||||
### Query Rewriting (works with any command):
|
||||
```bash
|
||||
# Rewrite query for better results (uses QueryRewriterAgent)
|
||||
@@ -1012,6 +1058,20 @@ praisonai "Complex analysis task" --planning --planning-reasoning
|
||||
praisonai "Task" --planning --auto-approve-plan
|
||||
```
|
||||
|
||||
### Tool Approval CLI:
|
||||
```bash
|
||||
# Auto-approve ALL tool executions (use with caution!)
|
||||
praisonai "run ls command" --trust
|
||||
|
||||
# Auto-approve tools up to a risk level (prompt for higher)
|
||||
# Levels: low, medium, high, critical
|
||||
praisonai "write to file" --approve-level high # Prompts for critical tools only
|
||||
praisonai "task" --approve-level medium # Prompts for high and critical
|
||||
|
||||
# Default behavior (no flags): prompts for all dangerous tools
|
||||
praisonai "run shell command" # Will prompt for approval
|
||||
```
|
||||
|
||||
### Memory CLI:
|
||||
```bash
|
||||
# Enable memory for agent (persists across sessions)
|
||||
@@ -1118,6 +1178,15 @@ praisonai workflow auto "Research AI trends" --pattern parallel
|
||||
# Generate routing workflow (classifier routes to specialists)
|
||||
praisonai workflow auto "Build a chatbot" --pattern routing
|
||||
|
||||
# Generate orchestrator-workers workflow (central orchestrator delegates)
|
||||
praisonai workflow auto "Comprehensive market analysis" --pattern orchestrator-workers
|
||||
|
||||
# Generate evaluator-optimizer workflow (iterative refinement)
|
||||
praisonai workflow auto "Write and refine article" --pattern evaluator-optimizer
|
||||
|
||||
# Specify output file
|
||||
praisonai workflow auto "Build a chatbot" --pattern routing
|
||||
|
||||
# Specify output file
|
||||
praisonai workflow auto "Research AI" --pattern sequential --output my_workflow.yaml
|
||||
```
|
||||
@@ -1127,7 +1196,7 @@ praisonai workflow auto "Research AI" --pattern sequential --output my_workflow.
|
||||
|------|-------------|
|
||||
| `--workflow-var key=value` | Set workflow variable (can be repeated) |
|
||||
| `--var key=value` | Set variable for YAML workflows |
|
||||
| `--pattern <pattern>` | Pattern for auto-generation (sequential, parallel, routing, loop) |
|
||||
| `--pattern <pattern>` | Pattern for auto-generation (sequential, parallel, routing, loop, orchestrator-workers, evaluator-optimizer) |
|
||||
| `--output <file>` | Output file for auto-generation |
|
||||
| `--llm <model>` | LLM model (e.g., openai/gpt-4o-mini) |
|
||||
| `--tools <tools>` | Tools (comma-separated, e.g., tavily) |
|
||||
@@ -1359,8 +1428,13 @@ praisonai "Complex analysis" --router --router-provider anthropic
|
||||
# Router automatically selects:
|
||||
# - Simple tasks → gpt-4o-mini, claude-3-haiku
|
||||
# - Complex tasks → gpt-4-turbo, claude-3-opus
|
||||
|
||||
# Create workflow with model routing template
|
||||
praisonai workflow create --template model-routing --output my_workflow.yaml
|
||||
```
|
||||
|
||||
Custom models can be configured in `agents.yaml`. See [Model Router Docs](https://docs.praison.ai/features/model-router) for details.
|
||||
|
||||
### Flow Display CLI:
|
||||
```bash
|
||||
# Enable visual workflow tracking
|
||||
@@ -1412,13 +1486,31 @@ praisonai mcp help
|
||||
|
||||
### AI Commit CLI:
|
||||
```bash
|
||||
# Generate AI commit message for staged changes
|
||||
# Full auto mode: stage all, security check, commit, and push
|
||||
praisonai commit -a
|
||||
|
||||
# Interactive mode (requires git add first)
|
||||
praisonai commit
|
||||
|
||||
# Generate, commit, and push
|
||||
# Interactive with auto-push
|
||||
praisonai commit --push
|
||||
|
||||
# Skip security check (not recommended)
|
||||
praisonai commit -a --no-verify
|
||||
```
|
||||
|
||||
**Features:**
|
||||
- 🤖 AI-generated conventional commit messages
|
||||
- 🔒 Built-in security scanning (API keys, passwords, secrets, sensitive files)
|
||||
- 📦 Auto-staging with `-a` flag
|
||||
- 🚀 Auto-push in full auto mode
|
||||
- ✏️ Edit message before commit in interactive mode
|
||||
|
||||
**Security Detection:**
|
||||
- API keys, secrets, tokens (AWS, GitHub, GitLab, Slack)
|
||||
- Passwords and private keys
|
||||
- Sensitive files (`.env`, `id_rsa`, `.pem`, `.key`, etc.)
|
||||
|
||||
### Serve CLI (API Server):
|
||||
```bash
|
||||
# Start API server for agents defined in YAML
|
||||
@@ -1449,6 +1541,55 @@ export N8N_API_KEY="your-api-key"
|
||||
praisonai agents.yaml --n8n
|
||||
```
|
||||
|
||||
### External Agents CLI:
|
||||
|
||||
Use external AI coding CLI tools (Claude Code, Gemini CLI, Codex CLI, Cursor CLI) as agent tools:
|
||||
|
||||
```bash
|
||||
# Use Claude Code for coding tasks
|
||||
praisonai "Refactor the auth module" --external-agent claude
|
||||
|
||||
# Use Gemini CLI for code analysis
|
||||
praisonai "Analyze codebase architecture" --external-agent gemini
|
||||
|
||||
# Use OpenAI Codex CLI
|
||||
praisonai "Fix all bugs in src/" --external-agent codex
|
||||
|
||||
# Use Cursor CLI
|
||||
praisonai "Add comprehensive tests" --external-agent cursor
|
||||
```
|
||||
|
||||
**Python API:**
|
||||
```python
|
||||
from praisonai.integrations import (
|
||||
ClaudeCodeIntegration,
|
||||
GeminiCLIIntegration,
|
||||
CodexCLIIntegration,
|
||||
CursorCLIIntegration
|
||||
)
|
||||
|
||||
# Create integration
|
||||
claude = ClaudeCodeIntegration(workspace="/project")
|
||||
|
||||
# Execute a coding task
|
||||
result = await claude.execute("Refactor the auth module")
|
||||
|
||||
# Use as agent tool
|
||||
from praisonai import Agent
|
||||
tool = claude.as_tool()
|
||||
agent = Agent(tools=[tool])
|
||||
```
|
||||
|
||||
**Environment Variables:**
|
||||
```bash
|
||||
export ANTHROPIC_API_KEY=your-key # Claude Code
|
||||
export GEMINI_API_KEY=your-key # Gemini CLI
|
||||
export OPENAI_API_KEY=your-key # Codex CLI
|
||||
export CURSOR_API_KEY=your-key # Cursor CLI
|
||||
```
|
||||
|
||||
See [External Agents Documentation](https://docs.praison.ai/code/external-agents) for more details.
|
||||
|
||||
### @Mentions in Prompts:
|
||||
```bash
|
||||
# Include file content in prompt
|
||||
@@ -1628,36 +1769,78 @@ server.run() # stdio for Claude Desktop
|
||||
| Security | Origin validation, DNS rebinding prevention |
|
||||
| WebSocket | Auto-reconnect with exponential backoff |
|
||||
|
||||
## A2A (Agent2Agent Protocol)
|
||||
|
||||
PraisonAI supports the [A2A Protocol](https://a2a-protocol.org) for agent-to-agent communication, enabling your agents to be discovered and collaborate with other AI agents.
|
||||
|
||||
### A2A Server (Expose Agent as A2A Server)
|
||||
```python
|
||||
from praisonaiagents import Agent, A2A
|
||||
from fastapi import FastAPI
|
||||
|
||||
# Create an agent with tools
|
||||
def search_web(query: str) -> str:
|
||||
"""Search the web for information."""
|
||||
return f"Results for: {query}"
|
||||
|
||||
agent = Agent(
|
||||
name="Research Assistant",
|
||||
role="Research Analyst",
|
||||
goal="Help users research topics",
|
||||
tools=[search_web]
|
||||
)
|
||||
|
||||
# Expose as A2A Server
|
||||
a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
# Run: uvicorn app:app --reload
|
||||
# Agent Card: GET /.well-known/agent.json
|
||||
# Status: GET /status
|
||||
```
|
||||
|
||||
### A2A Features
|
||||
| Feature | Description |
|
||||
|---------|-------------|
|
||||
| Agent Card | JSON metadata for agent discovery |
|
||||
| Skills Extraction | Auto-generate skills from tools |
|
||||
| Task Management | Stateful task lifecycle |
|
||||
| Streaming | SSE streaming for real-time updates |
|
||||
|
||||
> **Documentation**: [docs.praison.ai/a2a](https://docs.praison.ai/a2a) | **Examples**: [examples/python/a2a](https://github.com/MervinPraison/PraisonAI/tree/main/examples/python/a2a)
|
||||
|
||||
## CLI Features
|
||||
|
||||
| Feature | Docs |
|
||||
|---------|:----:|
|
||||
| 🔄 Query Rewrite - RAG optimization | [📖](https://docs.praison.ai/cli/query-rewrite) |
|
||||
| 🔬 Deep Research - Automated research | [📖](https://docs.praison.ai/cli/deep-research) |
|
||||
| 📋 Planning - Step-by-step execution | [📖](https://docs.praison.ai/cli/planning) |
|
||||
| 💾 Memory - Persistent agent memory | [📖](https://docs.praison.ai/cli/memory) |
|
||||
| 📜 Rules - Auto-discovered instructions | [📖](https://docs.praison.ai/cli/rules) |
|
||||
| 🔄 Workflow - Multi-step workflows | [📖](https://docs.praison.ai/cli/workflow) |
|
||||
| 🪝 Hooks - Event-driven actions | [📖](https://docs.praison.ai/cli/hooks) |
|
||||
| 🧠 Claude Memory - Anthropic memory tool | [📖](https://docs.praison.ai/cli/claude-memory) |
|
||||
| 🛡️ Guardrail - Output validation | [📖](https://docs.praison.ai/cli/guardrail) |
|
||||
| 📊 Metrics - Token usage tracking | [📖](https://docs.praison.ai/cli/metrics) |
|
||||
| 🖼️ Image - Vision processing | [📖](https://docs.praison.ai/cli/image) |
|
||||
| 📡 Telemetry - Usage monitoring | [📖](https://docs.praison.ai/cli/telemetry) |
|
||||
| 🔌 MCP - Model Context Protocol | [📖](https://docs.praison.ai/cli/mcp) |
|
||||
| ⚡ Fast Context - Codebase search | [📖](https://docs.praison.ai/cli/fast-context) |
|
||||
| 📚 Knowledge - RAG management | [📖](https://docs.praison.ai/cli/knowledge) |
|
||||
| 💬 Session - Conversation management | [📖](https://docs.praison.ai/cli/session) |
|
||||
| 🔧 Tools - Tool discovery | [📖](https://docs.praison.ai/cli/tools) |
|
||||
| 🤝 Handoff - Agent delegation | [📖](https://docs.praison.ai/cli/handoff) |
|
||||
| 🧠 Auto Memory - Memory extraction | [📖](https://docs.praison.ai/cli/auto-memory) |
|
||||
| 📋 Todo - Task management | [📖](https://docs.praison.ai/cli/todo) |
|
||||
| 🎯 Router - Smart model selection | [📖](https://docs.praison.ai/cli/router) |
|
||||
| 📈 Flow Display - Visual workflow | [📖](https://docs.praison.ai/cli/flow-display) |
|
||||
| ✨ Prompt Expansion - Detailed prompts | [📖](https://docs.praison.ai/cli/prompt-expansion) |
|
||||
| 🌐 Web Search - Real-time search | [📖](https://docs.praison.ai/cli/web-search) |
|
||||
| 📥 Web Fetch - URL content retrieval | [📖](https://docs.praison.ai/cli/web-fetch) |
|
||||
| 💾 Prompt Caching - Cost reduction | [📖](https://docs.praison.ai/cli/prompt-caching) |
|
||||
| 🔄 Query Rewrite - RAG optimization | [📖](https://docs.praison.ai/docs/cli/query-rewrite) |
|
||||
| 🔬 Deep Research - Automated research | [📖](https://docs.praison.ai/docs/cli/deep-research) |
|
||||
| 📋 Planning - Step-by-step execution | [📖](https://docs.praison.ai/docs/cli/planning) |
|
||||
| 💾 Memory - Persistent agent memory | [📖](https://docs.praison.ai/docs/cli/memory) |
|
||||
| 📜 Rules - Auto-discovered instructions | [📖](https://docs.praison.ai/docs/cli/rules) |
|
||||
| 🔄 Workflow - Multi-step workflows | [📖](https://docs.praison.ai/docs/cli/workflow) |
|
||||
| 🪝 Hooks - Event-driven actions | [📖](https://docs.praison.ai/docs/cli/hooks) |
|
||||
| 🧠 Claude Memory - Anthropic memory tool | [📖](https://docs.praison.ai/docs/cli/claude-memory) |
|
||||
| 🛡️ Guardrail - Output validation | [📖](https://docs.praison.ai/docs/cli/guardrail) |
|
||||
| 📊 Metrics - Token usage tracking | [📖](https://docs.praison.ai/docs/cli/metrics) |
|
||||
| 🖼️ Image - Vision processing | [📖](https://docs.praison.ai/docs/cli/image) |
|
||||
| 📡 Telemetry - Usage monitoring | [📖](https://docs.praison.ai/docs/cli/telemetry) |
|
||||
| 🔌 MCP - Model Context Protocol | [📖](https://docs.praison.ai/docs/cli/mcp) |
|
||||
| ⚡ Fast Context - Codebase search | [📖](https://docs.praison.ai/docs/cli/fast-context) |
|
||||
| 📚 Knowledge - RAG management | [📖](https://docs.praison.ai/docs/cli/knowledge) |
|
||||
| 💬 Session - Conversation management | [📖](https://docs.praison.ai/docs/cli/session) |
|
||||
| 🔧 Tools - Tool discovery | [📖](https://docs.praison.ai/docs/cli/tools) |
|
||||
| 🤝 Handoff - Agent delegation | [📖](https://docs.praison.ai/docs/cli/handoff) |
|
||||
| 🧠 Auto Memory - Memory extraction | [📖](https://docs.praison.ai/docs/cli/auto-memory) |
|
||||
| 📋 Todo - Task management | [📖](https://docs.praison.ai/docs/cli/todo) |
|
||||
| 🎯 Router - Smart model selection | [📖](https://docs.praison.ai/docs/cli/router) |
|
||||
| 📈 Flow Display - Visual workflow | [📖](https://docs.praison.ai/docs/cli/flow-display) |
|
||||
| ✨ Prompt Expansion - Detailed prompts | [📖](https://docs.praison.ai/docs/cli/prompt-expansion) |
|
||||
| 🌐 Web Search - Real-time search | [📖](https://docs.praison.ai/docs/cli/web-search) |
|
||||
| 📥 Web Fetch - URL content retrieval | [📖](https://docs.praison.ai/docs/cli/web-fetch) |
|
||||
| 💾 Prompt Caching - Cost reduction | [📖](https://docs.praison.ai/docs/cli/prompt-caching) |
|
||||
|
||||
---
|
||||
|
||||
@@ -2209,7 +2392,7 @@ PraisonAI provides zero-dependency persistent memory for agents. For detailed ex
|
||||
- 📖 **Wikipedia Agent** - Search and extract Wikipedia information
|
||||
- 💻 **Programming Agent** - Code development and analysis
|
||||
- 📝 **Markdown Agent** - Generate and format Markdown content
|
||||
- 🔀 **Router Agent** - Dynamic task routing with cost optimisation
|
||||
- 🔀 **Model Router** - Smart model selection based on task complexity
|
||||
|
||||
### MCP Protocol
|
||||
|
||||
@@ -2218,11 +2401,19 @@ PraisonAI provides zero-dependency persistent memory for agents. For detailed ex
|
||||
- 🔐 **MCP Security** - Origin validation, DNS rebinding prevention, secure sessions
|
||||
- 🔄 **MCP Resumability** - SSE stream recovery via Last-Event-ID
|
||||
|
||||
### A2A & A2UI Protocols
|
||||
|
||||
- 🔗 **A2A Protocol** - Agent-to-Agent communication for inter-agent collaboration
|
||||
- 🖼️ **A2UI Protocol** - Agent-to-User Interface for generating rich UIs from agents
|
||||
- 📋 **UI Templates** - ChatTemplate, ListTemplate, FormTemplate, DashboardTemplate
|
||||
- 🔧 **Surface Builder** - Fluent API for building declarative UIs
|
||||
|
||||
### Safety & Control
|
||||
|
||||
- 🤝 **Agent Handoffs** - Transfer context between specialised agents
|
||||
- 🛡️ **Guardrails** - Input/output validation and safety checks
|
||||
- ✅ **Human Approval** - Require human confirmation for critical actions
|
||||
- 🔐 **Tool Approval CLI** - `--trust` (auto-approve all) and `--approve-level` (risk-based approval)
|
||||
- 💬 **Sessions Management** - Isolated conversation contexts
|
||||
- 🔄 **Stateful Agents** - Maintain state across interactions
|
||||
|
||||
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=2.3.35" \
|
||||
"praisonai>=2.3.63" \
|
||||
"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>=2.3.35" \
|
||||
"praisonai>=2.3.63" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[chat]" \
|
||||
"praisonai[realtime]" \
|
||||
|
||||
@@ -0,0 +1,25 @@
|
||||
# Dockerfile for PraisonAI Serve API
|
||||
# Deploy to Railway, Render, Fly.io, or any container platform
|
||||
#
|
||||
# Build: docker build -f Dockerfile.serve -t praisonai-serve .
|
||||
# Run: docker run -p 8005:8005 -e OPENAI_API_KEY=sk-xxx praisonai-serve
|
||||
|
||||
FROM python:3.11-slim
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# Install dependencies
|
||||
RUN pip install --no-cache-dir praisonai praisonaiagents
|
||||
|
||||
# Copy agents configuration
|
||||
COPY agents.yaml .
|
||||
|
||||
# Expose the API port
|
||||
EXPOSE 8005
|
||||
|
||||
# Health check
|
||||
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
|
||||
CMD curl -f http://localhost:8005/health || exit 1
|
||||
|
||||
# Start the API server
|
||||
CMD ["praisonai", "serve", "agents.yaml", "--host", "0.0.0.0", "--port", "8005"]
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=2.3.35" \
|
||||
"praisonai>=2.3.63" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[crewai]"
|
||||
|
||||
|
||||
@@ -0,0 +1,49 @@
|
||||
# PraisonAI Examples
|
||||
|
||||
This folder contains examples for PraisonAI. For detailed documentation, visit [docs.praison.ai](https://docs.praison.ai).
|
||||
|
||||
## Structure
|
||||
|
||||
```
|
||||
examples/
|
||||
├── python/ # Python examples
|
||||
│ ├── agents/ # Agent examples (single, multi, router, etc.)
|
||||
│ ├── workflows/ # Workflow patterns (routing, parallel, loop)
|
||||
│ ├── tools/ # Custom tools examples
|
||||
│ ├── mcp/ # MCP protocol examples
|
||||
│ ├── memory/ # Memory and sessions
|
||||
│ ├── code/ # Code editing and external CLI tools
|
||||
│ └── ...
|
||||
├── yaml/ # YAML workflow examples
|
||||
└── cookbooks/ # Complete use-case examples
|
||||
```
|
||||
|
||||
## Quick Links
|
||||
|
||||
| Category | Examples | Docs |
|
||||
|----------|----------|------|
|
||||
| **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) |
|
||||
| **MCP** | [python/mcp/](python/mcp/) | [📖](https://docs.praison.ai/mcp) |
|
||||
| **Memory** | [python/memory/](python/memory/) | [📖](https://docs.praison.ai/concepts/memory) |
|
||||
| **Tools** | [python/tools/](python/tools/) | [📖](https://docs.praison.ai/tools) |
|
||||
| **Code** | [python/code/](python/code/) | [📖](https://docs.praison.ai/code) |
|
||||
| **YAML** | [yaml/](yaml/) | [📖](https://docs.praison.ai/features/yaml-workflows) |
|
||||
|
||||
## Running Examples
|
||||
|
||||
```bash
|
||||
# Install PraisonAI
|
||||
pip install praisonai
|
||||
|
||||
# Set API key
|
||||
export OPENAI_API_KEY=your_key_here
|
||||
|
||||
# Run an example
|
||||
python examples/python/agents/single-agent.py
|
||||
```
|
||||
|
||||
## CLI Commands
|
||||
|
||||
See the main [README.md](../README.md#-cli--no-code-interface) for all CLI commands.
|
||||
@@ -0,0 +1,53 @@
|
||||
"""
|
||||
PraisonAI A2A Server Example
|
||||
|
||||
Expose a PraisonAI Agent as an A2A (Agent2Agent) Server.
|
||||
This enables other AI agents to discover and communicate with your agent.
|
||||
|
||||
Run:
|
||||
uvicorn a2a-server:app --reload
|
||||
|
||||
Endpoints:
|
||||
GET /.well-known/agent.json - Agent Card for discovery
|
||||
GET /status - Server status
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, A2A
|
||||
from fastapi import FastAPI
|
||||
|
||||
# Create an agent with tools
|
||||
def search_web(query: str) -> str:
|
||||
"""Search the web for information."""
|
||||
return f"Search results for: {query}"
|
||||
|
||||
def calculate(expression: str) -> str:
|
||||
"""Calculate a mathematical expression."""
|
||||
try:
|
||||
return f"Result: {eval(expression)}"
|
||||
except Exception:
|
||||
return "Invalid expression"
|
||||
|
||||
agent = Agent(
|
||||
name="Research Assistant",
|
||||
role="Research Analyst",
|
||||
goal="Help users research topics and answer questions",
|
||||
tools=[search_web, calculate]
|
||||
)
|
||||
|
||||
# Expose as A2A Server
|
||||
a2a = A2A(
|
||||
agent=agent,
|
||||
url="http://localhost:8000/a2a",
|
||||
version="1.0.0"
|
||||
)
|
||||
|
||||
# Create FastAPI app
|
||||
app = FastAPI(
|
||||
title="PraisonAI A2A Server",
|
||||
description="A2A-compatible agent server"
|
||||
)
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
uvicorn.run(app, host="0.0.0.0", port=8000)
|
||||
@@ -0,0 +1,132 @@
|
||||
"""
|
||||
AutoAgents Workflow Patterns Example
|
||||
|
||||
This example demonstrates the new workflow auto-generation features:
|
||||
- Dynamic agent count based on task complexity
|
||||
- Multiple workflow patterns (sequential, parallel, routing, orchestrator-workers, evaluator-optimizer)
|
||||
- Pattern recommendation based on task keywords
|
||||
|
||||
Documentation: https://docs.praison.ai/features/autoagents
|
||||
CLI Reference: https://docs.praison.ai/nocode/auto
|
||||
"""
|
||||
|
||||
from praisonai.auto import AutoGenerator, WorkflowAutoGenerator
|
||||
import os
|
||||
import tempfile
|
||||
|
||||
# Ensure API key is set
|
||||
if not os.environ.get("OPENAI_API_KEY"):
|
||||
print("Please set OPENAI_API_KEY environment variable")
|
||||
exit(1)
|
||||
|
||||
print("=" * 60)
|
||||
print("AutoAgents Workflow Patterns Demo")
|
||||
print("=" * 60)
|
||||
|
||||
# =============================================================================
|
||||
# Example 1: Dynamic Agent Count (Simple vs Complex Tasks)
|
||||
# =============================================================================
|
||||
print("\n📊 Example 1: Dynamic Agent Count")
|
||||
print("-" * 40)
|
||||
|
||||
# Simple task - should create 1-2 agents
|
||||
with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f:
|
||||
simple_file = f.name
|
||||
|
||||
simple_generator = AutoGenerator(
|
||||
topic="Write a haiku about spring",
|
||||
agent_file=simple_file,
|
||||
framework="praisonai"
|
||||
)
|
||||
|
||||
print("Simple task: 'Write a haiku about spring'")
|
||||
result = simple_generator.generate()
|
||||
print(f"Generated: {result}")
|
||||
|
||||
# Complex task - should create 3-4 agents
|
||||
with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f:
|
||||
complex_file = f.name
|
||||
|
||||
complex_generator = AutoGenerator(
|
||||
topic="Research AI trends, analyze market data, write a comprehensive report with executive summary",
|
||||
agent_file=complex_file,
|
||||
framework="praisonai"
|
||||
)
|
||||
|
||||
print("\nComplex task: 'Research AI trends, analyze market data...'")
|
||||
result = complex_generator.generate()
|
||||
print(f"Generated: {result}")
|
||||
|
||||
# =============================================================================
|
||||
# Example 2: Pattern Recommendation
|
||||
# =============================================================================
|
||||
print("\n🎯 Example 2: Pattern Recommendation")
|
||||
print("-" * 40)
|
||||
|
||||
test_tasks = [
|
||||
("Write a blog post", "sequential"),
|
||||
("Research from multiple sources simultaneously", "parallel"),
|
||||
("Classify and route customer requests", "routing"),
|
||||
("Comprehensive analysis and break down the problem", "orchestrator-workers"),
|
||||
("Refine and improve content quality", "evaluator-optimizer"),
|
||||
]
|
||||
|
||||
for task, expected in test_tasks:
|
||||
generator = WorkflowAutoGenerator(topic=task)
|
||||
recommended = generator.recommend_pattern()
|
||||
status = "✅" if recommended == expected else "⚠️"
|
||||
print(f"{status} Task: '{task[:40]}...'")
|
||||
print(f" Recommended: {recommended}")
|
||||
|
||||
# =============================================================================
|
||||
# Example 3: Generate Workflow with Specific Pattern
|
||||
# =============================================================================
|
||||
print("\n🔄 Example 3: Generate Workflows with Patterns")
|
||||
print("-" * 40)
|
||||
|
||||
patterns = ["sequential", "parallel", "orchestrator-workers", "evaluator-optimizer"]
|
||||
|
||||
for pattern in patterns:
|
||||
with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f:
|
||||
workflow_file = f.name
|
||||
|
||||
generator = WorkflowAutoGenerator(
|
||||
topic="Create a market analysis report",
|
||||
workflow_file=workflow_file
|
||||
)
|
||||
|
||||
print(f"\n📋 Pattern: {pattern}")
|
||||
result = generator.generate(pattern=pattern)
|
||||
print(f" Generated: {result}")
|
||||
|
||||
# Read and show structure
|
||||
import yaml
|
||||
with open(result, 'r') as f:
|
||||
data = yaml.safe_load(f)
|
||||
print(f" Agents: {list(data.get('agents', {}).keys())}")
|
||||
print(f" Steps: {len(data.get('steps', []))}")
|
||||
|
||||
# =============================================================================
|
||||
# Example 4: CLI Usage (for reference)
|
||||
# =============================================================================
|
||||
print("\n💻 Example 4: CLI Commands (for reference)")
|
||||
print("-" * 40)
|
||||
print("""
|
||||
# Auto-generate agents (dynamic count)
|
||||
praisonai --auto "Write a haiku about spring"
|
||||
|
||||
# Auto-generate workflow with pattern
|
||||
praisonai workflow auto "Research and write a report" --pattern sequential
|
||||
praisonai workflow auto "Research from multiple sources" --pattern parallel
|
||||
praisonai workflow auto "Comprehensive market analysis" --pattern orchestrator-workers
|
||||
praisonai workflow auto "Refine content quality" --pattern evaluator-optimizer
|
||||
|
||||
# With output file
|
||||
praisonai workflow auto "Customer support routing" --pattern routing --output support.yaml
|
||||
""")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("✅ AutoAgents Workflow Patterns Demo Complete!")
|
||||
print("=" * 60)
|
||||
print("\nDocumentation: https://docs.praison.ai/features/autoagents")
|
||||
print("CLI Reference: https://docs.praison.ai/nocode/auto")
|
||||
@@ -0,0 +1,38 @@
|
||||
"""
|
||||
Autonomy Modes Example for PraisonAI CLI.
|
||||
|
||||
Control AI autonomy: suggest, auto_edit, full_auto.
|
||||
Docs: https://docs.praison.ai/cli/autonomy-modes
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import AutonomyModeHandler
|
||||
from praisonai.cli.features.autonomy_mode import ActionRequest, ActionType
|
||||
|
||||
# Initialize with suggest mode (safest)
|
||||
handler = AutonomyModeHandler()
|
||||
manager = handler.initialize(mode="suggest")
|
||||
|
||||
print(f"Current mode: {handler.get_mode()}")
|
||||
print("Available modes: suggest, auto_edit, full_auto")
|
||||
|
||||
# Create an action request
|
||||
action = ActionRequest(
|
||||
action_type=ActionType.FILE_WRITE,
|
||||
description="Edit src/main.py to add logging",
|
||||
details={"file": "src/main.py"}
|
||||
)
|
||||
|
||||
# In suggest mode, this would require approval
|
||||
# For demo, we'll just show the action
|
||||
print(f"\nAction: {action.description}")
|
||||
print(f"Type: {action.action_type.value}")
|
||||
print("Would require approval in 'suggest' mode")
|
||||
|
||||
# Change to auto_edit mode
|
||||
handler.set_mode("auto_edit")
|
||||
print(f"\nChanged to: {handler.get_mode()}")
|
||||
print("File edits now auto-approved, shell commands still require approval")
|
||||
|
||||
# Get statistics
|
||||
stats = handler.get_stats()
|
||||
print(f"\nStats: {stats}")
|
||||
@@ -0,0 +1,34 @@
|
||||
"""
|
||||
Cost Tracking Example for PraisonAI CLI.
|
||||
|
||||
Real-time token usage and cost monitoring.
|
||||
Docs: https://docs.praison.ai/cli/cost-tracking
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import CostTrackerHandler
|
||||
|
||||
# Initialize tracker
|
||||
handler = CostTrackerHandler()
|
||||
tracker = handler.initialize(session_id="demo-session")
|
||||
|
||||
# Track some requests
|
||||
handler.track_request("gpt-4o", input_tokens=1000, output_tokens=500)
|
||||
handler.track_request("gpt-4o-mini", input_tokens=2000, output_tokens=800)
|
||||
handler.track_request("claude-3-5-sonnet", input_tokens=1500, output_tokens=600)
|
||||
|
||||
# Get totals
|
||||
print(f"Total tokens: {handler.get_tokens():,}")
|
||||
print(f"Total cost: ${handler.get_cost():.4f}")
|
||||
|
||||
# Get detailed summary
|
||||
summary = handler.get_summary()
|
||||
print("\n=== Session Summary ===")
|
||||
print(f"Session ID: {summary['session_id']}")
|
||||
print(f"Total requests: {summary['total_requests']}")
|
||||
print(f"Input tokens: {summary['total_input_tokens']:,}")
|
||||
print(f"Output tokens: {summary['total_output_tokens']:,}")
|
||||
print(f"Total cost: ${summary['total_cost']:.4f}")
|
||||
print(f"Avg cost/request: ${summary['avg_cost_per_request']:.4f}")
|
||||
|
||||
# Display formatted (uses Rich if available)
|
||||
handler.display_summary()
|
||||
@@ -0,0 +1,45 @@
|
||||
"""
|
||||
Git Integration Example for PraisonAI CLI.
|
||||
|
||||
Auto-commit with AI messages, diff viewing, undo.
|
||||
Docs: https://docs.praison.ai/cli/git-integration
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import GitIntegrationHandler
|
||||
|
||||
# Initialize
|
||||
handler = GitIntegrationHandler(verbose=True)
|
||||
git = handler.initialize(repo_path=".")
|
||||
|
||||
# Check if it's a git repo
|
||||
if not git.is_repo:
|
||||
print("Not a git repository!")
|
||||
exit(1)
|
||||
|
||||
# Show status
|
||||
print("=== Git Status ===")
|
||||
status = handler.show_status()
|
||||
print(f"Branch: {status.branch}")
|
||||
print(f"Staged: {len(status.staged_files)}")
|
||||
print(f"Modified: {len(status.modified_files)}")
|
||||
print(f"Untracked: {len(status.untracked_files)}")
|
||||
|
||||
# Show diff (if any changes)
|
||||
if status.has_changes:
|
||||
print("\n=== Diff ===")
|
||||
diff = handler.show_diff()
|
||||
if diff:
|
||||
print(diff[:300] + "..." if len(diff) > 300 else diff)
|
||||
|
||||
# Show recent commits
|
||||
print("\n=== Recent Commits ===")
|
||||
commits = handler.show_log(count=5)
|
||||
for c in commits:
|
||||
print(f" {c.short_hash} {c.message[:50]}")
|
||||
|
||||
# To commit with AI message:
|
||||
# commit = handler.commit() # Auto-generates message
|
||||
# commit = handler.commit(message="Custom message")
|
||||
|
||||
# To undo last commit:
|
||||
# handler.undo(soft=True) # Keeps changes staged
|
||||
@@ -0,0 +1,49 @@
|
||||
"""
|
||||
Interactive TUI Example for PraisonAI CLI.
|
||||
|
||||
Rich terminal interface with completions and history.
|
||||
Docs: https://docs.praison.ai/cli/interactive-tui
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import InteractiveTUIHandler
|
||||
from praisonai.cli.features.interactive_tui import InteractiveConfig
|
||||
|
||||
# Custom configuration
|
||||
config = InteractiveConfig(
|
||||
prompt="ai> ",
|
||||
multiline=True,
|
||||
enable_completions=True,
|
||||
show_status_bar=True
|
||||
)
|
||||
|
||||
# Define callbacks
|
||||
def on_input(text):
|
||||
"""Handle regular input."""
|
||||
return f"You said: {text}"
|
||||
|
||||
def on_command(cmd):
|
||||
"""Handle slash commands."""
|
||||
if cmd == "/exit":
|
||||
return {"type": "exit"}
|
||||
return {"type": "command", "message": f"Executed: {cmd}"}
|
||||
|
||||
# Initialize
|
||||
handler = InteractiveTUIHandler()
|
||||
session = handler.initialize(
|
||||
config=config,
|
||||
on_input=on_input,
|
||||
on_command=on_command
|
||||
)
|
||||
|
||||
# Add commands for completion
|
||||
session.add_commands(["help", "exit", "cost", "model", "plan"])
|
||||
|
||||
# Add symbols from codebase
|
||||
session.add_symbols(["MyClass", "my_function"])
|
||||
|
||||
print("Interactive TUI initialized!")
|
||||
print("Commands available: /help, /exit, /cost, /model, /plan")
|
||||
print("Run handler.run() to start interactive session")
|
||||
|
||||
# Uncomment to run interactive session:
|
||||
# handler.run()
|
||||
@@ -0,0 +1,24 @@
|
||||
"""
|
||||
Repository Map Example for PraisonAI CLI.
|
||||
|
||||
Intelligent codebase mapping with symbol extraction.
|
||||
Docs: https://docs.praison.ai/cli/repo-map
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import RepoMapHandler
|
||||
|
||||
# Initialize with current directory
|
||||
handler = RepoMapHandler(verbose=True)
|
||||
repo_map = handler.initialize(root=".")
|
||||
|
||||
# Get the repository map
|
||||
print("=== Repository Map ===")
|
||||
map_str = handler.get_map()
|
||||
print(map_str[:500] if len(map_str) > 500 else map_str)
|
||||
print("..." if len(map_str) > 500 else "")
|
||||
|
||||
# Refresh after file changes
|
||||
handler.refresh()
|
||||
|
||||
# Get symbols for a specific file (if exists)
|
||||
# symbols = handler.get_context("MyClass")
|
||||
@@ -0,0 +1,42 @@
|
||||
"""
|
||||
Sandbox Execution Example for PraisonAI CLI.
|
||||
|
||||
Secure isolated command execution (--sandbox flag).
|
||||
Docs: https://docs.praison.ai/cli/sandbox-execution
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import SandboxExecutorHandler
|
||||
from praisonai.cli.features.sandbox_executor import SandboxMode
|
||||
|
||||
# Initialize with basic sandbox
|
||||
handler = SandboxExecutorHandler(verbose=True)
|
||||
sandbox = handler.initialize(mode="basic")
|
||||
|
||||
print(f"Sandbox mode: {handler.get_mode()}")
|
||||
print(f"Sandbox enabled: {handler.is_enabled}")
|
||||
|
||||
# Execute a safe command
|
||||
print("\n=== Safe Command ===")
|
||||
result = handler.execute("echo 'Hello from sandbox!'")
|
||||
print(f"Success: {result.success}")
|
||||
print(f"Output: {result.stdout.strip()}")
|
||||
print(f"Sandboxed: {result.was_sandboxed}")
|
||||
|
||||
# Try a blocked command
|
||||
print("\n=== Blocked Command ===")
|
||||
result = handler.execute("rm -rf /")
|
||||
print(f"Success: {result.success}")
|
||||
print(f"Violations: {result.policy_violations}")
|
||||
|
||||
# Validate command before execution
|
||||
print("\n=== Command Validation ===")
|
||||
violations = handler.validate_command("sudo apt install something")
|
||||
if violations:
|
||||
print(f"Command blocked: {violations}")
|
||||
else:
|
||||
print("Command allowed")
|
||||
|
||||
# Available modes
|
||||
print("\n=== Available Modes ===")
|
||||
for mode in SandboxMode:
|
||||
print(f" {mode.value}")
|
||||
@@ -0,0 +1,51 @@
|
||||
"""
|
||||
Slash Commands Example for PraisonAI CLI.
|
||||
|
||||
Demonstrates interactive slash commands like /help, /cost, /model.
|
||||
Docs: https://docs.praison.ai/cli/slash-commands
|
||||
"""
|
||||
|
||||
from praisonai.cli.features import SlashCommandHandler
|
||||
from praisonai.cli.features.slash_commands import SlashCommand, CommandKind
|
||||
|
||||
# Create handler
|
||||
handler = SlashCommandHandler()
|
||||
|
||||
# Execute commands
|
||||
print("=== /help ===")
|
||||
result = handler.execute("/help")
|
||||
print(result.get("message", ""))
|
||||
|
||||
print("\n=== /cost ===")
|
||||
result = handler.execute("/cost")
|
||||
print(result.get("message", ""))
|
||||
|
||||
print("\n=== /model ===")
|
||||
result = handler.execute("/model")
|
||||
print(result.get("message", ""))
|
||||
|
||||
# Check if input is a command
|
||||
print("\n=== Command Detection ===")
|
||||
print(f"/help is command: {handler.is_command('/help')}")
|
||||
print(f"hello is command: {handler.is_command('hello')}")
|
||||
|
||||
# Get completions for auto-complete
|
||||
print("\n=== Completions for '/he' ===")
|
||||
completions = handler.get_completions("/he")
|
||||
print(completions)
|
||||
|
||||
# Register custom command
|
||||
def my_custom_handler(args, context):
|
||||
return {"type": "custom", "message": f"Custom command with args: {args}"}
|
||||
|
||||
custom_cmd = SlashCommand(
|
||||
name="mycommand",
|
||||
description="My custom command",
|
||||
handler=my_custom_handler,
|
||||
kind=CommandKind.ACTION,
|
||||
aliases=["mc"]
|
||||
)
|
||||
|
||||
handler.register(custom_cmd)
|
||||
result = handler.execute("/mycommand arg1 arg2")
|
||||
print(f"\n=== Custom Command ===\n{result.get('message', '')}")
|
||||
@@ -0,0 +1,34 @@
|
||||
"""
|
||||
Claude Code CLI Integration Example
|
||||
|
||||
Demonstrates how to use Claude Code CLI as an agent tool in PraisonAI.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from praisonai.integrations import ClaudeCodeIntegration
|
||||
|
||||
async def main():
|
||||
# Create Claude Code integration
|
||||
claude = ClaudeCodeIntegration(
|
||||
workspace=".",
|
||||
output_format="json",
|
||||
skip_permissions=True,
|
||||
system_prompt="Be concise and follow best practices",
|
||||
allowed_tools=["Read", "Write", "Bash"]
|
||||
)
|
||||
|
||||
# Check availability
|
||||
print(f"Claude CLI available: {claude.is_available}")
|
||||
print(f"Claude SDK available: {claude.sdk_available}")
|
||||
|
||||
# Execute a coding task
|
||||
result = await claude.execute("List all Python files in the current directory")
|
||||
print(f"Result: {result}")
|
||||
|
||||
# Stream output
|
||||
print("\nStreaming output:")
|
||||
async for event in claude.stream("Explain the project structure"):
|
||||
print(event)
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,60 @@
|
||||
"""
|
||||
Code Editing Tools Example
|
||||
|
||||
Demonstrates how to use PraisonAI's code editing tools with SEARCH/REPLACE diffs.
|
||||
"""
|
||||
|
||||
from praisonai.code import (
|
||||
set_workspace,
|
||||
code_read_file,
|
||||
code_write_file,
|
||||
code_apply_diff,
|
||||
code_list_files,
|
||||
code_execute_command,
|
||||
CODE_TOOLS
|
||||
)
|
||||
|
||||
# Set workspace
|
||||
set_workspace(".")
|
||||
|
||||
# List files
|
||||
print("Files in current directory:")
|
||||
files = code_list_files(".", recursive=False)
|
||||
for f in files:
|
||||
print(f" {f}")
|
||||
|
||||
# Read a file
|
||||
print("\nReading example file:")
|
||||
try:
|
||||
content = code_read_file("README.md", start_line=1, end_line=10)
|
||||
print(content)
|
||||
except Exception as e:
|
||||
print(f" File not found: {e}")
|
||||
|
||||
# Write a file
|
||||
print("\nWriting test file:")
|
||||
code_write_file("test_output.txt", "Hello from PraisonAI Code Tools!")
|
||||
print(" Created test_output.txt")
|
||||
|
||||
# Apply a diff
|
||||
print("\nApplying diff:")
|
||||
diff = """
|
||||
<<<<<<< SEARCH
|
||||
Hello from PraisonAI Code Tools!
|
||||
=======
|
||||
Hello from PraisonAI Code Tools!
|
||||
This line was added by a diff.
|
||||
>>>>>>> REPLACE
|
||||
"""
|
||||
result = code_apply_diff("test_output.txt", diff)
|
||||
print(f" {result}")
|
||||
|
||||
# Execute command
|
||||
print("\nExecuting command:")
|
||||
output = code_execute_command("cat test_output.txt")
|
||||
print(f" {output}")
|
||||
|
||||
# Cleanup
|
||||
import os
|
||||
os.remove("test_output.txt")
|
||||
print("\nCleanup complete.")
|
||||
@@ -0,0 +1,36 @@
|
||||
"""
|
||||
Codex CLI Integration Example
|
||||
|
||||
Demonstrates how to use OpenAI Codex CLI as an agent tool in PraisonAI.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from praisonai.integrations import CodexCLIIntegration
|
||||
|
||||
async def main():
|
||||
# Create Codex CLI integration
|
||||
codex = CodexCLIIntegration(
|
||||
workspace=".",
|
||||
full_auto=True,
|
||||
sandbox="danger-full-access",
|
||||
json_output=True
|
||||
)
|
||||
|
||||
# Check availability
|
||||
print(f"Codex CLI available: {codex.is_available}")
|
||||
print(f"Full Auto: {codex.full_auto}")
|
||||
print(f"Sandbox: {codex.sandbox}")
|
||||
|
||||
# Execute a coding task
|
||||
result = await codex.execute("List files in the current directory")
|
||||
print(f"Result: {result}")
|
||||
|
||||
# Stream JSON events
|
||||
print("\nStreaming events:")
|
||||
async for event in codex.stream("Explain the project"):
|
||||
event_type = event.get("type", "")
|
||||
if event_type == "item.completed":
|
||||
print(f" {event}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,37 @@
|
||||
"""
|
||||
Cursor CLI Integration Example
|
||||
|
||||
Demonstrates how to use Cursor CLI as an agent tool in PraisonAI.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from praisonai.integrations import CursorCLIIntegration
|
||||
|
||||
async def main():
|
||||
# Create Cursor CLI integration
|
||||
cursor = CursorCLIIntegration(
|
||||
workspace=".",
|
||||
output_format="json",
|
||||
force=True,
|
||||
model="gpt-5",
|
||||
stream_partial=True
|
||||
)
|
||||
|
||||
# Check availability
|
||||
print(f"Cursor CLI available: {cursor.is_available}")
|
||||
print(f"Force mode: {cursor.force}")
|
||||
print(f"Model: {cursor.model}")
|
||||
|
||||
# Execute a coding task
|
||||
result = await cursor.execute("List files in the current directory")
|
||||
print(f"Result: {result}")
|
||||
|
||||
# Stream output
|
||||
print("\nStreaming output:")
|
||||
async for event in cursor.stream("Explain the project"):
|
||||
content = event.get("content", "")
|
||||
if content:
|
||||
print(content, end="", flush=True)
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,58 @@
|
||||
"""
|
||||
External Agents Integration Example
|
||||
|
||||
Demonstrates how to use all external CLI integrations as agent tools.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from praisonai.integrations import (
|
||||
ClaudeCodeIntegration,
|
||||
GeminiCLIIntegration,
|
||||
CodexCLIIntegration,
|
||||
CursorCLIIntegration,
|
||||
get_available_integrations
|
||||
)
|
||||
|
||||
async def main():
|
||||
# Check availability of all integrations
|
||||
print("=== External CLI Integrations ===\n")
|
||||
|
||||
availability = get_available_integrations()
|
||||
print("Availability:")
|
||||
for name, avail in availability.items():
|
||||
status = "✅" if avail else "❌"
|
||||
print(f" {status} {name}")
|
||||
|
||||
# Create integrations
|
||||
print("\n--- Claude Code ---")
|
||||
claude = ClaudeCodeIntegration(workspace=".", skip_permissions=True)
|
||||
print(f"CLI: {claude.cli_command}")
|
||||
print(f"Available: {claude.is_available}")
|
||||
tool = claude.as_tool()
|
||||
print(f"Tool: {tool.__name__}")
|
||||
|
||||
print("\n--- Gemini CLI ---")
|
||||
gemini = GeminiCLIIntegration(workspace=".", model="gemini-2.5-flash")
|
||||
print(f"CLI: {gemini.cli_command}")
|
||||
print(f"Available: {gemini.is_available}")
|
||||
tool = gemini.as_tool()
|
||||
print(f"Tool: {tool.__name__}")
|
||||
|
||||
print("\n--- Codex CLI ---")
|
||||
codex = CodexCLIIntegration(workspace=".", full_auto=True)
|
||||
print(f"CLI: {codex.cli_command}")
|
||||
print(f"Available: {codex.is_available}")
|
||||
tool = codex.as_tool()
|
||||
print(f"Tool: {tool.__name__}")
|
||||
|
||||
print("\n--- Cursor CLI ---")
|
||||
cursor = CursorCLIIntegration(workspace=".", force=True)
|
||||
print(f"CLI: {cursor.cli_command}")
|
||||
print(f"Available: {cursor.is_available}")
|
||||
tool = cursor.as_tool()
|
||||
print(f"Tool: {tool.__name__}")
|
||||
|
||||
print("\n=== All integrations ready ===")
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,33 @@
|
||||
"""
|
||||
Gemini CLI Integration Example
|
||||
|
||||
Demonstrates how to use Gemini CLI as an agent tool in PraisonAI.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from praisonai.integrations import GeminiCLIIntegration
|
||||
|
||||
async def main():
|
||||
# Create Gemini CLI integration
|
||||
gemini = GeminiCLIIntegration(
|
||||
workspace=".",
|
||||
model="gemini-2.5-flash",
|
||||
output_format="json",
|
||||
include_directories=["../lib", "../docs"]
|
||||
)
|
||||
|
||||
# Check availability
|
||||
print(f"Gemini CLI available: {gemini.is_available}")
|
||||
print(f"Model: {gemini.model}")
|
||||
|
||||
# Execute a coding task
|
||||
result = await gemini.execute("Analyze the code structure")
|
||||
print(f"Result: {result}")
|
||||
|
||||
# Execute with stats
|
||||
result, stats = await gemini.execute_with_stats("Explain main.py")
|
||||
print(f"Result: {result}")
|
||||
print(f"Stats: {stats}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,11 +1,48 @@
|
||||
"""
|
||||
AutoAgents Example
|
||||
|
||||
AutoAgents automatically creates and manages AI agents based on high-level instructions.
|
||||
It features dynamic agent count based on task complexity.
|
||||
|
||||
Documentation: https://docs.praison.ai/features/autoagents
|
||||
CLI Reference: https://docs.praison.ai/nocode/auto
|
||||
|
||||
New Features:
|
||||
- Dynamic agent count (1-4 based on task complexity)
|
||||
- Workflow patterns: sequential, parallel, routing, orchestrator-workers, evaluator-optimizer
|
||||
- Pattern recommendation based on task keywords
|
||||
- Tool preservation from LLM suggestions
|
||||
"""
|
||||
|
||||
from praisonaiagents import AutoAgents
|
||||
from praisonaiagents.tools import duckduckgo
|
||||
|
||||
# Basic usage - AutoAgents analyzes complexity and creates optimal agents
|
||||
agents = AutoAgents(
|
||||
instructions="Search for information about AI Agents",
|
||||
tools=[duckduckgo],
|
||||
process="sequential",
|
||||
verbose=True
|
||||
process="sequential", # or "hierarchical"
|
||||
verbose=True,
|
||||
max_agents=3 # Maximum number of agents to create
|
||||
)
|
||||
|
||||
agents.start()
|
||||
result = agents.start()
|
||||
print(result)
|
||||
|
||||
# =============================================================================
|
||||
# CLI Usage Examples (for reference)
|
||||
# =============================================================================
|
||||
#
|
||||
# # Auto-generate agents (dynamic count based on complexity)
|
||||
# praisonai --auto "Write a haiku about spring"
|
||||
# praisonai --auto "Research AI trends, analyze data, write report"
|
||||
#
|
||||
# # Auto-generate workflow with specific pattern
|
||||
# praisonai workflow auto "Research and write" --pattern sequential
|
||||
# praisonai workflow auto "Research from multiple sources" --pattern parallel
|
||||
# praisonai workflow auto "Comprehensive analysis" --pattern orchestrator-workers
|
||||
# praisonai workflow auto "Refine content quality" --pattern evaluator-optimizer
|
||||
#
|
||||
# # With framework selection
|
||||
# praisonai --framework crewai --auto "Create a movie script"
|
||||
# praisonai --framework autogen --auto "Create a movie script"
|
||||
@@ -9,6 +9,8 @@ Usage:
|
||||
export OPENAI_API_KEY=your_key
|
||||
python benchmarks/execution_benchmark.py
|
||||
python benchmarks/execution_benchmark.py --no-save
|
||||
python benchmarks/execution_benchmark.py --iterations 5
|
||||
python benchmarks/execution_benchmark.py --model gpt-4o --iterations 10
|
||||
"""
|
||||
|
||||
import time
|
||||
@@ -16,14 +18,10 @@ import os
|
||||
import argparse
|
||||
from importlib.metadata import version as get_version
|
||||
|
||||
# Check API key
|
||||
if not os.environ.get('OPENAI_API_KEY'):
|
||||
print("ERROR: Set OPENAI_API_KEY environment variable")
|
||||
exit(1)
|
||||
|
||||
MODEL = "gpt-4o-mini"
|
||||
ITERATIONS = 3
|
||||
PROMPT = "What is 2+2? Reply with just the number."
|
||||
# Defaults (can be overridden via CLI)
|
||||
DEFAULT_MODEL = "gpt-4o-mini"
|
||||
DEFAULT_ITERATIONS = 3
|
||||
DEFAULT_PROMPT = "What is 2+2? Reply with just the number."
|
||||
|
||||
|
||||
def get_package_versions():
|
||||
@@ -42,24 +40,24 @@ def get_package_versions():
|
||||
return versions
|
||||
|
||||
|
||||
def benchmark_praisonai():
|
||||
def benchmark_praisonai(model, iterations, prompt):
|
||||
"""Benchmark PraisonAI agent execution using agent.start()"""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
print("\n--- PraisonAI ---")
|
||||
print(f"Method: agent.start()")
|
||||
print("Method: agent.start()")
|
||||
|
||||
times = []
|
||||
for i in range(ITERATIONS):
|
||||
for i in range(iterations):
|
||||
agent = Agent(
|
||||
name="Calculator",
|
||||
instructions="You are a helpful assistant. Be very brief.",
|
||||
llm=MODEL,
|
||||
llm=model,
|
||||
verbose=False
|
||||
)
|
||||
|
||||
start = time.perf_counter()
|
||||
response = agent.start(PROMPT)
|
||||
response = agent.start(prompt)
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
times.append(elapsed)
|
||||
@@ -70,24 +68,24 @@ def benchmark_praisonai():
|
||||
return avg
|
||||
|
||||
|
||||
def benchmark_praisonai_litellm():
|
||||
def benchmark_praisonai_litellm(model, iterations, prompt):
|
||||
"""Benchmark PraisonAI with LiteLLM backend using agent.start()"""
|
||||
from praisonaiagents import Agent
|
||||
|
||||
print("\n--- PraisonAI (LiteLLM) ---")
|
||||
print(f"Method: agent.start()")
|
||||
print("Method: agent.start()")
|
||||
|
||||
times = []
|
||||
for i in range(ITERATIONS):
|
||||
for i in range(iterations):
|
||||
agent = Agent(
|
||||
name="Calculator",
|
||||
instructions="You are a helpful assistant. Be very brief.",
|
||||
llm=f"openai/{MODEL}",
|
||||
llm=f"openai/{model}",
|
||||
verbose=False
|
||||
)
|
||||
|
||||
start = time.perf_counter()
|
||||
response = agent.start(PROMPT)
|
||||
response = agent.start(prompt)
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
times.append(elapsed)
|
||||
@@ -98,23 +96,23 @@ def benchmark_praisonai_litellm():
|
||||
return avg
|
||||
|
||||
|
||||
def benchmark_agno():
|
||||
def benchmark_agno(model, iterations, prompt):
|
||||
"""Benchmark Agno agent execution using agent.run()"""
|
||||
from agno.agent import Agent
|
||||
from agno.models.openai import OpenAIChat
|
||||
|
||||
print("\n--- Agno ---")
|
||||
print(f"Method: agent.run()")
|
||||
print("Method: agent.run()")
|
||||
|
||||
times = []
|
||||
for i in range(ITERATIONS):
|
||||
for i in range(iterations):
|
||||
agent = Agent(
|
||||
model=OpenAIChat(id=MODEL),
|
||||
model=OpenAIChat(id=model),
|
||||
instructions=["You are a helpful assistant. Be very brief."],
|
||||
)
|
||||
|
||||
start = time.perf_counter()
|
||||
response = agent.run(PROMPT)
|
||||
response = agent.run(prompt)
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
times.append(elapsed)
|
||||
@@ -127,25 +125,25 @@ def benchmark_agno():
|
||||
return avg
|
||||
|
||||
|
||||
def benchmark_crewai():
|
||||
def benchmark_crewai(model, iterations, prompt):
|
||||
"""Benchmark CrewAI agent execution using crew.kickoff()"""
|
||||
from crewai import Agent, Task, Crew
|
||||
|
||||
print("\n--- CrewAI ---")
|
||||
print(f"Method: crew.kickoff()")
|
||||
print("Method: crew.kickoff()")
|
||||
|
||||
times = []
|
||||
for i in range(ITERATIONS):
|
||||
for i in range(iterations):
|
||||
agent = Agent(
|
||||
role="Calculator",
|
||||
goal="Answer math questions",
|
||||
backstory="You are a helpful assistant.",
|
||||
llm=MODEL,
|
||||
llm=model,
|
||||
verbose=False
|
||||
)
|
||||
|
||||
task = Task(
|
||||
description=PROMPT,
|
||||
description=prompt,
|
||||
expected_output="A number",
|
||||
agent=agent
|
||||
)
|
||||
@@ -168,7 +166,7 @@ def benchmark_crewai():
|
||||
return avg
|
||||
|
||||
|
||||
def save_results(results: dict):
|
||||
def save_results(results: dict, model: str, iterations: int, prompt: str):
|
||||
"""Save results to markdown file."""
|
||||
import os
|
||||
from datetime import datetime
|
||||
@@ -183,9 +181,9 @@ def save_results(results: dict):
|
||||
with open(filepath, 'w') as f:
|
||||
f.write('# PraisonAI Agents - Real Execution Benchmark\n\n')
|
||||
f.write(f'**Generated:** {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n')
|
||||
f.write(f'**Model:** {MODEL}\n')
|
||||
f.write(f'**Iterations:** {ITERATIONS}\n')
|
||||
f.write(f'**Prompt:** "{PROMPT}"\n\n')
|
||||
f.write(f'**Model:** {model}\n')
|
||||
f.write(f'**Iterations:** {iterations}\n')
|
||||
f.write(f'**Prompt:** "{prompt}"\n\n')
|
||||
f.write('## Results\n\n')
|
||||
f.write('| Framework | Method | Avg Time | Relative |\n')
|
||||
f.write('|-----------|--------|----------|----------|\n')
|
||||
@@ -224,14 +222,26 @@ def save_results(results: dict):
|
||||
if __name__ == '__main__':
|
||||
parser = argparse.ArgumentParser(description='PraisonAI Agents - Real Execution Benchmark')
|
||||
parser.add_argument('--no-save', action='store_true', help='Do not save results to file')
|
||||
parser.add_argument('--model', '-m', type=str, default=DEFAULT_MODEL, help=f'Model to use (default: {DEFAULT_MODEL})')
|
||||
parser.add_argument('--iterations', '-i', type=int, default=DEFAULT_ITERATIONS, help=f'Number of iterations (default: {DEFAULT_ITERATIONS})')
|
||||
parser.add_argument('--prompt', '-p', type=str, default=DEFAULT_PROMPT, help=f'Prompt to use (default: "{DEFAULT_PROMPT}")')
|
||||
args = parser.parse_args()
|
||||
|
||||
# Check API key
|
||||
if not os.environ.get('OPENAI_API_KEY'):
|
||||
print("ERROR: Set OPENAI_API_KEY environment variable")
|
||||
exit(1)
|
||||
|
||||
model = args.model
|
||||
iterations = args.iterations
|
||||
prompt = args.prompt
|
||||
|
||||
print('=' * 60)
|
||||
print('PraisonAI Agents - Real Execution Benchmark')
|
||||
print('=' * 60)
|
||||
print(f'\nModel: {MODEL}')
|
||||
print(f'Iterations: {ITERATIONS}')
|
||||
print(f'Prompt: "{PROMPT}"')
|
||||
print(f'\nModel: {model}')
|
||||
print(f'Iterations: {iterations}')
|
||||
print(f'Prompt: "{prompt}"')
|
||||
|
||||
versions = get_package_versions()
|
||||
print('\nPackage versions:')
|
||||
@@ -242,22 +252,22 @@ if __name__ == '__main__':
|
||||
|
||||
# Run benchmarks
|
||||
try:
|
||||
results['PraisonAI'] = benchmark_praisonai()
|
||||
results['PraisonAI'] = benchmark_praisonai(model, iterations, prompt)
|
||||
except Exception as e:
|
||||
print(f"PraisonAI error: {e}")
|
||||
|
||||
try:
|
||||
results['PraisonAI (LiteLLM)'] = benchmark_praisonai_litellm()
|
||||
results['PraisonAI (LiteLLM)'] = benchmark_praisonai_litellm(model, iterations, prompt)
|
||||
except Exception as e:
|
||||
print(f"PraisonAI (LiteLLM) error: {e}")
|
||||
|
||||
try:
|
||||
results['Agno'] = benchmark_agno()
|
||||
results['Agno'] = benchmark_agno(model, iterations, prompt)
|
||||
except Exception as e:
|
||||
print(f"Agno error: {e}")
|
||||
|
||||
try:
|
||||
results['CrewAI'] = benchmark_crewai()
|
||||
results['CrewAI'] = benchmark_crewai(model, iterations, prompt)
|
||||
except Exception as e:
|
||||
print(f"CrewAI error: {e}")
|
||||
|
||||
@@ -281,6 +291,6 @@ if __name__ == '__main__':
|
||||
|
||||
# Save results (unless --no-save)
|
||||
if results and not args.no_save:
|
||||
save_results(results)
|
||||
save_results(results, model, iterations, prompt)
|
||||
elif args.no_save:
|
||||
print('\nResults not saved (--no-save flag used)')
|
||||
@@ -0,0 +1,90 @@
|
||||
"""
|
||||
Unified Web Search Example
|
||||
|
||||
This example demonstrates the search_web tool that automatically tries
|
||||
multiple search providers with fallback support.
|
||||
|
||||
Search Provider Priority:
|
||||
1. Tavily (requires TAVILY_API_KEY + tavily-python)
|
||||
2. Exa (requires EXA_API_KEY + exa_py)
|
||||
3. You.com (requires YDC_API_KEY + youdotcom)
|
||||
4. DuckDuckGo (requires duckduckgo_search package, no API key)
|
||||
5. SearxNG (requires requests + running SearxNG instance)
|
||||
|
||||
Installation:
|
||||
pip install praisonaiagents duckduckgo_search
|
||||
|
||||
Usage:
|
||||
python web_search_example.py
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.tools import search_web, get_available_providers
|
||||
|
||||
|
||||
def main():
|
||||
print("=" * 60)
|
||||
print("Unified Web Search - Provider Status")
|
||||
print("=" * 60)
|
||||
|
||||
# Check which providers are available
|
||||
providers = get_available_providers()
|
||||
for p in providers:
|
||||
status = "✓ Available" if p["available"] else f"✗ {p['reason']}"
|
||||
print(f" {p['name']:12} {status}")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example 1: Basic Search")
|
||||
print("=" * 60)
|
||||
|
||||
# Simple search - automatically uses best available provider
|
||||
results = search_web("Python programming best practices", max_results=3)
|
||||
|
||||
if results and "error" not in results[0]:
|
||||
print(f"\nFound {len(results)} results using {results[0].get('provider', 'unknown')}:\n")
|
||||
for r in results:
|
||||
print(f" Title: {r.get('title', 'N/A')[:60]}...")
|
||||
print(f" URL: {r.get('url', 'N/A')}")
|
||||
print()
|
||||
else:
|
||||
print(f"\nSearch failed: {results}")
|
||||
|
||||
print("=" * 60)
|
||||
print("Example 2: Specify Providers")
|
||||
print("=" * 60)
|
||||
|
||||
# Only try specific providers
|
||||
results = search_web(
|
||||
"machine learning tutorials",
|
||||
max_results=3,
|
||||
providers=["duckduckgo", "tavily"] # Try these in order
|
||||
)
|
||||
|
||||
if results and "error" not in results[0]:
|
||||
print(f"\nFound {len(results)} results using {results[0].get('provider', 'unknown')}:\n")
|
||||
for r in results:
|
||||
print(f" Title: {r.get('title', 'N/A')[:60]}...")
|
||||
print(f" URL: {r.get('url', 'N/A')}")
|
||||
print()
|
||||
else:
|
||||
print(f"\nSearch failed: {results}")
|
||||
|
||||
print("=" * 60)
|
||||
print("Example 3: With PraisonAI Agent")
|
||||
print("=" * 60)
|
||||
|
||||
# Use search_web as an agent tool
|
||||
agent = Agent(
|
||||
name="SearchAgent",
|
||||
role="Web Researcher",
|
||||
goal="Find and summarize information from the web",
|
||||
instructions="Search the web and provide concise summaries of findings.",
|
||||
tools=[search_web]
|
||||
)
|
||||
|
||||
result = agent.start("What are the top 3 AI trends in 2025?")
|
||||
print(f"\nAgent Response:\n{result}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -305,3 +305,21 @@ __all__.extend([
|
||||
'LineRange'
|
||||
])
|
||||
|
||||
# AG-UI support (optional, lazy loaded)
|
||||
try:
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
__all__.append('AGUI')
|
||||
_agui_available = True
|
||||
except ImportError:
|
||||
_agui_available = False
|
||||
AGUI = None
|
||||
|
||||
# A2A support (optional, lazy loaded)
|
||||
try:
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
__all__.append('A2A')
|
||||
_a2a_available = True
|
||||
except ImportError:
|
||||
_a2a_available = False
|
||||
A2A = None
|
||||
|
||||
@@ -55,10 +55,10 @@ def _get_all_noisy_loggers() -> List[str]:
|
||||
|
||||
def _configure_loggers():
|
||||
"""Configure all loggers based on LOGLEVEL environment variable."""
|
||||
loglevel = os.environ.get('LOGLEVEL', 'INFO').upper()
|
||||
loglevel = os.environ.get('LOGLEVEL', 'WARNING').upper()
|
||||
|
||||
# When DEBUG is set, allow some HTTP logging for API endpoints
|
||||
if loglevel == 'DEBUG':
|
||||
# When DEBUG or INFO is set, allow some HTTP logging for API endpoints
|
||||
if loglevel in ('DEBUG', 'INFO'):
|
||||
allowed_debug_loggers = {"httpx", "httpx._client", "openai._client"}
|
||||
|
||||
for logger_name in _get_all_noisy_loggers():
|
||||
@@ -109,10 +109,10 @@ def configure_root_logger():
|
||||
"""Configure the root logger with RichHandler."""
|
||||
from rich.logging import RichHandler
|
||||
|
||||
loglevel = os.environ.get('LOGLEVEL', 'INFO').upper()
|
||||
loglevel = os.environ.get('LOGLEVEL', 'WARNING').upper()
|
||||
|
||||
logging.basicConfig(
|
||||
level=getattr(logging, loglevel, logging.INFO),
|
||||
level=getattr(logging, loglevel, logging.WARNING),
|
||||
format="%(asctime)s %(filename)s:%(lineno)d %(levelname)s %(message)s",
|
||||
datefmt="[%X]",
|
||||
handlers=[RichHandler(rich_tracebacks=True)],
|
||||
|
||||
@@ -29,7 +29,9 @@ SUPPRESSED_PATTERNS = [
|
||||
"PydanticSerializationUnexpectedValue",
|
||||
"Expected 9 fields but got 5 for type `Message`",
|
||||
"Expected `StreamingChoices` but got `Choices`",
|
||||
"serialized value may not be as expected"
|
||||
"serialized value may not be as expected",
|
||||
"Mixing V1 models and V2 models",
|
||||
"Please upgrade `Settings` to V2"
|
||||
]
|
||||
|
||||
@functools.wraps(_original_warn)
|
||||
|
||||
@@ -1538,13 +1538,13 @@ Your Goal: {self.goal}"""
|
||||
logging.debug(f"{self.name} executing tool {function_name} with arguments: {arguments}")
|
||||
|
||||
# Check if approval is required for this tool
|
||||
from ..approval import is_approval_required, console_approval_callback, get_risk_level, mark_approved, ApprovalDecision
|
||||
from ..approval import is_approval_required, console_approval_callback, get_risk_level, mark_approved, ApprovalDecision, get_approval_callback
|
||||
if is_approval_required(function_name):
|
||||
risk_level = get_risk_level(function_name)
|
||||
logging.info(f"Tool {function_name} requires approval (risk level: {risk_level})")
|
||||
logging.debug(f"Tool {function_name} requires approval (risk level: {risk_level})")
|
||||
|
||||
# Use global approval callback or default console callback
|
||||
callback = approval_callback or console_approval_callback
|
||||
callback = get_approval_callback() or console_approval_callback
|
||||
|
||||
try:
|
||||
decision = callback(function_name, arguments, risk_level)
|
||||
|
||||
@@ -43,6 +43,15 @@ def set_approval_callback(callback_fn: Callable):
|
||||
global approval_callback
|
||||
approval_callback = callback_fn
|
||||
|
||||
def get_approval_callback() -> Optional[Callable]:
|
||||
"""Get the current approval callback function.
|
||||
|
||||
Returns the custom callback if set, otherwise None.
|
||||
This should be used instead of directly accessing approval_callback
|
||||
to ensure the latest callback is always used.
|
||||
"""
|
||||
return approval_callback
|
||||
|
||||
def mark_approved(tool_name: str):
|
||||
"""Mark a tool as approved in the current context."""
|
||||
approved = _approved_context.get(set())
|
||||
@@ -90,7 +99,7 @@ def require_approval(risk_level: RiskLevel = "high"):
|
||||
except Exception as e:
|
||||
# Fallback to sync approval if async fails
|
||||
logging.warning(f"Async approval failed, using sync fallback: {e}")
|
||||
callback = approval_callback or console_approval_callback
|
||||
callback = get_approval_callback() or console_approval_callback
|
||||
decision = callback(tool_name, kwargs, risk_level)
|
||||
|
||||
if not decision.approved:
|
||||
@@ -198,7 +207,7 @@ async def request_approval(function_name: str, arguments: Dict[str, Any]) -> App
|
||||
risk_level = TOOL_RISK_LEVELS.get(function_name, "medium")
|
||||
|
||||
# Use custom callback if set, otherwise use console callback
|
||||
callback = approval_callback or console_approval_callback
|
||||
callback = get_approval_callback() or console_approval_callback
|
||||
|
||||
try:
|
||||
# Handle async callbacks
|
||||
|
||||
@@ -1054,7 +1054,7 @@ class LLM:
|
||||
**kwargs
|
||||
) -> str:
|
||||
"""Enhanced get_response with all OpenAI-like features"""
|
||||
logging.info(f"Getting response from {self.model}")
|
||||
logging.debug(f"Getting response from {self.model}")
|
||||
# Log all self values when in debug mode
|
||||
self._log_llm_config(
|
||||
'LLM instance',
|
||||
@@ -2472,7 +2472,7 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
|
||||
"""Async version of get_response with identical functionality."""
|
||||
try:
|
||||
import litellm
|
||||
logging.info(f"Getting async response from {self.model}")
|
||||
logging.debug(f"Getting async response from {self.model}")
|
||||
# Log all self values when in debug mode
|
||||
self._log_llm_config(
|
||||
'get_response_async',
|
||||
|
||||
@@ -19,6 +19,15 @@ from rich.console import Console
|
||||
from rich.live import Live
|
||||
import inspect
|
||||
|
||||
# Import display_tool_call for callback support (lazy import to avoid circular imports)
|
||||
_display_tool_call = None
|
||||
def _get_display_tool_call():
|
||||
global _display_tool_call
|
||||
if _display_tool_call is None:
|
||||
from ..main import display_tool_call
|
||||
_display_tool_call = display_tool_call
|
||||
return _display_tool_call
|
||||
|
||||
# Constants
|
||||
LOCAL_SERVER_API_KEY_PLACEHOLDER = "not-needed"
|
||||
|
||||
@@ -978,16 +987,19 @@ class OpenAIClient:
|
||||
function_name = tool_call.function.name
|
||||
arguments = json.loads(tool_call.function.arguments)
|
||||
|
||||
# Always trigger callback for tool call tracking (even when verbose=False)
|
||||
display_tool_call_fn = _get_display_tool_call()
|
||||
display_tool_call_fn(f"Calling function: {function_name}", console=console if verbose else None)
|
||||
|
||||
if verbose and console:
|
||||
console.print(f"[bold]Calling function:[/bold] {function_name}")
|
||||
console.print(f"[dim]Arguments:[/dim] {arguments}")
|
||||
|
||||
# Execute the tool
|
||||
tool_result = execute_tool_fn(function_name, arguments)
|
||||
results_str = json.dumps(tool_result) if tool_result else "Function returned an empty output"
|
||||
|
||||
if verbose and console:
|
||||
console.print(f"[dim]Result:[/dim] {results_str}")
|
||||
# Trigger callback with result
|
||||
display_tool_call_fn(f"Function {function_name} returned: {results_str[:200]}{'...' if len(results_str) > 200 else ''}", console=console if verbose else None)
|
||||
|
||||
messages.append({
|
||||
"role": "tool",
|
||||
@@ -1150,8 +1162,11 @@ class OpenAIClient:
|
||||
function_name = tool_call.function.name
|
||||
arguments = json.loads(tool_call.function.arguments)
|
||||
|
||||
# Always trigger callback for tool call tracking (even when verbose=False)
|
||||
display_tool_call_fn = _get_display_tool_call()
|
||||
display_tool_call_fn(f"Calling function: {function_name}", console=console if verbose else None)
|
||||
|
||||
if verbose and console:
|
||||
console.print(f"[bold]Calling function:[/bold] {function_name}")
|
||||
console.print(f"[dim]Arguments:[/dim] {arguments}")
|
||||
|
||||
# Execute the tool (async)
|
||||
@@ -1167,8 +1182,8 @@ class OpenAIClient:
|
||||
|
||||
results_str = json.dumps(tool_result) if tool_result else "Function returned an empty output"
|
||||
|
||||
if verbose and console:
|
||||
console.print(f"[dim]Result:[/dim] {results_str}")
|
||||
# Trigger callback with result
|
||||
display_tool_call_fn(f"Function {function_name} returned: {results_str[:200]}{'...' if len(results_str) > 200 else ''}", console=console if verbose else None)
|
||||
|
||||
messages.append({
|
||||
"role": "tool",
|
||||
@@ -1299,6 +1314,10 @@ class OpenAIClient:
|
||||
yield f"\n[Error parsing arguments for {function_name if 'function_name' in locals() else 'unknown function'}: {str(e)}]"
|
||||
continue
|
||||
|
||||
# Always trigger callback for tool call tracking (even when verbose=False)
|
||||
display_tool_call_fn = _get_display_tool_call()
|
||||
display_tool_call_fn(f"Calling function: {function_name}", console=None)
|
||||
|
||||
if verbose:
|
||||
yield f"\n[Calling function: {function_name}]"
|
||||
|
||||
@@ -1311,6 +1330,9 @@ class OpenAIClient:
|
||||
if verbose:
|
||||
yield f"\n[Function error: {str(e)}]"
|
||||
|
||||
# Trigger callback with result
|
||||
display_tool_call_fn(f"Function {function_name} returned: {results_str[:200]}{'...' if len(results_str) > 200 else ''}", console=None)
|
||||
|
||||
if verbose:
|
||||
yield f"\n[Function result: {results_str}]"
|
||||
|
||||
|
||||
@@ -231,15 +231,15 @@ def display_tool_call(message: str, console=None):
|
||||
if not message or not message.strip():
|
||||
logging.debug("Empty message in display_tool_call, returning early")
|
||||
return
|
||||
if console is None:
|
||||
console = Console()
|
||||
message = _clean_display_content(str(message))
|
||||
logging.debug(f"Cleaned message in display_tool_call: {repr(message)}")
|
||||
|
||||
# Execute synchronous callbacks
|
||||
# Execute synchronous callbacks (always, even when console is None)
|
||||
execute_sync_callback('tool_call', message=message)
|
||||
|
||||
console.print(Panel.fit(Text(message, style="bold cyan"), title="Tool Call", border_style="green"))
|
||||
# Only print panel if console is provided (verbose mode)
|
||||
if console is not None:
|
||||
console.print(Panel.fit(Text(message, style="bold cyan"), title="Tool Call", border_style="green"))
|
||||
|
||||
def display_error(message: str, console=None):
|
||||
if not message or not message.strip():
|
||||
|
||||
@@ -218,6 +218,10 @@ TOOL_MAPPINGS = {
|
||||
'crawl4ai_extract_sync': ('.crawl4ai_tools', None),
|
||||
'Crawl4AITools': ('.crawl4ai_tools', 'Crawl4AITools'),
|
||||
'crawl4ai_tools': ('.crawl4ai_tools', None),
|
||||
|
||||
# Unified Web Search (auto-fallback across providers)
|
||||
'search_web': ('.web_search', None),
|
||||
'get_available_providers': ('.web_search', None),
|
||||
}
|
||||
|
||||
_instances = {} # Cache for class instances
|
||||
@@ -254,7 +258,8 @@ def __getattr__(name: str) -> Any:
|
||||
'exa', 'exa_search', 'exa_search_contents', 'exa_find_similar', 'exa_answer',
|
||||
'exa_search_async', 'exa_search_contents_async', 'exa_answer_async',
|
||||
'crawl4ai', 'crawl4ai_many', 'crawl4ai_extract', 'crawl4ai_llm_extract',
|
||||
'crawl4ai_sync', 'crawl4ai_extract_sync'
|
||||
'crawl4ai_sync', 'crawl4ai_extract_sync',
|
||||
'search_web', 'get_available_providers'
|
||||
]:
|
||||
return getattr(module, name)
|
||||
if name in ['file_tools', 'pandas_tools', 'wikipedia_tools',
|
||||
|
||||
@@ -14,6 +14,7 @@ Usage:
|
||||
context, cleaned_prompt = parser.process("@file:main.py explain this code")
|
||||
"""
|
||||
|
||||
import os
|
||||
import re
|
||||
import logging
|
||||
from pathlib import Path
|
||||
@@ -43,10 +44,14 @@ class MentionsParser:
|
||||
"url": re.compile(r'@url:(https?://[^\s]+)'),
|
||||
}
|
||||
|
||||
# Default max file chars: 500K (~125K tokens) - fits GPT-4o (128K), Claude 3.5 (200K)
|
||||
DEFAULT_MAX_FILE_CHARS = 500000
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
workspace_path: Optional[str] = None,
|
||||
verbose: int = 0
|
||||
verbose: int = 0,
|
||||
max_file_chars: Optional[int] = None
|
||||
):
|
||||
"""
|
||||
Initialize MentionsParser.
|
||||
@@ -54,10 +59,24 @@ class MentionsParser:
|
||||
Args:
|
||||
workspace_path: Path to workspace/project root
|
||||
verbose: Verbosity level
|
||||
max_file_chars: Maximum characters to include from files.
|
||||
Default: 500000 (500K chars, ~125K tokens).
|
||||
Set to 0 for no limit.
|
||||
Can be overridden via PRAISON_MAX_FILE_CHARS env var.
|
||||
"""
|
||||
self.workspace_path = Path(workspace_path) if workspace_path else Path.cwd()
|
||||
self.verbose = verbose
|
||||
|
||||
# Configure max file chars: constructor > env var > default
|
||||
if max_file_chars is not None:
|
||||
self.max_file_chars = max_file_chars
|
||||
else:
|
||||
env_val = os.environ.get('PRAISON_MAX_FILE_CHARS')
|
||||
if env_val is not None:
|
||||
self.max_file_chars = int(env_val)
|
||||
else:
|
||||
self.max_file_chars = self.DEFAULT_MAX_FILE_CHARS
|
||||
|
||||
# Lazy-loaded managers
|
||||
self._docs_manager = None
|
||||
self._rules_manager = None
|
||||
@@ -158,9 +177,15 @@ class MentionsParser:
|
||||
|
||||
content = full_path.read_text(encoding="utf-8")
|
||||
|
||||
# Limit content size
|
||||
if len(content) > 50000:
|
||||
content = content[:50000] + "\n... (truncated)"
|
||||
# Limit content size (0 means no limit)
|
||||
if self.max_file_chars > 0 and len(content) > self.max_file_chars:
|
||||
original_size = len(content)
|
||||
content = content[:self.max_file_chars] + "\n... (truncated)"
|
||||
self._log(
|
||||
f"File {file_path} truncated from {original_size:,} to {self.max_file_chars:,} chars. "
|
||||
f"Set PRAISON_MAX_FILE_CHARS=0 for no limit.",
|
||||
logging.WARNING
|
||||
)
|
||||
|
||||
# Detect language for code fence
|
||||
ext = full_path.suffix.lower()
|
||||
@@ -253,9 +278,9 @@ class MentionsParser:
|
||||
with urllib.request.urlopen(req, timeout=10) as response:
|
||||
content = response.read().decode('utf-8', errors='ignore')
|
||||
|
||||
# Limit content size
|
||||
if len(content) > 50000:
|
||||
content = content[:50000] + "\n... (truncated)"
|
||||
# Limit content size (0 means no limit)
|
||||
if self.max_file_chars > 0 and len(content) > self.max_file_chars:
|
||||
content = content[:self.max_file_chars] + "\n... (truncated)"
|
||||
|
||||
# Try to extract text from HTML
|
||||
if '<html' in content.lower():
|
||||
|
||||
@@ -0,0 +1,329 @@
|
||||
"""Unified web search tool with automatic fallback across multiple providers.
|
||||
|
||||
This module provides a single `search_web` function that automatically tries
|
||||
multiple search providers in order, falling back to the next if one fails.
|
||||
|
||||
Search Provider Priority:
|
||||
1. Tavily (requires TAVILY_API_KEY + tavily-python)
|
||||
2. Exa (requires EXA_API_KEY + exa_py)
|
||||
3. You.com (requires YDC_API_KEY + youdotcom)
|
||||
4. DuckDuckGo (requires duckduckgo_search package, no API key)
|
||||
5. SearxNG (requires requests + running SearxNG instance)
|
||||
|
||||
Usage:
|
||||
from praisonaiagents.tools import search_web
|
||||
|
||||
# Simple search - automatically uses best available provider
|
||||
results = search_web("AI news 2024")
|
||||
|
||||
# With max results
|
||||
results = search_web("Python tutorials", max_results=10)
|
||||
"""
|
||||
|
||||
from typing import List, Dict, Any, Optional
|
||||
import logging
|
||||
import os
|
||||
from importlib import util
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def _check_tavily() -> tuple[bool, Optional[str]]:
|
||||
"""Check if Tavily is available."""
|
||||
if util.find_spec("tavily") is None:
|
||||
return False, "tavily-python package not installed"
|
||||
if not os.environ.get("TAVILY_API_KEY"):
|
||||
return False, "TAVILY_API_KEY not set"
|
||||
return True, None
|
||||
|
||||
|
||||
def _check_exa() -> tuple[bool, Optional[str]]:
|
||||
"""Check if Exa is available."""
|
||||
if util.find_spec("exa_py") is None:
|
||||
return False, "exa_py package not installed"
|
||||
if not os.environ.get("EXA_API_KEY"):
|
||||
return False, "EXA_API_KEY not set"
|
||||
return True, None
|
||||
|
||||
|
||||
def _check_youdotcom() -> tuple[bool, Optional[str]]:
|
||||
"""Check if You.com is available."""
|
||||
if util.find_spec("youdotcom") is None:
|
||||
return False, "youdotcom package not installed"
|
||||
if not os.environ.get("YDC_API_KEY"):
|
||||
return False, "YDC_API_KEY not set"
|
||||
return True, None
|
||||
|
||||
|
||||
def _check_duckduckgo() -> tuple[bool, Optional[str]]:
|
||||
"""Check if DuckDuckGo is available."""
|
||||
if util.find_spec("duckduckgo_search") is None:
|
||||
return False, "duckduckgo_search package not installed"
|
||||
return True, None
|
||||
|
||||
|
||||
def _check_searxng() -> tuple[bool, Optional[str]]:
|
||||
"""Check if SearxNG is available."""
|
||||
if util.find_spec("requests") is None:
|
||||
return False, "requests package not installed"
|
||||
return True, None
|
||||
|
||||
|
||||
def _search_tavily(query: str, max_results: int = 5) -> List[Dict[str, Any]]:
|
||||
"""Search using Tavily."""
|
||||
from tavily import TavilyClient
|
||||
|
||||
client = TavilyClient(api_key=os.environ.get("TAVILY_API_KEY"))
|
||||
response = client.search(query=query, max_results=max_results)
|
||||
|
||||
results = []
|
||||
for r in response.get("results", []):
|
||||
results.append({
|
||||
"title": r.get("title", ""),
|
||||
"url": r.get("url", ""),
|
||||
"snippet": r.get("content", ""),
|
||||
"provider": "tavily"
|
||||
})
|
||||
return results
|
||||
|
||||
|
||||
def _search_exa(query: str, max_results: int = 5) -> List[Dict[str, Any]]:
|
||||
"""Search using Exa."""
|
||||
from exa_py import Exa
|
||||
|
||||
client = Exa(os.environ.get("EXA_API_KEY"))
|
||||
response = client.search(query=query, num_results=max_results)
|
||||
|
||||
results = []
|
||||
for r in response.results:
|
||||
results.append({
|
||||
"title": getattr(r, "title", "") or "",
|
||||
"url": r.url,
|
||||
"snippet": getattr(r, "text", "") or "",
|
||||
"provider": "exa"
|
||||
})
|
||||
return results
|
||||
|
||||
|
||||
def _search_youdotcom(query: str, max_results: int = 5) -> List[Dict[str, Any]]:
|
||||
"""Search using You.com."""
|
||||
from youdotcom import You
|
||||
|
||||
client = You(api_key_auth=os.environ.get("YDC_API_KEY"))
|
||||
response = client.search.unified(query=query, count=max_results)
|
||||
|
||||
results = []
|
||||
# Handle response object
|
||||
if hasattr(response, 'results'):
|
||||
web_results = getattr(response.results, 'web', []) or []
|
||||
for r in web_results[:max_results]:
|
||||
results.append({
|
||||
"title": getattr(r, "title", "") or "",
|
||||
"url": getattr(r, "url", "") or "",
|
||||
"snippet": getattr(r, "description", "") or "",
|
||||
"provider": "youdotcom"
|
||||
})
|
||||
elif isinstance(response, dict):
|
||||
web_results = response.get("results", {}).get("web", [])
|
||||
for r in web_results[:max_results]:
|
||||
results.append({
|
||||
"title": r.get("title", ""),
|
||||
"url": r.get("url", ""),
|
||||
"snippet": r.get("description", ""),
|
||||
"provider": "youdotcom"
|
||||
})
|
||||
return results
|
||||
|
||||
|
||||
def _search_duckduckgo(query: str, max_results: int = 5) -> List[Dict[str, Any]]:
|
||||
"""Search using DuckDuckGo."""
|
||||
from duckduckgo_search import DDGS
|
||||
|
||||
results = []
|
||||
ddgs = DDGS()
|
||||
for result in ddgs.text(keywords=query, max_results=max_results):
|
||||
results.append({
|
||||
"title": result.get("title", ""),
|
||||
"url": result.get("href", ""),
|
||||
"snippet": result.get("body", ""),
|
||||
"provider": "duckduckgo"
|
||||
})
|
||||
return results
|
||||
|
||||
|
||||
def _search_searxng(query: str, max_results: int = 5, searxng_url: Optional[str] = None) -> List[Dict[str, Any]]:
|
||||
"""Search using SearxNG."""
|
||||
import requests
|
||||
|
||||
url = searxng_url or os.environ.get("SEARXNG_URL", "http://localhost:32768/search")
|
||||
|
||||
params = {
|
||||
'q': query,
|
||||
'format': 'json',
|
||||
'engines': 'google,bing,duckduckgo',
|
||||
'safesearch': '1'
|
||||
}
|
||||
|
||||
response = requests.get(url, params=params, timeout=10)
|
||||
response.raise_for_status()
|
||||
|
||||
raw_results = response.json().get('results', [])
|
||||
|
||||
results = []
|
||||
for result in raw_results[:max_results]:
|
||||
results.append({
|
||||
"title": result.get("title", ""),
|
||||
"url": result.get("url", ""),
|
||||
"snippet": result.get("content", ""),
|
||||
"provider": "searxng"
|
||||
})
|
||||
return results
|
||||
|
||||
|
||||
# Provider configuration: (name, check_func, search_func)
|
||||
SEARCH_PROVIDERS = [
|
||||
("tavily", _check_tavily, _search_tavily),
|
||||
("exa", _check_exa, _search_exa),
|
||||
("youdotcom", _check_youdotcom, _search_youdotcom),
|
||||
("duckduckgo", _check_duckduckgo, _search_duckduckgo),
|
||||
("searxng", _check_searxng, _search_searxng),
|
||||
]
|
||||
|
||||
|
||||
def search_web(
|
||||
query: str,
|
||||
max_results: int = 5,
|
||||
providers: Optional[List[str]] = None,
|
||||
searxng_url: Optional[str] = None,
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Search the web using multiple providers with automatic fallback.
|
||||
|
||||
Tries each search provider in order until one succeeds. For each provider,
|
||||
it first checks if the API key is set (if required) and if the package is
|
||||
installed, then attempts the search. If the search fails, it moves to the
|
||||
next provider.
|
||||
|
||||
Args:
|
||||
query: The search query string
|
||||
max_results: Maximum number of results to return (default: 5)
|
||||
providers: Optional list of provider names to try, in order.
|
||||
If not specified, uses default order:
|
||||
["tavily", "exa", "youdotcom", "duckduckgo", "searxng"]
|
||||
searxng_url: Optional custom SearxNG instance URL
|
||||
|
||||
Returns:
|
||||
List of search results, each containing:
|
||||
- title: Result title
|
||||
- url: Result URL
|
||||
- snippet: Result description/snippet
|
||||
- provider: Name of the provider that returned the result
|
||||
|
||||
If all providers fail, returns a list with a single error dict.
|
||||
|
||||
Example:
|
||||
# Use default provider order
|
||||
results = search_web("AI news 2024")
|
||||
|
||||
# Specify providers to try
|
||||
results = search_web("Python tutorials", providers=["duckduckgo", "tavily"])
|
||||
|
||||
# With custom SearxNG URL
|
||||
results = search_web("tech news", searxng_url="http://my-searxng:8080/search")
|
||||
"""
|
||||
errors = []
|
||||
|
||||
# Determine which providers to try
|
||||
if providers:
|
||||
# Filter to only valid provider names
|
||||
provider_order = []
|
||||
for name in providers:
|
||||
for pname, check_fn, search_fn in SEARCH_PROVIDERS:
|
||||
if pname == name.lower():
|
||||
provider_order.append((pname, check_fn, search_fn))
|
||||
break
|
||||
else:
|
||||
provider_order = SEARCH_PROVIDERS
|
||||
|
||||
for provider_name, check_func, search_func in provider_order:
|
||||
# Step 1: Check if provider is available (API key + package)
|
||||
is_available, check_error = check_func()
|
||||
if not is_available:
|
||||
logger.debug(f"Skipping {provider_name}: {check_error}")
|
||||
errors.append(f"{provider_name}: {check_error}")
|
||||
continue
|
||||
|
||||
# Step 2: Try to search
|
||||
try:
|
||||
logger.debug(f"Trying {provider_name} for query: {query}")
|
||||
|
||||
if provider_name == "searxng":
|
||||
results = search_func(query, max_results, searxng_url)
|
||||
else:
|
||||
results = search_func(query, max_results)
|
||||
|
||||
if results:
|
||||
logger.info(f"search_web: Successfully used {provider_name}")
|
||||
return results
|
||||
else:
|
||||
errors.append(f"{provider_name}: No results returned")
|
||||
|
||||
except Exception as e:
|
||||
error_msg = f"{provider_name}: {str(e)}"
|
||||
logger.debug(f"Search failed with {provider_name}: {e}")
|
||||
errors.append(error_msg)
|
||||
continue
|
||||
|
||||
# All providers failed
|
||||
error_summary = "; ".join(errors) if errors else "No search providers available"
|
||||
logger.error(f"search_web: All providers failed - {error_summary}")
|
||||
return [{"error": f"All search providers failed: {error_summary}"}]
|
||||
|
||||
|
||||
def get_available_providers() -> List[Dict[str, Any]]:
|
||||
"""Get list of available search providers and their status.
|
||||
|
||||
Returns:
|
||||
List of dicts with provider info:
|
||||
- name: Provider name
|
||||
- available: Whether the provider is ready to use
|
||||
- reason: Reason if not available
|
||||
|
||||
Example:
|
||||
providers = get_available_providers()
|
||||
for p in providers:
|
||||
print(f"{p['name']}: {'✓' if p['available'] else '✗'} {p.get('reason', '')}")
|
||||
"""
|
||||
result = []
|
||||
for name, check_func, _ in SEARCH_PROVIDERS:
|
||||
is_available, error = check_func()
|
||||
result.append({
|
||||
"name": name,
|
||||
"available": is_available,
|
||||
"reason": error if not is_available else None
|
||||
})
|
||||
return result
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Example usage and provider status check
|
||||
print("=" * 60)
|
||||
print("Web Search Tool - Provider Status")
|
||||
print("=" * 60)
|
||||
|
||||
providers = get_available_providers()
|
||||
for p in providers:
|
||||
status = "✓ Available" if p["available"] else f"✗ {p['reason']}"
|
||||
print(f" {p['name']:12} {status}")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Testing search_web...")
|
||||
print("=" * 60)
|
||||
|
||||
results = search_web("Python programming", max_results=3)
|
||||
if results and "error" not in results[0]:
|
||||
print(f"\nFound {len(results)} results using {results[0].get('provider', 'unknown')}:")
|
||||
for r in results:
|
||||
print(f"\n Title: {r.get('title', 'N/A')[:50]}...")
|
||||
print(f" URL: {r.get('url', 'N/A')}")
|
||||
else:
|
||||
print(f"\nSearch failed: {results}")
|
||||
@@ -0,0 +1,13 @@
|
||||
"""
|
||||
UI Integrations for PraisonAI Agents
|
||||
|
||||
This module provides UI protocol integrations for exposing PraisonAI Agents
|
||||
via various frontend protocols.
|
||||
|
||||
Available integrations:
|
||||
- agui: AG-UI (Agent-User Interface) protocol for CopilotKit and compatible frontends
|
||||
"""
|
||||
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
|
||||
__all__ = ["AGUI"]
|
||||
@@ -0,0 +1,74 @@
|
||||
"""
|
||||
A2A Protocol Integration for PraisonAI Agents
|
||||
|
||||
This module provides A2A (Agent2Agent) protocol support,
|
||||
enabling PraisonAI Agents to be exposed as A2A Servers
|
||||
for agent-to-agent communication.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Assistant", role="Helper", goal="Help users")
|
||||
a2a = A2A(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
# Agent Card available at: GET /.well-known/agent.json
|
||||
# A2A endpoint at: POST /a2a (JSON-RPC)
|
||||
"""
|
||||
|
||||
from praisonaiagents.ui.a2a.a2a import A2A
|
||||
from praisonaiagents.ui.a2a.types import (
|
||||
# Enums
|
||||
TaskState,
|
||||
Role,
|
||||
# Part types
|
||||
TextPart,
|
||||
FilePart,
|
||||
DataPart,
|
||||
# Core types
|
||||
Message,
|
||||
TaskStatus,
|
||||
Task,
|
||||
Artifact,
|
||||
# Agent Card types
|
||||
AgentSkill,
|
||||
AgentCapabilities,
|
||||
AgentCard,
|
||||
# Request/Response types
|
||||
MessageConfig,
|
||||
SendMessageRequest,
|
||||
# Streaming events
|
||||
TaskStatusUpdateEvent,
|
||||
TaskArtifactUpdateEvent,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
# Main class
|
||||
"A2A",
|
||||
# Enums
|
||||
"TaskState",
|
||||
"Role",
|
||||
# Part types
|
||||
"TextPart",
|
||||
"FilePart",
|
||||
"DataPart",
|
||||
# Core types
|
||||
"Message",
|
||||
"TaskStatus",
|
||||
"Task",
|
||||
"Artifact",
|
||||
# Agent Card types
|
||||
"AgentSkill",
|
||||
"AgentCapabilities",
|
||||
"AgentCard",
|
||||
# Request/Response types
|
||||
"MessageConfig",
|
||||
"SendMessageRequest",
|
||||
# Streaming events
|
||||
"TaskStatusUpdateEvent",
|
||||
"TaskArtifactUpdateEvent",
|
||||
]
|
||||
@@ -0,0 +1,154 @@
|
||||
"""
|
||||
A2A - Main A2A Interface Class
|
||||
|
||||
Exposes PraisonAI Agents via the A2A (Agent2Agent) protocol.
|
||||
"""
|
||||
|
||||
import logging
|
||||
from typing import List, Optional, TYPE_CHECKING
|
||||
|
||||
from praisonaiagents.ui.a2a.types import AgentCard
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from praisonaiagents import Agent, PraisonAIAgents
|
||||
from fastapi import APIRouter
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class A2A:
|
||||
"""
|
||||
A2A Interface for PraisonAI Agents.
|
||||
|
||||
Exposes a PraisonAI Agent or PraisonAIAgents workflow via the A2A protocol,
|
||||
enabling agent-to-agent communication with other A2A-compatible systems.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Assistant", role="Helper", goal="Help users")
|
||||
a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
# Agent Card at: GET /.well-known/agent.json
|
||||
# A2A endpoint at: POST /a2a
|
||||
|
||||
Args:
|
||||
agent: Single PraisonAI Agent instance
|
||||
agents: PraisonAIAgents instance for multi-agent workflows
|
||||
name: Name for the A2A endpoint (defaults to agent name)
|
||||
description: Description of the agent
|
||||
url: URL where the A2A endpoint is hosted
|
||||
version: Version string for the agent
|
||||
prefix: URL prefix for the router
|
||||
tags: OpenAPI tags for the router
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
agent: Optional["Agent"] = None,
|
||||
agents: Optional["PraisonAIAgents"] = None,
|
||||
name: Optional[str] = None,
|
||||
description: Optional[str] = None,
|
||||
url: str = "http://localhost:8000/a2a",
|
||||
version: str = "1.0.0",
|
||||
prefix: str = "",
|
||||
tags: Optional[List[str]] = None,
|
||||
):
|
||||
if agent is None and agents is None:
|
||||
raise ValueError("A2A requires an agent or agents instance")
|
||||
|
||||
self.agent = agent
|
||||
self.agents = agents
|
||||
self.url = url
|
||||
self.version = version
|
||||
self.prefix = prefix
|
||||
self.tags = tags or ["A2A"]
|
||||
|
||||
# Set name from agent if not provided
|
||||
if name:
|
||||
self.name = name
|
||||
elif agent and hasattr(agent, 'name'):
|
||||
self.name = agent.name
|
||||
elif agents and hasattr(agents, 'name'):
|
||||
self.name = agents.name
|
||||
else:
|
||||
self.name = "PraisonAI Agent"
|
||||
|
||||
# Set description
|
||||
if description:
|
||||
self.description = description
|
||||
elif agent and hasattr(agent, 'role'):
|
||||
self.description = agent.role
|
||||
else:
|
||||
self.description = "PraisonAI Agent via A2A"
|
||||
|
||||
# Initialize task store
|
||||
self.task_store = TaskStore()
|
||||
|
||||
# Router cache
|
||||
self._router: Optional["APIRouter"] = None
|
||||
self._agent_card: Optional[AgentCard] = None
|
||||
|
||||
def get_agent_card(self) -> AgentCard:
|
||||
"""
|
||||
Get the Agent Card for this A2A instance.
|
||||
|
||||
Returns:
|
||||
AgentCard object for A2A discovery
|
||||
"""
|
||||
if self._agent_card is None:
|
||||
self._agent_card = generate_agent_card(
|
||||
agent=self.agent,
|
||||
url=self.url,
|
||||
version=self.version,
|
||||
streaming=True,
|
||||
)
|
||||
return self._agent_card
|
||||
|
||||
def get_router(self) -> "APIRouter":
|
||||
"""
|
||||
Get the FastAPI router for this A2A instance.
|
||||
|
||||
Returns:
|
||||
FastAPI APIRouter with A2A endpoints
|
||||
"""
|
||||
if self._router is None:
|
||||
self._router = self._create_router()
|
||||
return self._router
|
||||
|
||||
def _create_router(self) -> "APIRouter":
|
||||
"""Create FastAPI router with A2A endpoints."""
|
||||
from fastapi import APIRouter
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
router = APIRouter(prefix=self.prefix, tags=self.tags)
|
||||
|
||||
# Agent Card endpoint (well-known URI)
|
||||
@router.get("/.well-known/agent.json")
|
||||
async def get_agent_card():
|
||||
"""Return the Agent Card for discovery."""
|
||||
card = self.get_agent_card()
|
||||
return JSONResponse(content=card.model_dump(by_alias=True, exclude_none=True))
|
||||
|
||||
# Status endpoint
|
||||
@router.get("/status")
|
||||
async def get_status():
|
||||
"""Return server status."""
|
||||
return {
|
||||
"status": "ok",
|
||||
"name": self.name,
|
||||
"version": self.version,
|
||||
}
|
||||
|
||||
# TODO: Add JSON-RPC endpoint for message/send
|
||||
# TODO: Add streaming endpoint for message/stream
|
||||
# TODO: Add task management endpoints
|
||||
|
||||
return router
|
||||
@@ -0,0 +1,123 @@
|
||||
"""
|
||||
A2A Agent Card Generation
|
||||
|
||||
Generate Agent Cards from PraisonAI Agents for A2A discovery.
|
||||
"""
|
||||
|
||||
import inspect
|
||||
from typing import TYPE_CHECKING, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2a.types import (
|
||||
AgentCard,
|
||||
AgentCapabilities,
|
||||
AgentSkill,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from praisonaiagents import Agent
|
||||
|
||||
|
||||
def extract_skills_from_tools(tools: Optional[List]) -> List[AgentSkill]:
|
||||
"""
|
||||
Extract AgentSkill objects from a list of tools.
|
||||
|
||||
Args:
|
||||
tools: List of tool functions or objects
|
||||
|
||||
Returns:
|
||||
List of AgentSkill objects
|
||||
"""
|
||||
if not tools:
|
||||
return []
|
||||
|
||||
skills = []
|
||||
|
||||
for tool in tools:
|
||||
# Skip non-callable items
|
||||
if not callable(tool):
|
||||
continue
|
||||
|
||||
# Get function name
|
||||
name = getattr(tool, '__name__', None)
|
||||
if not name:
|
||||
continue
|
||||
|
||||
# Get description from docstring
|
||||
docstring = inspect.getdoc(tool)
|
||||
description = docstring.split('\n')[0] if docstring else f"Tool: {name}"
|
||||
|
||||
# Create skill
|
||||
skill = AgentSkill(
|
||||
id=name,
|
||||
name=name,
|
||||
description=description,
|
||||
tags=["tool"],
|
||||
)
|
||||
skills.append(skill)
|
||||
|
||||
return skills
|
||||
|
||||
|
||||
def generate_agent_card(
|
||||
agent: "Agent",
|
||||
url: str,
|
||||
version: str = "1.0.0",
|
||||
streaming: bool = False,
|
||||
push_notifications: bool = False,
|
||||
) -> AgentCard:
|
||||
"""
|
||||
Generate an A2A Agent Card from a PraisonAI Agent.
|
||||
|
||||
Args:
|
||||
agent: PraisonAI Agent instance
|
||||
url: URL where the A2A endpoint is hosted
|
||||
version: Version string for the agent
|
||||
streaming: Whether streaming is supported
|
||||
push_notifications: Whether push notifications are supported
|
||||
|
||||
Returns:
|
||||
AgentCard object for A2A discovery
|
||||
"""
|
||||
# Get agent name
|
||||
name = getattr(agent, 'name', None) or "PraisonAI Agent"
|
||||
|
||||
# Build description from role, goal, or instructions
|
||||
description_parts = []
|
||||
|
||||
role = getattr(agent, 'role', None)
|
||||
if role:
|
||||
description_parts.append(role)
|
||||
|
||||
goal = getattr(agent, 'goal', None)
|
||||
if goal:
|
||||
description_parts.append(goal)
|
||||
|
||||
instructions = getattr(agent, 'instructions', None)
|
||||
if instructions and not description_parts:
|
||||
# Use first line of instructions if no role/goal
|
||||
description_parts.append(instructions.split('\n')[0][:200])
|
||||
|
||||
description = ". ".join(description_parts) if description_parts else "PraisonAI Agent"
|
||||
|
||||
# Extract skills from tools
|
||||
tools = getattr(agent, 'tools', None)
|
||||
skills = extract_skills_from_tools(tools)
|
||||
|
||||
# Build capabilities
|
||||
capabilities = AgentCapabilities(
|
||||
streaming=streaming,
|
||||
push_notifications=push_notifications,
|
||||
)
|
||||
|
||||
# Create Agent Card
|
||||
card = AgentCard(
|
||||
name=name,
|
||||
url=url,
|
||||
version=version,
|
||||
description=description,
|
||||
capabilities=capabilities,
|
||||
skills=skills if skills else None,
|
||||
provider={"name": "PraisonAI"},
|
||||
)
|
||||
|
||||
return card
|
||||
@@ -0,0 +1,131 @@
|
||||
"""
|
||||
A2A Message Conversion
|
||||
|
||||
Convert between A2A protocol messages and PraisonAI internal format.
|
||||
"""
|
||||
|
||||
import uuid
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2a.types import (
|
||||
Message,
|
||||
Role,
|
||||
TextPart,
|
||||
Artifact,
|
||||
)
|
||||
|
||||
|
||||
def a2a_to_praisonai_messages(messages: List[Message]) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Convert A2A messages to PraisonAI/OpenAI chat format.
|
||||
|
||||
Args:
|
||||
messages: List of A2A Message objects
|
||||
|
||||
Returns:
|
||||
List of dicts in OpenAI chat format {"role": ..., "content": ...}
|
||||
"""
|
||||
result = []
|
||||
|
||||
for msg in messages:
|
||||
# Map A2A role to OpenAI role
|
||||
role = "user" if msg.role == Role.USER else "assistant"
|
||||
|
||||
# Combine all text parts
|
||||
content_parts = []
|
||||
for part in msg.parts:
|
||||
if isinstance(part, TextPart):
|
||||
content_parts.append(part.text)
|
||||
elif hasattr(part, 'text'):
|
||||
content_parts.append(part.text)
|
||||
|
||||
content = " ".join(content_parts)
|
||||
|
||||
result.append({
|
||||
"role": role,
|
||||
"content": content,
|
||||
})
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def praisonai_to_a2a_message(
|
||||
response: str,
|
||||
message_id: Optional[str] = None,
|
||||
context_id: Optional[str] = None,
|
||||
task_id: Optional[str] = None,
|
||||
) -> Message:
|
||||
"""
|
||||
Convert PraisonAI response to A2A Message.
|
||||
|
||||
Args:
|
||||
response: Text response from agent
|
||||
message_id: Optional message ID (auto-generated if not provided)
|
||||
context_id: Optional context ID
|
||||
task_id: Optional task ID
|
||||
|
||||
Returns:
|
||||
A2A Message object
|
||||
"""
|
||||
msg_id = message_id or f"msg-{uuid.uuid4().hex[:12]}"
|
||||
|
||||
return Message(
|
||||
message_id=msg_id,
|
||||
role=Role.AGENT,
|
||||
parts=[TextPart(text=response)],
|
||||
context_id=context_id,
|
||||
task_id=task_id,
|
||||
)
|
||||
|
||||
|
||||
def create_artifact(
|
||||
content: str,
|
||||
artifact_id: Optional[str] = None,
|
||||
name: Optional[str] = None,
|
||||
description: Optional[str] = None,
|
||||
) -> Artifact:
|
||||
"""
|
||||
Create an A2A Artifact from response content.
|
||||
|
||||
Args:
|
||||
content: Text content for the artifact
|
||||
artifact_id: Optional artifact ID (auto-generated if not provided)
|
||||
name: Optional artifact name
|
||||
description: Optional artifact description
|
||||
|
||||
Returns:
|
||||
A2A Artifact object
|
||||
"""
|
||||
art_id = artifact_id or f"art-{uuid.uuid4().hex[:12]}"
|
||||
|
||||
return Artifact(
|
||||
artifact_id=art_id,
|
||||
name=name,
|
||||
description=description,
|
||||
parts=[TextPart(text=content)],
|
||||
)
|
||||
|
||||
|
||||
def extract_user_input(messages: List[Message]) -> str:
|
||||
"""
|
||||
Extract the last user input from a list of messages.
|
||||
|
||||
Args:
|
||||
messages: List of A2A Message objects
|
||||
|
||||
Returns:
|
||||
Text content of the last user message, or empty string if none
|
||||
"""
|
||||
# Find the last user message
|
||||
for msg in reversed(messages):
|
||||
if msg.role == Role.USER:
|
||||
# Combine text parts
|
||||
content_parts = []
|
||||
for part in msg.parts:
|
||||
if isinstance(part, TextPart):
|
||||
content_parts.append(part.text)
|
||||
elif hasattr(part, 'text'):
|
||||
content_parts.append(part.text)
|
||||
return " ".join(content_parts)
|
||||
|
||||
return ""
|
||||
@@ -0,0 +1,189 @@
|
||||
"""
|
||||
A2A Streaming Events
|
||||
|
||||
SSE streaming support for A2A task updates.
|
||||
"""
|
||||
|
||||
import json
|
||||
from typing import AsyncIterator, Optional
|
||||
|
||||
from praisonaiagents.ui.a2a.types import (
|
||||
Task,
|
||||
TaskState,
|
||||
TaskStatus,
|
||||
TaskStatusUpdateEvent,
|
||||
TaskArtifactUpdateEvent,
|
||||
Artifact,
|
||||
TextPart,
|
||||
)
|
||||
|
||||
|
||||
class A2AEventEncoder:
|
||||
"""Encode A2A events for SSE streaming."""
|
||||
|
||||
@staticmethod
|
||||
def encode_event(event_type: str, data: dict) -> str:
|
||||
"""
|
||||
Encode an event for SSE streaming.
|
||||
|
||||
Args:
|
||||
event_type: Type of event (e.g., "task.status", "task.artifact")
|
||||
data: Event data as dict
|
||||
|
||||
Returns:
|
||||
SSE-formatted string
|
||||
"""
|
||||
json_data = json.dumps(data, default=str)
|
||||
return f"event: {event_type}\ndata: {json_data}\n\n"
|
||||
|
||||
@staticmethod
|
||||
def encode_task_status(event: TaskStatusUpdateEvent) -> str:
|
||||
"""Encode TaskStatusUpdateEvent for SSE."""
|
||||
data = event.model_dump(by_alias=True, exclude_none=True)
|
||||
return A2AEventEncoder.encode_event("task.status", data)
|
||||
|
||||
@staticmethod
|
||||
def encode_task_artifact(event: TaskArtifactUpdateEvent) -> str:
|
||||
"""Encode TaskArtifactUpdateEvent for SSE."""
|
||||
data = event.model_dump(by_alias=True, exclude_none=True)
|
||||
return A2AEventEncoder.encode_event("task.artifact", data)
|
||||
|
||||
@staticmethod
|
||||
def encode_task(task: Task) -> str:
|
||||
"""Encode Task object for SSE."""
|
||||
data = task.model_dump(by_alias=True, exclude_none=True)
|
||||
return A2AEventEncoder.encode_event("task", data)
|
||||
|
||||
@staticmethod
|
||||
def encode_done() -> str:
|
||||
"""Encode stream completion event."""
|
||||
return "event: done\ndata: {}\n\n"
|
||||
|
||||
|
||||
def create_status_event(
|
||||
task_id: str,
|
||||
state: TaskState,
|
||||
context_id: Optional[str] = None,
|
||||
final: bool = False,
|
||||
) -> TaskStatusUpdateEvent:
|
||||
"""
|
||||
Create a TaskStatusUpdateEvent.
|
||||
|
||||
Args:
|
||||
task_id: Task ID
|
||||
state: New task state
|
||||
context_id: Optional context ID
|
||||
final: Whether this is the final event
|
||||
|
||||
Returns:
|
||||
TaskStatusUpdateEvent
|
||||
"""
|
||||
return TaskStatusUpdateEvent(
|
||||
task_id=task_id,
|
||||
context_id=context_id,
|
||||
status=TaskStatus(state=state),
|
||||
final=final,
|
||||
)
|
||||
|
||||
|
||||
def create_artifact_event(
|
||||
task_id: str,
|
||||
content: str,
|
||||
artifact_id: Optional[str] = None,
|
||||
context_id: Optional[str] = None,
|
||||
append: bool = False,
|
||||
last_chunk: bool = False,
|
||||
) -> TaskArtifactUpdateEvent:
|
||||
"""
|
||||
Create a TaskArtifactUpdateEvent.
|
||||
|
||||
Args:
|
||||
task_id: Task ID
|
||||
content: Artifact content
|
||||
artifact_id: Optional artifact ID
|
||||
context_id: Optional context ID
|
||||
append: Whether to append to existing artifact
|
||||
last_chunk: Whether this is the last chunk
|
||||
|
||||
Returns:
|
||||
TaskArtifactUpdateEvent
|
||||
"""
|
||||
import uuid
|
||||
art_id = artifact_id or f"art-{uuid.uuid4().hex[:12]}"
|
||||
|
||||
artifact = Artifact(
|
||||
artifact_id=art_id,
|
||||
parts=[TextPart(text=content)],
|
||||
)
|
||||
|
||||
return TaskArtifactUpdateEvent(
|
||||
task_id=task_id,
|
||||
context_id=context_id,
|
||||
artifact=artifact,
|
||||
append=append,
|
||||
last_chunk=last_chunk,
|
||||
)
|
||||
|
||||
|
||||
async def stream_agent_response(
|
||||
agent,
|
||||
user_input: str,
|
||||
task_id: str,
|
||||
context_id: Optional[str] = None,
|
||||
) -> AsyncIterator[str]:
|
||||
"""
|
||||
Stream agent response as A2A events.
|
||||
|
||||
Args:
|
||||
agent: PraisonAI Agent instance
|
||||
user_input: User input text
|
||||
task_id: Task ID
|
||||
context_id: Optional context ID
|
||||
|
||||
Yields:
|
||||
SSE-formatted event strings
|
||||
"""
|
||||
encoder = A2AEventEncoder()
|
||||
|
||||
# Emit working status
|
||||
working_event = create_status_event(
|
||||
task_id=task_id,
|
||||
state=TaskState.WORKING,
|
||||
context_id=context_id,
|
||||
)
|
||||
yield encoder.encode_task_status(working_event)
|
||||
|
||||
try:
|
||||
# Get response from agent
|
||||
response = agent.chat(user_input)
|
||||
|
||||
# Emit artifact with response
|
||||
artifact_event = create_artifact_event(
|
||||
task_id=task_id,
|
||||
content=str(response),
|
||||
context_id=context_id,
|
||||
last_chunk=True,
|
||||
)
|
||||
yield encoder.encode_task_artifact(artifact_event)
|
||||
|
||||
# Emit completed status
|
||||
completed_event = create_status_event(
|
||||
task_id=task_id,
|
||||
state=TaskState.COMPLETED,
|
||||
context_id=context_id,
|
||||
final=True,
|
||||
)
|
||||
yield encoder.encode_task_status(completed_event)
|
||||
|
||||
except Exception:
|
||||
# Emit failed status
|
||||
failed_event = create_status_event(
|
||||
task_id=task_id,
|
||||
state=TaskState.FAILED,
|
||||
context_id=context_id,
|
||||
final=True,
|
||||
)
|
||||
yield encoder.encode_task_status(failed_event)
|
||||
|
||||
# Emit done
|
||||
yield encoder.encode_done()
|
||||
@@ -0,0 +1,209 @@
|
||||
"""
|
||||
A2A Task Store
|
||||
|
||||
In-memory storage for A2A Task lifecycle management.
|
||||
"""
|
||||
|
||||
import uuid
|
||||
from datetime import datetime, timezone
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2a.types import (
|
||||
Task,
|
||||
TaskState,
|
||||
TaskStatus,
|
||||
Message,
|
||||
Artifact,
|
||||
)
|
||||
|
||||
|
||||
class TaskStore:
|
||||
"""
|
||||
In-memory store for A2A Tasks.
|
||||
|
||||
Manages task lifecycle including creation, status updates,
|
||||
artifact storage, and message history.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
"""Initialize empty task store."""
|
||||
self._tasks: Dict[str, Task] = {}
|
||||
|
||||
def create_task(self, message: Message, context_id: Optional[str] = None) -> Task:
|
||||
"""
|
||||
Create a new task from an incoming message.
|
||||
|
||||
Args:
|
||||
message: The initial message that triggers the task
|
||||
context_id: Optional context ID (uses message's context_id if not provided)
|
||||
|
||||
Returns:
|
||||
Newly created Task in SUBMITTED state
|
||||
"""
|
||||
task_id = f"task-{uuid.uuid4().hex[:12]}"
|
||||
ctx_id = context_id or message.context_id
|
||||
|
||||
# Create initial status
|
||||
status = TaskStatus(
|
||||
state=TaskState.SUBMITTED,
|
||||
timestamp=datetime.now(timezone.utc).isoformat(),
|
||||
)
|
||||
|
||||
# Create task with initial message in history
|
||||
task = Task(
|
||||
id=task_id,
|
||||
context_id=ctx_id,
|
||||
status=status,
|
||||
history=[message],
|
||||
artifacts=None,
|
||||
)
|
||||
|
||||
self._tasks[task_id] = task
|
||||
return task
|
||||
|
||||
def get_task(self, task_id: str) -> Optional[Task]:
|
||||
"""
|
||||
Retrieve a task by its ID.
|
||||
|
||||
Args:
|
||||
task_id: The task ID to look up
|
||||
|
||||
Returns:
|
||||
Task if found, None otherwise
|
||||
"""
|
||||
return self._tasks.get(task_id)
|
||||
|
||||
def update_status(
|
||||
self,
|
||||
task_id: str,
|
||||
state: TaskState,
|
||||
message: Optional[Message] = None,
|
||||
) -> Optional[Task]:
|
||||
"""
|
||||
Update the status of a task.
|
||||
|
||||
Args:
|
||||
task_id: The task ID to update
|
||||
state: New task state
|
||||
message: Optional status message
|
||||
|
||||
Returns:
|
||||
Updated Task if found, None otherwise
|
||||
"""
|
||||
task = self._tasks.get(task_id)
|
||||
if not task:
|
||||
return None
|
||||
|
||||
# Create new status
|
||||
new_status = TaskStatus(
|
||||
state=state,
|
||||
message=message,
|
||||
timestamp=datetime.now(timezone.utc).isoformat(),
|
||||
)
|
||||
|
||||
# Update task (create new instance for immutability)
|
||||
updated = Task(
|
||||
id=task.id,
|
||||
context_id=task.context_id,
|
||||
status=new_status,
|
||||
artifacts=task.artifacts,
|
||||
history=task.history,
|
||||
metadata=task.metadata,
|
||||
)
|
||||
|
||||
self._tasks[task_id] = updated
|
||||
return updated
|
||||
|
||||
def add_artifact(self, task_id: str, artifact: Artifact) -> Optional[Task]:
|
||||
"""
|
||||
Add an artifact to a task.
|
||||
|
||||
Args:
|
||||
task_id: The task ID to update
|
||||
artifact: Artifact to add
|
||||
|
||||
Returns:
|
||||
Updated Task if found, None otherwise
|
||||
"""
|
||||
task = self._tasks.get(task_id)
|
||||
if not task:
|
||||
return None
|
||||
|
||||
# Get existing artifacts or create new list
|
||||
artifacts = list(task.artifacts) if task.artifacts else []
|
||||
artifacts.append(artifact)
|
||||
|
||||
# Update task
|
||||
updated = Task(
|
||||
id=task.id,
|
||||
context_id=task.context_id,
|
||||
status=task.status,
|
||||
artifacts=artifacts,
|
||||
history=task.history,
|
||||
metadata=task.metadata,
|
||||
)
|
||||
|
||||
self._tasks[task_id] = updated
|
||||
return updated
|
||||
|
||||
def add_to_history(self, task_id: str, message: Message) -> Optional[Task]:
|
||||
"""
|
||||
Add a message to task history.
|
||||
|
||||
Args:
|
||||
task_id: The task ID to update
|
||||
message: Message to add to history
|
||||
|
||||
Returns:
|
||||
Updated Task if found, None otherwise
|
||||
"""
|
||||
task = self._tasks.get(task_id)
|
||||
if not task:
|
||||
return None
|
||||
|
||||
# Get existing history or create new list
|
||||
history = list(task.history) if task.history else []
|
||||
history.append(message)
|
||||
|
||||
# Update task
|
||||
updated = Task(
|
||||
id=task.id,
|
||||
context_id=task.context_id,
|
||||
status=task.status,
|
||||
artifacts=task.artifacts,
|
||||
history=history,
|
||||
metadata=task.metadata,
|
||||
)
|
||||
|
||||
self._tasks[task_id] = updated
|
||||
return updated
|
||||
|
||||
def list_tasks(self, context_id: Optional[str] = None) -> List[Task]:
|
||||
"""
|
||||
List all tasks, optionally filtered by context.
|
||||
|
||||
Args:
|
||||
context_id: Optional context ID to filter by
|
||||
|
||||
Returns:
|
||||
List of tasks
|
||||
"""
|
||||
if context_id:
|
||||
return [t for t in self._tasks.values() if t.context_id == context_id]
|
||||
return list(self._tasks.values())
|
||||
|
||||
def cancel_task(self, task_id: str) -> Optional[Task]:
|
||||
"""
|
||||
Cancel a task.
|
||||
|
||||
Args:
|
||||
task_id: The task ID to cancel
|
||||
|
||||
Returns:
|
||||
Updated Task if found, None otherwise
|
||||
"""
|
||||
return self.update_status(task_id, TaskState.CANCELLED)
|
||||
|
||||
def clear(self):
|
||||
"""Clear all tasks from the store."""
|
||||
self._tasks.clear()
|
||||
@@ -0,0 +1,266 @@
|
||||
"""
|
||||
A2A Protocol Types
|
||||
|
||||
Pydantic models for the Agent2Agent (A2A) protocol.
|
||||
Based on the A2A Protocol Specification v1.0.
|
||||
"""
|
||||
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, Union
|
||||
from pydantic import BaseModel, ConfigDict, Field
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Enums
|
||||
# =============================================================================
|
||||
|
||||
class TaskState(str, Enum):
|
||||
"""
|
||||
Defines the possible lifecycle states of a Task.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.3.
|
||||
"""
|
||||
SUBMITTED = "submitted"
|
||||
WORKING = "working"
|
||||
COMPLETED = "completed"
|
||||
FAILED = "failed"
|
||||
CANCELLED = "cancelled"
|
||||
INPUT_REQUIRED = "input_required"
|
||||
AUTH_REQUIRED = "auth_required"
|
||||
|
||||
|
||||
class Role(str, Enum):
|
||||
"""
|
||||
Defines the sender of a message in A2A protocol communication.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.5.
|
||||
"""
|
||||
USER = "user"
|
||||
AGENT = "agent"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Part Types
|
||||
# =============================================================================
|
||||
|
||||
class TextPart(BaseModel):
|
||||
"""
|
||||
A text content part.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.6.
|
||||
"""
|
||||
text: str
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
class FilePart(BaseModel):
|
||||
"""
|
||||
A file content part.
|
||||
|
||||
Can contain either a URI reference or inline bytes.
|
||||
Based on A2A Protocol Specification Section 4.1.7.
|
||||
"""
|
||||
file_uri: Optional[str] = Field(default=None, alias="fileWithUri")
|
||||
file_bytes: Optional[bytes] = Field(default=None, alias="fileWithBytes")
|
||||
media_type: Optional[str] = Field(default=None, alias="mediaType")
|
||||
name: Optional[str] = None
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
|
||||
class DataPart(BaseModel):
|
||||
"""
|
||||
A structured data part (JSON blob).
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.8.
|
||||
"""
|
||||
data: Dict[str, Any]
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
# Union type for all Part types
|
||||
Part = Union[TextPart, FilePart, DataPart]
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Core Types
|
||||
# =============================================================================
|
||||
|
||||
class Message(BaseModel):
|
||||
"""
|
||||
A communication turn between client and server.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.4.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
message_id: str = Field(alias="messageId")
|
||||
role: Role
|
||||
parts: List[Part]
|
||||
context_id: Optional[str] = Field(default=None, alias="contextId")
|
||||
task_id: Optional[str] = Field(default=None, alias="taskId")
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
extensions: Optional[Dict[str, str]] = None
|
||||
reference_task_ids: Optional[List[str]] = Field(default=None, alias="referenceTaskIds")
|
||||
|
||||
|
||||
class TaskStatus(BaseModel):
|
||||
"""
|
||||
Container for the status of a task.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.2.
|
||||
"""
|
||||
state: TaskState
|
||||
message: Optional[Message] = None
|
||||
timestamp: Optional[str] = None
|
||||
|
||||
|
||||
class Artifact(BaseModel):
|
||||
"""
|
||||
An output generated by the agent as a result of a task.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.9.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
artifact_id: str = Field(alias="artifactId")
|
||||
name: Optional[str] = None
|
||||
description: Optional[str] = None
|
||||
parts: List[Part]
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
extensions: Optional[Dict[str, str]] = None
|
||||
|
||||
|
||||
class Task(BaseModel):
|
||||
"""
|
||||
The core unit of action for A2A.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.1.1.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
id: str
|
||||
context_id: Optional[str] = Field(default=None, alias="contextId")
|
||||
status: TaskStatus
|
||||
artifacts: Optional[List[Artifact]] = None
|
||||
history: Optional[List[Message]] = None
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Agent Card Types
|
||||
# =============================================================================
|
||||
|
||||
class AgentSkill(BaseModel):
|
||||
"""
|
||||
Describes a skill/capability of an agent.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.4.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
id: str
|
||||
name: str
|
||||
description: str
|
||||
tags: Optional[List[str]] = None
|
||||
examples: Optional[List[str]] = None
|
||||
input_modes: Optional[List[str]] = Field(default=None, alias="inputModes")
|
||||
output_modes: Optional[List[str]] = Field(default=None, alias="outputModes")
|
||||
|
||||
|
||||
class AgentCapabilities(BaseModel):
|
||||
"""
|
||||
Describes the capabilities of an agent.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.4.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
streaming: bool = False
|
||||
push_notifications: bool = Field(default=False, alias="pushNotifications")
|
||||
state_transition_history: bool = Field(default=False, alias="stateTransitionHistory")
|
||||
|
||||
|
||||
class AgentCard(BaseModel):
|
||||
"""
|
||||
JSON metadata document describing an agent.
|
||||
|
||||
Published by an A2A Server for discovery.
|
||||
Based on A2A Protocol Specification Section 8.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
name: str
|
||||
url: str
|
||||
version: str
|
||||
description: Optional[str] = None
|
||||
capabilities: AgentCapabilities
|
||||
skills: Optional[List[AgentSkill]] = None
|
||||
default_input_modes: Optional[List[str]] = Field(default=None, alias="defaultInputModes")
|
||||
default_output_modes: Optional[List[str]] = Field(default=None, alias="defaultOutputModes")
|
||||
provider: Optional[Dict[str, str]] = None
|
||||
documentation_url: Optional[str] = Field(default=None, alias="documentationUrl")
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Request/Response Types
|
||||
# =============================================================================
|
||||
|
||||
class MessageConfig(BaseModel):
|
||||
"""
|
||||
Configuration for message sending.
|
||||
|
||||
Based on A2A Protocol Specification Section 3.2.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
accept_content_types: Optional[List[str]] = Field(default=None, alias="acceptContentTypes")
|
||||
blocking: Optional[bool] = None
|
||||
history_length: Optional[int] = Field(default=None, alias="historyLength")
|
||||
|
||||
|
||||
class SendMessageRequest(BaseModel):
|
||||
"""
|
||||
Request to send a message to an agent.
|
||||
|
||||
Based on A2A Protocol Specification Section 3.1.1.
|
||||
"""
|
||||
message: Message
|
||||
configuration: Optional[MessageConfig] = None
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Streaming Event Types
|
||||
# =============================================================================
|
||||
|
||||
class TaskStatusUpdateEvent(BaseModel):
|
||||
"""
|
||||
Event sent by agent to notify client of task status change.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.2.1.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
task_id: str = Field(alias="taskId")
|
||||
context_id: Optional[str] = Field(default=None, alias="contextId")
|
||||
status: TaskStatus
|
||||
final: bool = False
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
class TaskArtifactUpdateEvent(BaseModel):
|
||||
"""
|
||||
Event sent when an artifact is generated.
|
||||
|
||||
Based on A2A Protocol Specification Section 4.2.2.
|
||||
"""
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
task_id: str = Field(alias="taskId")
|
||||
context_id: Optional[str] = Field(default=None, alias="contextId")
|
||||
artifact: Artifact
|
||||
append: bool = False
|
||||
last_chunk: bool = Field(default=False, alias="lastChunk")
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
@@ -0,0 +1,126 @@
|
||||
"""
|
||||
A2UI (Agent-to-User Interface) Protocol Integration for PraisonAI Agents
|
||||
|
||||
This module provides A2UI protocol support, enabling PraisonAI Agents
|
||||
to generate rich, interactive UIs declaratively via JSON.
|
||||
|
||||
A2UI is Google's open standard that allows agents to "speak UI" by sending
|
||||
declarative JSON describing UI components, which clients then render natively.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents.ui.a2ui import (
|
||||
# Message types
|
||||
CreateSurfaceMessage,
|
||||
UpdateComponentsMessage,
|
||||
UpdateDataModelMessage,
|
||||
DeleteSurfaceMessage,
|
||||
# Component types
|
||||
TextComponent,
|
||||
ImageComponent,
|
||||
ButtonComponent,
|
||||
CardComponent,
|
||||
RowComponent,
|
||||
ColumnComponent,
|
||||
# Extension helpers
|
||||
create_a2ui_part,
|
||||
is_a2ui_part,
|
||||
)
|
||||
"""
|
||||
|
||||
from praisonaiagents.ui.a2ui.types import (
|
||||
# Data binding
|
||||
PathBinding,
|
||||
resolve_string_or_path,
|
||||
# Action types
|
||||
ActionContext,
|
||||
Action,
|
||||
# Children types
|
||||
ChildrenTemplate,
|
||||
# Component types
|
||||
TextComponent,
|
||||
ImageComponent,
|
||||
IconComponent,
|
||||
ButtonComponent,
|
||||
CardComponent,
|
||||
RowComponent,
|
||||
ColumnComponent,
|
||||
ListComponent,
|
||||
TextFieldComponent,
|
||||
CheckBoxComponent,
|
||||
SliderComponent,
|
||||
DateTimeInputComponent,
|
||||
# Message types
|
||||
CreateSurfaceMessage,
|
||||
UpdateComponentsMessage,
|
||||
UpdateDataModelMessage,
|
||||
DeleteSurfaceMessage,
|
||||
# Data part
|
||||
A2UIDataPart,
|
||||
)
|
||||
|
||||
from praisonaiagents.ui.a2ui.extension import (
|
||||
A2UI_MIME_TYPE,
|
||||
A2UI_EXTENSION_URI,
|
||||
STANDARD_CATALOG_ID,
|
||||
create_a2ui_part,
|
||||
is_a2ui_part,
|
||||
get_a2ui_agent_extension,
|
||||
AgentExtension,
|
||||
)
|
||||
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
from praisonaiagents.ui.a2ui.templates import (
|
||||
ChatTemplate,
|
||||
ListTemplate,
|
||||
FormTemplate,
|
||||
DashboardTemplate,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
# Data binding
|
||||
"PathBinding",
|
||||
"resolve_string_or_path",
|
||||
# Action types
|
||||
"ActionContext",
|
||||
"Action",
|
||||
# Children types
|
||||
"ChildrenTemplate",
|
||||
# Component types
|
||||
"TextComponent",
|
||||
"ImageComponent",
|
||||
"IconComponent",
|
||||
"ButtonComponent",
|
||||
"CardComponent",
|
||||
"RowComponent",
|
||||
"ColumnComponent",
|
||||
"ListComponent",
|
||||
"TextFieldComponent",
|
||||
"CheckBoxComponent",
|
||||
"SliderComponent",
|
||||
"DateTimeInputComponent",
|
||||
# Message types
|
||||
"CreateSurfaceMessage",
|
||||
"UpdateComponentsMessage",
|
||||
"UpdateDataModelMessage",
|
||||
"DeleteSurfaceMessage",
|
||||
# Data part
|
||||
"A2UIDataPart",
|
||||
# Extension
|
||||
"A2UI_MIME_TYPE",
|
||||
"A2UI_EXTENSION_URI",
|
||||
"STANDARD_CATALOG_ID",
|
||||
"create_a2ui_part",
|
||||
"is_a2ui_part",
|
||||
"get_a2ui_agent_extension",
|
||||
"AgentExtension",
|
||||
# Surface builder
|
||||
"Surface",
|
||||
# Agent wrapper
|
||||
"A2UIAgent",
|
||||
# Templates
|
||||
"ChatTemplate",
|
||||
"ListTemplate",
|
||||
"FormTemplate",
|
||||
"DashboardTemplate",
|
||||
]
|
||||
@@ -0,0 +1,358 @@
|
||||
"""
|
||||
A2UI Agent Integration
|
||||
|
||||
Provides A2UIAgent wrapper for generating A2UI responses from PraisonAI agents.
|
||||
"""
|
||||
|
||||
import uuid
|
||||
from typing import Any, Dict, List, Optional, TYPE_CHECKING
|
||||
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import (
|
||||
PathBinding,
|
||||
A2UIDataPart,
|
||||
)
|
||||
from praisonaiagents.ui.a2ui.extension import (
|
||||
create_a2ui_part,
|
||||
STANDARD_CATALOG_ID,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from praisonaiagents import Agent
|
||||
|
||||
|
||||
class A2UIAgent:
|
||||
"""
|
||||
A2UI wrapper for PraisonAI agents.
|
||||
|
||||
Provides methods to generate A2UI responses from agent interactions.
|
||||
|
||||
Example:
|
||||
>>> from praisonaiagents import Agent
|
||||
>>> from praisonaiagents.ui.a2ui import A2UIAgent
|
||||
>>>
|
||||
>>> agent = Agent(name="Assistant", role="Helper", goal="Help users")
|
||||
>>> a2ui_agent = A2UIAgent(agent=agent)
|
||||
>>>
|
||||
>>> # Render a simple text response
|
||||
>>> messages = a2ui_agent.render_text("Hello, World!")
|
||||
>>>
|
||||
>>> # Render a list of items
|
||||
>>> messages = a2ui_agent.render_list(
|
||||
... title="Results",
|
||||
... items=[{"name": "Item 1"}, {"name": "Item 2"}]
|
||||
... )
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
agent: "Agent",
|
||||
surface_id: Optional[str] = None,
|
||||
catalog_id: str = STANDARD_CATALOG_ID,
|
||||
):
|
||||
"""
|
||||
Initialize A2UIAgent wrapper.
|
||||
|
||||
Args:
|
||||
agent: The PraisonAI Agent to wrap
|
||||
surface_id: Unique ID for the UI surface (auto-generated if not provided)
|
||||
catalog_id: The component catalog to use
|
||||
"""
|
||||
self.agent = agent
|
||||
self.surface_id = surface_id or f"surface-{uuid.uuid4().hex[:8]}"
|
||||
self.catalog_id = catalog_id
|
||||
self._surface: Optional[Surface] = None
|
||||
|
||||
def get_surface(self) -> Surface:
|
||||
"""
|
||||
Get the underlying Surface object.
|
||||
|
||||
Creates a new Surface if one doesn't exist.
|
||||
|
||||
Returns:
|
||||
The Surface object
|
||||
"""
|
||||
if self._surface is None:
|
||||
self._surface = Surface(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
return self._surface
|
||||
|
||||
def _reset_surface(self) -> Surface:
|
||||
"""Reset and return a new Surface."""
|
||||
self._surface = Surface(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
return self._surface
|
||||
|
||||
# =========================================================================
|
||||
# Rendering methods
|
||||
# =========================================================================
|
||||
|
||||
def render_text(
|
||||
self,
|
||||
text: str,
|
||||
title: Optional[str] = None,
|
||||
usage_hint: str = "body",
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Render a simple text response as A2UI.
|
||||
|
||||
Args:
|
||||
text: The text content to display
|
||||
title: Optional title heading
|
||||
usage_hint: Text style hint (h1, h2, body, caption)
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = self._reset_surface()
|
||||
|
||||
children = []
|
||||
|
||||
if title:
|
||||
surface.text(id="title", text=title, usage_hint="h1")
|
||||
children.append("title")
|
||||
|
||||
surface.text(id="content", text=text, usage_hint=usage_hint)
|
||||
children.append("content")
|
||||
|
||||
# Add root column
|
||||
surface.column(id="root", children=children)
|
||||
|
||||
return surface.to_messages()
|
||||
|
||||
def render_list(
|
||||
self,
|
||||
title: str,
|
||||
items: List[Dict[str, Any]],
|
||||
item_title_key: str = "title",
|
||||
item_description_key: str = "description",
|
||||
item_image_key: Optional[str] = None,
|
||||
item_action: Optional[str] = None,
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Render a list of items as A2UI cards.
|
||||
|
||||
Args:
|
||||
title: List title
|
||||
items: List of item dictionaries
|
||||
item_title_key: Key for item title in each dict
|
||||
item_description_key: Key for item description
|
||||
item_image_key: Optional key for item image URL
|
||||
item_action: Optional action name for item buttons
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = self._reset_surface()
|
||||
|
||||
# Title
|
||||
surface.text(id="list-title", text=title, usage_hint="h1")
|
||||
|
||||
# Create card for each item
|
||||
card_ids = []
|
||||
for i, item in enumerate(items):
|
||||
card_id = f"card-{i}"
|
||||
content_id = f"card-content-{i}"
|
||||
title_id = f"item-title-{i}"
|
||||
desc_id = f"item-desc-{i}"
|
||||
|
||||
# Item title
|
||||
surface.text(
|
||||
id=title_id,
|
||||
text=item.get(item_title_key, f"Item {i+1}"),
|
||||
usage_hint="h3"
|
||||
)
|
||||
|
||||
# Item description
|
||||
surface.text(
|
||||
id=desc_id,
|
||||
text=item.get(item_description_key, ""),
|
||||
usage_hint="body"
|
||||
)
|
||||
|
||||
content_children = [title_id, desc_id]
|
||||
|
||||
# Optional action button
|
||||
if item_action:
|
||||
btn_id = f"btn-{i}"
|
||||
btn_text_id = f"btn-text-{i}"
|
||||
surface.text(id=btn_text_id, text="Select")
|
||||
surface.button(
|
||||
id=btn_id,
|
||||
child=btn_text_id,
|
||||
action_name=item_action,
|
||||
action_context=[{"key": "index", "value": i}],
|
||||
primary=True
|
||||
)
|
||||
content_children.append(btn_id)
|
||||
|
||||
# Card content column
|
||||
surface.column(id=content_id, children=content_children)
|
||||
|
||||
# Card
|
||||
surface.card(id=card_id, child=content_id)
|
||||
card_ids.append(card_id)
|
||||
|
||||
# List column
|
||||
surface.column(id="item-list", children=card_ids)
|
||||
|
||||
# Root column
|
||||
surface.column(id="root", children=["list-title", "item-list"])
|
||||
|
||||
# Set data
|
||||
surface.set_data("items", items)
|
||||
|
||||
return surface.to_messages()
|
||||
|
||||
def render_form(
|
||||
self,
|
||||
title: str,
|
||||
fields: List[Dict[str, str]],
|
||||
submit_action: str = "submit",
|
||||
submit_label: str = "Submit",
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Render a form as A2UI.
|
||||
|
||||
Args:
|
||||
title: Form title
|
||||
fields: List of field definitions with id, label, type
|
||||
submit_action: Action name for submit button
|
||||
submit_label: Label for submit button
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = self._reset_surface()
|
||||
|
||||
# Title
|
||||
surface.text(id="form-title", text=title, usage_hint="h1")
|
||||
|
||||
# Fields
|
||||
field_ids = []
|
||||
form_data = {}
|
||||
|
||||
for field in fields:
|
||||
field_id = field.get("id", f"field-{len(field_ids)}")
|
||||
label = field.get("label", field_id)
|
||||
field_type = field.get("type", "text")
|
||||
|
||||
surface.text_field(
|
||||
id=field_id,
|
||||
label=label,
|
||||
text=PathBinding(path=f"/{field_id}"),
|
||||
field_type=field_type,
|
||||
)
|
||||
field_ids.append(field_id)
|
||||
form_data[field_id] = field.get("default", "")
|
||||
|
||||
# Submit button
|
||||
surface.text(id="submit-text", text=submit_label)
|
||||
|
||||
# Build action context from fields
|
||||
action_context = [
|
||||
{"key": f["id"], "value": {"path": f"/{f['id']}"}}
|
||||
for f in fields
|
||||
]
|
||||
|
||||
surface.button(
|
||||
id="submit-btn",
|
||||
child="submit-text",
|
||||
action_name=submit_action,
|
||||
action_context=action_context,
|
||||
primary=True,
|
||||
)
|
||||
field_ids.append("submit-btn")
|
||||
|
||||
# Form column
|
||||
surface.column(id="form-fields", children=field_ids)
|
||||
|
||||
# Root column
|
||||
surface.column(id="root", children=["form-title", "form-fields"])
|
||||
|
||||
# Set initial form data
|
||||
for key, value in form_data.items():
|
||||
surface.set_data(key, value)
|
||||
|
||||
return surface.to_messages()
|
||||
|
||||
# =========================================================================
|
||||
# Agent interaction methods
|
||||
# =========================================================================
|
||||
|
||||
async def chat_async(self, message: str) -> str:
|
||||
"""
|
||||
Send a message to the agent and get a response.
|
||||
|
||||
Args:
|
||||
message: The message to send
|
||||
|
||||
Returns:
|
||||
The agent's response text
|
||||
"""
|
||||
# Use the agent's chat method
|
||||
if hasattr(self.agent, 'chat'):
|
||||
response = self.agent.chat(message)
|
||||
return response
|
||||
elif hasattr(self.agent, 'run'):
|
||||
response = self.agent.run(message)
|
||||
return response
|
||||
else:
|
||||
raise NotImplementedError("Agent does not have chat or run method")
|
||||
|
||||
def chat(self, message: str) -> str:
|
||||
"""
|
||||
Send a message to the agent and get a response (sync).
|
||||
|
||||
Args:
|
||||
message: The message to send
|
||||
|
||||
Returns:
|
||||
The agent's response text
|
||||
"""
|
||||
if hasattr(self.agent, 'chat'):
|
||||
return self.agent.chat(message)
|
||||
elif hasattr(self.agent, 'run'):
|
||||
return self.agent.run(message)
|
||||
else:
|
||||
raise NotImplementedError("Agent does not have chat or run method")
|
||||
|
||||
# =========================================================================
|
||||
# Export methods
|
||||
# =========================================================================
|
||||
|
||||
def to_messages(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Get the current surface as A2UI messages.
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
return self.get_surface().to_messages()
|
||||
|
||||
def to_json(self, indent: Optional[int] = None) -> str:
|
||||
"""
|
||||
Get the current surface as JSON string.
|
||||
|
||||
Args:
|
||||
indent: JSON indentation level
|
||||
|
||||
Returns:
|
||||
JSON string of A2UI messages
|
||||
"""
|
||||
return self.get_surface().to_json(indent=indent)
|
||||
|
||||
def to_a2a_part(self) -> A2UIDataPart:
|
||||
"""
|
||||
Get the current surface as an A2A DataPart.
|
||||
|
||||
Returns:
|
||||
A2UIDataPart with A2UI MIME type
|
||||
"""
|
||||
messages = self.to_messages()
|
||||
# For A2A, we send messages as a list
|
||||
return create_a2ui_part({"messages": messages})
|
||||
@@ -0,0 +1,115 @@
|
||||
"""
|
||||
A2UI Extension for A2A Protocol
|
||||
|
||||
Provides helpers for integrating A2UI with the A2A (Agent-to-Agent) protocol.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
from praisonaiagents.ui.a2ui.types import A2UIDataPart
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Constants
|
||||
# =============================================================================
|
||||
|
||||
A2UI_EXTENSION_URI = "https://a2ui.org/a2a-extension/a2ui/v0.9"
|
||||
A2UI_MIME_TYPE = "application/json+a2ui"
|
||||
STANDARD_CATALOG_ID = "https://raw.githubusercontent.com/google/A2UI/refs/heads/main/specification/0.9/json/standard_catalog_definition.json"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Agent Extension Type
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class AgentExtension:
|
||||
"""
|
||||
A2A Agent Extension configuration.
|
||||
|
||||
Describes an extension that an agent supports.
|
||||
"""
|
||||
uri: str
|
||||
description: str = ""
|
||||
params: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Helper Functions
|
||||
# =============================================================================
|
||||
|
||||
def create_a2ui_part(a2ui_data: Dict[str, Any]) -> A2UIDataPart:
|
||||
"""
|
||||
Create an A2UI data part for A2A integration.
|
||||
|
||||
Wraps A2UI data in an A2UIDataPart with the appropriate MIME type.
|
||||
|
||||
Args:
|
||||
a2ui_data: The A2UI data dictionary (e.g., createSurface, updateComponents)
|
||||
|
||||
Returns:
|
||||
An A2UIDataPart with the A2UI MIME type in metadata
|
||||
|
||||
Example:
|
||||
>>> part = create_a2ui_part({"createSurface": {"surfaceId": "main", "catalogId": "..."}})
|
||||
>>> part.metadata["mimeType"]
|
||||
'application/json+a2ui'
|
||||
"""
|
||||
return A2UIDataPart(
|
||||
data=a2ui_data,
|
||||
metadata={"mimeType": A2UI_MIME_TYPE}
|
||||
)
|
||||
|
||||
|
||||
def is_a2ui_part(part: A2UIDataPart) -> bool:
|
||||
"""
|
||||
Check if a data part contains A2UI data.
|
||||
|
||||
Args:
|
||||
part: The data part to check
|
||||
|
||||
Returns:
|
||||
True if the part contains A2UI data (has A2UI MIME type), False otherwise
|
||||
|
||||
Example:
|
||||
>>> part = create_a2ui_part({"createSurface": {...}})
|
||||
>>> is_a2ui_part(part)
|
||||
True
|
||||
"""
|
||||
if not isinstance(part, A2UIDataPart):
|
||||
return False
|
||||
if part.metadata is None:
|
||||
return False
|
||||
return part.metadata.get("mimeType") == A2UI_MIME_TYPE
|
||||
|
||||
|
||||
def get_a2ui_agent_extension(
|
||||
accepts_inline_custom_catalog: bool = False,
|
||||
) -> AgentExtension:
|
||||
"""
|
||||
Create the A2UI AgentExtension configuration.
|
||||
|
||||
Returns an AgentExtension that can be added to an A2A Agent Card
|
||||
to indicate A2UI support.
|
||||
|
||||
Args:
|
||||
accepts_inline_custom_catalog: Whether the agent accepts inline custom catalogs
|
||||
|
||||
Returns:
|
||||
The configured A2UI AgentExtension
|
||||
|
||||
Example:
|
||||
>>> ext = get_a2ui_agent_extension()
|
||||
>>> ext.uri
|
||||
'https://a2ui.org/a2a-extension/a2ui/v0.9'
|
||||
"""
|
||||
params: Optional[Dict[str, Any]] = None
|
||||
if accepts_inline_custom_catalog:
|
||||
params = {"acceptsInlineCustomCatalog": True}
|
||||
|
||||
return AgentExtension(
|
||||
uri=A2UI_EXTENSION_URI,
|
||||
description="Provides agent-driven UI using the A2UI JSON format.",
|
||||
params=params
|
||||
)
|
||||
@@ -0,0 +1,364 @@
|
||||
"""
|
||||
A2UI Surface Builder
|
||||
|
||||
Provides a fluent API for building A2UI surfaces with components and data.
|
||||
"""
|
||||
|
||||
import json
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2ui.extension import STANDARD_CATALOG_ID
|
||||
from praisonaiagents.ui.a2ui.types import (
|
||||
Component,
|
||||
TextComponent,
|
||||
ImageComponent,
|
||||
ButtonComponent,
|
||||
CardComponent,
|
||||
RowComponent,
|
||||
ColumnComponent,
|
||||
ListComponent,
|
||||
TextFieldComponent,
|
||||
Action,
|
||||
ActionContext,
|
||||
PathBinding,
|
||||
CreateSurfaceMessage,
|
||||
UpdateComponentsMessage,
|
||||
UpdateDataModelMessage,
|
||||
StringOrPath,
|
||||
ChildrenType,
|
||||
)
|
||||
|
||||
|
||||
class Surface:
|
||||
"""
|
||||
A2UI Surface builder for creating rich agent-generated UIs.
|
||||
|
||||
Provides a fluent API for adding components and data, then
|
||||
generating the A2UI JSON messages.
|
||||
|
||||
Example:
|
||||
>>> surface = Surface(surface_id="main")
|
||||
>>> surface.text(id="title", text="Hello World", usage_hint="h1")
|
||||
>>> surface.button(id="submit", child="submit-text", action_name="submit")
|
||||
>>> surface.set_data("title", "Hello World")
|
||||
>>> messages = surface.to_messages()
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
surface_id: str,
|
||||
catalog_id: str = STANDARD_CATALOG_ID,
|
||||
):
|
||||
"""
|
||||
Initialize a new Surface.
|
||||
|
||||
Args:
|
||||
surface_id: Unique identifier for this surface
|
||||
catalog_id: The component catalog to use (defaults to standard catalog)
|
||||
"""
|
||||
self.surface_id = surface_id
|
||||
self.catalog_id = catalog_id
|
||||
self.components: List[Component] = []
|
||||
self.data: Dict[str, Any] = {}
|
||||
|
||||
def add(self, component: Component) -> "Surface":
|
||||
"""
|
||||
Add a component to the surface.
|
||||
|
||||
Args:
|
||||
component: The component to add
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
self.components.append(component)
|
||||
return self
|
||||
|
||||
def set_data(self, key: str, value: Any) -> "Surface":
|
||||
"""
|
||||
Set a value in the data model.
|
||||
|
||||
Args:
|
||||
key: The key in the data model
|
||||
value: The value to set
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
self.data[key] = value
|
||||
return self
|
||||
|
||||
# =========================================================================
|
||||
# Helper methods for common components
|
||||
# =========================================================================
|
||||
|
||||
def text(
|
||||
self,
|
||||
id: str,
|
||||
text: StringOrPath,
|
||||
usage_hint: Optional[str] = None,
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a Text component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
text: Text content or path binding
|
||||
usage_hint: Style hint (h1, h2, h3, body, caption)
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(TextComponent(
|
||||
id=id,
|
||||
text=text,
|
||||
usage_hint=usage_hint,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def image(
|
||||
self,
|
||||
id: str,
|
||||
url: StringOrPath,
|
||||
fit: Optional[str] = None,
|
||||
usage_hint: Optional[str] = None,
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add an Image component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
url: Image URL or path binding
|
||||
fit: Image fit (contain, cover, fill, none, scale-down)
|
||||
usage_hint: Size hint (icon, avatar, smallFeature, etc.)
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(ImageComponent(
|
||||
id=id,
|
||||
url=url,
|
||||
fit=fit,
|
||||
usage_hint=usage_hint,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def button(
|
||||
self,
|
||||
id: str,
|
||||
child: str,
|
||||
action_name: Optional[str] = None,
|
||||
action_context: Optional[List[Dict[str, Any]]] = None,
|
||||
primary: bool = False,
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a Button component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
child: Child component ID (usually a Text component)
|
||||
action_name: Name of the action to trigger
|
||||
action_context: List of {key, value} dicts for action context
|
||||
primary: Whether this is a primary button
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
action = None
|
||||
if action_name:
|
||||
context = []
|
||||
if action_context:
|
||||
for ctx in action_context:
|
||||
value = ctx.get("value")
|
||||
if isinstance(value, dict) and "path" in value:
|
||||
value = PathBinding(path=value["path"])
|
||||
context.append(ActionContext(key=ctx["key"], value=value))
|
||||
action = Action(name=action_name, context=context)
|
||||
|
||||
return self.add(ButtonComponent(
|
||||
id=id,
|
||||
child=child,
|
||||
action=action,
|
||||
primary=primary,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def card(
|
||||
self,
|
||||
id: str,
|
||||
child: str,
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a Card component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
child: Child component ID
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(CardComponent(
|
||||
id=id,
|
||||
child=child,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def row(
|
||||
self,
|
||||
id: str,
|
||||
children: ChildrenType,
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a Row (horizontal layout) component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
children: List of child IDs or ChildrenTemplate
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(RowComponent(
|
||||
id=id,
|
||||
children=children,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def column(
|
||||
self,
|
||||
id: str,
|
||||
children: ChildrenType,
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a Column (vertical layout) component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
children: List of child IDs or ChildrenTemplate
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(ColumnComponent(
|
||||
id=id,
|
||||
children=children,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def list(
|
||||
self,
|
||||
id: str,
|
||||
children: ChildrenType,
|
||||
direction: str = "vertical",
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a List component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
children: List of child IDs or ChildrenTemplate for dynamic lists
|
||||
direction: "vertical" or "horizontal"
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(ListComponent(
|
||||
id=id,
|
||||
children=children,
|
||||
direction=direction,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
def text_field(
|
||||
self,
|
||||
id: str,
|
||||
label: StringOrPath,
|
||||
text: StringOrPath,
|
||||
field_type: str = "text",
|
||||
weight: Optional[float] = None,
|
||||
) -> "Surface":
|
||||
"""
|
||||
Add a TextField input component.
|
||||
|
||||
Args:
|
||||
id: Component ID
|
||||
label: Field label
|
||||
text: Text value or path binding
|
||||
field_type: Input type (text, number, email, etc.)
|
||||
weight: Flex weight
|
||||
|
||||
Returns:
|
||||
self for method chaining
|
||||
"""
|
||||
return self.add(TextFieldComponent(
|
||||
id=id,
|
||||
label=label,
|
||||
text=text,
|
||||
field_type=field_type,
|
||||
weight=weight,
|
||||
))
|
||||
|
||||
# =========================================================================
|
||||
# Message generation
|
||||
# =========================================================================
|
||||
|
||||
def to_messages(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Generate A2UI messages for this surface.
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
messages: List[Dict[str, Any]] = []
|
||||
|
||||
# 1. CreateSurface message
|
||||
create_msg = CreateSurfaceMessage(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
messages.append(create_msg.to_dict())
|
||||
|
||||
# 2. UpdateComponents message (if we have components)
|
||||
if self.components:
|
||||
update_msg = UpdateComponentsMessage(
|
||||
surface_id=self.surface_id,
|
||||
components=self.components,
|
||||
)
|
||||
messages.append(update_msg.to_dict())
|
||||
|
||||
# 3. UpdateDataModel message (if we have data)
|
||||
if self.data:
|
||||
data_msg = UpdateDataModelMessage(
|
||||
surface_id=self.surface_id,
|
||||
value=self.data,
|
||||
)
|
||||
messages.append(data_msg.to_dict())
|
||||
|
||||
return messages
|
||||
|
||||
def to_json(self, indent: Optional[int] = None) -> str:
|
||||
"""
|
||||
Generate A2UI messages as a JSON string.
|
||||
|
||||
Args:
|
||||
indent: JSON indentation level (None for compact)
|
||||
|
||||
Returns:
|
||||
JSON string of A2UI messages
|
||||
"""
|
||||
return json.dumps(self.to_messages(), indent=indent)
|
||||
@@ -0,0 +1,17 @@
|
||||
"""
|
||||
A2UI Templates
|
||||
|
||||
Pre-built UI templates for common use cases.
|
||||
"""
|
||||
|
||||
from praisonaiagents.ui.a2ui.templates.chat import ChatTemplate
|
||||
from praisonaiagents.ui.a2ui.templates.list import ListTemplate
|
||||
from praisonaiagents.ui.a2ui.templates.form import FormTemplate
|
||||
from praisonaiagents.ui.a2ui.templates.dashboard import DashboardTemplate
|
||||
|
||||
__all__ = [
|
||||
"ChatTemplate",
|
||||
"ListTemplate",
|
||||
"FormTemplate",
|
||||
"DashboardTemplate",
|
||||
]
|
||||
@@ -0,0 +1,122 @@
|
||||
"""
|
||||
Chat Template for A2UI
|
||||
|
||||
Provides a conversational chat UI template.
|
||||
"""
|
||||
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.extension import STANDARD_CATALOG_ID
|
||||
|
||||
|
||||
class ChatTemplate:
|
||||
"""
|
||||
Chat UI template for conversational interfaces.
|
||||
|
||||
Creates a chat-style UI with user and agent messages.
|
||||
|
||||
Example:
|
||||
>>> template = ChatTemplate(surface_id="chat")
|
||||
>>> template.add_user_message("Hello!")
|
||||
>>> template.add_agent_message("Hi there! How can I help?")
|
||||
>>> messages = template.to_messages()
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
surface_id: str = "chat",
|
||||
catalog_id: str = STANDARD_CATALOG_ID,
|
||||
title: Optional[str] = None,
|
||||
):
|
||||
"""
|
||||
Initialize ChatTemplate.
|
||||
|
||||
Args:
|
||||
surface_id: Unique ID for the surface
|
||||
catalog_id: Component catalog to use
|
||||
title: Optional title for the chat
|
||||
"""
|
||||
self.surface_id = surface_id
|
||||
self.catalog_id = catalog_id
|
||||
self.title = title
|
||||
self.messages: List[Dict[str, Any]] = []
|
||||
|
||||
def add_user_message(self, content: str) -> "ChatTemplate":
|
||||
"""
|
||||
Add a user message.
|
||||
|
||||
Args:
|
||||
content: Message content
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.messages.append({
|
||||
"role": "user",
|
||||
"content": content,
|
||||
})
|
||||
return self
|
||||
|
||||
def add_agent_message(self, content: str) -> "ChatTemplate":
|
||||
"""
|
||||
Add an agent message.
|
||||
|
||||
Args:
|
||||
content: Message content
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.messages.append({
|
||||
"role": "agent",
|
||||
"content": content,
|
||||
})
|
||||
return self
|
||||
|
||||
def to_messages(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Generate A2UI messages for the chat.
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = Surface(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
|
||||
children = []
|
||||
|
||||
# Title if provided
|
||||
if self.title:
|
||||
surface.text(id="chat-title", text=self.title, usage_hint="h1")
|
||||
children.append("chat-title")
|
||||
|
||||
# Message components
|
||||
msg_ids = []
|
||||
for i, msg in enumerate(self.messages):
|
||||
msg_id = f"msg-{i}"
|
||||
role = msg["role"]
|
||||
content = msg["content"]
|
||||
|
||||
# Style based on role
|
||||
if role == "user":
|
||||
surface.text(id=msg_id, text=f"You: {content}", usage_hint="body")
|
||||
else:
|
||||
surface.text(id=msg_id, text=f"Agent: {content}", usage_hint="body")
|
||||
|
||||
msg_ids.append(msg_id)
|
||||
|
||||
# Messages column
|
||||
if msg_ids:
|
||||
surface.column(id="messages", children=msg_ids)
|
||||
children.append("messages")
|
||||
|
||||
# Root column
|
||||
surface.column(id="root", children=children)
|
||||
|
||||
# Set data
|
||||
surface.set_data("messages", self.messages)
|
||||
|
||||
return surface.to_messages()
|
||||
@@ -0,0 +1,128 @@
|
||||
"""
|
||||
Dashboard Template for A2UI
|
||||
|
||||
Provides a dashboard UI template with multiple panels.
|
||||
"""
|
||||
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.extension import STANDARD_CATALOG_ID
|
||||
|
||||
|
||||
class DashboardTemplate:
|
||||
"""
|
||||
Dashboard UI template with multiple panels.
|
||||
|
||||
Creates a dashboard layout with cards for each panel.
|
||||
|
||||
Example:
|
||||
>>> template = DashboardTemplate(surface_id="dashboard", title="My Dashboard")
|
||||
>>> template.add_panel(id="stats", title="Statistics", content="100 items")
|
||||
>>> template.add_panel(id="chart", title="Chart", content="[Chart here]")
|
||||
>>> messages = template.to_messages()
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
surface_id: str = "dashboard",
|
||||
title: str = "Dashboard",
|
||||
catalog_id: str = STANDARD_CATALOG_ID,
|
||||
columns: int = 2,
|
||||
):
|
||||
"""
|
||||
Initialize DashboardTemplate.
|
||||
|
||||
Args:
|
||||
surface_id: Unique ID for the surface
|
||||
title: Dashboard title
|
||||
catalog_id: Component catalog to use
|
||||
columns: Number of columns in the grid
|
||||
"""
|
||||
self.surface_id = surface_id
|
||||
self.title = title
|
||||
self.catalog_id = catalog_id
|
||||
self.columns = columns
|
||||
self.panels: List[Dict[str, Any]] = []
|
||||
|
||||
def add_panel(
|
||||
self,
|
||||
id: str,
|
||||
title: str,
|
||||
content: str,
|
||||
weight: Optional[float] = None,
|
||||
) -> "DashboardTemplate":
|
||||
"""
|
||||
Add a panel to the dashboard.
|
||||
|
||||
Args:
|
||||
id: Panel ID
|
||||
title: Panel title
|
||||
content: Panel content text
|
||||
weight: Optional flex weight
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.panels.append({
|
||||
"id": id,
|
||||
"title": title,
|
||||
"content": content,
|
||||
"weight": weight,
|
||||
})
|
||||
return self
|
||||
|
||||
def to_messages(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Generate A2UI messages for the dashboard.
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = Surface(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
|
||||
# Title
|
||||
surface.text(id="dashboard-title", text=self.title, usage_hint="h1")
|
||||
|
||||
# Create cards for each panel
|
||||
card_ids = []
|
||||
for panel in self.panels:
|
||||
panel_id = panel["id"]
|
||||
content_id = f"{panel_id}-content"
|
||||
title_id = f"{panel_id}-title"
|
||||
text_id = f"{panel_id}-text"
|
||||
|
||||
# Panel title
|
||||
surface.text(id=title_id, text=panel["title"], usage_hint="h3")
|
||||
|
||||
# Panel content
|
||||
surface.text(id=text_id, text=panel["content"], usage_hint="body")
|
||||
|
||||
# Panel content column
|
||||
surface.column(id=content_id, children=[title_id, text_id])
|
||||
|
||||
# Panel card
|
||||
surface.card(id=panel_id, child=content_id, weight=panel.get("weight"))
|
||||
card_ids.append(panel_id)
|
||||
|
||||
# Arrange panels in rows based on columns setting
|
||||
row_ids = []
|
||||
for i in range(0, len(card_ids), self.columns):
|
||||
row_cards = card_ids[i:i + self.columns]
|
||||
row_id = f"row-{i // self.columns}"
|
||||
surface.row(id=row_id, children=row_cards)
|
||||
row_ids.append(row_id)
|
||||
|
||||
# Panels container
|
||||
surface.column(id="panels", children=row_ids)
|
||||
|
||||
# Root column
|
||||
surface.column(id="root", children=["dashboard-title", "panels"])
|
||||
|
||||
# Set data
|
||||
surface.set_data("panels", self.panels)
|
||||
|
||||
return surface.to_messages()
|
||||
@@ -0,0 +1,205 @@
|
||||
"""
|
||||
Form Template for A2UI
|
||||
|
||||
Provides a form UI template for data collection.
|
||||
"""
|
||||
|
||||
from typing import Any, Dict, List
|
||||
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import PathBinding
|
||||
from praisonaiagents.ui.a2ui.extension import STANDARD_CATALOG_ID
|
||||
|
||||
|
||||
class FormTemplate:
|
||||
"""
|
||||
Form UI template for data collection.
|
||||
|
||||
Creates a form with various input fields and a submit button.
|
||||
|
||||
Example:
|
||||
>>> template = FormTemplate(surface_id="form", title="Contact")
|
||||
>>> template.add_text_field(id="name", label="Name")
|
||||
>>> template.add_email_field(id="email", label="Email")
|
||||
>>> template.set_submit_action("submit_form", "Send")
|
||||
>>> messages = template.to_messages()
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
surface_id: str = "form",
|
||||
title: str = "Form",
|
||||
catalog_id: str = STANDARD_CATALOG_ID,
|
||||
):
|
||||
"""
|
||||
Initialize FormTemplate.
|
||||
|
||||
Args:
|
||||
surface_id: Unique ID for the surface
|
||||
title: Form title
|
||||
catalog_id: Component catalog to use
|
||||
"""
|
||||
self.surface_id = surface_id
|
||||
self.title = title
|
||||
self.catalog_id = catalog_id
|
||||
self.fields: List[Dict[str, Any]] = []
|
||||
self.submit_action = "submit"
|
||||
self.submit_label = "Submit"
|
||||
|
||||
def add_text_field(
|
||||
self,
|
||||
id: str,
|
||||
label: str,
|
||||
default: str = "",
|
||||
required: bool = False,
|
||||
) -> "FormTemplate":
|
||||
"""
|
||||
Add a text input field.
|
||||
|
||||
Args:
|
||||
id: Field ID
|
||||
label: Field label
|
||||
default: Default value
|
||||
required: Whether field is required
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.fields.append({
|
||||
"id": id,
|
||||
"label": label,
|
||||
"type": "text",
|
||||
"default": default,
|
||||
"required": required,
|
||||
})
|
||||
return self
|
||||
|
||||
def add_number_field(
|
||||
self,
|
||||
id: str,
|
||||
label: str,
|
||||
default: float = 0,
|
||||
required: bool = False,
|
||||
) -> "FormTemplate":
|
||||
"""
|
||||
Add a number input field.
|
||||
|
||||
Args:
|
||||
id: Field ID
|
||||
label: Field label
|
||||
default: Default value
|
||||
required: Whether field is required
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.fields.append({
|
||||
"id": id,
|
||||
"label": label,
|
||||
"type": "number",
|
||||
"default": default,
|
||||
"required": required,
|
||||
})
|
||||
return self
|
||||
|
||||
def add_email_field(
|
||||
self,
|
||||
id: str,
|
||||
label: str,
|
||||
default: str = "",
|
||||
required: bool = False,
|
||||
) -> "FormTemplate":
|
||||
"""
|
||||
Add an email input field.
|
||||
|
||||
Args:
|
||||
id: Field ID
|
||||
label: Field label
|
||||
default: Default value
|
||||
required: Whether field is required
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.fields.append({
|
||||
"id": id,
|
||||
"label": label,
|
||||
"type": "email",
|
||||
"default": default,
|
||||
"required": required,
|
||||
})
|
||||
return self
|
||||
|
||||
def set_submit_action(
|
||||
self,
|
||||
action: str,
|
||||
label: str = "Submit",
|
||||
) -> "FormTemplate":
|
||||
"""
|
||||
Set the submit button action.
|
||||
|
||||
Args:
|
||||
action: Action name
|
||||
label: Button label
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
self.submit_action = action
|
||||
self.submit_label = label
|
||||
return self
|
||||
|
||||
def to_messages(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Generate A2UI messages for the form.
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = Surface(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
|
||||
# Title
|
||||
surface.text(id="form-title", text=self.title, usage_hint="h1")
|
||||
|
||||
# Fields
|
||||
field_ids = []
|
||||
for field in self.fields:
|
||||
field_id = field["id"]
|
||||
surface.text_field(
|
||||
id=field_id,
|
||||
label=field["label"],
|
||||
text=PathBinding(path=f"/{field_id}"),
|
||||
field_type=field["type"],
|
||||
)
|
||||
field_ids.append(field_id)
|
||||
|
||||
# Set default value
|
||||
surface.set_data(field_id, field.get("default", ""))
|
||||
|
||||
# Submit button
|
||||
surface.text(id="submit-text", text=self.submit_label)
|
||||
|
||||
action_context = [
|
||||
{"key": f["id"], "value": {"path": f"/{f['id']}"}}
|
||||
for f in self.fields
|
||||
]
|
||||
|
||||
surface.button(
|
||||
id="submit-btn",
|
||||
child="submit-text",
|
||||
action_name=self.submit_action,
|
||||
action_context=action_context,
|
||||
primary=True,
|
||||
)
|
||||
field_ids.append("submit-btn")
|
||||
|
||||
# Form fields column
|
||||
surface.column(id="fields", children=field_ids)
|
||||
|
||||
# Root column
|
||||
surface.column(id="root", children=["form-title", "fields"])
|
||||
|
||||
return surface.to_messages()
|
||||
@@ -0,0 +1,147 @@
|
||||
"""
|
||||
List Template for A2UI
|
||||
|
||||
Provides a list UI template for displaying items.
|
||||
"""
|
||||
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.extension import STANDARD_CATALOG_ID
|
||||
|
||||
|
||||
class ListTemplate:
|
||||
"""
|
||||
List UI template for displaying items.
|
||||
|
||||
Creates a list of cards with title, description, and optional image.
|
||||
|
||||
Example:
|
||||
>>> template = ListTemplate(surface_id="list", title="Results")
|
||||
>>> template.add_item(title="Item 1", description="First item")
|
||||
>>> template.add_item(title="Item 2", description="Second item")
|
||||
>>> messages = template.to_messages()
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
surface_id: str = "list",
|
||||
title: str = "Items",
|
||||
catalog_id: str = STANDARD_CATALOG_ID,
|
||||
):
|
||||
"""
|
||||
Initialize ListTemplate.
|
||||
|
||||
Args:
|
||||
surface_id: Unique ID for the surface
|
||||
title: List title
|
||||
catalog_id: Component catalog to use
|
||||
"""
|
||||
self.surface_id = surface_id
|
||||
self.title = title
|
||||
self.catalog_id = catalog_id
|
||||
self.items: List[Dict[str, Any]] = []
|
||||
|
||||
def add_item(
|
||||
self,
|
||||
title: str,
|
||||
description: str = "",
|
||||
image_url: Optional[str] = None,
|
||||
action: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> "ListTemplate":
|
||||
"""
|
||||
Add an item to the list.
|
||||
|
||||
Args:
|
||||
title: Item title
|
||||
description: Item description
|
||||
image_url: Optional image URL
|
||||
action: Optional action name for item button
|
||||
metadata: Optional additional metadata
|
||||
|
||||
Returns:
|
||||
self for chaining
|
||||
"""
|
||||
item = {
|
||||
"title": title,
|
||||
"description": description,
|
||||
}
|
||||
if image_url:
|
||||
item["image_url"] = image_url
|
||||
if action:
|
||||
item["action"] = action
|
||||
if metadata:
|
||||
item.update(metadata)
|
||||
|
||||
self.items.append(item)
|
||||
return self
|
||||
|
||||
def to_messages(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Generate A2UI messages for the list.
|
||||
|
||||
Returns:
|
||||
List of A2UI message dictionaries
|
||||
"""
|
||||
surface = Surface(
|
||||
surface_id=self.surface_id,
|
||||
catalog_id=self.catalog_id,
|
||||
)
|
||||
|
||||
# Title
|
||||
surface.text(id="list-title", text=self.title, usage_hint="h1")
|
||||
|
||||
# Create cards for each item
|
||||
card_ids = []
|
||||
for i, item in enumerate(self.items):
|
||||
card_id = f"card-{i}"
|
||||
content_id = f"content-{i}"
|
||||
title_id = f"title-{i}"
|
||||
desc_id = f"desc-{i}"
|
||||
|
||||
# Item title
|
||||
surface.text(id=title_id, text=item["title"], usage_hint="h3")
|
||||
|
||||
# Item description
|
||||
surface.text(id=desc_id, text=item.get("description", ""), usage_hint="body")
|
||||
|
||||
content_children = [title_id, desc_id]
|
||||
|
||||
# Optional image
|
||||
if item.get("image_url"):
|
||||
img_id = f"img-{i}"
|
||||
surface.image(id=img_id, url=item["image_url"], usage_hint="smallFeature")
|
||||
content_children.insert(0, img_id)
|
||||
|
||||
# Optional action button
|
||||
if item.get("action"):
|
||||
btn_id = f"btn-{i}"
|
||||
btn_text_id = f"btn-text-{i}"
|
||||
surface.text(id=btn_text_id, text="Select")
|
||||
surface.button(
|
||||
id=btn_id,
|
||||
child=btn_text_id,
|
||||
action_name=item["action"],
|
||||
action_context=[{"key": "index", "value": i}],
|
||||
primary=True,
|
||||
)
|
||||
content_children.append(btn_id)
|
||||
|
||||
# Card content
|
||||
surface.column(id=content_id, children=content_children)
|
||||
|
||||
# Card
|
||||
surface.card(id=card_id, child=content_id)
|
||||
card_ids.append(card_id)
|
||||
|
||||
# Items column
|
||||
surface.column(id="items", children=card_ids)
|
||||
|
||||
# Root column
|
||||
surface.column(id="root", children=["list-title", "items"])
|
||||
|
||||
# Set data
|
||||
surface.set_data("items", self.items)
|
||||
|
||||
return surface.to_messages()
|
||||
@@ -0,0 +1,523 @@
|
||||
"""
|
||||
A2UI Protocol Types
|
||||
|
||||
Pydantic-style classes for the A2UI (Agent-to-User Interface) protocol.
|
||||
Based on the A2UI Specification v0.9.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Dict, List, Optional, Union
|
||||
from enum import Enum
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Data Binding Types
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class PathBinding:
|
||||
"""
|
||||
A reference to a value in the data model.
|
||||
|
||||
Used for data binding in A2UI components.
|
||||
"""
|
||||
path: str
|
||||
|
||||
def to_dict(self) -> Dict[str, str]:
|
||||
return {"path": self.path}
|
||||
|
||||
|
||||
# Type alias for values that can be literal or path-bound
|
||||
StringOrPath = Union[str, PathBinding]
|
||||
NumberOrPath = Union[int, float, PathBinding]
|
||||
BooleanOrPath = Union[bool, PathBinding]
|
||||
|
||||
|
||||
def resolve_string_or_path(value: StringOrPath) -> Union[str, Dict[str, str]]:
|
||||
"""Resolve a StringOrPath to its serialized form."""
|
||||
if isinstance(value, PathBinding):
|
||||
return value.to_dict()
|
||||
return value
|
||||
|
||||
|
||||
def resolve_number_or_path(value: NumberOrPath) -> Union[int, float, Dict[str, str]]:
|
||||
"""Resolve a NumberOrPath to its serialized form."""
|
||||
if isinstance(value, PathBinding):
|
||||
return value.to_dict()
|
||||
return value
|
||||
|
||||
|
||||
def resolve_boolean_or_path(value: BooleanOrPath) -> Union[bool, Dict[str, str]]:
|
||||
"""Resolve a BooleanOrPath to its serialized form."""
|
||||
if isinstance(value, PathBinding):
|
||||
return value.to_dict()
|
||||
return value
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Action Types
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class ActionContext:
|
||||
"""
|
||||
A key-value pair for action context.
|
||||
|
||||
Used to pass data from UI to action handlers.
|
||||
"""
|
||||
key: str
|
||||
value: Union[str, int, float, bool, PathBinding]
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
if isinstance(self.value, PathBinding):
|
||||
return {"key": self.key, "value": self.value.to_dict()}
|
||||
return {"key": self.key, "value": self.value}
|
||||
|
||||
|
||||
@dataclass
|
||||
class Action:
|
||||
"""
|
||||
An action triggered by a UI component (e.g., button click).
|
||||
"""
|
||||
name: str
|
||||
context: List[ActionContext] = field(default_factory=list)
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"name": self.name,
|
||||
"context": [c.to_dict() for c in self.context]
|
||||
}
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Children Types
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class ChildrenTemplate:
|
||||
"""
|
||||
A template for generating dynamic children from a data model list.
|
||||
"""
|
||||
component_id: str
|
||||
path: str
|
||||
|
||||
def to_dict(self) -> Dict[str, str]:
|
||||
return {
|
||||
"componentId": self.component_id,
|
||||
"path": self.path
|
||||
}
|
||||
|
||||
|
||||
# Type alias for children - either explicit list or template
|
||||
ChildrenType = Union[List[str], ChildrenTemplate]
|
||||
|
||||
|
||||
def resolve_children(children: ChildrenType) -> Union[List[str], Dict[str, str]]:
|
||||
"""Resolve children to serialized form."""
|
||||
if isinstance(children, ChildrenTemplate):
|
||||
return children.to_dict()
|
||||
return children
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Component Types
|
||||
# =============================================================================
|
||||
|
||||
class UsageHint(str, Enum):
|
||||
"""Text usage hints for styling."""
|
||||
H1 = "h1"
|
||||
H2 = "h2"
|
||||
H3 = "h3"
|
||||
H4 = "h4"
|
||||
H5 = "h5"
|
||||
CAPTION = "caption"
|
||||
BODY = "body"
|
||||
|
||||
|
||||
class ImageFit(str, Enum):
|
||||
"""Image fit options."""
|
||||
CONTAIN = "contain"
|
||||
COVER = "cover"
|
||||
FILL = "fill"
|
||||
NONE = "none"
|
||||
SCALE_DOWN = "scale-down"
|
||||
|
||||
|
||||
class ImageUsageHint(str, Enum):
|
||||
"""Image usage hints."""
|
||||
ICON = "icon"
|
||||
AVATAR = "avatar"
|
||||
SMALL_FEATURE = "smallFeature"
|
||||
MEDIUM_FEATURE = "mediumFeature"
|
||||
LARGE_FEATURE = "largeFeature"
|
||||
HEADER = "header"
|
||||
|
||||
|
||||
@dataclass
|
||||
class TextComponent:
|
||||
"""Text display component."""
|
||||
id: str
|
||||
text: StringOrPath
|
||||
usage_hint: Optional[str] = None
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Text",
|
||||
"text": resolve_string_or_path(self.text)
|
||||
}
|
||||
if self.usage_hint:
|
||||
result["usageHint"] = self.usage_hint
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class ImageComponent:
|
||||
"""Image display component."""
|
||||
id: str
|
||||
url: StringOrPath
|
||||
fit: Optional[str] = None
|
||||
usage_hint: Optional[str] = None
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Image",
|
||||
"url": resolve_string_or_path(self.url)
|
||||
}
|
||||
if self.fit:
|
||||
result["fit"] = self.fit
|
||||
if self.usage_hint:
|
||||
result["usageHint"] = self.usage_hint
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class IconComponent:
|
||||
"""Icon display component."""
|
||||
id: str
|
||||
name: StringOrPath
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Icon",
|
||||
"name": resolve_string_or_path(self.name)
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class ButtonComponent:
|
||||
"""Button component with action."""
|
||||
id: str
|
||||
child: str
|
||||
action: Optional[Action] = None
|
||||
primary: bool = False
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Button",
|
||||
"child": self.child
|
||||
}
|
||||
if self.primary:
|
||||
result["primary"] = True
|
||||
if self.action:
|
||||
result["action"] = self.action.to_dict()
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class CardComponent:
|
||||
"""Card container component."""
|
||||
id: str
|
||||
child: str
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Card",
|
||||
"child": self.child
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class RowComponent:
|
||||
"""Horizontal layout component."""
|
||||
id: str
|
||||
children: ChildrenType
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Row",
|
||||
"children": resolve_children(self.children)
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class ColumnComponent:
|
||||
"""Vertical layout component."""
|
||||
id: str
|
||||
children: ChildrenType
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Column",
|
||||
"children": resolve_children(self.children)
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class ListComponent:
|
||||
"""List component for repeating items."""
|
||||
id: str
|
||||
children: ChildrenType
|
||||
direction: str = "vertical"
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "List",
|
||||
"direction": self.direction,
|
||||
"children": resolve_children(self.children)
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class TextFieldComponent:
|
||||
"""Text input field component."""
|
||||
id: str
|
||||
label: StringOrPath
|
||||
text: StringOrPath
|
||||
field_type: str = "text"
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "TextField",
|
||||
"label": resolve_string_or_path(self.label),
|
||||
"text": resolve_string_or_path(self.text),
|
||||
"type": self.field_type
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class CheckBoxComponent:
|
||||
"""Checkbox input component."""
|
||||
id: str
|
||||
label: StringOrPath
|
||||
checked: BooleanOrPath = False
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "CheckBox",
|
||||
"label": resolve_string_or_path(self.label),
|
||||
"checked": resolve_boolean_or_path(self.checked)
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class SliderComponent:
|
||||
"""Slider input component."""
|
||||
id: str
|
||||
min_value: NumberOrPath
|
||||
max_value: NumberOrPath
|
||||
value: NumberOrPath
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "Slider",
|
||||
"min": resolve_number_or_path(self.min_value),
|
||||
"max": resolve_number_or_path(self.max_value),
|
||||
"value": resolve_number_or_path(self.value)
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class DateTimeInputComponent:
|
||||
"""Date/time input component."""
|
||||
id: str
|
||||
label: StringOrPath
|
||||
value: StringOrPath
|
||||
enable_date: bool = True
|
||||
enable_time: bool = False
|
||||
weight: Optional[float] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"id": self.id,
|
||||
"component": "DateTimeInput",
|
||||
"label": resolve_string_or_path(self.label),
|
||||
"value": resolve_string_or_path(self.value),
|
||||
"enableDate": self.enable_date,
|
||||
"enableTime": self.enable_time
|
||||
}
|
||||
if self.weight is not None:
|
||||
result["weight"] = self.weight
|
||||
return result
|
||||
|
||||
|
||||
# Type alias for any component
|
||||
Component = Union[
|
||||
TextComponent,
|
||||
ImageComponent,
|
||||
IconComponent,
|
||||
ButtonComponent,
|
||||
CardComponent,
|
||||
RowComponent,
|
||||
ColumnComponent,
|
||||
ListComponent,
|
||||
TextFieldComponent,
|
||||
CheckBoxComponent,
|
||||
SliderComponent,
|
||||
DateTimeInputComponent,
|
||||
]
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Message Types
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class CreateSurfaceMessage:
|
||||
"""
|
||||
Message to create a new UI surface.
|
||||
|
||||
Signals the client to create a new surface and begin rendering it.
|
||||
"""
|
||||
surface_id: str
|
||||
catalog_id: str
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"createSurface": {
|
||||
"surfaceId": self.surface_id,
|
||||
"catalogId": self.catalog_id
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class UpdateComponentsMessage:
|
||||
"""
|
||||
Message to update surface components.
|
||||
|
||||
Updates a surface with a new set of components.
|
||||
"""
|
||||
surface_id: str
|
||||
components: List[Component]
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"updateComponents": {
|
||||
"surfaceId": self.surface_id,
|
||||
"components": [c.to_dict() for c in self.components]
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class UpdateDataModelMessage:
|
||||
"""
|
||||
Message to update the data model.
|
||||
|
||||
Updates the data model for an existing surface.
|
||||
"""
|
||||
surface_id: str
|
||||
value: Any
|
||||
path: str = "/"
|
||||
op: str = "replace"
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {
|
||||
"updateDataModel": {
|
||||
"surfaceId": self.surface_id,
|
||||
"path": self.path,
|
||||
"op": self.op,
|
||||
"value": self.value
|
||||
}
|
||||
}
|
||||
return result
|
||||
|
||||
|
||||
@dataclass
|
||||
class DeleteSurfaceMessage:
|
||||
"""
|
||||
Message to delete a surface.
|
||||
|
||||
Signals the client to delete the surface.
|
||||
"""
|
||||
surface_id: str
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"deleteSurface": {
|
||||
"surfaceId": self.surface_id
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Data Part Type
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class A2UIDataPart:
|
||||
"""
|
||||
A2UI data part for A2A integration.
|
||||
|
||||
Wraps A2UI data with the appropriate MIME type.
|
||||
"""
|
||||
data: Dict[str, Any]
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
result: Dict[str, Any] = {"data": self.data}
|
||||
if self.metadata:
|
||||
result["metadata"] = self.metadata
|
||||
return result
|
||||
@@ -0,0 +1,22 @@
|
||||
"""
|
||||
AG-UI Protocol Integration for PraisonAI Agents
|
||||
|
||||
This module provides AG-UI (Agent-User Interface) protocol support,
|
||||
enabling PraisonAI Agents to be exposed via a standardized streaming API
|
||||
compatible with CopilotKit and other AG-UI frontends.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Assistant", role="Helper", goal="Help users")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
"""
|
||||
|
||||
from praisonaiagents.ui.agui.agui import AGUI
|
||||
|
||||
__all__ = ["AGUI"]
|
||||
@@ -0,0 +1,203 @@
|
||||
"""
|
||||
AGUI - Main AG-UI Interface Class
|
||||
|
||||
Exposes PraisonAI Agents via the AG-UI protocol.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import uuid
|
||||
from typing import AsyncIterator, List, Optional, TYPE_CHECKING
|
||||
|
||||
from praisonaiagents.ui.agui.types import (
|
||||
BaseEvent,
|
||||
RunAgentInput,
|
||||
)
|
||||
from praisonaiagents.ui.agui.conversion import (
|
||||
agui_messages_to_praisonai,
|
||||
validate_state,
|
||||
extract_user_input,
|
||||
)
|
||||
from praisonaiagents.ui.agui.streaming import (
|
||||
create_run_error_event,
|
||||
async_stream_agent_response,
|
||||
async_stream_agents_response,
|
||||
)
|
||||
from praisonaiagents.ui.agui.encoder import EventEncoder
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from praisonaiagents import Agent, PraisonAIAgents
|
||||
from fastapi import APIRouter
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class AGUI:
|
||||
"""
|
||||
AG-UI Interface for PraisonAI Agents.
|
||||
|
||||
Exposes a PraisonAI Agent or PraisonAIAgents workflow via the AG-UI protocol,
|
||||
enabling integration with CopilotKit and other AG-UI compatible frontends.
|
||||
|
||||
Usage:
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Assistant", role="Helper", goal="Help users")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
Args:
|
||||
agent: Single PraisonAI Agent instance
|
||||
agents: PraisonAIAgents instance for multi-agent workflows
|
||||
name: Name for the AG-UI endpoint (defaults to agent name)
|
||||
description: Description of the agent
|
||||
prefix: URL prefix for the router (e.g., "/api/v1")
|
||||
tags: OpenAPI tags for the router
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
agent: Optional["Agent"] = None,
|
||||
agents: Optional["PraisonAIAgents"] = None,
|
||||
name: Optional[str] = None,
|
||||
description: Optional[str] = None,
|
||||
prefix: str = "",
|
||||
tags: Optional[List[str]] = None,
|
||||
):
|
||||
if agent is None and agents is None:
|
||||
raise ValueError("AGUI requires an agent or agents instance")
|
||||
|
||||
self.agent = agent
|
||||
self.agents = agents
|
||||
self.prefix = prefix
|
||||
self.tags = tags or ["AGUI"]
|
||||
|
||||
# Set name from agent if not provided
|
||||
if name:
|
||||
self.name = name
|
||||
elif agent and hasattr(agent, 'name'):
|
||||
self.name = agent.name
|
||||
elif agents and hasattr(agents, 'name'):
|
||||
self.name = agents.name
|
||||
else:
|
||||
self.name = "PraisonAI Agent"
|
||||
|
||||
# Set description
|
||||
if description:
|
||||
self.description = description
|
||||
elif agent and hasattr(agent, 'role'):
|
||||
self.description = agent.role
|
||||
else:
|
||||
self.description = "PraisonAI Agent via AG-UI"
|
||||
|
||||
self._router: Optional["APIRouter"] = None
|
||||
|
||||
def get_router(self) -> "APIRouter":
|
||||
"""
|
||||
Get the FastAPI router for this AGUI instance.
|
||||
|
||||
Returns:
|
||||
FastAPI APIRouter with AG-UI endpoints
|
||||
"""
|
||||
from fastapi import APIRouter
|
||||
from fastapi.responses import StreamingResponse
|
||||
|
||||
if self._router is not None:
|
||||
return self._router
|
||||
|
||||
self._router = APIRouter(prefix=self.prefix, tags=self.tags)
|
||||
|
||||
# Attach routes
|
||||
self._attach_routes(self._router)
|
||||
|
||||
return self._router
|
||||
|
||||
def _attach_routes(self, router: "APIRouter") -> None:
|
||||
"""Attach AG-UI routes to the router."""
|
||||
from fastapi.responses import StreamingResponse
|
||||
|
||||
encoder = EventEncoder()
|
||||
|
||||
@router.post("/agui")
|
||||
async def run_agent_agui(run_input: RunAgentInput):
|
||||
"""Run the agent via AG-UI protocol."""
|
||||
async def event_generator():
|
||||
async for event in self._run_agent(run_input):
|
||||
yield encoder.encode(event)
|
||||
|
||||
return StreamingResponse(
|
||||
event_generator(),
|
||||
media_type="text/event-stream",
|
||||
headers={
|
||||
"Cache-Control": "no-cache",
|
||||
"Connection": "keep-alive",
|
||||
"Access-Control-Allow-Origin": "*",
|
||||
"Access-Control-Allow-Methods": "POST, GET, OPTIONS",
|
||||
"Access-Control-Allow-Headers": "*",
|
||||
},
|
||||
)
|
||||
|
||||
@router.get("/status")
|
||||
async def get_status():
|
||||
"""Get agent status."""
|
||||
return {"status": "available"}
|
||||
|
||||
async def _run_agent(self, run_input: RunAgentInput) -> AsyncIterator[BaseEvent]:
|
||||
"""
|
||||
Run the agent with the given input.
|
||||
|
||||
Args:
|
||||
run_input: AG-UI run input
|
||||
|
||||
Yields:
|
||||
AG-UI events
|
||||
"""
|
||||
run_id = run_input.run_id or str(uuid.uuid4())
|
||||
thread_id = run_input.thread_id
|
||||
|
||||
try:
|
||||
# Convert messages
|
||||
messages = run_input.messages or []
|
||||
|
||||
# Extract user input
|
||||
user_input = extract_user_input(messages)
|
||||
|
||||
# Validate state
|
||||
session_state = validate_state(run_input.state, thread_id)
|
||||
|
||||
# Get user_id from forwarded_props if available
|
||||
user_id = None
|
||||
if run_input.forwarded_props and isinstance(run_input.forwarded_props, dict):
|
||||
user_id = run_input.forwarded_props.get("user_id")
|
||||
|
||||
# Run appropriate handler
|
||||
if self.agent:
|
||||
async for event in async_stream_agent_response(
|
||||
agent=self.agent,
|
||||
user_input=user_input,
|
||||
thread_id=thread_id,
|
||||
run_id=run_id,
|
||||
session_state=session_state,
|
||||
messages=agui_messages_to_praisonai(messages),
|
||||
):
|
||||
yield event
|
||||
|
||||
elif self.agents:
|
||||
async for event in async_stream_agents_response(
|
||||
agents=self.agents,
|
||||
user_input=user_input,
|
||||
thread_id=thread_id,
|
||||
run_id=run_id,
|
||||
session_state=session_state,
|
||||
):
|
||||
yield event
|
||||
|
||||
else:
|
||||
yield create_run_error_event("No agent or agents configured")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error running agent: {e}", exc_info=True)
|
||||
yield create_run_error_event(str(e))
|
||||
@@ -0,0 +1,211 @@
|
||||
"""
|
||||
AG-UI Message Conversion
|
||||
|
||||
Converts between AG-UI message format and PraisonAI message format.
|
||||
"""
|
||||
|
||||
import logging
|
||||
from typing import Any, Dict, List, Optional, Set
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from praisonaiagents.ui.agui.types import Message, ToolCall, FunctionCall
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def agui_messages_to_praisonai(messages: List[Message]) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Convert AG-UI messages to PraisonAI format.
|
||||
|
||||
Args:
|
||||
messages: List of AG-UI Message objects
|
||||
|
||||
Returns:
|
||||
List of message dictionaries in PraisonAI format
|
||||
"""
|
||||
if not messages:
|
||||
return []
|
||||
|
||||
# Track tool_call_ids that have results to avoid duplicates
|
||||
tool_call_ids_with_results: Set[str] = set()
|
||||
for msg in messages:
|
||||
if msg.role == "tool" and msg.tool_call_id:
|
||||
tool_call_ids_with_results.add(msg.tool_call_id)
|
||||
|
||||
result: List[Dict[str, Any]] = []
|
||||
seen_tool_call_ids: Set[str] = set()
|
||||
|
||||
for msg in messages:
|
||||
# Skip system messages - agent builds its own
|
||||
if msg.role == "system":
|
||||
continue
|
||||
|
||||
if msg.role == "tool":
|
||||
# Deduplicate tool results
|
||||
if msg.tool_call_id in seen_tool_call_ids:
|
||||
logger.debug(f"Skipping duplicate tool result: {msg.tool_call_id}")
|
||||
continue
|
||||
if msg.tool_call_id:
|
||||
seen_tool_call_ids.add(msg.tool_call_id)
|
||||
|
||||
result.append({
|
||||
"role": "tool",
|
||||
"content": msg.content or "",
|
||||
"tool_call_id": msg.tool_call_id,
|
||||
})
|
||||
|
||||
elif msg.role == "assistant":
|
||||
msg_dict: Dict[str, Any] = {
|
||||
"role": "assistant",
|
||||
"content": msg.content or "",
|
||||
}
|
||||
|
||||
if msg.tool_calls:
|
||||
# Include all tool_calls (filtering only when there are results to match)
|
||||
tool_calls_list = [
|
||||
{
|
||||
"id": tc.id,
|
||||
"function": {
|
||||
"name": tc.function.name,
|
||||
"arguments": tc.function.arguments,
|
||||
},
|
||||
"type": "function",
|
||||
}
|
||||
for tc in msg.tool_calls
|
||||
]
|
||||
if tool_calls_list:
|
||||
msg_dict["tool_calls"] = tool_calls_list
|
||||
|
||||
result.append(msg_dict)
|
||||
|
||||
elif msg.role == "user":
|
||||
result.append({
|
||||
"role": "user",
|
||||
"content": msg.content or "",
|
||||
})
|
||||
|
||||
else:
|
||||
logger.warning(f"Unknown message role: {msg.role}")
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def praisonai_messages_to_agui(messages: List[Dict[str, Any]]) -> List[Message]:
|
||||
"""
|
||||
Convert PraisonAI messages to AG-UI format.
|
||||
|
||||
Args:
|
||||
messages: List of message dictionaries in PraisonAI format
|
||||
|
||||
Returns:
|
||||
List of AG-UI Message objects
|
||||
"""
|
||||
if not messages:
|
||||
return []
|
||||
|
||||
result: List[Message] = []
|
||||
|
||||
for msg in messages:
|
||||
role = msg.get("role", "user")
|
||||
content = msg.get("content", "")
|
||||
|
||||
if role == "tool":
|
||||
result.append(Message(
|
||||
role="tool",
|
||||
content=content,
|
||||
tool_call_id=msg.get("tool_call_id"),
|
||||
))
|
||||
|
||||
elif role == "assistant":
|
||||
tool_calls = None
|
||||
if "tool_calls" in msg and msg["tool_calls"]:
|
||||
tool_calls = [
|
||||
ToolCall(
|
||||
id=tc.get("id", ""),
|
||||
function=FunctionCall(
|
||||
name=tc.get("function", {}).get("name", ""),
|
||||
arguments=tc.get("function", {}).get("arguments", "{}"),
|
||||
),
|
||||
)
|
||||
for tc in msg["tool_calls"]
|
||||
]
|
||||
|
||||
result.append(Message(
|
||||
role="assistant",
|
||||
content=content,
|
||||
tool_calls=tool_calls,
|
||||
))
|
||||
|
||||
elif role == "user":
|
||||
result.append(Message(
|
||||
role="user",
|
||||
content=content,
|
||||
))
|
||||
|
||||
elif role == "system":
|
||||
result.append(Message(
|
||||
role="system",
|
||||
content=content,
|
||||
))
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def validate_state(state: Any, thread_id: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Validate and convert state to a dictionary.
|
||||
|
||||
Args:
|
||||
state: The state to validate (can be dict, Pydantic model, or other)
|
||||
thread_id: Thread ID for logging
|
||||
|
||||
Returns:
|
||||
State as a dictionary, or None if invalid
|
||||
"""
|
||||
if state is None:
|
||||
return None
|
||||
|
||||
if isinstance(state, dict):
|
||||
return state
|
||||
|
||||
if isinstance(state, BaseModel):
|
||||
try:
|
||||
return state.model_dump()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Try to_dict method
|
||||
if hasattr(state, "to_dict") and callable(getattr(state, "to_dict")):
|
||||
try:
|
||||
result = state.to_dict()
|
||||
if isinstance(result, dict):
|
||||
return result
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
logger.warning(
|
||||
f"State must be a dict, got {type(state).__name__}. "
|
||||
f"State will be ignored. Thread: {thread_id}"
|
||||
)
|
||||
return None
|
||||
|
||||
|
||||
def extract_user_input(messages: List[Message]) -> str:
|
||||
"""
|
||||
Extract the last user message content.
|
||||
|
||||
Args:
|
||||
messages: List of AG-UI messages
|
||||
|
||||
Returns:
|
||||
Content of the last user message, or empty string
|
||||
"""
|
||||
if not messages:
|
||||
return ""
|
||||
|
||||
for msg in reversed(messages):
|
||||
if msg.role == "user" and msg.content:
|
||||
return msg.content
|
||||
|
||||
return ""
|
||||
@@ -0,0 +1,30 @@
|
||||
"""
|
||||
AG-UI Event Encoder
|
||||
|
||||
Encodes AG-UI events to Server-Sent Events (SSE) format.
|
||||
"""
|
||||
|
||||
from praisonaiagents.ui.agui.types import BaseEvent
|
||||
|
||||
|
||||
class EventEncoder:
|
||||
"""Encodes AG-UI events to SSE format."""
|
||||
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def get_content_type(self) -> str:
|
||||
"""Returns the content type for SSE."""
|
||||
return "text/event-stream"
|
||||
|
||||
def encode(self, event: BaseEvent) -> str:
|
||||
"""
|
||||
Encode an event to SSE format.
|
||||
|
||||
Args:
|
||||
event: The event to encode
|
||||
|
||||
Returns:
|
||||
SSE formatted string
|
||||
"""
|
||||
return f"data: {event.model_dump_json(by_alias=True, exclude_none=True)}\n\n"
|
||||
@@ -0,0 +1,372 @@
|
||||
"""
|
||||
AG-UI Event Streaming
|
||||
|
||||
Provides utilities for streaming PraisonAI agent responses as AG-UI events.
|
||||
"""
|
||||
|
||||
import uuid
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Set
|
||||
|
||||
from praisonaiagents.ui.agui.types import (
|
||||
BaseEvent,
|
||||
TextMessageStartEvent,
|
||||
TextMessageContentEvent,
|
||||
TextMessageEndEvent,
|
||||
ToolCallStartEvent,
|
||||
ToolCallArgsEvent,
|
||||
ToolCallEndEvent,
|
||||
ToolCallResultEvent,
|
||||
RunStartedEvent,
|
||||
RunFinishedEvent,
|
||||
RunErrorEvent,
|
||||
StepStartedEvent,
|
||||
StepFinishedEvent,
|
||||
StateSnapshotEvent,
|
||||
)
|
||||
|
||||
|
||||
@dataclass
|
||||
class EventBuffer:
|
||||
"""Buffer to manage event ordering constraints."""
|
||||
|
||||
active_tool_call_ids: Set[str] = field(default_factory=set)
|
||||
ended_tool_call_ids: Set[str] = field(default_factory=set)
|
||||
current_text_message_id: str = ""
|
||||
next_text_message_id: str = field(default_factory=lambda: str(uuid.uuid4()))
|
||||
pending_tool_calls_parent_id: str = ""
|
||||
|
||||
def start_tool_call(self, tool_call_id: str) -> None:
|
||||
"""Start a new tool call."""
|
||||
self.active_tool_call_ids.add(tool_call_id)
|
||||
|
||||
def end_tool_call(self, tool_call_id: str) -> None:
|
||||
"""End a tool call."""
|
||||
self.active_tool_call_ids.discard(tool_call_id)
|
||||
self.ended_tool_call_ids.add(tool_call_id)
|
||||
|
||||
def start_text_message(self) -> str:
|
||||
"""Start a new text message and return its ID."""
|
||||
self.current_text_message_id = self.next_text_message_id
|
||||
self.next_text_message_id = str(uuid.uuid4())
|
||||
return self.current_text_message_id
|
||||
|
||||
def get_parent_message_id_for_tool_call(self) -> str:
|
||||
"""Get the message ID to use as parent for tool calls."""
|
||||
if self.pending_tool_calls_parent_id:
|
||||
return self.pending_tool_calls_parent_id
|
||||
return self.current_text_message_id
|
||||
|
||||
|
||||
# Event Creation Functions
|
||||
|
||||
def create_text_message_events(
|
||||
content: str,
|
||||
message_id: Optional[str] = None,
|
||||
role: str = "assistant"
|
||||
) -> Iterator[BaseEvent]:
|
||||
"""
|
||||
Create text message events for a complete message.
|
||||
|
||||
Args:
|
||||
content: The message content
|
||||
message_id: Optional message ID (generated if not provided)
|
||||
role: Message role (default: assistant)
|
||||
|
||||
Yields:
|
||||
TextMessageStartEvent, TextMessageContentEvent(s), TextMessageEndEvent
|
||||
"""
|
||||
msg_id = message_id or str(uuid.uuid4())
|
||||
|
||||
yield TextMessageStartEvent(message_id=msg_id, role=role)
|
||||
|
||||
if content:
|
||||
yield TextMessageContentEvent(message_id=msg_id, delta=content)
|
||||
|
||||
yield TextMessageEndEvent(message_id=msg_id)
|
||||
|
||||
|
||||
def stream_text_chunks(
|
||||
chunks: Iterator[str],
|
||||
message_id: Optional[str] = None,
|
||||
role: str = "assistant"
|
||||
) -> Iterator[BaseEvent]:
|
||||
"""
|
||||
Stream text chunks as AG-UI events.
|
||||
|
||||
Args:
|
||||
chunks: Iterator of text chunks
|
||||
message_id: Optional message ID
|
||||
role: Message role
|
||||
|
||||
Yields:
|
||||
AG-UI events for the text stream
|
||||
"""
|
||||
msg_id = message_id or str(uuid.uuid4())
|
||||
|
||||
yield TextMessageStartEvent(message_id=msg_id, role=role)
|
||||
|
||||
for chunk in chunks:
|
||||
if chunk:
|
||||
yield TextMessageContentEvent(message_id=msg_id, delta=chunk)
|
||||
|
||||
yield TextMessageEndEvent(message_id=msg_id)
|
||||
|
||||
|
||||
def create_tool_call_events(
|
||||
tool_call_id: str,
|
||||
tool_name: str,
|
||||
arguments: str,
|
||||
parent_message_id: Optional[str] = None
|
||||
) -> Iterator[BaseEvent]:
|
||||
"""
|
||||
Create tool call events.
|
||||
|
||||
Args:
|
||||
tool_call_id: Unique ID for the tool call
|
||||
tool_name: Name of the tool being called
|
||||
arguments: JSON string of arguments
|
||||
parent_message_id: Optional parent message ID
|
||||
|
||||
Yields:
|
||||
ToolCallStartEvent, ToolCallArgsEvent, ToolCallEndEvent
|
||||
"""
|
||||
yield ToolCallStartEvent(
|
||||
tool_call_id=tool_call_id,
|
||||
tool_call_name=tool_name,
|
||||
parent_message_id=parent_message_id
|
||||
)
|
||||
|
||||
yield ToolCallArgsEvent(
|
||||
tool_call_id=tool_call_id,
|
||||
delta=arguments
|
||||
)
|
||||
|
||||
yield ToolCallEndEvent(tool_call_id=tool_call_id)
|
||||
|
||||
|
||||
def create_tool_result_event(
|
||||
tool_call_id: str,
|
||||
content: str,
|
||||
message_id: Optional[str] = None
|
||||
) -> ToolCallResultEvent:
|
||||
"""
|
||||
Create a tool result event.
|
||||
|
||||
Args:
|
||||
tool_call_id: ID of the tool call this is a result for
|
||||
content: Result content
|
||||
message_id: Optional message ID
|
||||
|
||||
Returns:
|
||||
ToolCallResultEvent
|
||||
"""
|
||||
return ToolCallResultEvent(
|
||||
message_id=message_id or str(uuid.uuid4()),
|
||||
tool_call_id=tool_call_id,
|
||||
content=content
|
||||
)
|
||||
|
||||
|
||||
# Run Lifecycle Events
|
||||
|
||||
def create_run_started_event(thread_id: str, run_id: str) -> RunStartedEvent:
|
||||
"""Create a run started event."""
|
||||
return RunStartedEvent(thread_id=thread_id, run_id=run_id)
|
||||
|
||||
|
||||
def create_run_finished_event(
|
||||
thread_id: str,
|
||||
run_id: str,
|
||||
result: Optional[Any] = None
|
||||
) -> RunFinishedEvent:
|
||||
"""Create a run finished event."""
|
||||
return RunFinishedEvent(thread_id=thread_id, run_id=run_id, result=result)
|
||||
|
||||
|
||||
def create_run_error_event(
|
||||
message: str,
|
||||
code: Optional[str] = None
|
||||
) -> RunErrorEvent:
|
||||
"""Create a run error event."""
|
||||
return RunErrorEvent(message=message, code=code)
|
||||
|
||||
|
||||
# Step Events
|
||||
|
||||
def create_step_started_event(step_name: str) -> StepStartedEvent:
|
||||
"""Create a step started event."""
|
||||
return StepStartedEvent(step_name=step_name)
|
||||
|
||||
|
||||
def create_step_finished_event(step_name: str) -> StepFinishedEvent:
|
||||
"""Create a step finished event."""
|
||||
return StepFinishedEvent(step_name=step_name)
|
||||
|
||||
|
||||
# State Events
|
||||
|
||||
def create_state_snapshot_event(state: Dict[str, Any]) -> StateSnapshotEvent:
|
||||
"""Create a state snapshot event."""
|
||||
return StateSnapshotEvent(snapshot=state)
|
||||
|
||||
|
||||
# Async Streaming
|
||||
|
||||
async def async_stream_response(
|
||||
response_stream: AsyncIterator[str],
|
||||
thread_id: str,
|
||||
run_id: str
|
||||
) -> AsyncIterator[BaseEvent]:
|
||||
"""
|
||||
Stream an async response as AG-UI events.
|
||||
|
||||
Args:
|
||||
response_stream: Async iterator of response chunks
|
||||
thread_id: Thread ID
|
||||
run_id: Run ID
|
||||
|
||||
Yields:
|
||||
AG-UI events
|
||||
"""
|
||||
# Emit run started
|
||||
yield create_run_started_event(thread_id, run_id)
|
||||
|
||||
message_id = str(uuid.uuid4())
|
||||
message_started = False
|
||||
|
||||
try:
|
||||
async for chunk in response_stream:
|
||||
if not message_started:
|
||||
yield TextMessageStartEvent(message_id=message_id, role="assistant")
|
||||
message_started = True
|
||||
|
||||
if chunk:
|
||||
yield TextMessageContentEvent(message_id=message_id, delta=chunk)
|
||||
|
||||
if message_started:
|
||||
yield TextMessageEndEvent(message_id=message_id)
|
||||
|
||||
# Emit run finished
|
||||
yield create_run_finished_event(thread_id, run_id)
|
||||
|
||||
except Exception as e:
|
||||
if message_started:
|
||||
yield TextMessageEndEvent(message_id=message_id)
|
||||
yield create_run_error_event(str(e))
|
||||
|
||||
|
||||
async def async_stream_agent_response(
|
||||
agent,
|
||||
user_input: str,
|
||||
thread_id: str,
|
||||
run_id: str,
|
||||
session_state: Optional[Dict[str, Any]] = None,
|
||||
messages: Optional[List[Dict[str, Any]]] = None
|
||||
) -> AsyncIterator[BaseEvent]:
|
||||
"""
|
||||
Stream an agent's response as AG-UI events.
|
||||
|
||||
Args:
|
||||
agent: PraisonAI Agent instance
|
||||
user_input: User input string
|
||||
thread_id: Thread ID
|
||||
run_id: Run ID
|
||||
session_state: Optional session state
|
||||
messages: Optional message history
|
||||
|
||||
Yields:
|
||||
AG-UI events
|
||||
"""
|
||||
import asyncio
|
||||
|
||||
# Emit run started
|
||||
yield create_run_started_event(thread_id, run_id)
|
||||
|
||||
message_id = str(uuid.uuid4())
|
||||
|
||||
try:
|
||||
# Check if agent has async chat method
|
||||
if hasattr(agent, 'achat'):
|
||||
response = await agent.achat(user_input)
|
||||
elif hasattr(agent, 'chat'):
|
||||
# Run sync chat in executor
|
||||
loop = asyncio.get_event_loop()
|
||||
response = await loop.run_in_executor(None, agent.chat, user_input)
|
||||
else:
|
||||
raise ValueError("Agent must have 'chat' or 'achat' method")
|
||||
|
||||
# Emit text message events
|
||||
yield TextMessageStartEvent(message_id=message_id, role="assistant")
|
||||
|
||||
if response:
|
||||
yield TextMessageContentEvent(message_id=message_id, delta=str(response))
|
||||
|
||||
yield TextMessageEndEvent(message_id=message_id)
|
||||
|
||||
# Emit run finished
|
||||
yield create_run_finished_event(thread_id, run_id)
|
||||
|
||||
except Exception as e:
|
||||
yield create_run_error_event(str(e))
|
||||
|
||||
|
||||
async def async_stream_agents_response(
|
||||
agents,
|
||||
user_input: str,
|
||||
thread_id: str,
|
||||
run_id: str,
|
||||
session_state: Optional[Dict[str, Any]] = None
|
||||
) -> AsyncIterator[BaseEvent]:
|
||||
"""
|
||||
Stream a PraisonAIAgents workflow response as AG-UI events.
|
||||
|
||||
Args:
|
||||
agents: PraisonAIAgents instance
|
||||
user_input: User input string
|
||||
thread_id: Thread ID
|
||||
run_id: Run ID
|
||||
session_state: Optional session state
|
||||
|
||||
Yields:
|
||||
AG-UI events
|
||||
"""
|
||||
import asyncio
|
||||
|
||||
# Emit run started
|
||||
yield create_run_started_event(thread_id, run_id)
|
||||
|
||||
message_id = str(uuid.uuid4())
|
||||
|
||||
try:
|
||||
# Check if agents has async start method
|
||||
if hasattr(agents, 'astart'):
|
||||
result = await agents.astart(user_input)
|
||||
elif hasattr(agents, 'start'):
|
||||
# Run sync start in executor
|
||||
loop = asyncio.get_event_loop()
|
||||
result = await loop.run_in_executor(None, agents.start, user_input)
|
||||
else:
|
||||
raise ValueError("Agents must have 'start' or 'astart' method")
|
||||
|
||||
# Emit text message events with result
|
||||
yield TextMessageStartEvent(message_id=message_id, role="assistant")
|
||||
|
||||
if result:
|
||||
# Handle different result types
|
||||
if isinstance(result, dict):
|
||||
content = result.get("output", str(result))
|
||||
elif hasattr(result, "raw"):
|
||||
content = result.raw
|
||||
else:
|
||||
content = str(result)
|
||||
|
||||
yield TextMessageContentEvent(message_id=message_id, delta=content)
|
||||
|
||||
yield TextMessageEndEvent(message_id=message_id)
|
||||
|
||||
# Emit run finished
|
||||
yield create_run_finished_event(thread_id, run_id)
|
||||
|
||||
except Exception as e:
|
||||
yield create_run_error_event(str(e))
|
||||
@@ -0,0 +1,183 @@
|
||||
"""
|
||||
AG-UI Protocol Types
|
||||
|
||||
This module defines the event types and message types for the AG-UI protocol,
|
||||
following the ag-ui-protocol specification.
|
||||
"""
|
||||
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Literal, Optional, Union
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
class EventType(str, Enum):
|
||||
"""AG-UI Event Types."""
|
||||
TEXT_MESSAGE_START = "TEXT_MESSAGE_START"
|
||||
TEXT_MESSAGE_CONTENT = "TEXT_MESSAGE_CONTENT"
|
||||
TEXT_MESSAGE_END = "TEXT_MESSAGE_END"
|
||||
TOOL_CALL_START = "TOOL_CALL_START"
|
||||
TOOL_CALL_ARGS = "TOOL_CALL_ARGS"
|
||||
TOOL_CALL_END = "TOOL_CALL_END"
|
||||
TOOL_CALL_RESULT = "TOOL_CALL_RESULT"
|
||||
STATE_SNAPSHOT = "STATE_SNAPSHOT"
|
||||
STATE_DELTA = "STATE_DELTA"
|
||||
RUN_STARTED = "RUN_STARTED"
|
||||
RUN_FINISHED = "RUN_FINISHED"
|
||||
RUN_ERROR = "RUN_ERROR"
|
||||
STEP_STARTED = "STEP_STARTED"
|
||||
STEP_FINISHED = "STEP_FINISHED"
|
||||
CUSTOM = "CUSTOM"
|
||||
|
||||
|
||||
class BaseEvent(BaseModel):
|
||||
"""Base event for all AG-UI events."""
|
||||
type: EventType
|
||||
timestamp: Optional[int] = None
|
||||
|
||||
model_config = {"use_enum_values": True}
|
||||
|
||||
|
||||
# Text Message Events
|
||||
class TextMessageStartEvent(BaseEvent):
|
||||
"""Event indicating the start of a text message."""
|
||||
type: Literal["TEXT_MESSAGE_START"] = "TEXT_MESSAGE_START"
|
||||
message_id: str
|
||||
role: str = "assistant"
|
||||
|
||||
|
||||
class TextMessageContentEvent(BaseEvent):
|
||||
"""Event containing text message content."""
|
||||
type: Literal["TEXT_MESSAGE_CONTENT"] = "TEXT_MESSAGE_CONTENT"
|
||||
message_id: str
|
||||
delta: str
|
||||
|
||||
|
||||
class TextMessageEndEvent(BaseEvent):
|
||||
"""Event indicating the end of a text message."""
|
||||
type: Literal["TEXT_MESSAGE_END"] = "TEXT_MESSAGE_END"
|
||||
message_id: str
|
||||
|
||||
|
||||
# Tool Call Events
|
||||
class ToolCallStartEvent(BaseEvent):
|
||||
"""Event indicating the start of a tool call."""
|
||||
type: Literal["TOOL_CALL_START"] = "TOOL_CALL_START"
|
||||
tool_call_id: str
|
||||
tool_call_name: str
|
||||
parent_message_id: Optional[str] = None
|
||||
|
||||
|
||||
class ToolCallArgsEvent(BaseEvent):
|
||||
"""Event containing tool call arguments."""
|
||||
type: Literal["TOOL_CALL_ARGS"] = "TOOL_CALL_ARGS"
|
||||
tool_call_id: str
|
||||
delta: str
|
||||
|
||||
|
||||
class ToolCallEndEvent(BaseEvent):
|
||||
"""Event indicating the end of a tool call."""
|
||||
type: Literal["TOOL_CALL_END"] = "TOOL_CALL_END"
|
||||
tool_call_id: str
|
||||
|
||||
|
||||
class ToolCallResultEvent(BaseEvent):
|
||||
"""Event containing tool call result."""
|
||||
type: Literal["TOOL_CALL_RESULT"] = "TOOL_CALL_RESULT"
|
||||
message_id: str
|
||||
tool_call_id: str
|
||||
content: str
|
||||
role: Optional[Literal["tool"]] = "tool"
|
||||
|
||||
|
||||
# Run Lifecycle Events
|
||||
class RunStartedEvent(BaseEvent):
|
||||
"""Event indicating a run has started."""
|
||||
type: Literal["RUN_STARTED"] = "RUN_STARTED"
|
||||
thread_id: str
|
||||
run_id: str
|
||||
parent_run_id: Optional[str] = None
|
||||
|
||||
|
||||
class RunFinishedEvent(BaseEvent):
|
||||
"""Event indicating a run has finished."""
|
||||
type: Literal["RUN_FINISHED"] = "RUN_FINISHED"
|
||||
thread_id: str
|
||||
run_id: str
|
||||
result: Optional[Any] = None
|
||||
|
||||
|
||||
class RunErrorEvent(BaseEvent):
|
||||
"""Event indicating a run error."""
|
||||
type: Literal["RUN_ERROR"] = "RUN_ERROR"
|
||||
message: str
|
||||
code: Optional[str] = None
|
||||
|
||||
|
||||
# Step Events
|
||||
class StepStartedEvent(BaseEvent):
|
||||
"""Event indicating a step has started."""
|
||||
type: Literal["STEP_STARTED"] = "STEP_STARTED"
|
||||
step_name: str
|
||||
|
||||
|
||||
class StepFinishedEvent(BaseEvent):
|
||||
"""Event indicating a step has finished."""
|
||||
type: Literal["STEP_FINISHED"] = "STEP_FINISHED"
|
||||
step_name: str
|
||||
|
||||
|
||||
# State Events
|
||||
class StateSnapshotEvent(BaseEvent):
|
||||
"""Event containing a state snapshot."""
|
||||
type: Literal["STATE_SNAPSHOT"] = "STATE_SNAPSHOT"
|
||||
snapshot: Dict[str, Any]
|
||||
|
||||
|
||||
# Message Types
|
||||
class FunctionCall(BaseModel):
|
||||
"""Function call in a tool call."""
|
||||
name: str
|
||||
arguments: str
|
||||
|
||||
|
||||
class ToolCall(BaseModel):
|
||||
"""Tool call in a message."""
|
||||
id: str
|
||||
function: FunctionCall
|
||||
type: str = "function"
|
||||
|
||||
|
||||
class Message(BaseModel):
|
||||
"""AG-UI Message type."""
|
||||
role: Literal["user", "assistant", "system", "tool"]
|
||||
content: Optional[str] = None
|
||||
tool_calls: Optional[List[ToolCall]] = None
|
||||
tool_call_id: Optional[str] = None
|
||||
name: Optional[str] = None
|
||||
|
||||
|
||||
class RunAgentInput(BaseModel):
|
||||
"""Input for running an agent."""
|
||||
thread_id: str
|
||||
run_id: Optional[str] = None
|
||||
messages: Optional[List[Message]] = Field(default_factory=list)
|
||||
state: Optional[Dict[str, Any]] = None
|
||||
forwarded_props: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
# Union type for all events
|
||||
Event = Union[
|
||||
TextMessageStartEvent,
|
||||
TextMessageContentEvent,
|
||||
TextMessageEndEvent,
|
||||
ToolCallStartEvent,
|
||||
ToolCallArgsEvent,
|
||||
ToolCallEndEvent,
|
||||
ToolCallResultEvent,
|
||||
StateSnapshotEvent,
|
||||
RunStartedEvent,
|
||||
RunFinishedEvent,
|
||||
RunErrorEvent,
|
||||
StepStartedEvent,
|
||||
StepFinishedEvent,
|
||||
]
|
||||
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
|
||||
|
||||
[project]
|
||||
name = "praisonaiagents"
|
||||
version = "0.1.14"
|
||||
version = "0.1.21"
|
||||
description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
"""A2A Protocol Tests"""
|
||||
@@ -0,0 +1,135 @@
|
||||
"""
|
||||
Tests for Main A2A Class
|
||||
|
||||
TDD: Write tests first, then implement A2A class.
|
||||
"""
|
||||
|
||||
|
||||
class TestA2AClass:
|
||||
"""Tests for A2A main class."""
|
||||
|
||||
def test_a2a_creation_with_agent(self):
|
||||
"""Test creating A2A with single agent."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test")
|
||||
a2a = A2A(agent=agent)
|
||||
|
||||
assert a2a.agent is not None
|
||||
assert a2a.name == "Test"
|
||||
|
||||
def test_a2a_creation_with_custom_name(self):
|
||||
"""Test creating A2A with custom name."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test")
|
||||
a2a = A2A(agent=agent, name="Custom Name")
|
||||
|
||||
assert a2a.name == "Custom Name"
|
||||
|
||||
def test_a2a_requires_agent(self):
|
||||
"""Test A2A requires agent or agents."""
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
import pytest
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
A2A()
|
||||
|
||||
def test_a2a_get_agent_card(self):
|
||||
"""Test getting Agent Card from A2A."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
agent = Agent(name="Card Test", role="Tester", goal="Test")
|
||||
a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
|
||||
|
||||
card = a2a.get_agent_card()
|
||||
|
||||
assert card.name == "Card Test"
|
||||
assert card.url == "http://localhost:8000/a2a"
|
||||
|
||||
def test_a2a_get_router(self):
|
||||
"""Test getting FastAPI router from A2A."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
agent = Agent(name="Router Test", role="Tester", goal="Test")
|
||||
a2a = A2A(agent=agent)
|
||||
|
||||
router = a2a.get_router()
|
||||
|
||||
assert router is not None
|
||||
# Check router has routes
|
||||
assert len(router.routes) > 0
|
||||
|
||||
|
||||
class TestA2ARouter:
|
||||
"""Tests for A2A FastAPI router endpoints."""
|
||||
|
||||
def test_agent_card_endpoint(self):
|
||||
"""Test /.well-known/agent.json endpoint."""
|
||||
from fastapi.testclient import TestClient
|
||||
from fastapi import FastAPI
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
agent = Agent(name="Endpoint Test", role="Tester", goal="Test")
|
||||
a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
response = client.get("/.well-known/agent.json")
|
||||
|
||||
assert response.status_code == 200
|
||||
data = response.json()
|
||||
assert data["name"] == "Endpoint Test"
|
||||
|
||||
def test_status_endpoint(self):
|
||||
"""Test /status endpoint."""
|
||||
from fastapi.testclient import TestClient
|
||||
from fastapi import FastAPI
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
agent = Agent(name="Status Test", role="Tester", goal="Test")
|
||||
a2a = A2A(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
response = client.get("/status")
|
||||
|
||||
assert response.status_code == 200
|
||||
data = response.json()
|
||||
assert data["status"] == "ok"
|
||||
|
||||
|
||||
class TestA2AWithTools:
|
||||
"""Tests for A2A with agent tools."""
|
||||
|
||||
def test_a2a_agent_card_includes_skills(self):
|
||||
"""Test Agent Card includes skills from tools."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a import A2A
|
||||
|
||||
def my_tool(x: str) -> str:
|
||||
"""A test tool."""
|
||||
return x
|
||||
|
||||
agent = Agent(
|
||||
name="Tool Agent",
|
||||
role="Helper",
|
||||
goal="Help",
|
||||
tools=[my_tool]
|
||||
)
|
||||
a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
|
||||
|
||||
card = a2a.get_agent_card()
|
||||
|
||||
assert card.skills is not None
|
||||
assert len(card.skills) >= 1
|
||||
@@ -0,0 +1,200 @@
|
||||
"""
|
||||
Tests for A2A Agent Card Generation
|
||||
|
||||
TDD: Write tests first, then implement agent_card module.
|
||||
"""
|
||||
|
||||
import json
|
||||
|
||||
|
||||
class TestAgentCardGeneration:
|
||||
"""Tests for generating Agent Card from PraisonAI Agent."""
|
||||
|
||||
def test_generate_agent_card_basic(self):
|
||||
"""Test generating Agent Card from basic Agent."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(
|
||||
name="Test Agent",
|
||||
role="Test Role",
|
||||
goal="Test Goal"
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
assert card.name == "Test Agent"
|
||||
assert card.url == "http://localhost:8000/a2a"
|
||||
assert card.version == "1.0.0"
|
||||
|
||||
def test_generate_agent_card_with_description(self):
|
||||
"""Test Agent Card includes description from role."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(
|
||||
name="Research Agent",
|
||||
role="Research Analyst",
|
||||
goal="Research topics thoroughly"
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
assert card.description is not None
|
||||
assert "Research" in card.description
|
||||
|
||||
def test_generate_agent_card_with_instructions(self):
|
||||
"""Test Agent Card from Agent with instructions."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(
|
||||
instructions="You are a helpful assistant that answers questions."
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
assert card.name is not None
|
||||
assert card.description is not None
|
||||
|
||||
def test_generate_agent_card_capabilities(self):
|
||||
"""Test Agent Card has correct capabilities."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test")
|
||||
|
||||
card = generate_agent_card(
|
||||
agent,
|
||||
url="http://localhost:8000/a2a",
|
||||
streaming=True
|
||||
)
|
||||
|
||||
assert card.capabilities.streaming is True
|
||||
|
||||
|
||||
class TestSkillsExtraction:
|
||||
"""Tests for extracting skills from Agent tools."""
|
||||
|
||||
def test_extract_skills_from_function(self):
|
||||
"""Test extracting skill from a function tool."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
def search_web(query: str) -> str:
|
||||
"""Search the web for information."""
|
||||
return f"Results for: {query}"
|
||||
|
||||
agent = Agent(
|
||||
name="Search Agent",
|
||||
role="Searcher",
|
||||
goal="Search the web",
|
||||
tools=[search_web]
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
assert card.skills is not None
|
||||
assert len(card.skills) >= 1
|
||||
|
||||
skill_names = [s.name for s in card.skills]
|
||||
assert "search_web" in skill_names
|
||||
|
||||
def test_extract_skills_with_description(self):
|
||||
"""Test skill description comes from function docstring."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
def calculate(expression: str) -> str:
|
||||
"""Calculate a mathematical expression."""
|
||||
return str(eval(expression))
|
||||
|
||||
agent = Agent(
|
||||
name="Calculator",
|
||||
role="Math Helper",
|
||||
goal="Do math",
|
||||
tools=[calculate]
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
calc_skill = next((s for s in card.skills if s.name == "calculate"), None)
|
||||
assert calc_skill is not None
|
||||
assert "mathematical" in calc_skill.description.lower()
|
||||
|
||||
def test_extract_skills_multiple_tools(self):
|
||||
"""Test extracting skills from multiple tools."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
def tool_one(x: str) -> str:
|
||||
"""First tool."""
|
||||
return x
|
||||
|
||||
def tool_two(y: str) -> str:
|
||||
"""Second tool."""
|
||||
return y
|
||||
|
||||
agent = Agent(
|
||||
name="Multi Tool Agent",
|
||||
role="Helper",
|
||||
goal="Help",
|
||||
tools=[tool_one, tool_two]
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
assert len(card.skills) >= 2
|
||||
|
||||
def test_no_skills_when_no_tools(self):
|
||||
"""Test Agent Card with no tools has empty skills."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(
|
||||
name="Simple Agent",
|
||||
role="Helper",
|
||||
goal="Help"
|
||||
)
|
||||
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
# Skills should be None or empty list
|
||||
assert card.skills is None or len(card.skills) == 0
|
||||
|
||||
|
||||
class TestAgentCardSerialization:
|
||||
"""Tests for Agent Card JSON serialization."""
|
||||
|
||||
def test_agent_card_to_json(self):
|
||||
"""Test Agent Card can be serialized to JSON."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test")
|
||||
card = generate_agent_card(agent, url="http://localhost:8000/a2a")
|
||||
|
||||
json_str = card.model_dump_json()
|
||||
data = json.loads(json_str)
|
||||
|
||||
assert "name" in data
|
||||
assert "url" in data
|
||||
assert "capabilities" in data
|
||||
|
||||
def test_agent_card_camel_case_keys(self):
|
||||
"""Test Agent Card JSON uses camelCase keys."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2a.agent_card import generate_agent_card
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test")
|
||||
card = generate_agent_card(
|
||||
agent,
|
||||
url="http://localhost:8000/a2a",
|
||||
streaming=True
|
||||
)
|
||||
|
||||
# Use by_alias to get camelCase
|
||||
data = card.model_dump(by_alias=True)
|
||||
|
||||
# Check capabilities uses camelCase
|
||||
assert "pushNotifications" in data["capabilities"]
|
||||
@@ -0,0 +1,190 @@
|
||||
"""
|
||||
Tests for A2A Message Conversion
|
||||
|
||||
TDD: Write tests first, then implement conversion module.
|
||||
"""
|
||||
|
||||
|
||||
class TestA2AToPraisonAI:
|
||||
"""Tests for converting A2A messages to PraisonAI format."""
|
||||
|
||||
def test_convert_user_message(self):
|
||||
"""Test converting A2A user message to PraisonAI format."""
|
||||
from praisonaiagents.ui.a2a.conversion import a2a_to_praisonai_messages
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
a2a_msg = Message(
|
||||
message_id="msg-1",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello, how are you?")]
|
||||
)
|
||||
|
||||
result = a2a_to_praisonai_messages([a2a_msg])
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "user"
|
||||
assert result[0]["content"] == "Hello, how are you?"
|
||||
|
||||
def test_convert_agent_message(self):
|
||||
"""Test converting A2A agent message to PraisonAI format."""
|
||||
from praisonaiagents.ui.a2a.conversion import a2a_to_praisonai_messages
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
a2a_msg = Message(
|
||||
message_id="msg-2",
|
||||
role=Role.AGENT,
|
||||
parts=[TextPart(text="I'm doing well, thanks!")]
|
||||
)
|
||||
|
||||
result = a2a_to_praisonai_messages([a2a_msg])
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "assistant"
|
||||
assert result[0]["content"] == "I'm doing well, thanks!"
|
||||
|
||||
def test_convert_multiple_parts(self):
|
||||
"""Test converting message with multiple text parts."""
|
||||
from praisonaiagents.ui.a2a.conversion import a2a_to_praisonai_messages
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
a2a_msg = Message(
|
||||
message_id="msg-3",
|
||||
role=Role.USER,
|
||||
parts=[
|
||||
TextPart(text="First part."),
|
||||
TextPart(text="Second part.")
|
||||
]
|
||||
)
|
||||
|
||||
result = a2a_to_praisonai_messages([a2a_msg])
|
||||
|
||||
assert "First part" in result[0]["content"]
|
||||
assert "Second part" in result[0]["content"]
|
||||
|
||||
def test_convert_conversation_history(self):
|
||||
"""Test converting full conversation history."""
|
||||
from praisonaiagents.ui.a2a.conversion import a2a_to_praisonai_messages
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
messages = [
|
||||
Message(message_id="m1", role=Role.USER, parts=[TextPart(text="Hi")]),
|
||||
Message(message_id="m2", role=Role.AGENT, parts=[TextPart(text="Hello!")]),
|
||||
Message(message_id="m3", role=Role.USER, parts=[TextPart(text="How are you?")]),
|
||||
]
|
||||
|
||||
result = a2a_to_praisonai_messages(messages)
|
||||
|
||||
assert len(result) == 3
|
||||
assert result[0]["role"] == "user"
|
||||
assert result[1]["role"] == "assistant"
|
||||
assert result[2]["role"] == "user"
|
||||
|
||||
|
||||
class TestPraisonAIToA2A:
|
||||
"""Tests for converting PraisonAI responses to A2A format."""
|
||||
|
||||
def test_convert_string_response(self):
|
||||
"""Test converting string response to A2A Message."""
|
||||
from praisonaiagents.ui.a2a.conversion import praisonai_to_a2a_message
|
||||
|
||||
response = "This is the agent's response."
|
||||
|
||||
result = praisonai_to_a2a_message(response)
|
||||
|
||||
assert result.role.value == "agent"
|
||||
assert len(result.parts) == 1
|
||||
assert result.parts[0].text == response
|
||||
|
||||
def test_convert_response_with_context(self):
|
||||
"""Test converting response with context_id."""
|
||||
from praisonaiagents.ui.a2a.conversion import praisonai_to_a2a_message
|
||||
|
||||
response = "Response text"
|
||||
|
||||
result = praisonai_to_a2a_message(response, context_id="ctx-123")
|
||||
|
||||
assert result.context_id == "ctx-123"
|
||||
|
||||
def test_convert_response_with_task(self):
|
||||
"""Test converting response with task_id."""
|
||||
from praisonaiagents.ui.a2a.conversion import praisonai_to_a2a_message
|
||||
|
||||
response = "Response text"
|
||||
|
||||
result = praisonai_to_a2a_message(response, task_id="task-456")
|
||||
|
||||
assert result.task_id == "task-456"
|
||||
|
||||
|
||||
class TestArtifactConversion:
|
||||
"""Tests for converting responses to A2A Artifacts."""
|
||||
|
||||
def test_create_artifact_from_response(self):
|
||||
"""Test creating Artifact from response."""
|
||||
from praisonaiagents.ui.a2a.conversion import create_artifact
|
||||
|
||||
response = "Generated content here."
|
||||
|
||||
artifact = create_artifact(response)
|
||||
|
||||
assert artifact.artifact_id is not None
|
||||
assert len(artifact.parts) == 1
|
||||
assert artifact.parts[0].text == response
|
||||
|
||||
def test_create_artifact_with_name(self):
|
||||
"""Test creating Artifact with name."""
|
||||
from praisonaiagents.ui.a2a.conversion import create_artifact
|
||||
|
||||
response = "Report content"
|
||||
|
||||
artifact = create_artifact(response, name="Report", description="Generated report")
|
||||
|
||||
assert artifact.name == "Report"
|
||||
assert artifact.description == "Generated report"
|
||||
|
||||
|
||||
class TestExtractUserInput:
|
||||
"""Tests for extracting user input from A2A messages."""
|
||||
|
||||
def test_extract_from_single_message(self):
|
||||
"""Test extracting user input from single message."""
|
||||
from praisonaiagents.ui.a2a.conversion import extract_user_input
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
msg = Message(
|
||||
message_id="m1",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="What is AI?")]
|
||||
)
|
||||
|
||||
result = extract_user_input([msg])
|
||||
|
||||
assert result == "What is AI?"
|
||||
|
||||
def test_extract_from_conversation(self):
|
||||
"""Test extracting last user input from conversation."""
|
||||
from praisonaiagents.ui.a2a.conversion import extract_user_input
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
messages = [
|
||||
Message(message_id="m1", role=Role.USER, parts=[TextPart(text="First question")]),
|
||||
Message(message_id="m2", role=Role.AGENT, parts=[TextPart(text="Answer")]),
|
||||
Message(message_id="m3", role=Role.USER, parts=[TextPart(text="Follow up question")]),
|
||||
]
|
||||
|
||||
result = extract_user_input(messages)
|
||||
|
||||
assert result == "Follow up question"
|
||||
|
||||
def test_extract_empty_when_no_user_message(self):
|
||||
"""Test extracting returns empty when no user message."""
|
||||
from praisonaiagents.ui.a2a.conversion import extract_user_input
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
messages = [
|
||||
Message(message_id="m1", role=Role.AGENT, parts=[TextPart(text="Hello")]),
|
||||
]
|
||||
|
||||
result = extract_user_input(messages)
|
||||
|
||||
assert result == ""
|
||||
@@ -0,0 +1,116 @@
|
||||
"""
|
||||
Tests for A2A Streaming Events
|
||||
"""
|
||||
|
||||
|
||||
class TestA2AEventEncoder:
|
||||
"""Tests for A2AEventEncoder."""
|
||||
|
||||
def test_encode_event(self):
|
||||
"""Test encoding a generic event."""
|
||||
from praisonaiagents.ui.a2a.streaming import A2AEventEncoder
|
||||
|
||||
result = A2AEventEncoder.encode_event("test", {"key": "value"})
|
||||
|
||||
assert "event: test" in result
|
||||
assert "data:" in result
|
||||
assert "key" in result
|
||||
|
||||
def test_encode_task_status(self):
|
||||
"""Test encoding TaskStatusUpdateEvent."""
|
||||
from praisonaiagents.ui.a2a.streaming import A2AEventEncoder
|
||||
from praisonaiagents.ui.a2a.types import TaskStatusUpdateEvent, TaskStatus, TaskState
|
||||
|
||||
event = TaskStatusUpdateEvent(
|
||||
task_id="task-123",
|
||||
status=TaskStatus(state=TaskState.WORKING),
|
||||
final=False,
|
||||
)
|
||||
|
||||
result = A2AEventEncoder.encode_task_status(event)
|
||||
|
||||
assert "event: task.status" in result
|
||||
assert "task-123" in result
|
||||
|
||||
def test_encode_task_artifact(self):
|
||||
"""Test encoding TaskArtifactUpdateEvent."""
|
||||
from praisonaiagents.ui.a2a.streaming import A2AEventEncoder
|
||||
from praisonaiagents.ui.a2a.types import TaskArtifactUpdateEvent, Artifact, TextPart
|
||||
|
||||
artifact = Artifact(
|
||||
artifact_id="art-1",
|
||||
parts=[TextPart(text="Result")]
|
||||
)
|
||||
event = TaskArtifactUpdateEvent(
|
||||
task_id="task-456",
|
||||
artifact=artifact,
|
||||
last_chunk=True,
|
||||
)
|
||||
|
||||
result = A2AEventEncoder.encode_task_artifact(event)
|
||||
|
||||
assert "event: task.artifact" in result
|
||||
assert "art-1" in result
|
||||
|
||||
def test_encode_done(self):
|
||||
"""Test encoding done event."""
|
||||
from praisonaiagents.ui.a2a.streaming import A2AEventEncoder
|
||||
|
||||
result = A2AEventEncoder.encode_done()
|
||||
|
||||
assert "event: done" in result
|
||||
|
||||
|
||||
class TestCreateEvents:
|
||||
"""Tests for event creation helpers."""
|
||||
|
||||
def test_create_status_event(self):
|
||||
"""Test creating status event."""
|
||||
from praisonaiagents.ui.a2a.streaming import create_status_event
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
|
||||
event = create_status_event(
|
||||
task_id="task-1",
|
||||
state=TaskState.WORKING,
|
||||
)
|
||||
|
||||
assert event.task_id == "task-1"
|
||||
assert event.status.state == TaskState.WORKING
|
||||
|
||||
def test_create_status_event_final(self):
|
||||
"""Test creating final status event."""
|
||||
from praisonaiagents.ui.a2a.streaming import create_status_event
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
|
||||
event = create_status_event(
|
||||
task_id="task-2",
|
||||
state=TaskState.COMPLETED,
|
||||
final=True,
|
||||
)
|
||||
|
||||
assert event.final is True
|
||||
|
||||
def test_create_artifact_event(self):
|
||||
"""Test creating artifact event."""
|
||||
from praisonaiagents.ui.a2a.streaming import create_artifact_event
|
||||
|
||||
event = create_artifact_event(
|
||||
task_id="task-3",
|
||||
content="Generated content",
|
||||
)
|
||||
|
||||
assert event.task_id == "task-3"
|
||||
assert event.artifact is not None
|
||||
assert len(event.artifact.parts) == 1
|
||||
|
||||
def test_create_artifact_event_last_chunk(self):
|
||||
"""Test creating last chunk artifact event."""
|
||||
from praisonaiagents.ui.a2a.streaming import create_artifact_event
|
||||
|
||||
event = create_artifact_event(
|
||||
task_id="task-4",
|
||||
content="Final content",
|
||||
last_chunk=True,
|
||||
)
|
||||
|
||||
assert event.last_chunk is True
|
||||
@@ -0,0 +1,225 @@
|
||||
"""
|
||||
Tests for A2A Task Store
|
||||
|
||||
TDD: Write tests first, then implement task_store module.
|
||||
"""
|
||||
|
||||
|
||||
class TestTaskStore:
|
||||
"""Tests for TaskStore class."""
|
||||
|
||||
def test_create_task(self):
|
||||
"""Test creating a new task."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart, TaskState
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-1",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
|
||||
task = store.create_task(msg)
|
||||
|
||||
assert task.id is not None
|
||||
assert task.status.state == TaskState.SUBMITTED
|
||||
|
||||
def test_create_task_with_context(self):
|
||||
"""Test creating task with context_id."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-2",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")],
|
||||
context_id="ctx-123"
|
||||
)
|
||||
|
||||
task = store.create_task(msg)
|
||||
|
||||
assert task.context_id == "ctx-123"
|
||||
|
||||
def test_get_task(self):
|
||||
"""Test retrieving a task by ID."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-3",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
|
||||
created = store.create_task(msg)
|
||||
retrieved = store.get_task(created.id)
|
||||
|
||||
assert retrieved is not None
|
||||
assert retrieved.id == created.id
|
||||
|
||||
def test_get_task_not_found(self):
|
||||
"""Test getting non-existent task returns None."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
|
||||
store = TaskStore()
|
||||
result = store.get_task("non-existent-id")
|
||||
|
||||
assert result is None
|
||||
|
||||
def test_update_status(self):
|
||||
"""Test updating task status."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart, TaskState
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-4",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
|
||||
task = store.create_task(msg)
|
||||
updated = store.update_status(task.id, TaskState.WORKING)
|
||||
|
||||
assert updated.status.state == TaskState.WORKING
|
||||
|
||||
def test_update_status_to_completed(self):
|
||||
"""Test updating task to completed state."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart, TaskState
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-5",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
|
||||
task = store.create_task(msg)
|
||||
store.update_status(task.id, TaskState.WORKING)
|
||||
updated = store.update_status(task.id, TaskState.COMPLETED)
|
||||
|
||||
assert updated.status.state == TaskState.COMPLETED
|
||||
|
||||
def test_add_artifact(self):
|
||||
"""Test adding artifact to task."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart, Artifact
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-6",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
|
||||
task = store.create_task(msg)
|
||||
artifact = Artifact(
|
||||
artifact_id="art-1",
|
||||
parts=[TextPart(text="Result")]
|
||||
)
|
||||
|
||||
updated = store.add_artifact(task.id, artifact)
|
||||
|
||||
assert updated.artifacts is not None
|
||||
assert len(updated.artifacts) == 1
|
||||
|
||||
def test_add_message_to_history(self):
|
||||
"""Test adding message to task history."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
store = TaskStore()
|
||||
msg1 = Message(
|
||||
message_id="msg-7",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Question")]
|
||||
)
|
||||
|
||||
task = store.create_task(msg1)
|
||||
|
||||
msg2 = Message(
|
||||
message_id="msg-8",
|
||||
role=Role.AGENT,
|
||||
parts=[TextPart(text="Answer")]
|
||||
)
|
||||
|
||||
updated = store.add_to_history(task.id, msg2)
|
||||
|
||||
assert updated.history is not None
|
||||
assert len(updated.history) >= 1
|
||||
|
||||
def test_list_tasks(self):
|
||||
"""Test listing all tasks."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
store = TaskStore()
|
||||
|
||||
for i in range(3):
|
||||
msg = Message(
|
||||
message_id=f"msg-{i}",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text=f"Message {i}")]
|
||||
)
|
||||
store.create_task(msg)
|
||||
|
||||
tasks = store.list_tasks()
|
||||
|
||||
assert len(tasks) == 3
|
||||
|
||||
def test_cancel_task(self):
|
||||
"""Test cancelling a task."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart, TaskState
|
||||
|
||||
store = TaskStore()
|
||||
msg = Message(
|
||||
message_id="msg-cancel",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
|
||||
task = store.create_task(msg)
|
||||
cancelled = store.cancel_task(task.id)
|
||||
|
||||
assert cancelled.status.state == TaskState.CANCELLED
|
||||
|
||||
|
||||
class TestTaskStoreContextManagement:
|
||||
"""Tests for context management in TaskStore."""
|
||||
|
||||
def test_tasks_grouped_by_context(self):
|
||||
"""Test getting tasks by context_id."""
|
||||
from praisonaiagents.ui.a2a.task_store import TaskStore
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
|
||||
store = TaskStore()
|
||||
|
||||
# Create tasks in context A
|
||||
for i in range(2):
|
||||
msg = Message(
|
||||
message_id=f"msg-a-{i}",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text=f"A{i}")],
|
||||
context_id="context-a"
|
||||
)
|
||||
store.create_task(msg)
|
||||
|
||||
# Create task in context B
|
||||
msg_b = Message(
|
||||
message_id="msg-b-1",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="B1")],
|
||||
context_id="context-b"
|
||||
)
|
||||
store.create_task(msg_b)
|
||||
|
||||
tasks_a = store.list_tasks(context_id="context-a")
|
||||
tasks_b = store.list_tasks(context_id="context-b")
|
||||
|
||||
assert len(tasks_a) == 2
|
||||
assert len(tasks_b) == 1
|
||||
@@ -0,0 +1,395 @@
|
||||
"""
|
||||
Tests for A2A Protocol Types
|
||||
|
||||
TDD: Write tests first, then implement types.
|
||||
"""
|
||||
|
||||
import json
|
||||
from datetime import datetime
|
||||
|
||||
|
||||
class TestTaskState:
|
||||
"""Tests for TaskState enum."""
|
||||
|
||||
def test_task_state_submitted(self):
|
||||
"""Test SUBMITTED state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.SUBMITTED == "submitted"
|
||||
|
||||
def test_task_state_working(self):
|
||||
"""Test WORKING state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.WORKING == "working"
|
||||
|
||||
def test_task_state_completed(self):
|
||||
"""Test COMPLETED state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.COMPLETED == "completed"
|
||||
|
||||
def test_task_state_failed(self):
|
||||
"""Test FAILED state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.FAILED == "failed"
|
||||
|
||||
def test_task_state_cancelled(self):
|
||||
"""Test CANCELLED state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.CANCELLED == "cancelled"
|
||||
|
||||
def test_task_state_input_required(self):
|
||||
"""Test INPUT_REQUIRED state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.INPUT_REQUIRED == "input_required"
|
||||
|
||||
def test_task_state_auth_required(self):
|
||||
"""Test AUTH_REQUIRED state exists."""
|
||||
from praisonaiagents.ui.a2a.types import TaskState
|
||||
assert TaskState.AUTH_REQUIRED == "auth_required"
|
||||
|
||||
|
||||
class TestRole:
|
||||
"""Tests for Role enum."""
|
||||
|
||||
def test_role_user(self):
|
||||
"""Test USER role exists."""
|
||||
from praisonaiagents.ui.a2a.types import Role
|
||||
assert Role.USER == "user"
|
||||
|
||||
def test_role_agent(self):
|
||||
"""Test AGENT role exists."""
|
||||
from praisonaiagents.ui.a2a.types import Role
|
||||
assert Role.AGENT == "agent"
|
||||
|
||||
|
||||
class TestPart:
|
||||
"""Tests for Part models."""
|
||||
|
||||
def test_text_part_creation(self):
|
||||
"""Test TextPart can be created."""
|
||||
from praisonaiagents.ui.a2a.types import TextPart
|
||||
part = TextPart(text="Hello, world!")
|
||||
assert part.text == "Hello, world!"
|
||||
|
||||
def test_file_part_with_uri(self):
|
||||
"""Test FilePart with URI."""
|
||||
from praisonaiagents.ui.a2a.types import FilePart
|
||||
part = FilePart(
|
||||
file_uri="https://example.com/file.pdf",
|
||||
media_type="application/pdf",
|
||||
name="document.pdf"
|
||||
)
|
||||
assert part.file_uri == "https://example.com/file.pdf"
|
||||
assert part.media_type == "application/pdf"
|
||||
|
||||
def test_file_part_with_bytes(self):
|
||||
"""Test FilePart with bytes."""
|
||||
from praisonaiagents.ui.a2a.types import FilePart
|
||||
part = FilePart(
|
||||
file_bytes=b"file content",
|
||||
media_type="text/plain",
|
||||
name="test.txt"
|
||||
)
|
||||
assert part.file_bytes == b"file content"
|
||||
|
||||
def test_data_part_creation(self):
|
||||
"""Test DataPart can be created."""
|
||||
from praisonaiagents.ui.a2a.types import DataPart
|
||||
part = DataPart(data={"key": "value", "count": 42})
|
||||
assert part.data == {"key": "value", "count": 42}
|
||||
|
||||
|
||||
class TestMessage:
|
||||
"""Tests for Message model."""
|
||||
|
||||
def test_message_creation(self):
|
||||
"""Test Message can be created."""
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
msg = Message(
|
||||
message_id="msg-123",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
assert msg.message_id == "msg-123"
|
||||
assert msg.role == Role.USER
|
||||
assert len(msg.parts) == 1
|
||||
|
||||
def test_message_with_context(self):
|
||||
"""Test Message with context_id."""
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
msg = Message(
|
||||
message_id="msg-456",
|
||||
role=Role.AGENT,
|
||||
parts=[TextPart(text="Response")],
|
||||
context_id="ctx-789"
|
||||
)
|
||||
assert msg.context_id == "ctx-789"
|
||||
|
||||
def test_message_with_task(self):
|
||||
"""Test Message with task_id."""
|
||||
from praisonaiagents.ui.a2a.types import Message, Role, TextPart
|
||||
msg = Message(
|
||||
message_id="msg-789",
|
||||
role=Role.AGENT,
|
||||
parts=[TextPart(text="Working on it")],
|
||||
task_id="task-123"
|
||||
)
|
||||
assert msg.task_id == "task-123"
|
||||
|
||||
|
||||
class TestTaskStatus:
|
||||
"""Tests for TaskStatus model."""
|
||||
|
||||
def test_task_status_creation(self):
|
||||
"""Test TaskStatus can be created."""
|
||||
from praisonaiagents.ui.a2a.types import TaskStatus, TaskState
|
||||
status = TaskStatus(state=TaskState.WORKING)
|
||||
assert status.state == TaskState.WORKING
|
||||
|
||||
def test_task_status_with_message(self):
|
||||
"""Test TaskStatus with message."""
|
||||
from praisonaiagents.ui.a2a.types import TaskStatus, TaskState, Message, Role, TextPart
|
||||
msg = Message(
|
||||
message_id="msg-1",
|
||||
role=Role.AGENT,
|
||||
parts=[TextPart(text="Processing...")]
|
||||
)
|
||||
status = TaskStatus(state=TaskState.WORKING, message=msg)
|
||||
assert status.message is not None
|
||||
|
||||
def test_task_status_with_timestamp(self):
|
||||
"""Test TaskStatus with timestamp."""
|
||||
from praisonaiagents.ui.a2a.types import TaskStatus, TaskState
|
||||
ts = datetime.utcnow().isoformat()
|
||||
status = TaskStatus(state=TaskState.COMPLETED, timestamp=ts)
|
||||
assert status.timestamp == ts
|
||||
|
||||
|
||||
class TestTask:
|
||||
"""Tests for Task model."""
|
||||
|
||||
def test_task_creation(self):
|
||||
"""Test Task can be created."""
|
||||
from praisonaiagents.ui.a2a.types import Task, TaskStatus, TaskState
|
||||
task = Task(
|
||||
id="task-123",
|
||||
status=TaskStatus(state=TaskState.SUBMITTED)
|
||||
)
|
||||
assert task.id == "task-123"
|
||||
assert task.status.state == TaskState.SUBMITTED
|
||||
|
||||
def test_task_with_context(self):
|
||||
"""Test Task with context_id."""
|
||||
from praisonaiagents.ui.a2a.types import Task, TaskStatus, TaskState
|
||||
task = Task(
|
||||
id="task-456",
|
||||
context_id="ctx-789",
|
||||
status=TaskStatus(state=TaskState.WORKING)
|
||||
)
|
||||
assert task.context_id == "ctx-789"
|
||||
|
||||
def test_task_with_artifacts(self):
|
||||
"""Test Task with artifacts."""
|
||||
from praisonaiagents.ui.a2a.types import Task, TaskStatus, TaskState, Artifact, TextPart
|
||||
artifact = Artifact(
|
||||
artifact_id="art-1",
|
||||
parts=[TextPart(text="Result")]
|
||||
)
|
||||
task = Task(
|
||||
id="task-789",
|
||||
status=TaskStatus(state=TaskState.COMPLETED),
|
||||
artifacts=[artifact]
|
||||
)
|
||||
assert len(task.artifacts) == 1
|
||||
|
||||
def test_task_with_history(self):
|
||||
"""Test Task with message history."""
|
||||
from praisonaiagents.ui.a2a.types import Task, TaskStatus, TaskState, Message, Role, TextPart
|
||||
msg1 = Message(message_id="m1", role=Role.USER, parts=[TextPart(text="Q")])
|
||||
msg2 = Message(message_id="m2", role=Role.AGENT, parts=[TextPart(text="A")])
|
||||
task = Task(
|
||||
id="task-abc",
|
||||
status=TaskStatus(state=TaskState.COMPLETED),
|
||||
history=[msg1, msg2]
|
||||
)
|
||||
assert len(task.history) == 2
|
||||
|
||||
|
||||
class TestArtifact:
|
||||
"""Tests for Artifact model."""
|
||||
|
||||
def test_artifact_creation(self):
|
||||
"""Test Artifact can be created."""
|
||||
from praisonaiagents.ui.a2a.types import Artifact, TextPart
|
||||
artifact = Artifact(
|
||||
artifact_id="art-123",
|
||||
parts=[TextPart(text="Generated content")]
|
||||
)
|
||||
assert artifact.artifact_id == "art-123"
|
||||
|
||||
def test_artifact_with_name(self):
|
||||
"""Test Artifact with name and description."""
|
||||
from praisonaiagents.ui.a2a.types import Artifact, TextPart
|
||||
artifact = Artifact(
|
||||
artifact_id="art-456",
|
||||
name="Report",
|
||||
description="Generated report",
|
||||
parts=[TextPart(text="Report content")]
|
||||
)
|
||||
assert artifact.name == "Report"
|
||||
assert artifact.description == "Generated report"
|
||||
|
||||
|
||||
class TestAgentSkill:
|
||||
"""Tests for AgentSkill model."""
|
||||
|
||||
def test_agent_skill_creation(self):
|
||||
"""Test AgentSkill can be created."""
|
||||
from praisonaiagents.ui.a2a.types import AgentSkill
|
||||
skill = AgentSkill(
|
||||
id="search",
|
||||
name="Web Search",
|
||||
description="Search the web for information"
|
||||
)
|
||||
assert skill.id == "search"
|
||||
assert skill.name == "Web Search"
|
||||
|
||||
def test_agent_skill_with_tags(self):
|
||||
"""Test AgentSkill with tags."""
|
||||
from praisonaiagents.ui.a2a.types import AgentSkill
|
||||
skill = AgentSkill(
|
||||
id="calc",
|
||||
name="Calculator",
|
||||
description="Perform calculations",
|
||||
tags=["math", "utility"]
|
||||
)
|
||||
assert skill.tags == ["math", "utility"]
|
||||
|
||||
def test_agent_skill_with_examples(self):
|
||||
"""Test AgentSkill with examples."""
|
||||
from praisonaiagents.ui.a2a.types import AgentSkill
|
||||
skill = AgentSkill(
|
||||
id="translate",
|
||||
name="Translator",
|
||||
description="Translate text",
|
||||
examples=["Translate hello to Spanish", "What is bonjour in English?"]
|
||||
)
|
||||
assert len(skill.examples) == 2
|
||||
|
||||
|
||||
class TestAgentCapabilities:
|
||||
"""Tests for AgentCapabilities model."""
|
||||
|
||||
def test_capabilities_creation(self):
|
||||
"""Test AgentCapabilities can be created."""
|
||||
from praisonaiagents.ui.a2a.types import AgentCapabilities
|
||||
caps = AgentCapabilities(streaming=True)
|
||||
assert caps.streaming is True
|
||||
|
||||
def test_capabilities_defaults(self):
|
||||
"""Test AgentCapabilities defaults."""
|
||||
from praisonaiagents.ui.a2a.types import AgentCapabilities
|
||||
caps = AgentCapabilities()
|
||||
assert caps.streaming is False
|
||||
assert caps.push_notifications is False
|
||||
|
||||
|
||||
class TestAgentCard:
|
||||
"""Tests for AgentCard model."""
|
||||
|
||||
def test_agent_card_creation(self):
|
||||
"""Test AgentCard can be created."""
|
||||
from praisonaiagents.ui.a2a.types import AgentCard, AgentCapabilities
|
||||
card = AgentCard(
|
||||
name="Research Agent",
|
||||
url="http://localhost:8000/a2a",
|
||||
version="1.0.0",
|
||||
capabilities=AgentCapabilities(streaming=True)
|
||||
)
|
||||
assert card.name == "Research Agent"
|
||||
assert card.url == "http://localhost:8000/a2a"
|
||||
|
||||
def test_agent_card_with_skills(self):
|
||||
"""Test AgentCard with skills."""
|
||||
from praisonaiagents.ui.a2a.types import AgentCard, AgentCapabilities, AgentSkill
|
||||
skill = AgentSkill(id="search", name="Search", description="Search web")
|
||||
card = AgentCard(
|
||||
name="Search Agent",
|
||||
url="http://localhost:8000/a2a",
|
||||
version="1.0.0",
|
||||
capabilities=AgentCapabilities(),
|
||||
skills=[skill]
|
||||
)
|
||||
assert len(card.skills) == 1
|
||||
|
||||
def test_agent_card_json_serialization(self):
|
||||
"""Test AgentCard can be serialized to JSON."""
|
||||
from praisonaiagents.ui.a2a.types import AgentCard, AgentCapabilities
|
||||
card = AgentCard(
|
||||
name="Test Agent",
|
||||
url="http://localhost:8000/a2a",
|
||||
version="1.0.0",
|
||||
capabilities=AgentCapabilities()
|
||||
)
|
||||
json_str = card.model_dump_json()
|
||||
data = json.loads(json_str)
|
||||
assert data["name"] == "Test Agent"
|
||||
|
||||
|
||||
class TestSendMessageRequest:
|
||||
"""Tests for SendMessageRequest model."""
|
||||
|
||||
def test_send_message_request_creation(self):
|
||||
"""Test SendMessageRequest can be created."""
|
||||
from praisonaiagents.ui.a2a.types import SendMessageRequest, Message, Role, TextPart
|
||||
msg = Message(
|
||||
message_id="msg-1",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Hello")]
|
||||
)
|
||||
req = SendMessageRequest(message=msg)
|
||||
assert req.message.message_id == "msg-1"
|
||||
|
||||
def test_send_message_request_with_config(self):
|
||||
"""Test SendMessageRequest with configuration."""
|
||||
from praisonaiagents.ui.a2a.types import SendMessageRequest, Message, Role, TextPart, MessageConfig
|
||||
msg = Message(
|
||||
message_id="msg-2",
|
||||
role=Role.USER,
|
||||
parts=[TextPart(text="Search for AI")]
|
||||
)
|
||||
config = MessageConfig(
|
||||
accept_content_types=["text/plain", "application/json"]
|
||||
)
|
||||
req = SendMessageRequest(message=msg, configuration=config)
|
||||
assert req.configuration is not None
|
||||
|
||||
|
||||
class TestStreamingEvents:
|
||||
"""Tests for streaming event models."""
|
||||
|
||||
def test_task_status_update_event(self):
|
||||
"""Test TaskStatusUpdateEvent creation."""
|
||||
from praisonaiagents.ui.a2a.types import TaskStatusUpdateEvent, TaskStatus, TaskState
|
||||
event = TaskStatusUpdateEvent(
|
||||
task_id="task-123",
|
||||
status=TaskStatus(state=TaskState.WORKING),
|
||||
final=False
|
||||
)
|
||||
assert event.task_id == "task-123"
|
||||
assert event.final is False
|
||||
|
||||
def test_task_artifact_update_event(self):
|
||||
"""Test TaskArtifactUpdateEvent creation."""
|
||||
from praisonaiagents.ui.a2a.types import TaskArtifactUpdateEvent, Artifact, TextPart
|
||||
artifact = Artifact(
|
||||
artifact_id="art-1",
|
||||
parts=[TextPart(text="Partial result")]
|
||||
)
|
||||
event = TaskArtifactUpdateEvent(
|
||||
task_id="task-456",
|
||||
artifact=artifact,
|
||||
append=True,
|
||||
last_chunk=False
|
||||
)
|
||||
assert event.append is True
|
||||
assert event.last_chunk is False
|
||||
@@ -0,0 +1 @@
|
||||
"""A2UI Tests Package."""
|
||||
@@ -0,0 +1,201 @@
|
||||
"""
|
||||
Tests for A2UI Agent Integration
|
||||
|
||||
TDD: Write tests first, then implement the A2UIAgent class.
|
||||
"""
|
||||
|
||||
import os
|
||||
import pytest
|
||||
|
||||
|
||||
# Skip tests if no API key
|
||||
pytestmark = pytest.mark.skipif(
|
||||
not os.environ.get("OPENAI_API_KEY"),
|
||||
reason="OPENAI_API_KEY not set"
|
||||
)
|
||||
|
||||
|
||||
class TestA2UIAgent:
|
||||
"""Test A2UIAgent wrapper class."""
|
||||
|
||||
def test_a2ui_agent_creation(self):
|
||||
"""Test A2UIAgent creation with an agent."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
|
||||
agent = Agent(
|
||||
name="TestAgent",
|
||||
role="Test assistant",
|
||||
goal="Help with testing"
|
||||
)
|
||||
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
assert a2ui_agent.agent is agent
|
||||
assert a2ui_agent.surface_id is not None
|
||||
|
||||
def test_a2ui_agent_with_custom_surface_id(self):
|
||||
"""Test A2UIAgent with custom surface ID."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent, surface_id="custom-surface")
|
||||
|
||||
assert a2ui_agent.surface_id == "custom-surface"
|
||||
|
||||
def test_render_text_response(self):
|
||||
"""Test rendering a simple text response as A2UI."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
# Render a simple text response
|
||||
messages = a2ui_agent.render_text("Hello, World!")
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2 # createSurface + updateComponents
|
||||
|
||||
# Check createSurface
|
||||
assert "createSurface" in messages[0]
|
||||
|
||||
# Check updateComponents has a text component
|
||||
update_msg = next((m for m in messages if "updateComponents" in m), None)
|
||||
assert update_msg is not None
|
||||
components = update_msg["updateComponents"]["components"]
|
||||
assert any(c.get("component") == "Text" for c in components)
|
||||
|
||||
def test_render_list_response(self):
|
||||
"""Test rendering a list of items as A2UI cards."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
items = [
|
||||
{"title": "Item 1", "description": "First item"},
|
||||
{"title": "Item 2", "description": "Second item"},
|
||||
]
|
||||
|
||||
messages = a2ui_agent.render_list(
|
||||
title="My Items",
|
||||
items=items,
|
||||
item_title_key="title",
|
||||
item_description_key="description"
|
||||
)
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2
|
||||
|
||||
def test_render_form(self):
|
||||
"""Test rendering a form as A2UI."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
fields = [
|
||||
{"id": "name", "label": "Name", "type": "text"},
|
||||
{"id": "email", "label": "Email", "type": "text"},
|
||||
]
|
||||
|
||||
messages = a2ui_agent.render_form(
|
||||
title="Contact Form",
|
||||
fields=fields,
|
||||
submit_action="submit_form"
|
||||
)
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2
|
||||
|
||||
# Check for TextField components
|
||||
update_msg = next((m for m in messages if "updateComponents" in m), None)
|
||||
assert update_msg is not None
|
||||
components = update_msg["updateComponents"]["components"]
|
||||
text_fields = [c for c in components if c.get("component") == "TextField"]
|
||||
assert len(text_fields) >= 2
|
||||
|
||||
def test_get_surface(self):
|
||||
"""Test getting the underlying Surface object."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
surface = a2ui_agent.get_surface()
|
||||
|
||||
assert isinstance(surface, Surface)
|
||||
assert surface.surface_id == a2ui_agent.surface_id
|
||||
|
||||
|
||||
class TestA2UIAgentWithLLM:
|
||||
"""Test A2UIAgent with actual LLM calls."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_chat_with_ui(self):
|
||||
"""Test chat that returns A2UI response."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
|
||||
agent = Agent(
|
||||
name="UIAgent",
|
||||
role="UI Generator",
|
||||
goal="Generate helpful UI responses",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
# This should work with the agent's chat
|
||||
response = await a2ui_agent.chat_async("Say hello")
|
||||
|
||||
assert response is not None
|
||||
# Response should contain text
|
||||
assert isinstance(response, str) or isinstance(response, dict)
|
||||
|
||||
|
||||
class TestA2UIAgentIntegration:
|
||||
"""Integration tests for A2UIAgent with A2A."""
|
||||
|
||||
def test_get_a2a_data_part(self):
|
||||
"""Test getting A2UI as A2A DataPart."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
from praisonaiagents.ui.a2ui.extension import is_a2ui_part
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
# Render something
|
||||
a2ui_agent.render_text("Hello")
|
||||
|
||||
# Get as A2A DataPart
|
||||
part = a2ui_agent.to_a2a_part()
|
||||
|
||||
assert part is not None
|
||||
assert is_a2ui_part(part)
|
||||
|
||||
def test_to_json(self):
|
||||
"""Test getting A2UI as JSON string."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui.agent import A2UIAgent
|
||||
import json
|
||||
|
||||
agent = Agent(name="TestAgent", role="Test", goal="Test")
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
# Render something
|
||||
a2ui_agent.render_text("Hello")
|
||||
|
||||
# Get as JSON
|
||||
json_str = a2ui_agent.to_json()
|
||||
|
||||
# Should be valid JSON
|
||||
parsed = json.loads(json_str)
|
||||
assert isinstance(parsed, list)
|
||||
@@ -0,0 +1,115 @@
|
||||
"""
|
||||
Tests for A2UI Extension Module
|
||||
|
||||
TDD: Write tests first, then implement the extension.
|
||||
"""
|
||||
|
||||
|
||||
class TestA2UIExtension:
|
||||
"""Test A2UI extension helpers for A2A integration."""
|
||||
|
||||
def test_a2ui_mime_type(self):
|
||||
"""Test A2UI MIME type constant."""
|
||||
from praisonaiagents.ui.a2ui.extension import A2UI_MIME_TYPE
|
||||
|
||||
assert A2UI_MIME_TYPE == "application/json+a2ui"
|
||||
|
||||
def test_a2ui_extension_uri(self):
|
||||
"""Test A2UI extension URI constant."""
|
||||
from praisonaiagents.ui.a2ui.extension import A2UI_EXTENSION_URI
|
||||
|
||||
assert "a2ui" in A2UI_EXTENSION_URI.lower()
|
||||
|
||||
def test_create_a2ui_part(self):
|
||||
"""Test create_a2ui_part wraps A2UI data in A2A DataPart."""
|
||||
from praisonaiagents.ui.a2ui.extension import create_a2ui_part, A2UI_MIME_TYPE
|
||||
|
||||
a2ui_data = {
|
||||
"createSurface": {
|
||||
"surfaceId": "main",
|
||||
"catalogId": "https://a2ui.dev/standard"
|
||||
}
|
||||
}
|
||||
|
||||
part = create_a2ui_part(a2ui_data)
|
||||
|
||||
# Should return a Part with DataPart root
|
||||
assert part is not None
|
||||
assert hasattr(part, 'data')
|
||||
assert part.data == a2ui_data
|
||||
assert part.metadata is not None
|
||||
assert part.metadata.get("mimeType") == A2UI_MIME_TYPE
|
||||
|
||||
def test_is_a2ui_part_true(self):
|
||||
"""Test is_a2ui_part returns True for A2UI parts."""
|
||||
from praisonaiagents.ui.a2ui.extension import create_a2ui_part, is_a2ui_part
|
||||
|
||||
a2ui_data = {"createSurface": {"surfaceId": "main", "catalogId": "test"}}
|
||||
part = create_a2ui_part(a2ui_data)
|
||||
|
||||
assert is_a2ui_part(part) is True
|
||||
|
||||
def test_is_a2ui_part_false(self):
|
||||
"""Test is_a2ui_part returns False for non-A2UI parts."""
|
||||
from praisonaiagents.ui.a2ui.extension import is_a2ui_part
|
||||
from praisonaiagents.ui.a2ui.types import A2UIDataPart
|
||||
|
||||
# Create a regular data part without A2UI mime type
|
||||
part = A2UIDataPart(data={"foo": "bar"}, metadata={"mimeType": "application/json"})
|
||||
|
||||
assert is_a2ui_part(part) is False
|
||||
|
||||
def test_get_a2ui_agent_extension(self):
|
||||
"""Test get_a2ui_agent_extension returns AgentExtension config."""
|
||||
from praisonaiagents.ui.a2ui.extension import get_a2ui_agent_extension
|
||||
|
||||
ext = get_a2ui_agent_extension()
|
||||
|
||||
assert ext is not None
|
||||
assert hasattr(ext, 'uri')
|
||||
assert "a2ui" in ext.uri.lower()
|
||||
assert hasattr(ext, 'description')
|
||||
|
||||
def test_get_a2ui_agent_extension_with_inline_catalog(self):
|
||||
"""Test get_a2ui_agent_extension with inline catalog support."""
|
||||
from praisonaiagents.ui.a2ui.extension import get_a2ui_agent_extension
|
||||
|
||||
ext = get_a2ui_agent_extension(accepts_inline_custom_catalog=True)
|
||||
|
||||
assert ext.params is not None
|
||||
assert ext.params.get("acceptsInlineCustomCatalog") is True
|
||||
|
||||
def test_standard_catalog_id(self):
|
||||
"""Test standard catalog ID constant."""
|
||||
from praisonaiagents.ui.a2ui.extension import STANDARD_CATALOG_ID
|
||||
|
||||
assert "standard_catalog" in STANDARD_CATALOG_ID.lower() or "a2ui" in STANDARD_CATALOG_ID.lower()
|
||||
|
||||
|
||||
class TestA2UIDataPart:
|
||||
"""Test A2UI DataPart type."""
|
||||
|
||||
def test_a2ui_data_part_creation(self):
|
||||
"""Test A2UIDataPart creation."""
|
||||
from praisonaiagents.ui.a2ui.types import A2UIDataPart
|
||||
|
||||
part = A2UIDataPart(
|
||||
data={"test": "value"},
|
||||
metadata={"mimeType": "application/json+a2ui"}
|
||||
)
|
||||
|
||||
assert part.data == {"test": "value"}
|
||||
assert part.metadata["mimeType"] == "application/json+a2ui"
|
||||
|
||||
def test_a2ui_data_part_to_dict(self):
|
||||
"""Test A2UIDataPart serialization."""
|
||||
from praisonaiagents.ui.a2ui.types import A2UIDataPart
|
||||
|
||||
part = A2UIDataPart(
|
||||
data={"createSurface": {"surfaceId": "main"}},
|
||||
metadata={"mimeType": "application/json+a2ui"}
|
||||
)
|
||||
|
||||
data = part.to_dict()
|
||||
assert "data" in data
|
||||
assert "metadata" in data
|
||||
@@ -0,0 +1,225 @@
|
||||
"""
|
||||
End-to-End Integration Tests for A2UI
|
||||
|
||||
Tests the complete A2UI workflow from agent to JSON output.
|
||||
"""
|
||||
|
||||
import json
|
||||
import os
|
||||
import pytest
|
||||
|
||||
|
||||
class TestA2UIEndToEnd:
|
||||
"""End-to-end integration tests."""
|
||||
|
||||
def test_complete_surface_workflow(self):
|
||||
"""Test complete workflow: create surface, add components, generate JSON."""
|
||||
from praisonaiagents.ui.a2ui import (
|
||||
Surface,
|
||||
PathBinding,
|
||||
)
|
||||
|
||||
# Create surface
|
||||
surface = Surface(surface_id="test-surface")
|
||||
|
||||
# Add components using fluent API
|
||||
surface.text(id="title", text="Welcome", usage_hint="h1")
|
||||
surface.text(id="subtitle", text=PathBinding(path="/subtitle"), usage_hint="h2")
|
||||
surface.button(
|
||||
id="action-btn",
|
||||
child="btn-text",
|
||||
action_name="do_action",
|
||||
action_context=[{"key": "id", "value": "123"}],
|
||||
primary=True
|
||||
)
|
||||
surface.text(id="btn-text", text="Click Me")
|
||||
surface.column(id="root", children=["title", "subtitle", "action-btn"])
|
||||
|
||||
# Set data
|
||||
surface.set_data("subtitle", "Hello World")
|
||||
|
||||
# Generate messages
|
||||
messages = surface.to_messages()
|
||||
|
||||
# Verify structure
|
||||
assert len(messages) == 3 # createSurface, updateComponents, updateDataModel
|
||||
|
||||
# Verify createSurface
|
||||
assert "createSurface" in messages[0]
|
||||
assert messages[0]["createSurface"]["surfaceId"] == "test-surface"
|
||||
|
||||
# Verify updateComponents
|
||||
assert "updateComponents" in messages[1]
|
||||
components = messages[1]["updateComponents"]["components"]
|
||||
assert len(components) == 5 # title, subtitle, btn, btn-text, root
|
||||
|
||||
# Verify updateDataModel
|
||||
assert "updateDataModel" in messages[2]
|
||||
assert messages[2]["updateDataModel"]["value"]["subtitle"] == "Hello World"
|
||||
|
||||
# Verify JSON output
|
||||
json_str = surface.to_json()
|
||||
parsed = json.loads(json_str)
|
||||
assert len(parsed) == 3
|
||||
|
||||
def test_a2ui_agent_render_workflow(self):
|
||||
"""Test A2UIAgent rendering workflow."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui import A2UIAgent
|
||||
|
||||
agent = Agent(
|
||||
name="TestAgent",
|
||||
role="Test assistant",
|
||||
goal="Help with testing"
|
||||
)
|
||||
|
||||
a2ui_agent = A2UIAgent(agent=agent, surface_id="agent-surface")
|
||||
|
||||
# Render text
|
||||
messages = a2ui_agent.render_text(
|
||||
text="This is a test response",
|
||||
title="Test Title"
|
||||
)
|
||||
|
||||
# Verify structure
|
||||
assert len(messages) >= 2
|
||||
assert "createSurface" in messages[0]
|
||||
|
||||
# Verify JSON export
|
||||
json_str = a2ui_agent.to_json()
|
||||
parsed = json.loads(json_str)
|
||||
assert isinstance(parsed, list)
|
||||
|
||||
def test_template_workflow(self):
|
||||
"""Test template-based workflow."""
|
||||
from praisonaiagents.ui.a2ui import (
|
||||
ChatTemplate,
|
||||
ListTemplate,
|
||||
FormTemplate,
|
||||
DashboardTemplate,
|
||||
)
|
||||
|
||||
# Chat template
|
||||
chat = ChatTemplate(surface_id="chat")
|
||||
chat.add_user_message("Hello!")
|
||||
chat.add_agent_message("Hi there!")
|
||||
chat_messages = chat.to_messages()
|
||||
assert len(chat_messages) >= 2
|
||||
|
||||
# List template
|
||||
list_template = ListTemplate(surface_id="list", title="Items")
|
||||
list_template.add_item(title="Item 1", description="First")
|
||||
list_template.add_item(title="Item 2", description="Second")
|
||||
list_messages = list_template.to_messages()
|
||||
assert len(list_messages) >= 2
|
||||
|
||||
# Form template
|
||||
form = FormTemplate(surface_id="form", title="Contact")
|
||||
form.add_text_field(id="name", label="Name")
|
||||
form.add_email_field(id="email", label="Email")
|
||||
form.set_submit_action("submit", "Send")
|
||||
form_messages = form.to_messages()
|
||||
assert len(form_messages) >= 2
|
||||
|
||||
# Dashboard template
|
||||
dashboard = DashboardTemplate(surface_id="dashboard", title="Dashboard")
|
||||
dashboard.add_panel(id="stats", title="Stats", content="100 items")
|
||||
dashboard.add_panel(id="chart", title="Chart", content="[Chart]")
|
||||
dashboard_messages = dashboard.to_messages()
|
||||
assert len(dashboard_messages) >= 2
|
||||
|
||||
def test_a2a_integration(self):
|
||||
"""Test A2A protocol integration."""
|
||||
from praisonaiagents.ui.a2ui import (
|
||||
Surface,
|
||||
create_a2ui_part,
|
||||
is_a2ui_part,
|
||||
A2UI_MIME_TYPE,
|
||||
)
|
||||
|
||||
# Create surface
|
||||
surface = Surface(surface_id="a2a-test")
|
||||
surface.text(id="msg", text="Hello from A2A")
|
||||
surface.column(id="root", children=["msg"])
|
||||
|
||||
# Get messages
|
||||
messages = surface.to_messages()
|
||||
|
||||
# Wrap in A2A DataPart
|
||||
part = create_a2ui_part({"messages": messages})
|
||||
|
||||
# Verify A2UI part
|
||||
assert is_a2ui_part(part)
|
||||
assert part.metadata["mimeType"] == A2UI_MIME_TYPE
|
||||
assert "messages" in part.data
|
||||
assert len(part.data["messages"]) >= 2
|
||||
|
||||
def test_data_binding_workflow(self):
|
||||
"""Test data binding with path references."""
|
||||
from praisonaiagents.ui.a2ui import (
|
||||
Surface,
|
||||
PathBinding,
|
||||
ChildrenTemplate,
|
||||
)
|
||||
|
||||
surface = Surface(surface_id="data-binding-test")
|
||||
|
||||
# Add components with data binding
|
||||
surface.text(id="title", text=PathBinding(path="/title"), usage_hint="h1")
|
||||
surface.text(id="item-template", text=PathBinding(path="/name"))
|
||||
|
||||
# Add list with template
|
||||
surface.list(
|
||||
id="items",
|
||||
children=ChildrenTemplate(component_id="item-template", path="/items"),
|
||||
direction="vertical"
|
||||
)
|
||||
|
||||
surface.column(id="root", children=["title", "items"])
|
||||
|
||||
# Set data
|
||||
surface.set_data("title", "My List")
|
||||
surface.set_data("items", [
|
||||
{"name": "Item 1"},
|
||||
{"name": "Item 2"},
|
||||
{"name": "Item 3"},
|
||||
])
|
||||
|
||||
messages = surface.to_messages()
|
||||
|
||||
# Verify data model
|
||||
data_msg = next((m for m in messages if "updateDataModel" in m), None)
|
||||
assert data_msg is not None
|
||||
assert data_msg["updateDataModel"]["value"]["title"] == "My List"
|
||||
assert len(data_msg["updateDataModel"]["value"]["items"]) == 3
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
not os.environ.get("OPENAI_API_KEY"),
|
||||
reason="OPENAI_API_KEY not set"
|
||||
)
|
||||
class TestA2UIWithLLM:
|
||||
"""Tests that require LLM API calls."""
|
||||
|
||||
def test_agent_chat_and_render(self):
|
||||
"""Test agent chat followed by UI rendering."""
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.ui.a2ui import A2UIAgent
|
||||
|
||||
agent = Agent(
|
||||
name="UIAgent",
|
||||
role="UI Generator",
|
||||
goal="Generate helpful responses",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
a2ui_agent = A2UIAgent(agent=agent)
|
||||
|
||||
# Chat with agent
|
||||
response = a2ui_agent.chat("What is 2+2?")
|
||||
|
||||
# Render response as UI
|
||||
messages = a2ui_agent.render_text(response, title="Answer")
|
||||
|
||||
assert len(messages) >= 2
|
||||
assert "createSurface" in messages[0]
|
||||
@@ -0,0 +1,228 @@
|
||||
"""
|
||||
Tests for A2UI Surface Builder
|
||||
|
||||
TDD: Write tests first, then implement the Surface class.
|
||||
"""
|
||||
|
||||
|
||||
class TestSurface:
|
||||
"""Test Surface builder class."""
|
||||
|
||||
def test_surface_creation(self):
|
||||
"""Test Surface creation with ID and catalog."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
|
||||
assert surface.surface_id == "main"
|
||||
assert surface.catalog_id is not None # Should have default
|
||||
|
||||
def test_surface_with_custom_catalog(self):
|
||||
"""Test Surface with custom catalog ID."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(
|
||||
surface_id="main",
|
||||
catalog_id="https://custom.catalog/v1"
|
||||
)
|
||||
|
||||
assert surface.catalog_id == "https://custom.catalog/v1"
|
||||
|
||||
def test_add_component(self):
|
||||
"""Test adding a component to the surface."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
text = TextComponent(id="title", text="Hello World", usage_hint="h1")
|
||||
|
||||
surface.add(text)
|
||||
|
||||
assert len(surface.components) == 1
|
||||
assert surface.components[0].id == "title"
|
||||
|
||||
def test_add_multiple_components(self):
|
||||
"""Test adding multiple components."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent, ButtonComponent
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.add(TextComponent(id="title", text="Hello"))
|
||||
surface.add(ButtonComponent(id="btn", child="btn-text"))
|
||||
|
||||
assert len(surface.components) == 2
|
||||
|
||||
def test_set_data(self):
|
||||
"""Test setting data model values."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.set_data("title", "Hello World")
|
||||
surface.set_data("count", 42)
|
||||
|
||||
assert surface.data["title"] == "Hello World"
|
||||
assert surface.data["count"] == 42
|
||||
|
||||
def test_set_nested_data(self):
|
||||
"""Test setting nested data model values."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.set_data("user", {"name": "John", "age": 30})
|
||||
|
||||
assert surface.data["user"]["name"] == "John"
|
||||
|
||||
def test_to_messages_creates_surface(self):
|
||||
"""Test to_messages generates CreateSurface message."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.add(TextComponent(id="title", text="Hello"))
|
||||
|
||||
messages = surface.to_messages()
|
||||
|
||||
assert len(messages) >= 1
|
||||
assert "createSurface" in messages[0]
|
||||
assert messages[0]["createSurface"]["surfaceId"] == "main"
|
||||
|
||||
def test_to_messages_includes_components(self):
|
||||
"""Test to_messages includes UpdateComponents message."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.add(TextComponent(id="title", text="Hello"))
|
||||
|
||||
messages = surface.to_messages()
|
||||
|
||||
# Should have createSurface and updateComponents
|
||||
assert len(messages) >= 2
|
||||
update_msg = next((m for m in messages if "updateComponents" in m), None)
|
||||
assert update_msg is not None
|
||||
assert len(update_msg["updateComponents"]["components"]) == 1
|
||||
|
||||
def test_to_messages_includes_data_model(self):
|
||||
"""Test to_messages includes UpdateDataModel message when data is set."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.add(TextComponent(id="title", text="Hello"))
|
||||
surface.set_data("title", "Hello World")
|
||||
|
||||
messages = surface.to_messages()
|
||||
|
||||
# Should have createSurface, updateComponents, and updateDataModel
|
||||
assert len(messages) == 3
|
||||
data_msg = next((m for m in messages if "updateDataModel" in m), None)
|
||||
assert data_msg is not None
|
||||
assert data_msg["updateDataModel"]["value"]["title"] == "Hello World"
|
||||
|
||||
def test_to_json(self):
|
||||
"""Test to_json returns JSON string."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
import json
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.add(TextComponent(id="title", text="Hello"))
|
||||
|
||||
json_str = surface.to_json()
|
||||
|
||||
# Should be valid JSON
|
||||
parsed = json.loads(json_str)
|
||||
assert isinstance(parsed, list)
|
||||
assert len(parsed) >= 2
|
||||
|
||||
|
||||
class TestSurfaceChaining:
|
||||
"""Test Surface method chaining."""
|
||||
|
||||
def test_add_returns_self(self):
|
||||
"""Test add() returns self for chaining."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
result = surface.add(TextComponent(id="title", text="Hello"))
|
||||
|
||||
assert result is surface
|
||||
|
||||
def test_set_data_returns_self(self):
|
||||
"""Test set_data() returns self for chaining."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
result = surface.set_data("key", "value")
|
||||
|
||||
assert result is surface
|
||||
|
||||
def test_fluent_api(self):
|
||||
"""Test fluent API for building surfaces."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent, ButtonComponent
|
||||
|
||||
surface = (
|
||||
Surface(surface_id="main")
|
||||
.add(TextComponent(id="title", text="Hello"))
|
||||
.add(ButtonComponent(id="btn", child="btn-text"))
|
||||
.set_data("title", "Hello World")
|
||||
)
|
||||
|
||||
assert len(surface.components) == 2
|
||||
assert surface.data["title"] == "Hello World"
|
||||
|
||||
|
||||
class TestSurfaceHelpers:
|
||||
"""Test Surface helper methods."""
|
||||
|
||||
def test_text_helper(self):
|
||||
"""Test text() helper method."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.text(id="title", text="Hello", usage_hint="h1")
|
||||
|
||||
assert len(surface.components) == 1
|
||||
assert surface.components[0].id == "title"
|
||||
|
||||
def test_button_helper(self):
|
||||
"""Test button() helper method."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.button(id="submit", child="submit-text", action_name="submit")
|
||||
|
||||
assert len(surface.components) == 1
|
||||
assert surface.components[0].id == "submit"
|
||||
|
||||
def test_card_helper(self):
|
||||
"""Test card() helper method."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.card(id="card-1", child="card-content")
|
||||
|
||||
assert len(surface.components) == 1
|
||||
assert surface.components[0].id == "card-1"
|
||||
|
||||
def test_row_helper(self):
|
||||
"""Test row() helper method."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.row(id="row-1", children=["col-1", "col-2"])
|
||||
|
||||
assert len(surface.components) == 1
|
||||
assert surface.components[0].id == "row-1"
|
||||
|
||||
def test_column_helper(self):
|
||||
"""Test column() helper method."""
|
||||
from praisonaiagents.ui.a2ui.surface import Surface
|
||||
|
||||
surface = Surface(surface_id="main")
|
||||
surface.column(id="col-1", children=["item-1", "item-2"])
|
||||
|
||||
assert len(surface.components) == 1
|
||||
assert surface.components[0].id == "col-1"
|
||||
@@ -0,0 +1,210 @@
|
||||
"""
|
||||
Tests for A2UI Templates
|
||||
|
||||
TDD: Write tests first, then implement the templates.
|
||||
"""
|
||||
|
||||
|
||||
class TestChatTemplate:
|
||||
"""Test ChatTemplate for conversational UIs."""
|
||||
|
||||
def test_chat_template_creation(self):
|
||||
"""Test ChatTemplate creation."""
|
||||
from praisonaiagents.ui.a2ui.templates import ChatTemplate
|
||||
|
||||
template = ChatTemplate(surface_id="chat")
|
||||
|
||||
assert template.surface_id == "chat"
|
||||
|
||||
def test_add_user_message(self):
|
||||
"""Test adding a user message."""
|
||||
from praisonaiagents.ui.a2ui.templates import ChatTemplate
|
||||
|
||||
template = ChatTemplate(surface_id="chat")
|
||||
template.add_user_message("Hello!")
|
||||
|
||||
assert len(template.messages) == 1
|
||||
assert template.messages[0]["role"] == "user"
|
||||
assert template.messages[0]["content"] == "Hello!"
|
||||
|
||||
def test_add_agent_message(self):
|
||||
"""Test adding an agent message."""
|
||||
from praisonaiagents.ui.a2ui.templates import ChatTemplate
|
||||
|
||||
template = ChatTemplate(surface_id="chat")
|
||||
template.add_agent_message("Hi there!")
|
||||
|
||||
assert len(template.messages) == 1
|
||||
assert template.messages[0]["role"] == "agent"
|
||||
|
||||
def test_to_messages(self):
|
||||
"""Test generating A2UI messages."""
|
||||
from praisonaiagents.ui.a2ui.templates import ChatTemplate
|
||||
|
||||
template = ChatTemplate(surface_id="chat")
|
||||
template.add_user_message("Hello!")
|
||||
template.add_agent_message("Hi there!")
|
||||
|
||||
messages = template.to_messages()
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2 # createSurface + updateComponents
|
||||
|
||||
|
||||
class TestListTemplate:
|
||||
"""Test ListTemplate for displaying lists of items."""
|
||||
|
||||
def test_list_template_creation(self):
|
||||
"""Test ListTemplate creation."""
|
||||
from praisonaiagents.ui.a2ui.templates import ListTemplate
|
||||
|
||||
template = ListTemplate(
|
||||
surface_id="list",
|
||||
title="My Items"
|
||||
)
|
||||
|
||||
assert template.surface_id == "list"
|
||||
assert template.title == "My Items"
|
||||
|
||||
def test_add_item(self):
|
||||
"""Test adding an item to the list."""
|
||||
from praisonaiagents.ui.a2ui.templates import ListTemplate
|
||||
|
||||
template = ListTemplate(surface_id="list", title="Items")
|
||||
template.add_item(title="Item 1", description="First item")
|
||||
|
||||
assert len(template.items) == 1
|
||||
assert template.items[0]["title"] == "Item 1"
|
||||
|
||||
def test_add_item_with_image(self):
|
||||
"""Test adding an item with an image."""
|
||||
from praisonaiagents.ui.a2ui.templates import ListTemplate
|
||||
|
||||
template = ListTemplate(surface_id="list", title="Items")
|
||||
template.add_item(
|
||||
title="Item 1",
|
||||
description="First item",
|
||||
image_url="https://example.com/image.jpg"
|
||||
)
|
||||
|
||||
assert template.items[0]["image_url"] == "https://example.com/image.jpg"
|
||||
|
||||
def test_to_messages(self):
|
||||
"""Test generating A2UI messages."""
|
||||
from praisonaiagents.ui.a2ui.templates import ListTemplate
|
||||
|
||||
template = ListTemplate(surface_id="list", title="Items")
|
||||
template.add_item(title="Item 1", description="First")
|
||||
template.add_item(title="Item 2", description="Second")
|
||||
|
||||
messages = template.to_messages()
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2
|
||||
|
||||
|
||||
class TestFormTemplate:
|
||||
"""Test FormTemplate for data collection forms."""
|
||||
|
||||
def test_form_template_creation(self):
|
||||
"""Test FormTemplate creation."""
|
||||
from praisonaiagents.ui.a2ui.templates import FormTemplate
|
||||
|
||||
template = FormTemplate(
|
||||
surface_id="form",
|
||||
title="Contact Form"
|
||||
)
|
||||
|
||||
assert template.surface_id == "form"
|
||||
assert template.title == "Contact Form"
|
||||
|
||||
def test_add_text_field(self):
|
||||
"""Test adding a text field."""
|
||||
from praisonaiagents.ui.a2ui.templates import FormTemplate
|
||||
|
||||
template = FormTemplate(surface_id="form", title="Form")
|
||||
template.add_text_field(id="name", label="Name")
|
||||
|
||||
assert len(template.fields) == 1
|
||||
assert template.fields[0]["id"] == "name"
|
||||
assert template.fields[0]["type"] == "text"
|
||||
|
||||
def test_add_number_field(self):
|
||||
"""Test adding a number field."""
|
||||
from praisonaiagents.ui.a2ui.templates import FormTemplate
|
||||
|
||||
template = FormTemplate(surface_id="form", title="Form")
|
||||
template.add_number_field(id="age", label="Age")
|
||||
|
||||
assert template.fields[0]["type"] == "number"
|
||||
|
||||
def test_add_email_field(self):
|
||||
"""Test adding an email field."""
|
||||
from praisonaiagents.ui.a2ui.templates import FormTemplate
|
||||
|
||||
template = FormTemplate(surface_id="form", title="Form")
|
||||
template.add_email_field(id="email", label="Email")
|
||||
|
||||
assert template.fields[0]["type"] == "email"
|
||||
|
||||
def test_set_submit_action(self):
|
||||
"""Test setting submit action."""
|
||||
from praisonaiagents.ui.a2ui.templates import FormTemplate
|
||||
|
||||
template = FormTemplate(surface_id="form", title="Form")
|
||||
template.set_submit_action("submit_form", "Send")
|
||||
|
||||
assert template.submit_action == "submit_form"
|
||||
assert template.submit_label == "Send"
|
||||
|
||||
def test_to_messages(self):
|
||||
"""Test generating A2UI messages."""
|
||||
from praisonaiagents.ui.a2ui.templates import FormTemplate
|
||||
|
||||
template = FormTemplate(surface_id="form", title="Form")
|
||||
template.add_text_field(id="name", label="Name")
|
||||
template.add_email_field(id="email", label="Email")
|
||||
|
||||
messages = template.to_messages()
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2
|
||||
|
||||
|
||||
class TestDashboardTemplate:
|
||||
"""Test DashboardTemplate for multi-panel dashboards."""
|
||||
|
||||
def test_dashboard_template_creation(self):
|
||||
"""Test DashboardTemplate creation."""
|
||||
from praisonaiagents.ui.a2ui.templates import DashboardTemplate
|
||||
|
||||
template = DashboardTemplate(
|
||||
surface_id="dashboard",
|
||||
title="My Dashboard"
|
||||
)
|
||||
|
||||
assert template.surface_id == "dashboard"
|
||||
assert template.title == "My Dashboard"
|
||||
|
||||
def test_add_panel(self):
|
||||
"""Test adding a panel."""
|
||||
from praisonaiagents.ui.a2ui.templates import DashboardTemplate
|
||||
|
||||
template = DashboardTemplate(surface_id="dashboard", title="Dashboard")
|
||||
template.add_panel(id="panel-1", title="Panel 1", content="Some content")
|
||||
|
||||
assert len(template.panels) == 1
|
||||
assert template.panels[0]["id"] == "panel-1"
|
||||
|
||||
def test_to_messages(self):
|
||||
"""Test generating A2UI messages."""
|
||||
from praisonaiagents.ui.a2ui.templates import DashboardTemplate
|
||||
|
||||
template = DashboardTemplate(surface_id="dashboard", title="Dashboard")
|
||||
template.add_panel(id="panel-1", title="Panel 1", content="Content 1")
|
||||
template.add_panel(id="panel-2", title="Panel 2", content="Content 2")
|
||||
|
||||
messages = template.to_messages()
|
||||
|
||||
assert isinstance(messages, list)
|
||||
assert len(messages) >= 2
|
||||
@@ -0,0 +1,318 @@
|
||||
"""
|
||||
Tests for A2UI Types Module
|
||||
|
||||
TDD: Write tests first, then implement the types.
|
||||
"""
|
||||
|
||||
|
||||
|
||||
class TestA2UIMessageTypes:
|
||||
"""Test A2UI message types: CreateSurface, UpdateComponents, UpdateDataModel, DeleteSurface."""
|
||||
|
||||
def test_create_surface_message(self):
|
||||
"""Test CreateSurface message creation."""
|
||||
from praisonaiagents.ui.a2ui.types import CreateSurfaceMessage
|
||||
|
||||
msg = CreateSurfaceMessage(
|
||||
surface_id="main",
|
||||
catalog_id="https://a2ui.dev/standard"
|
||||
)
|
||||
|
||||
assert msg.surface_id == "main"
|
||||
assert msg.catalog_id == "https://a2ui.dev/standard"
|
||||
|
||||
# Test serialization
|
||||
data = msg.to_dict()
|
||||
assert "createSurface" in data
|
||||
assert data["createSurface"]["surfaceId"] == "main"
|
||||
assert data["createSurface"]["catalogId"] == "https://a2ui.dev/standard"
|
||||
|
||||
def test_update_components_message(self):
|
||||
"""Test UpdateComponents message creation."""
|
||||
from praisonaiagents.ui.a2ui.types import UpdateComponentsMessage, TextComponent
|
||||
|
||||
text = TextComponent(id="title", text="Hello World", usage_hint="h1")
|
||||
msg = UpdateComponentsMessage(
|
||||
surface_id="main",
|
||||
components=[text]
|
||||
)
|
||||
|
||||
assert msg.surface_id == "main"
|
||||
assert len(msg.components) == 1
|
||||
|
||||
# Test serialization
|
||||
data = msg.to_dict()
|
||||
assert "updateComponents" in data
|
||||
assert data["updateComponents"]["surfaceId"] == "main"
|
||||
assert len(data["updateComponents"]["components"]) == 1
|
||||
|
||||
def test_update_data_model_message(self):
|
||||
"""Test UpdateDataModel message creation."""
|
||||
from praisonaiagents.ui.a2ui.types import UpdateDataModelMessage
|
||||
|
||||
msg = UpdateDataModelMessage(
|
||||
surface_id="main",
|
||||
path="/",
|
||||
op="replace",
|
||||
value={"title": "Hello", "items": []}
|
||||
)
|
||||
|
||||
assert msg.surface_id == "main"
|
||||
assert msg.path == "/"
|
||||
assert msg.op == "replace"
|
||||
assert msg.value == {"title": "Hello", "items": []}
|
||||
|
||||
# Test serialization
|
||||
data = msg.to_dict()
|
||||
assert "updateDataModel" in data
|
||||
assert data["updateDataModel"]["surfaceId"] == "main"
|
||||
|
||||
def test_delete_surface_message(self):
|
||||
"""Test DeleteSurface message creation."""
|
||||
from praisonaiagents.ui.a2ui.types import DeleteSurfaceMessage
|
||||
|
||||
msg = DeleteSurfaceMessage(surface_id="main")
|
||||
|
||||
assert msg.surface_id == "main"
|
||||
|
||||
# Test serialization
|
||||
data = msg.to_dict()
|
||||
assert "deleteSurface" in data
|
||||
assert data["deleteSurface"]["surfaceId"] == "main"
|
||||
|
||||
|
||||
class TestA2UIComponentTypes:
|
||||
"""Test A2UI component types."""
|
||||
|
||||
def test_text_component(self):
|
||||
"""Test Text component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent
|
||||
|
||||
text = TextComponent(id="title", text="Hello World", usage_hint="h1")
|
||||
|
||||
assert text.id == "title"
|
||||
assert text.text == "Hello World"
|
||||
assert text.usage_hint == "h1"
|
||||
|
||||
# Test serialization
|
||||
data = text.to_dict()
|
||||
assert data["id"] == "title"
|
||||
assert data["component"] == "Text"
|
||||
assert data["text"] == "Hello World"
|
||||
assert data["usageHint"] == "h1"
|
||||
|
||||
def test_text_component_with_path(self):
|
||||
"""Test Text component with data binding path."""
|
||||
from praisonaiagents.ui.a2ui.types import TextComponent, PathBinding
|
||||
|
||||
text = TextComponent(id="title", text=PathBinding(path="/title"))
|
||||
|
||||
data = text.to_dict()
|
||||
assert data["text"] == {"path": "/title"}
|
||||
|
||||
def test_image_component(self):
|
||||
"""Test Image component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import ImageComponent
|
||||
|
||||
img = ImageComponent(
|
||||
id="hero",
|
||||
url="https://example.com/image.jpg",
|
||||
fit="cover",
|
||||
usage_hint="header"
|
||||
)
|
||||
|
||||
assert img.id == "hero"
|
||||
assert img.url == "https://example.com/image.jpg"
|
||||
assert img.fit == "cover"
|
||||
|
||||
data = img.to_dict()
|
||||
assert data["component"] == "Image"
|
||||
assert data["url"] == "https://example.com/image.jpg"
|
||||
|
||||
def test_button_component(self):
|
||||
"""Test Button component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import ButtonComponent, Action, ActionContext
|
||||
|
||||
action = Action(
|
||||
name="submit",
|
||||
context=[
|
||||
ActionContext(key="value", value="test")
|
||||
]
|
||||
)
|
||||
btn = ButtonComponent(
|
||||
id="submit-btn",
|
||||
child="submit-text",
|
||||
primary=True,
|
||||
action=action
|
||||
)
|
||||
|
||||
assert btn.id == "submit-btn"
|
||||
assert btn.child == "submit-text"
|
||||
assert btn.primary is True
|
||||
|
||||
data = btn.to_dict()
|
||||
assert data["component"] == "Button"
|
||||
assert data["action"]["name"] == "submit"
|
||||
|
||||
def test_card_component(self):
|
||||
"""Test Card component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import CardComponent
|
||||
|
||||
card = CardComponent(id="card-1", child="card-content")
|
||||
|
||||
assert card.id == "card-1"
|
||||
assert card.child == "card-content"
|
||||
|
||||
data = card.to_dict()
|
||||
assert data["component"] == "Card"
|
||||
assert data["child"] == "card-content"
|
||||
|
||||
def test_row_component(self):
|
||||
"""Test Row component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import RowComponent
|
||||
|
||||
row = RowComponent(id="row-1", children=["col-1", "col-2"])
|
||||
|
||||
assert row.id == "row-1"
|
||||
assert row.children == ["col-1", "col-2"]
|
||||
|
||||
data = row.to_dict()
|
||||
assert data["component"] == "Row"
|
||||
assert data["children"] == ["col-1", "col-2"]
|
||||
|
||||
def test_column_component(self):
|
||||
"""Test Column component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import ColumnComponent
|
||||
|
||||
col = ColumnComponent(id="col-1", children=["item-1", "item-2"])
|
||||
|
||||
assert col.id == "col-1"
|
||||
assert col.children == ["item-1", "item-2"]
|
||||
|
||||
data = col.to_dict()
|
||||
assert data["component"] == "Column"
|
||||
|
||||
def test_list_component(self):
|
||||
"""Test List component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import ListComponent, ChildrenTemplate
|
||||
|
||||
template = ChildrenTemplate(component_id="item-template", path="/items")
|
||||
lst = ListComponent(id="item-list", direction="vertical", children=template)
|
||||
|
||||
assert lst.id == "item-list"
|
||||
assert lst.direction == "vertical"
|
||||
|
||||
data = lst.to_dict()
|
||||
assert data["component"] == "List"
|
||||
assert data["children"]["componentId"] == "item-template"
|
||||
assert data["children"]["path"] == "/items"
|
||||
|
||||
def test_text_field_component(self):
|
||||
"""Test TextField component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import TextFieldComponent, PathBinding
|
||||
|
||||
field = TextFieldComponent(
|
||||
id="name-field",
|
||||
label="Name",
|
||||
text=PathBinding(path="/name"),
|
||||
field_type="text"
|
||||
)
|
||||
|
||||
assert field.id == "name-field"
|
||||
assert field.label == "Name"
|
||||
|
||||
data = field.to_dict()
|
||||
assert data["component"] == "TextField"
|
||||
assert data["label"] == "Name"
|
||||
assert data["text"] == {"path": "/name"}
|
||||
|
||||
def test_checkbox_component(self):
|
||||
"""Test CheckBox component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import CheckBoxComponent, PathBinding
|
||||
|
||||
cb = CheckBoxComponent(
|
||||
id="agree-cb",
|
||||
label="I agree",
|
||||
checked=PathBinding(path="/agreed")
|
||||
)
|
||||
|
||||
data = cb.to_dict()
|
||||
assert data["component"] == "CheckBox"
|
||||
assert data["label"] == "I agree"
|
||||
|
||||
def test_slider_component(self):
|
||||
"""Test Slider component creation."""
|
||||
from praisonaiagents.ui.a2ui.types import SliderComponent
|
||||
|
||||
slider = SliderComponent(
|
||||
id="volume",
|
||||
min_value=0,
|
||||
max_value=100,
|
||||
value=50
|
||||
)
|
||||
|
||||
data = slider.to_dict()
|
||||
assert data["component"] == "Slider"
|
||||
assert data["min"] == 0
|
||||
assert data["max"] == 100
|
||||
|
||||
|
||||
class TestDataBindingTypes:
|
||||
"""Test data binding types."""
|
||||
|
||||
def test_path_binding(self):
|
||||
"""Test PathBinding for data model references."""
|
||||
from praisonaiagents.ui.a2ui.types import PathBinding
|
||||
|
||||
path = PathBinding(path="/user/name")
|
||||
|
||||
assert path.path == "/user/name"
|
||||
assert path.to_dict() == {"path": "/user/name"}
|
||||
|
||||
def test_string_or_path_literal(self):
|
||||
"""Test StringOrPath with literal string."""
|
||||
from praisonaiagents.ui.a2ui.types import resolve_string_or_path
|
||||
|
||||
result = resolve_string_or_path("Hello")
|
||||
assert result == "Hello"
|
||||
|
||||
def test_string_or_path_binding(self):
|
||||
"""Test StringOrPath with path binding."""
|
||||
from praisonaiagents.ui.a2ui.types import resolve_string_or_path, PathBinding
|
||||
|
||||
result = resolve_string_or_path(PathBinding(path="/title"))
|
||||
assert result == {"path": "/title"}
|
||||
|
||||
|
||||
class TestActionTypes:
|
||||
"""Test action types for button events."""
|
||||
|
||||
def test_action_creation(self):
|
||||
"""Test Action creation."""
|
||||
from praisonaiagents.ui.a2ui.types import Action, ActionContext
|
||||
|
||||
action = Action(
|
||||
name="book_restaurant",
|
||||
context=[
|
||||
ActionContext(key="restaurantName", value="The Fancy Place"),
|
||||
ActionContext(key="address", value="123 Main St")
|
||||
]
|
||||
)
|
||||
|
||||
assert action.name == "book_restaurant"
|
||||
assert len(action.context) == 2
|
||||
|
||||
data = action.to_dict()
|
||||
assert data["name"] == "book_restaurant"
|
||||
assert len(data["context"]) == 2
|
||||
assert data["context"][0]["key"] == "restaurantName"
|
||||
|
||||
def test_action_context_with_path(self):
|
||||
"""Test ActionContext with path binding."""
|
||||
from praisonaiagents.ui.a2ui.types import ActionContext, PathBinding
|
||||
|
||||
ctx = ActionContext(key="name", value=PathBinding(path="/restaurant/name"))
|
||||
|
||||
data = ctx.to_dict()
|
||||
assert data["key"] == "name"
|
||||
assert data["value"] == {"path": "/restaurant/name"}
|
||||
@@ -0,0 +1 @@
|
||||
"""Tests for AG-UI integration."""
|
||||
@@ -0,0 +1,188 @@
|
||||
"""
|
||||
Test AGUI Class - TDD Tests for Main Interface Class
|
||||
|
||||
Phase 5: AGUI Class Tests
|
||||
- Test AGUI initialization with Agent
|
||||
- Test AGUI initialization with PraisonAIAgents
|
||||
- Test get_router returns FastAPI router
|
||||
- Test validation errors
|
||||
"""
|
||||
|
||||
|
||||
class TestAGUIInitialization:
|
||||
"""Test AGUI class initialization."""
|
||||
|
||||
def test_agui_init_with_agent(self):
|
||||
"""Test AGUI initialization with single Agent."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
assert agui.agent == agent
|
||||
assert agui.agents is None
|
||||
|
||||
def test_agui_init_with_agents(self):
|
||||
"""Test AGUI initialization with PraisonAIAgents."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent, Task, PraisonAIAgents
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
task = Task(description="Test task", expected_output="Result", agent=agent)
|
||||
agents = PraisonAIAgents(agents=[agent], tasks=[task])
|
||||
|
||||
agui = AGUI(agents=agents)
|
||||
|
||||
assert agui.agents == agents
|
||||
assert agui.agent is None
|
||||
|
||||
def test_agui_requires_agent_or_agents(self):
|
||||
"""Test AGUI raises error if neither agent nor agents provided."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
import pytest
|
||||
|
||||
with pytest.raises(ValueError, match="requires an agent or agents"):
|
||||
AGUI()
|
||||
|
||||
def test_agui_custom_prefix(self):
|
||||
"""Test AGUI with custom prefix."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent, prefix="/api/v1")
|
||||
|
||||
assert agui.prefix == "/api/v1"
|
||||
|
||||
def test_agui_custom_tags(self):
|
||||
"""Test AGUI with custom tags."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent, tags=["Custom", "Tags"])
|
||||
|
||||
assert agui.tags == ["Custom", "Tags"]
|
||||
|
||||
def test_agui_default_tags(self):
|
||||
"""Test AGUI default tags."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
assert agui.tags == ["AGUI"]
|
||||
|
||||
|
||||
class TestAGUIRouter:
|
||||
"""Test AGUI router generation."""
|
||||
|
||||
def test_get_router_returns_api_router(self):
|
||||
"""Test get_router returns FastAPI APIRouter."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import APIRouter
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
router = agui.get_router()
|
||||
|
||||
assert isinstance(router, APIRouter)
|
||||
|
||||
def test_router_has_agui_endpoint(self):
|
||||
"""Test router has /agui POST endpoint."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
router = agui.get_router()
|
||||
|
||||
# Check routes
|
||||
route_paths = [route.path for route in router.routes]
|
||||
assert "/agui" in route_paths
|
||||
|
||||
def test_router_has_status_endpoint(self):
|
||||
"""Test router has /status GET endpoint."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
router = agui.get_router()
|
||||
|
||||
# Check routes
|
||||
route_paths = [route.path for route in router.routes]
|
||||
assert "/status" in route_paths
|
||||
|
||||
def test_router_with_prefix(self):
|
||||
"""Test router respects prefix."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent, prefix="/api/v1")
|
||||
|
||||
router = agui.get_router()
|
||||
|
||||
assert router.prefix == "/api/v1"
|
||||
|
||||
|
||||
class TestAGUIIntegration:
|
||||
"""Test AGUI integration with FastAPI."""
|
||||
|
||||
def test_include_router_in_fastapi(self):
|
||||
"""Test including AGUI router in FastAPI app."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
# Check app has routes
|
||||
route_paths = [route.path for route in app.routes]
|
||||
assert "/agui" in route_paths
|
||||
assert "/status" in route_paths
|
||||
|
||||
|
||||
class TestAGUIName:
|
||||
"""Test AGUI name and description."""
|
||||
|
||||
def test_agui_name(self):
|
||||
"""Test AGUI name property."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent, name="My Agent")
|
||||
|
||||
assert agui.name == "My Agent"
|
||||
|
||||
def test_agui_description(self):
|
||||
"""Test AGUI description property."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent, description="A test agent")
|
||||
|
||||
assert agui.description == "A test agent"
|
||||
|
||||
def test_agui_default_name_from_agent(self):
|
||||
"""Test AGUI uses agent name by default."""
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="TestAgent", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
assert agui.name == "TestAgent"
|
||||
@@ -0,0 +1,286 @@
|
||||
"""
|
||||
Test AG-UI Message Conversion - TDD Tests for Message Format Conversion
|
||||
|
||||
Phase 3: Message Conversion Tests
|
||||
- Test converting AG-UI messages to PraisonAI format
|
||||
- Test converting PraisonAI messages to AG-UI format
|
||||
- Test handling of tool calls
|
||||
- Test handling of tool results
|
||||
- Test edge cases (empty messages, missing fields)
|
||||
"""
|
||||
|
||||
class TestAGUIToPraisonAIConversion:
|
||||
"""Test converting AG-UI messages to PraisonAI format."""
|
||||
|
||||
def test_convert_user_message(self):
|
||||
"""Test converting a user message."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
agui_messages = [Message(role="user", content="Hello")]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "user"
|
||||
assert result[0]["content"] == "Hello"
|
||||
|
||||
def test_convert_assistant_message(self):
|
||||
"""Test converting an assistant message."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
agui_messages = [Message(role="assistant", content="Hi there!")]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "assistant"
|
||||
assert result[0]["content"] == "Hi there!"
|
||||
|
||||
def test_convert_tool_message(self):
|
||||
"""Test converting a tool result message."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
agui_messages = [Message(role="tool", content="Search results", tool_call_id="tc-123")]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "tool"
|
||||
assert result[0]["content"] == "Search results"
|
||||
assert result[0]["tool_call_id"] == "tc-123"
|
||||
|
||||
def test_convert_assistant_with_tool_calls(self):
|
||||
"""Test converting assistant message with tool calls."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message, ToolCall, FunctionCall
|
||||
|
||||
agui_messages = [
|
||||
Message(
|
||||
role="assistant",
|
||||
content="",
|
||||
tool_calls=[
|
||||
ToolCall(
|
||||
id="tc-123",
|
||||
function=FunctionCall(name="search", arguments='{"query": "test"}')
|
||||
)
|
||||
]
|
||||
)
|
||||
]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "assistant"
|
||||
assert "tool_calls" in result[0]
|
||||
assert len(result[0]["tool_calls"]) == 1
|
||||
assert result[0]["tool_calls"][0]["function"]["name"] == "search"
|
||||
|
||||
def test_convert_multiple_messages(self):
|
||||
"""Test converting multiple messages."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
agui_messages = [
|
||||
Message(role="user", content="Hello"),
|
||||
Message(role="assistant", content="Hi!"),
|
||||
Message(role="user", content="How are you?"),
|
||||
]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
assert len(result) == 3
|
||||
assert result[0]["role"] == "user"
|
||||
assert result[1]["role"] == "assistant"
|
||||
assert result[2]["role"] == "user"
|
||||
|
||||
def test_convert_empty_messages(self):
|
||||
"""Test converting empty message list."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
|
||||
result = agui_messages_to_praisonai([])
|
||||
assert result == []
|
||||
|
||||
def test_skip_system_messages(self):
|
||||
"""Test that system messages are skipped (agent builds its own)."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
agui_messages = [
|
||||
Message(role="system", content="You are helpful"),
|
||||
Message(role="user", content="Hello"),
|
||||
]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
# System message should be skipped
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "user"
|
||||
|
||||
|
||||
class TestPraisonAIToAGUIConversion:
|
||||
"""Test converting PraisonAI messages to AG-UI format."""
|
||||
|
||||
def test_convert_user_message(self):
|
||||
"""Test converting a user message."""
|
||||
from praisonaiagents.ui.agui.conversion import praisonai_messages_to_agui
|
||||
|
||||
praison_messages = [{"role": "user", "content": "Hello"}]
|
||||
result = praisonai_messages_to_agui(praison_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0].role == "user"
|
||||
assert result[0].content == "Hello"
|
||||
|
||||
def test_convert_assistant_message(self):
|
||||
"""Test converting an assistant message."""
|
||||
from praisonaiagents.ui.agui.conversion import praisonai_messages_to_agui
|
||||
|
||||
praison_messages = [{"role": "assistant", "content": "Hi there!"}]
|
||||
result = praisonai_messages_to_agui(praison_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0].role == "assistant"
|
||||
assert result[0].content == "Hi there!"
|
||||
|
||||
def test_convert_tool_result(self):
|
||||
"""Test converting a tool result message."""
|
||||
from praisonaiagents.ui.agui.conversion import praisonai_messages_to_agui
|
||||
|
||||
praison_messages = [
|
||||
{"role": "tool", "content": "Search results", "tool_call_id": "tc-123"}
|
||||
]
|
||||
result = praisonai_messages_to_agui(praison_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0].role == "tool"
|
||||
assert result[0].content == "Search results"
|
||||
assert result[0].tool_call_id == "tc-123"
|
||||
|
||||
def test_convert_assistant_with_tool_calls(self):
|
||||
"""Test converting assistant message with tool calls."""
|
||||
from praisonaiagents.ui.agui.conversion import praisonai_messages_to_agui
|
||||
|
||||
praison_messages = [
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "tc-123",
|
||||
"function": {
|
||||
"name": "search",
|
||||
"arguments": '{"query": "test"}'
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
result = praisonai_messages_to_agui(praison_messages)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0].role == "assistant"
|
||||
assert result[0].tool_calls is not None
|
||||
assert len(result[0].tool_calls) == 1
|
||||
assert result[0].tool_calls[0].function.name == "search"
|
||||
|
||||
def test_convert_empty_messages(self):
|
||||
"""Test converting empty message list."""
|
||||
from praisonaiagents.ui.agui.conversion import praisonai_messages_to_agui
|
||||
|
||||
result = praisonai_messages_to_agui([])
|
||||
assert result == []
|
||||
|
||||
|
||||
class TestStateConversion:
|
||||
"""Test state conversion utilities."""
|
||||
|
||||
def test_validate_dict_state(self):
|
||||
"""Test validating dict state."""
|
||||
from praisonaiagents.ui.agui.conversion import validate_state
|
||||
|
||||
state = {"key": "value"}
|
||||
result = validate_state(state, "thread-123")
|
||||
|
||||
assert result == {"key": "value"}
|
||||
|
||||
def test_validate_none_state(self):
|
||||
"""Test validating None state."""
|
||||
from praisonaiagents.ui.agui.conversion import validate_state
|
||||
|
||||
result = validate_state(None, "thread-123")
|
||||
assert result is None
|
||||
|
||||
def test_validate_pydantic_state(self):
|
||||
"""Test validating Pydantic model state."""
|
||||
from praisonaiagents.ui.agui.conversion import validate_state
|
||||
from pydantic import BaseModel
|
||||
|
||||
class TestState(BaseModel):
|
||||
key: str = "value"
|
||||
|
||||
state = TestState()
|
||||
result = validate_state(state, "thread-123")
|
||||
|
||||
assert result == {"key": "value"}
|
||||
|
||||
def test_validate_invalid_state_returns_none(self):
|
||||
"""Test that invalid state returns None."""
|
||||
from praisonaiagents.ui.agui.conversion import validate_state
|
||||
|
||||
# A string is not a valid state
|
||||
result = validate_state("invalid", "thread-123")
|
||||
assert result is None
|
||||
|
||||
|
||||
class TestToolCallDeduplication:
|
||||
"""Test tool call deduplication logic."""
|
||||
|
||||
def test_deduplicate_tool_results(self):
|
||||
"""Test that duplicate tool results are deduplicated."""
|
||||
from praisonaiagents.ui.agui.conversion import agui_messages_to_praisonai
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
# Same tool_call_id appearing twice
|
||||
agui_messages = [
|
||||
Message(role="tool", content="Result 1", tool_call_id="tc-123"),
|
||||
Message(role="tool", content="Result 2", tool_call_id="tc-123"), # Duplicate
|
||||
]
|
||||
result = agui_messages_to_praisonai(agui_messages)
|
||||
|
||||
# Should only have one result
|
||||
assert len(result) == 1
|
||||
assert result[0]["content"] == "Result 1" # First one wins
|
||||
|
||||
|
||||
class TestExtractUserInput:
|
||||
"""Test extracting user input from messages."""
|
||||
|
||||
def test_extract_last_user_message(self):
|
||||
"""Test extracting the last user message."""
|
||||
from praisonaiagents.ui.agui.conversion import extract_user_input
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
messages = [
|
||||
Message(role="user", content="First message"),
|
||||
Message(role="assistant", content="Response"),
|
||||
Message(role="user", content="Last message"),
|
||||
]
|
||||
result = extract_user_input(messages)
|
||||
|
||||
assert result == "Last message"
|
||||
|
||||
def test_extract_from_empty_messages(self):
|
||||
"""Test extracting from empty messages."""
|
||||
from praisonaiagents.ui.agui.conversion import extract_user_input
|
||||
|
||||
result = extract_user_input([])
|
||||
assert result == ""
|
||||
|
||||
def test_extract_no_user_messages(self):
|
||||
"""Test extracting when no user messages exist."""
|
||||
from praisonaiagents.ui.agui.conversion import extract_user_input
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
|
||||
messages = [
|
||||
Message(role="assistant", content="Hello"),
|
||||
]
|
||||
result = extract_user_input(messages)
|
||||
|
||||
assert result == ""
|
||||
@@ -0,0 +1,311 @@
|
||||
"""
|
||||
Test AG-UI Integration - TDD Tests for End-to-End Integration
|
||||
|
||||
Phase 7: Integration Tests
|
||||
- Test full flow with single Agent
|
||||
- Test full flow with PraisonAIAgents
|
||||
- Test tool calling flow
|
||||
- Test error recovery
|
||||
- Test state persistence
|
||||
"""
|
||||
|
||||
class TestSingleAgentIntegration:
|
||||
"""Test integration with single Agent."""
|
||||
|
||||
def test_single_agent_chat_flow(self):
|
||||
"""Test complete chat flow with single agent."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
import json
|
||||
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
role="Helpful Assistant",
|
||||
goal="Help users with their questions",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
# Send a message
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "test-thread",
|
||||
"messages": [{"role": "user", "content": "Say hello"}]
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
# Parse SSE events
|
||||
events = []
|
||||
for line in response.text.split("\n"):
|
||||
if line.startswith("data: "):
|
||||
event_data = json.loads(line[6:])
|
||||
events.append(event_data)
|
||||
|
||||
# Should have run started event
|
||||
event_types = [e.get("type") for e in events]
|
||||
assert "RUN_STARTED" in event_types
|
||||
assert "RUN_FINISHED" in event_types or "RUN_ERROR" in event_types
|
||||
|
||||
|
||||
class TestMultiAgentIntegration:
|
||||
"""Test integration with PraisonAIAgents."""
|
||||
|
||||
def test_multi_agent_workflow_flow(self):
|
||||
"""Test complete workflow with multiple agents."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent, Task, PraisonAIAgents
|
||||
from fastapi import FastAPI
|
||||
import json
|
||||
|
||||
# Create agents
|
||||
researcher = Agent(
|
||||
name="Researcher",
|
||||
role="Research Analyst",
|
||||
goal="Research topics thoroughly",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
writer = Agent(
|
||||
name="Writer",
|
||||
role="Content Writer",
|
||||
goal="Write engaging content",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Create tasks
|
||||
research_task = Task(
|
||||
description="Research the topic: {topic}",
|
||||
expected_output="Research findings",
|
||||
agent=researcher
|
||||
)
|
||||
write_task = Task(
|
||||
description="Write about the research",
|
||||
expected_output="Written article",
|
||||
agent=writer
|
||||
)
|
||||
|
||||
# Create PraisonAIAgents
|
||||
agents = PraisonAIAgents(
|
||||
agents=[researcher, writer],
|
||||
tasks=[research_task, write_task]
|
||||
)
|
||||
|
||||
agui = AGUI(agents=agents)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "test-thread",
|
||||
"messages": [{"role": "user", "content": "Research AI"}]
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
|
||||
class TestToolCallingIntegration:
|
||||
"""Test integration with tool calling."""
|
||||
|
||||
def test_agent_with_tools(self):
|
||||
"""Test agent with tools integration."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
import json
|
||||
|
||||
def search_tool(query: str) -> str:
|
||||
"""Search for information."""
|
||||
return f"Search results for: {query}"
|
||||
|
||||
agent = Agent(
|
||||
name="SearchAgent",
|
||||
role="Search Assistant",
|
||||
goal="Help users search for information",
|
||||
tools=[search_tool],
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "test-thread",
|
||||
"messages": [{"role": "user", "content": "Search for Python tutorials"}]
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
# Parse events
|
||||
events = []
|
||||
for line in response.text.split("\n"):
|
||||
if line.startswith("data: "):
|
||||
event_data = json.loads(line[6:])
|
||||
events.append(event_data)
|
||||
|
||||
# Check for tool call events (may or may not have them depending on LLM response)
|
||||
event_types = [e.get("type") for e in events]
|
||||
assert "RUN_STARTED" in event_types
|
||||
|
||||
|
||||
class TestStateManagement:
|
||||
"""Test state management in AG-UI."""
|
||||
|
||||
def test_state_passed_to_agent(self):
|
||||
"""Test that state is passed to agent."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(
|
||||
name="StatefulAgent",
|
||||
role="Stateful Assistant",
|
||||
goal="Remember context",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "test-thread",
|
||||
"messages": [{"role": "user", "content": "Hello"}],
|
||||
"state": {"user_name": "John", "preferences": {"language": "en"}}
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
|
||||
class TestConversationHistory:
|
||||
"""Test conversation history handling."""
|
||||
|
||||
def test_multiple_messages_in_history(self):
|
||||
"""Test handling multiple messages in conversation history."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(
|
||||
name="ChatAgent",
|
||||
role="Chat Assistant",
|
||||
goal="Have conversations",
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "test-thread",
|
||||
"messages": [
|
||||
{"role": "user", "content": "My name is John"},
|
||||
{"role": "assistant", "content": "Hello John!"},
|
||||
{"role": "user", "content": "What is my name?"}
|
||||
]
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
|
||||
class TestErrorRecovery:
|
||||
"""Test error recovery scenarios."""
|
||||
|
||||
def test_graceful_error_handling(self):
|
||||
"""Test graceful error handling."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
import json
|
||||
|
||||
# Agent with invalid LLM should handle error gracefully
|
||||
agent = Agent(
|
||||
name="ErrorAgent",
|
||||
role="Error Test",
|
||||
goal="Test error handling",
|
||||
llm="invalid-model-name"
|
||||
)
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "test-thread",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Should not crash, should return error event
|
||||
assert response.status_code == 200
|
||||
|
||||
# Parse events
|
||||
events = []
|
||||
for line in response.text.split("\n"):
|
||||
if line.startswith("data: "):
|
||||
try:
|
||||
event_data = json.loads(line[6:])
|
||||
events.append(event_data)
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
# Should have error event
|
||||
event_types = [e.get("type") for e in events]
|
||||
assert "RUN_ERROR" in event_types or "RUN_FINISHED" in event_types
|
||||
|
||||
|
||||
class TestPerformance:
|
||||
"""Test performance - ensure no impact on existing functionality."""
|
||||
|
||||
def test_agui_import_does_not_slow_package(self):
|
||||
"""Test that importing AGUI doesn't slow down package import."""
|
||||
import time
|
||||
|
||||
start = time.time()
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
import_time = time.time() - start
|
||||
|
||||
# Import should be fast (< 1 second)
|
||||
assert import_time < 1.0
|
||||
|
||||
def test_agui_lazy_loading(self):
|
||||
"""Test that AGUI uses lazy loading where possible."""
|
||||
# This test ensures we don't import heavy dependencies until needed
|
||||
import sys
|
||||
|
||||
# Remove agui from cache if present
|
||||
modules_to_remove = [k for k in sys.modules.keys() if 'agui' in k]
|
||||
for mod in modules_to_remove:
|
||||
del sys.modules[mod]
|
||||
|
||||
# Import should not load FastAPI until get_router is called
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
# FastAPI should be loaded when get_router is called
|
||||
router = agui.get_router()
|
||||
assert router is not None
|
||||
@@ -0,0 +1,266 @@
|
||||
"""
|
||||
Test AG-UI Router - TDD Tests for FastAPI HTTP Endpoints
|
||||
|
||||
Phase 6: FastAPI Router Tests
|
||||
- Test /agui POST endpoint
|
||||
- Test /status GET endpoint
|
||||
- Test request validation
|
||||
- Test streaming response
|
||||
- Test error handling
|
||||
"""
|
||||
|
||||
class TestStatusEndpoint:
|
||||
"""Test /status endpoint."""
|
||||
|
||||
def test_status_endpoint_returns_available(self):
|
||||
"""Test status endpoint returns available status."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
response = client.get("/status")
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json() == {"status": "available"}
|
||||
|
||||
|
||||
class TestAGUIEndpoint:
|
||||
"""Test /agui POST endpoint."""
|
||||
|
||||
def test_agui_endpoint_accepts_post(self):
|
||||
"""Test /agui endpoint accepts POST requests."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
# Minimal valid request
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Should return streaming response (200)
|
||||
assert response.status_code == 200
|
||||
|
||||
def test_agui_endpoint_returns_streaming_response(self):
|
||||
"""Test /agui endpoint returns streaming response."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Check content type is event-stream
|
||||
assert "text/event-stream" in response.headers.get("content-type", "")
|
||||
|
||||
def test_agui_endpoint_requires_thread_id(self):
|
||||
"""Test /agui endpoint requires thread_id."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
# Missing thread_id
|
||||
response = client.post("/agui", json={
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Should return validation error
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
class TestAGUIEndpointWithState:
|
||||
"""Test /agui endpoint with state."""
|
||||
|
||||
def test_agui_endpoint_accepts_state(self):
|
||||
"""Test /agui endpoint accepts state parameter."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}],
|
||||
"state": {"custom_key": "custom_value"}
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
|
||||
class TestAGUIEndpointWithRunId:
|
||||
"""Test /agui endpoint with run_id."""
|
||||
|
||||
def test_agui_endpoint_accepts_run_id(self):
|
||||
"""Test /agui endpoint accepts run_id parameter."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"run_id": "run-456",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
|
||||
def test_agui_endpoint_generates_run_id_if_missing(self):
|
||||
"""Test /agui endpoint generates run_id if not provided."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Should succeed even without run_id
|
||||
assert response.status_code == 200
|
||||
|
||||
|
||||
class TestAGUIEndpointCORS:
|
||||
"""Test /agui endpoint CORS headers."""
|
||||
|
||||
def test_agui_endpoint_cors_headers(self):
|
||||
"""Test /agui endpoint includes CORS headers."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Check CORS headers
|
||||
assert response.headers.get("access-control-allow-origin") == "*"
|
||||
|
||||
|
||||
class TestAGUIEndpointErrorHandling:
|
||||
"""Test /agui endpoint error handling."""
|
||||
|
||||
def test_agui_endpoint_handles_agent_error(self):
|
||||
"""Test /agui endpoint handles agent errors gracefully."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
# Create agent that will fail
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
# This should not crash the server
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}]
|
||||
})
|
||||
|
||||
# Should return 200 with error event in stream
|
||||
assert response.status_code == 200
|
||||
|
||||
|
||||
class TestAGUIEndpointWithForwardedProps:
|
||||
"""Test /agui endpoint with forwarded_props."""
|
||||
|
||||
def test_agui_endpoint_accepts_forwarded_props(self):
|
||||
"""Test /agui endpoint accepts forwarded_props."""
|
||||
from fastapi.testclient import TestClient
|
||||
from praisonaiagents.ui.agui import AGUI
|
||||
from praisonaiagents import Agent
|
||||
from fastapi import FastAPI
|
||||
|
||||
agent = Agent(name="Test", role="Tester", goal="Test things")
|
||||
agui = AGUI(agent=agent)
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(agui.get_router())
|
||||
|
||||
client = TestClient(app)
|
||||
|
||||
response = client.post("/agui", json={
|
||||
"thread_id": "thread-123",
|
||||
"messages": [{"role": "user", "content": "Hello"}],
|
||||
"forwarded_props": {"user_id": "user-123"}
|
||||
})
|
||||
|
||||
assert response.status_code == 200
|
||||
@@ -0,0 +1,240 @@
|
||||
"""
|
||||
Test AG-UI Event Streaming - TDD Tests for Streaming PraisonAI Responses
|
||||
|
||||
Phase 4: Event Streaming Tests
|
||||
- Test streaming text content as AG-UI events
|
||||
- Test streaming tool calls as AG-UI events
|
||||
- Test run lifecycle events (start, finish, error)
|
||||
- Test step events
|
||||
- Test event ordering
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
|
||||
|
||||
class TestTextMessageStreaming:
|
||||
"""Test streaming text messages."""
|
||||
|
||||
def test_stream_simple_text(self):
|
||||
"""Test streaming simple text content."""
|
||||
from praisonaiagents.ui.agui.streaming import create_text_message_events
|
||||
|
||||
events = list(create_text_message_events(
|
||||
content="Hello, world!",
|
||||
message_id="msg-123"
|
||||
))
|
||||
|
||||
# Should have start, content, end events
|
||||
assert len(events) == 3
|
||||
assert events[0].type == "TEXT_MESSAGE_START"
|
||||
assert events[0].message_id == "msg-123"
|
||||
assert events[1].type == "TEXT_MESSAGE_CONTENT"
|
||||
assert events[1].delta == "Hello, world!"
|
||||
assert events[2].type == "TEXT_MESSAGE_END"
|
||||
|
||||
def test_stream_chunked_text(self):
|
||||
"""Test streaming text in chunks."""
|
||||
from praisonaiagents.ui.agui.streaming import stream_text_chunks
|
||||
|
||||
chunks = ["Hello", ", ", "world", "!"]
|
||||
events = list(stream_text_chunks(chunks, message_id="msg-123"))
|
||||
|
||||
# Should have start, 4 content events, end
|
||||
assert len(events) == 6
|
||||
assert events[0].type == "TEXT_MESSAGE_START"
|
||||
assert events[1].delta == "Hello"
|
||||
assert events[2].delta == ", "
|
||||
assert events[3].delta == "world"
|
||||
assert events[4].delta == "!"
|
||||
assert events[5].type == "TEXT_MESSAGE_END"
|
||||
|
||||
def test_stream_empty_text(self):
|
||||
"""Test streaming empty text."""
|
||||
from praisonaiagents.ui.agui.streaming import create_text_message_events
|
||||
|
||||
events = list(create_text_message_events(content="", message_id="msg-123"))
|
||||
|
||||
# Should still have start and end, but no content
|
||||
assert len(events) == 2
|
||||
assert events[0].type == "TEXT_MESSAGE_START"
|
||||
assert events[1].type == "TEXT_MESSAGE_END"
|
||||
|
||||
|
||||
class TestToolCallStreaming:
|
||||
"""Test streaming tool calls."""
|
||||
|
||||
def test_stream_tool_call(self):
|
||||
"""Test streaming a tool call."""
|
||||
from praisonaiagents.ui.agui.streaming import create_tool_call_events
|
||||
|
||||
events = list(create_tool_call_events(
|
||||
tool_call_id="tc-123",
|
||||
tool_name="search",
|
||||
arguments='{"query": "test"}',
|
||||
parent_message_id="msg-123"
|
||||
))
|
||||
|
||||
# Should have start, args, end events
|
||||
assert len(events) == 3
|
||||
assert events[0].type == "TOOL_CALL_START"
|
||||
assert events[0].tool_call_id == "tc-123"
|
||||
assert events[0].tool_call_name == "search"
|
||||
assert events[1].type == "TOOL_CALL_ARGS"
|
||||
assert events[1].delta == '{"query": "test"}'
|
||||
assert events[2].type == "TOOL_CALL_END"
|
||||
|
||||
def test_stream_tool_result(self):
|
||||
"""Test streaming a tool result."""
|
||||
from praisonaiagents.ui.agui.streaming import create_tool_result_event
|
||||
|
||||
event = create_tool_result_event(
|
||||
tool_call_id="tc-123",
|
||||
content="Search results...",
|
||||
message_id="msg-456"
|
||||
)
|
||||
|
||||
assert event.type == "TOOL_CALL_RESULT"
|
||||
assert event.tool_call_id == "tc-123"
|
||||
assert event.content == "Search results..."
|
||||
|
||||
|
||||
class TestRunLifecycleEvents:
|
||||
"""Test run lifecycle events."""
|
||||
|
||||
def test_create_run_started_event(self):
|
||||
"""Test creating run started event."""
|
||||
from praisonaiagents.ui.agui.streaming import create_run_started_event
|
||||
|
||||
event = create_run_started_event(thread_id="thread-123", run_id="run-456")
|
||||
|
||||
assert event.type == "RUN_STARTED"
|
||||
assert event.thread_id == "thread-123"
|
||||
assert event.run_id == "run-456"
|
||||
|
||||
def test_create_run_finished_event(self):
|
||||
"""Test creating run finished event."""
|
||||
from praisonaiagents.ui.agui.streaming import create_run_finished_event
|
||||
|
||||
event = create_run_finished_event(thread_id="thread-123", run_id="run-456")
|
||||
|
||||
assert event.type == "RUN_FINISHED"
|
||||
assert event.thread_id == "thread-123"
|
||||
assert event.run_id == "run-456"
|
||||
|
||||
def test_create_run_error_event(self):
|
||||
"""Test creating run error event."""
|
||||
from praisonaiagents.ui.agui.streaming import create_run_error_event
|
||||
|
||||
event = create_run_error_event(message="Something went wrong", code="ERR001")
|
||||
|
||||
assert event.type == "RUN_ERROR"
|
||||
assert event.message == "Something went wrong"
|
||||
assert event.code == "ERR001"
|
||||
|
||||
|
||||
class TestStepEvents:
|
||||
"""Test step events."""
|
||||
|
||||
def test_create_step_started_event(self):
|
||||
"""Test creating step started event."""
|
||||
from praisonaiagents.ui.agui.streaming import create_step_started_event
|
||||
|
||||
event = create_step_started_event(step_name="research")
|
||||
|
||||
assert event.type == "STEP_STARTED"
|
||||
assert event.step_name == "research"
|
||||
|
||||
def test_create_step_finished_event(self):
|
||||
"""Test creating step finished event."""
|
||||
from praisonaiagents.ui.agui.streaming import create_step_finished_event
|
||||
|
||||
event = create_step_finished_event(step_name="research")
|
||||
|
||||
assert event.type == "STEP_FINISHED"
|
||||
assert event.step_name == "research"
|
||||
|
||||
|
||||
class TestEventBuffer:
|
||||
"""Test EventBuffer for managing event ordering."""
|
||||
|
||||
def test_event_buffer_creation(self):
|
||||
"""Test EventBuffer creation."""
|
||||
from praisonaiagents.ui.agui.streaming import EventBuffer
|
||||
|
||||
buffer = EventBuffer()
|
||||
assert buffer.active_tool_call_ids == set()
|
||||
assert buffer.current_text_message_id == ""
|
||||
|
||||
def test_event_buffer_start_tool_call(self):
|
||||
"""Test starting a tool call in buffer."""
|
||||
from praisonaiagents.ui.agui.streaming import EventBuffer
|
||||
|
||||
buffer = EventBuffer()
|
||||
buffer.start_tool_call("tc-123")
|
||||
|
||||
assert "tc-123" in buffer.active_tool_call_ids
|
||||
|
||||
def test_event_buffer_end_tool_call(self):
|
||||
"""Test ending a tool call in buffer."""
|
||||
from praisonaiagents.ui.agui.streaming import EventBuffer
|
||||
|
||||
buffer = EventBuffer()
|
||||
buffer.start_tool_call("tc-123")
|
||||
buffer.end_tool_call("tc-123")
|
||||
|
||||
assert "tc-123" not in buffer.active_tool_call_ids
|
||||
assert "tc-123" in buffer.ended_tool_call_ids
|
||||
|
||||
def test_event_buffer_start_text_message(self):
|
||||
"""Test starting a text message in buffer."""
|
||||
from praisonaiagents.ui.agui.streaming import EventBuffer
|
||||
|
||||
buffer = EventBuffer()
|
||||
msg_id = buffer.start_text_message()
|
||||
|
||||
assert msg_id != ""
|
||||
assert buffer.current_text_message_id == msg_id
|
||||
|
||||
|
||||
class TestAsyncStreaming:
|
||||
"""Test async streaming functionality."""
|
||||
|
||||
def test_async_stream_response(self):
|
||||
"""Test async streaming of agent response."""
|
||||
async def run_test():
|
||||
from praisonaiagents.ui.agui.streaming import async_stream_response
|
||||
|
||||
# Mock response chunks
|
||||
async def mock_chunks():
|
||||
yield "Hello"
|
||||
yield ", "
|
||||
yield "world!"
|
||||
|
||||
events = []
|
||||
async for event in async_stream_response(
|
||||
response_stream=mock_chunks(),
|
||||
thread_id="thread-123",
|
||||
run_id="run-456"
|
||||
):
|
||||
events.append(event)
|
||||
|
||||
# Should have run_started, text events, run_finished
|
||||
assert len(events) > 0
|
||||
assert events[0].type == "RUN_STARTED"
|
||||
assert events[-1].type == "RUN_FINISHED"
|
||||
|
||||
asyncio.run(run_test())
|
||||
|
||||
|
||||
class TestStateSnapshotEvents:
|
||||
"""Test state snapshot events."""
|
||||
|
||||
def test_create_state_snapshot_event(self):
|
||||
"""Test creating state snapshot event."""
|
||||
from praisonaiagents.ui.agui.streaming import create_state_snapshot_event
|
||||
|
||||
state = {"task": "research", "progress": 50}
|
||||
event = create_state_snapshot_event(state)
|
||||
|
||||
assert event.type == "STATE_SNAPSHOT"
|
||||
assert event.snapshot == state
|
||||
@@ -0,0 +1,327 @@
|
||||
"""
|
||||
Test AG-UI Types - TDD Tests for Event and Message Types
|
||||
|
||||
Phase 2: Core Types Tests
|
||||
- Test EventType enum values
|
||||
- Test BaseEvent creation
|
||||
- Test all event type classes
|
||||
- Test message type classes
|
||||
- Test RunAgentInput validation
|
||||
"""
|
||||
|
||||
import json
|
||||
|
||||
|
||||
class TestEventType:
|
||||
"""Test EventType enum."""
|
||||
|
||||
def test_event_type_text_message_start(self):
|
||||
"""Test TEXT_MESSAGE_START event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TEXT_MESSAGE_START == "TEXT_MESSAGE_START"
|
||||
|
||||
def test_event_type_text_message_content(self):
|
||||
"""Test TEXT_MESSAGE_CONTENT event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TEXT_MESSAGE_CONTENT == "TEXT_MESSAGE_CONTENT"
|
||||
|
||||
def test_event_type_text_message_end(self):
|
||||
"""Test TEXT_MESSAGE_END event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TEXT_MESSAGE_END == "TEXT_MESSAGE_END"
|
||||
|
||||
def test_event_type_tool_call_start(self):
|
||||
"""Test TOOL_CALL_START event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TOOL_CALL_START == "TOOL_CALL_START"
|
||||
|
||||
def test_event_type_tool_call_args(self):
|
||||
"""Test TOOL_CALL_ARGS event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TOOL_CALL_ARGS == "TOOL_CALL_ARGS"
|
||||
|
||||
def test_event_type_tool_call_end(self):
|
||||
"""Test TOOL_CALL_END event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TOOL_CALL_END == "TOOL_CALL_END"
|
||||
|
||||
def test_event_type_tool_call_result(self):
|
||||
"""Test TOOL_CALL_RESULT event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.TOOL_CALL_RESULT == "TOOL_CALL_RESULT"
|
||||
|
||||
def test_event_type_run_started(self):
|
||||
"""Test RUN_STARTED event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.RUN_STARTED == "RUN_STARTED"
|
||||
|
||||
def test_event_type_run_finished(self):
|
||||
"""Test RUN_FINISHED event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.RUN_FINISHED == "RUN_FINISHED"
|
||||
|
||||
def test_event_type_run_error(self):
|
||||
"""Test RUN_ERROR event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.RUN_ERROR == "RUN_ERROR"
|
||||
|
||||
def test_event_type_step_started(self):
|
||||
"""Test STEP_STARTED event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.STEP_STARTED == "STEP_STARTED"
|
||||
|
||||
def test_event_type_step_finished(self):
|
||||
"""Test STEP_FINISHED event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.STEP_FINISHED == "STEP_FINISHED"
|
||||
|
||||
def test_event_type_state_snapshot(self):
|
||||
"""Test STATE_SNAPSHOT event type exists."""
|
||||
from praisonaiagents.ui.agui.types import EventType
|
||||
assert EventType.STATE_SNAPSHOT == "STATE_SNAPSHOT"
|
||||
|
||||
|
||||
class TestBaseEvent:
|
||||
"""Test BaseEvent class."""
|
||||
|
||||
def test_base_event_creation(self):
|
||||
"""Test BaseEvent can be created."""
|
||||
from praisonaiagents.ui.agui.types import BaseEvent, EventType
|
||||
event = BaseEvent(type=EventType.RUN_STARTED)
|
||||
assert event.type == EventType.RUN_STARTED
|
||||
|
||||
def test_base_event_timestamp_optional(self):
|
||||
"""Test BaseEvent timestamp is optional."""
|
||||
from praisonaiagents.ui.agui.types import BaseEvent, EventType
|
||||
event = BaseEvent(type=EventType.RUN_STARTED)
|
||||
assert event.timestamp is None
|
||||
|
||||
def test_base_event_to_dict(self):
|
||||
"""Test BaseEvent can be converted to dict."""
|
||||
from praisonaiagents.ui.agui.types import BaseEvent, EventType
|
||||
event = BaseEvent(type=EventType.RUN_STARTED)
|
||||
data = event.model_dump()
|
||||
assert data["type"] == "RUN_STARTED"
|
||||
|
||||
|
||||
class TestTextMessageEvents:
|
||||
"""Test text message event classes."""
|
||||
|
||||
def test_text_message_start_event(self):
|
||||
"""Test TextMessageStartEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import TextMessageStartEvent
|
||||
event = TextMessageStartEvent(message_id="msg-123", role="assistant")
|
||||
assert event.message_id == "msg-123"
|
||||
assert event.role == "assistant"
|
||||
assert event.type == "TEXT_MESSAGE_START"
|
||||
|
||||
def test_text_message_content_event(self):
|
||||
"""Test TextMessageContentEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import TextMessageContentEvent
|
||||
event = TextMessageContentEvent(message_id="msg-123", delta="Hello")
|
||||
assert event.message_id == "msg-123"
|
||||
assert event.delta == "Hello"
|
||||
assert event.type == "TEXT_MESSAGE_CONTENT"
|
||||
|
||||
def test_text_message_end_event(self):
|
||||
"""Test TextMessageEndEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import TextMessageEndEvent
|
||||
event = TextMessageEndEvent(message_id="msg-123")
|
||||
assert event.message_id == "msg-123"
|
||||
assert event.type == "TEXT_MESSAGE_END"
|
||||
|
||||
|
||||
class TestToolCallEvents:
|
||||
"""Test tool call event classes."""
|
||||
|
||||
def test_tool_call_start_event(self):
|
||||
"""Test ToolCallStartEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import ToolCallStartEvent
|
||||
event = ToolCallStartEvent(
|
||||
tool_call_id="tc-123",
|
||||
tool_call_name="search",
|
||||
parent_message_id="msg-123"
|
||||
)
|
||||
assert event.tool_call_id == "tc-123"
|
||||
assert event.tool_call_name == "search"
|
||||
assert event.parent_message_id == "msg-123"
|
||||
assert event.type == "TOOL_CALL_START"
|
||||
|
||||
def test_tool_call_args_event(self):
|
||||
"""Test ToolCallArgsEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import ToolCallArgsEvent
|
||||
event = ToolCallArgsEvent(tool_call_id="tc-123", delta='{"query": "test"}')
|
||||
assert event.tool_call_id == "tc-123"
|
||||
assert event.delta == '{"query": "test"}'
|
||||
assert event.type == "TOOL_CALL_ARGS"
|
||||
|
||||
def test_tool_call_end_event(self):
|
||||
"""Test ToolCallEndEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import ToolCallEndEvent
|
||||
event = ToolCallEndEvent(tool_call_id="tc-123")
|
||||
assert event.tool_call_id == "tc-123"
|
||||
assert event.type == "TOOL_CALL_END"
|
||||
|
||||
def test_tool_call_result_event(self):
|
||||
"""Test ToolCallResultEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import ToolCallResultEvent
|
||||
event = ToolCallResultEvent(
|
||||
message_id="msg-456",
|
||||
tool_call_id="tc-123",
|
||||
content="Search results..."
|
||||
)
|
||||
assert event.message_id == "msg-456"
|
||||
assert event.tool_call_id == "tc-123"
|
||||
assert event.content == "Search results..."
|
||||
assert event.type == "TOOL_CALL_RESULT"
|
||||
|
||||
|
||||
class TestRunEvents:
|
||||
"""Test run lifecycle event classes."""
|
||||
|
||||
def test_run_started_event(self):
|
||||
"""Test RunStartedEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import RunStartedEvent
|
||||
event = RunStartedEvent(thread_id="thread-123", run_id="run-456")
|
||||
assert event.thread_id == "thread-123"
|
||||
assert event.run_id == "run-456"
|
||||
assert event.type == "RUN_STARTED"
|
||||
|
||||
def test_run_finished_event(self):
|
||||
"""Test RunFinishedEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import RunFinishedEvent
|
||||
event = RunFinishedEvent(thread_id="thread-123", run_id="run-456")
|
||||
assert event.thread_id == "thread-123"
|
||||
assert event.run_id == "run-456"
|
||||
assert event.type == "RUN_FINISHED"
|
||||
|
||||
def test_run_error_event(self):
|
||||
"""Test RunErrorEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import RunErrorEvent
|
||||
event = RunErrorEvent(message="Something went wrong")
|
||||
assert event.message == "Something went wrong"
|
||||
assert event.type == "RUN_ERROR"
|
||||
|
||||
|
||||
class TestStepEvents:
|
||||
"""Test step event classes."""
|
||||
|
||||
def test_step_started_event(self):
|
||||
"""Test StepStartedEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import StepStartedEvent
|
||||
event = StepStartedEvent(step_name="research")
|
||||
assert event.step_name == "research"
|
||||
assert event.type == "STEP_STARTED"
|
||||
|
||||
def test_step_finished_event(self):
|
||||
"""Test StepFinishedEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import StepFinishedEvent
|
||||
event = StepFinishedEvent(step_name="research")
|
||||
assert event.step_name == "research"
|
||||
assert event.type == "STEP_FINISHED"
|
||||
|
||||
|
||||
class TestStateEvents:
|
||||
"""Test state event classes."""
|
||||
|
||||
def test_state_snapshot_event(self):
|
||||
"""Test StateSnapshotEvent creation."""
|
||||
from praisonaiagents.ui.agui.types import StateSnapshotEvent
|
||||
event = StateSnapshotEvent(snapshot={"key": "value"})
|
||||
assert event.snapshot == {"key": "value"}
|
||||
assert event.type == "STATE_SNAPSHOT"
|
||||
|
||||
|
||||
class TestMessageTypes:
|
||||
"""Test message type classes."""
|
||||
|
||||
def test_user_message(self):
|
||||
"""Test UserMessage creation."""
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
msg = Message(role="user", content="Hello")
|
||||
assert msg.role == "user"
|
||||
assert msg.content == "Hello"
|
||||
|
||||
def test_assistant_message(self):
|
||||
"""Test AssistantMessage creation."""
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
msg = Message(role="assistant", content="Hi there!")
|
||||
assert msg.role == "assistant"
|
||||
assert msg.content == "Hi there!"
|
||||
|
||||
def test_tool_message(self):
|
||||
"""Test ToolMessage creation."""
|
||||
from praisonaiagents.ui.agui.types import Message
|
||||
msg = Message(role="tool", content="Result", tool_call_id="tc-123")
|
||||
assert msg.role == "tool"
|
||||
assert msg.content == "Result"
|
||||
assert msg.tool_call_id == "tc-123"
|
||||
|
||||
|
||||
class TestToolCall:
|
||||
"""Test ToolCall type."""
|
||||
|
||||
def test_tool_call_creation(self):
|
||||
"""Test ToolCall creation."""
|
||||
from praisonaiagents.ui.agui.types import ToolCall, FunctionCall
|
||||
tc = ToolCall(
|
||||
id="tc-123",
|
||||
function=FunctionCall(name="search", arguments='{"query": "test"}')
|
||||
)
|
||||
assert tc.id == "tc-123"
|
||||
assert tc.function.name == "search"
|
||||
assert tc.function.arguments == '{"query": "test"}'
|
||||
|
||||
|
||||
class TestRunAgentInput:
|
||||
"""Test RunAgentInput type."""
|
||||
|
||||
def test_run_agent_input_creation(self):
|
||||
"""Test RunAgentInput creation."""
|
||||
from praisonaiagents.ui.agui.types import RunAgentInput, Message
|
||||
input_data = RunAgentInput(
|
||||
thread_id="thread-123",
|
||||
run_id="run-456",
|
||||
messages=[Message(role="user", content="Hello")]
|
||||
)
|
||||
assert input_data.thread_id == "thread-123"
|
||||
assert input_data.run_id == "run-456"
|
||||
assert len(input_data.messages) == 1
|
||||
|
||||
def test_run_agent_input_optional_fields(self):
|
||||
"""Test RunAgentInput optional fields."""
|
||||
from praisonaiagents.ui.agui.types import RunAgentInput
|
||||
input_data = RunAgentInput(thread_id="thread-123")
|
||||
assert input_data.thread_id == "thread-123"
|
||||
assert input_data.run_id is None
|
||||
assert input_data.messages is None or len(input_data.messages) == 0
|
||||
assert input_data.state is None
|
||||
|
||||
|
||||
class TestEventSerialization:
|
||||
"""Test event serialization to JSON."""
|
||||
|
||||
def test_event_json_serialization(self):
|
||||
"""Test events can be serialized to JSON."""
|
||||
from praisonaiagents.ui.agui.types import TextMessageStartEvent
|
||||
event = TextMessageStartEvent(message_id="msg-123", role="assistant")
|
||||
json_str = event.model_dump_json()
|
||||
data = json.loads(json_str)
|
||||
assert data["type"] == "TEXT_MESSAGE_START"
|
||||
assert data["message_id"] == "msg-123"
|
||||
|
||||
def test_event_sse_format(self):
|
||||
"""Test events can be formatted as SSE."""
|
||||
from praisonaiagents.ui.agui.types import TextMessageStartEvent
|
||||
from praisonaiagents.ui.agui.encoder import EventEncoder
|
||||
|
||||
encoder = EventEncoder()
|
||||
event = TextMessageStartEvent(message_id="msg-123", role="assistant")
|
||||
sse = encoder.encode(event)
|
||||
|
||||
assert sse.startswith("data: ")
|
||||
assert sse.endswith("\n\n")
|
||||
# Parse the JSON part
|
||||
json_part = sse[6:-2] # Remove "data: " prefix and "\n\n" suffix
|
||||
data = json.loads(json_part)
|
||||
assert data["type"] == "TEXT_MESSAGE_START"
|
||||
@@ -0,0 +1,217 @@
|
||||
"""
|
||||
Unit tests for configurable max_file_chars in MentionsParser.
|
||||
|
||||
TDD approach: Write tests first, then implement.
|
||||
"""
|
||||
|
||||
import os
|
||||
import pytest
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from unittest.mock import patch
|
||||
|
||||
|
||||
class TestMentionsParserConfigurableLimit:
|
||||
"""Test suite for configurable file truncation limit."""
|
||||
|
||||
@pytest.fixture
|
||||
def temp_workspace(self):
|
||||
"""Create a temporary workspace with test files."""
|
||||
with tempfile.TemporaryDirectory() as tmpdir:
|
||||
yield Path(tmpdir)
|
||||
|
||||
@pytest.fixture
|
||||
def small_file(self, temp_workspace):
|
||||
"""Create a small test file (1KB)."""
|
||||
file_path = temp_workspace / "small.py"
|
||||
content = "# Small file\n" + "x = 1\n" * 100 # ~700 chars
|
||||
file_path.write_text(content)
|
||||
return file_path
|
||||
|
||||
@pytest.fixture
|
||||
def large_file(self, temp_workspace):
|
||||
"""Create a large test file (100KB)."""
|
||||
file_path = temp_workspace / "large.py"
|
||||
content = "# Large file\n" + "x = 'a' * 100\n" * 7000 # ~100KB
|
||||
file_path.write_text(content)
|
||||
return file_path
|
||||
|
||||
@pytest.fixture
|
||||
def huge_file(self, temp_workspace):
|
||||
"""Create a huge test file (600KB)."""
|
||||
file_path = temp_workspace / "huge.py"
|
||||
content = "# Huge file\n" + "x = 'a' * 100\n" * 42000 # ~600KB
|
||||
file_path.write_text(content)
|
||||
return file_path
|
||||
|
||||
# ===== Test 1.1: Default value (500K) =====
|
||||
def test_default_max_file_chars_is_500k(self, temp_workspace):
|
||||
"""Default max_file_chars should be 500,000."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(workspace_path=str(temp_workspace))
|
||||
assert parser.max_file_chars == 500000
|
||||
|
||||
# ===== Test 1.2: Custom value via constructor =====
|
||||
def test_custom_max_file_chars_via_constructor(self, temp_workspace):
|
||||
"""max_file_chars should be configurable via constructor."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=100000
|
||||
)
|
||||
assert parser.max_file_chars == 100000
|
||||
|
||||
def test_custom_max_file_chars_zero_means_no_limit(self, temp_workspace):
|
||||
"""max_file_chars=0 should mean no truncation."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=0
|
||||
)
|
||||
assert parser.max_file_chars == 0
|
||||
|
||||
# ===== Test 1.3: Environment variable override =====
|
||||
def test_env_var_override(self, temp_workspace):
|
||||
"""PRAISON_MAX_FILE_CHARS env var should override default."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
with patch.dict(os.environ, {'PRAISON_MAX_FILE_CHARS': '200000'}):
|
||||
# Need to reimport to pick up env var
|
||||
parser = MentionsParser(workspace_path=str(temp_workspace))
|
||||
assert parser.max_file_chars == 200000
|
||||
|
||||
def test_constructor_takes_precedence_over_env_var(self, temp_workspace):
|
||||
"""Constructor value should take precedence over env var."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
with patch.dict(os.environ, {'PRAISON_MAX_FILE_CHARS': '200000'}):
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=100000
|
||||
)
|
||||
assert parser.max_file_chars == 100000
|
||||
|
||||
# ===== Test 1.4: No-limit mode =====
|
||||
def test_no_truncation_when_limit_is_zero(self, temp_workspace, huge_file):
|
||||
"""File should not be truncated when max_file_chars=0."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=0
|
||||
)
|
||||
|
||||
context, _ = parser.process(f"@file:{huge_file.name} explain")
|
||||
|
||||
# Should contain full content, no truncation message
|
||||
assert "(truncated)" not in context
|
||||
# Should have the full file content
|
||||
original_size = huge_file.read_text().__len__()
|
||||
# Context includes header and code fence, so check it's close
|
||||
assert len(context) >= original_size
|
||||
|
||||
# ===== Test 1.5: Truncation behavior =====
|
||||
def test_truncation_at_custom_limit(self, temp_workspace, large_file):
|
||||
"""File should be truncated at custom limit."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=10000 # 10KB limit
|
||||
)
|
||||
|
||||
context, _ = parser.process(f"@file:{large_file.name} explain")
|
||||
|
||||
# Should be truncated
|
||||
assert "(truncated)" in context
|
||||
# Content should be around the limit (plus header/fence overhead)
|
||||
assert len(context) < 15000 # Some overhead for markdown
|
||||
|
||||
def test_no_truncation_when_file_under_limit(self, temp_workspace, small_file):
|
||||
"""Small files should not be truncated."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=500000
|
||||
)
|
||||
|
||||
context, _ = parser.process(f"@file:{small_file.name} explain")
|
||||
|
||||
# Should NOT be truncated
|
||||
assert "(truncated)" not in context
|
||||
|
||||
def test_truncation_warning_logged(self, temp_workspace, large_file, caplog):
|
||||
"""Warning should be logged when file is truncated."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
import logging
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=10000,
|
||||
verbose=1
|
||||
)
|
||||
|
||||
with caplog.at_level(logging.WARNING):
|
||||
parser.process(f"@file:{large_file.name} explain")
|
||||
|
||||
# Should log a warning about truncation
|
||||
assert any("truncat" in record.message.lower() for record in caplog.records)
|
||||
|
||||
# ===== Test: URL truncation also uses configurable limit =====
|
||||
def test_url_truncation_uses_same_limit(self, temp_workspace):
|
||||
"""URL content should also respect max_file_chars."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
parser = MentionsParser(
|
||||
workspace_path=str(temp_workspace),
|
||||
max_file_chars=100000
|
||||
)
|
||||
|
||||
# URL truncation should use the same limit
|
||||
assert parser.max_file_chars == 100000
|
||||
|
||||
# ===== Test: Backward compatibility =====
|
||||
def test_backward_compatible_no_args(self, temp_workspace):
|
||||
"""Parser should work without max_file_chars argument."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
|
||||
# Should not raise any errors
|
||||
parser = MentionsParser(workspace_path=str(temp_workspace))
|
||||
assert hasattr(parser, 'max_file_chars')
|
||||
|
||||
# ===== Test: Performance - no impact on small files =====
|
||||
def test_performance_small_file(self, temp_workspace, small_file):
|
||||
"""Processing small files should be fast."""
|
||||
from praisonaiagents.tools.mentions import MentionsParser
|
||||
import time
|
||||
|
||||
parser = MentionsParser(workspace_path=str(temp_workspace))
|
||||
|
||||
start = time.time()
|
||||
for _ in range(100):
|
||||
parser.process(f"@file:{small_file.name} explain")
|
||||
elapsed = time.time() - start
|
||||
|
||||
# 100 iterations should complete in under 1 second
|
||||
assert elapsed < 1.0, f"Performance regression: {elapsed}s for 100 iterations"
|
||||
|
||||
|
||||
class TestProcessMentionsFunction:
|
||||
"""Test the convenience function."""
|
||||
|
||||
def test_process_mentions_uses_default_limit(self):
|
||||
"""process_mentions function should use default limit."""
|
||||
from praisonaiagents.tools.mentions import process_mentions
|
||||
|
||||
# The function should create a parser with default settings
|
||||
# Just verify it works without errors
|
||||
context, cleaned = process_mentions("hello world")
|
||||
assert cleaned == "hello world"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__, "-v"])
|
||||
Generated
+1
-1
@@ -2422,7 +2422,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "praisonaiagents"
|
||||
version = "0.1.14"
|
||||
version = "0.1.21"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "aiohttp" },
|
||||
|
||||
+229
-38
@@ -6,10 +6,13 @@
|
||||
</picture>
|
||||
</p>
|
||||
|
||||
<!-- mcp-name: io.github.MervinPraison/praisonai -->
|
||||
|
||||
<p align="center">
|
||||
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://static.pepy.tech/badge/PraisonAI" alt="Total Downloads" /></a>
|
||||
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/github/v/release/MervinPraison/PraisonAI" alt="Latest Stable Version" /></a>
|
||||
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License" /></a>
|
||||
<a href="https://registry.modelcontextprotocol.io/servers/io.github.MervinPraison/praisonai"><img src="https://img.shields.io/badge/MCP-Registry-blue" alt="MCP Registry" /></a>
|
||||
</p>
|
||||
|
||||
<div align="center">
|
||||
@@ -60,6 +63,7 @@ PraisonAI is a production-ready Multi-AI Agents framework with self-reflection,
|
||||
- [Planning & Workflows](#planning--workflows)
|
||||
- [Specialised Agents](#specialised-agents)
|
||||
- [MCP Protocol](#mcp-protocol)
|
||||
- [A2A & A2UI Protocols](#a2a--a2ui-protocols)
|
||||
- [Safety & Control](#safety--control)
|
||||
- [Developer Tools](#developer-tools)
|
||||
- [📊 Process Types & Patterns](#-process-types--patterns)
|
||||
@@ -187,7 +191,14 @@ npm install praisonai
|
||||
| 📚 Add Custom Knowledge | [Example](examples/python/concepts/knowledge-agents.py) | [📖](https://docs.praison.ai/features/knowledge) |
|
||||
| 🧠 Memory (Short & Long Term) | [Example](examples/python/general/memory_example.py) | [📖](https://docs.praison.ai/concepts/memory) |
|
||||
| 📄 Chat with PDF Agents | [Example](examples/python/concepts/chat-with-pdf.py) | [📖](https://docs.praison.ai/features/chat-with-pdf) |
|
||||
| 💻 Code Interpreter Agents | [Example](examples/python/agents/code-agent.py) | [📖](https://docs.praison.ai/features/codeagent) |
|
||||
| **💻 Code** | | |
|
||||
| ↳ Code Interpreter Agents | [Example](examples/python/agents/code-agent.py) | [📖](https://docs.praison.ai/features/codeagent) |
|
||||
| ↳ AI Code Editing Tools | [Example](examples/python/code/code_editing_example.py) | [📖](https://docs.praison.ai/code/editing) |
|
||||
| ↳ External Agents (All) | [Example](examples/python/code/external_agents_example.py) | [📖](https://docs.praison.ai/code/external-agents) |
|
||||
| ↳ Claude Code CLI | [Example](examples/python/code/claude_code_example.py) | [📖](https://docs.praison.ai/code/claude-code) |
|
||||
| ↳ Gemini CLI | [Example](examples/python/code/gemini_cli_example.py) | [📖](https://docs.praison.ai/code/gemini-cli) |
|
||||
| ↳ Codex CLI | [Example](examples/python/code/codex_cli_example.py) | [📖](https://docs.praison.ai/code/codex-cli) |
|
||||
| ↳ Cursor CLI | [Example](examples/python/code/cursor_cli_example.py) | [📖](https://docs.praison.ai/code/cursor-cli) |
|
||||
| 📚 RAG Agents | [Example](examples/python/concepts/rag-agents.py) | [📖](https://docs.praison.ai/features/rag) |
|
||||
| 🤔 Async & Parallel Processing | [Example](examples/python/general/async_example.py) | [📖](https://docs.praison.ai/features/async) |
|
||||
| 🔢 Math Agents | [Example](examples/python/agents/math-agent.py) | [📖](https://docs.praison.ai/features/mathagent) |
|
||||
@@ -205,6 +216,7 @@ npm install praisonai
|
||||
| 🧠 Claude Memory Tool | [Example](#claude-memory-tool-cli) | [📖](https://docs.praison.ai/features/claude-memory-tool) |
|
||||
| 💾 File-Based Memory | [Example](examples/python/general/memory_example.py) | [📖](https://docs.praison.ai/concepts/memory) |
|
||||
| 🔍 Built-in Search Tools | [Example](examples/python/agents/websearch-agent.py) | [📖](https://docs.praison.ai/tools/tavily) |
|
||||
| 🔎 Unified Web Search | [Example](src/praisonai-agents/examples/web_search_example.py) | [📖](https://docs.praison.ai/tools/web-search) |
|
||||
| 📋 Planning Mode | [Example](examples/python/agents/planning-agent.py) | [📖](https://docs.praison.ai/features/planning-mode) |
|
||||
| 🔧 Planning Tools | [Example](#3-agent-with-planning-mode) | [📖](https://docs.praison.ai/features/planning-mode) |
|
||||
| 🧠 Planning Reasoning | [Example](#3-agent-with-planning-mode) | [📖](https://docs.praison.ai/features/planning-mode) |
|
||||
@@ -224,7 +236,7 @@ npm install praisonai
|
||||
| 💻 Programming Agent | [Example](examples/python/agents/programming-agent.py) | [📖](https://docs.praison.ai/agents/programming) |
|
||||
| 📝 Markdown Agent | [Example](examples/python/agents/markdown-agent.py) | [📖](https://docs.praison.ai/agents/markdown) |
|
||||
| 📝 Prompt Expander Agent | [Example](#prompt-expansion) | [📖](https://docs.praison.ai/agents/prompt-expander) |
|
||||
| 🔀 Router Agent | [Example](examples/python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/routing) |
|
||||
| 🔀 Model Router | [Example](examples/python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/model-router) |
|
||||
| ⛓️ Prompt Chaining | [Example](examples/python/general/prompt_chaining.py) | [📖](https://docs.praison.ai/features/promptchaining) |
|
||||
| 🔍 Evaluator Optimiser | [Example](examples/python/general/evaluator-optimiser.py) | [📖](https://docs.praison.ai/features/evaluator-optimiser) |
|
||||
| 👷 Orchestrator Workers | [Example](examples/python/general/orchestrator-workers.py) | [📖](https://docs.praison.ai/features/orchestrator-worker) |
|
||||
@@ -240,12 +252,20 @@ npm install praisonai
|
||||
| 🪝 Hooks | [Example](#9-hooks) | [📖](https://docs.praison.ai/features/hooks) |
|
||||
| 📈 Telemetry | [Example](examples/python/telemetry/production-telemetry-example.py) | [📖](https://docs.praison.ai/features/telemetry) |
|
||||
| 📹 Camera Integration | [Example](examples/python/camera/) | [📖](https://docs.praison.ai/features/camera-integration) |
|
||||
| 📄 Project Docs (.praison/docs/) | [Example](#docs-cli) | [📖](https://docs.praison.ai/cli/docs) |
|
||||
| 🔌 MCP Config Management | [Example](#mcp-config-cli) | [📖](https://docs.praison.ai/cli/mcp) |
|
||||
| 💬 AI Commit Messages | [Example](#ai-commit-cli) | [📖](https://docs.praison.ai/cli/commit) |
|
||||
| @ @Mentions in Prompts | [Example](#mentions-in-prompts) | [📖](https://docs.praison.ai/cli/mentions) |
|
||||
| 💾 Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
|
||||
| 📜 History in Context | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
|
||||
| 📄 Project Docs (.praison/docs/) | [Example](#docs-cli) | [📖](https://docs.praison.ai/docs/cli/docs) |
|
||||
| 🔌 MCP Config Management | [Example](#mcp-config-cli) | [📖](https://docs.praison.ai/docs/cli/mcp) |
|
||||
| 💬 AI Commit Messages | [Example](#ai-commit-cli) | [📖](https://docs.praison.ai/docs/cli/commit) |
|
||||
| @ @Mentions in Prompts | [Example](#mentions-in-prompts) | [📖](https://docs.praison.ai/docs/cli/mentions) |
|
||||
| 💾 Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/docs/cli/session) |
|
||||
| 📜 History in Context | [Example](#session-management-python) | [📖](https://docs.praison.ai/docs/cli/session) |
|
||||
| **🖥️ CLI Features** | | |
|
||||
| ↳ Slash Commands | [Example](examples/python/cli/slash_commands_example.py) | [📖](https://docs.praison.ai/docs/cli/slash-commands) |
|
||||
| ↳ Autonomy Modes | [Example](examples/python/cli/autonomy_modes_example.py) | [📖](https://docs.praison.ai/docs/cli/autonomy-modes) |
|
||||
| ↳ Cost Tracking | [Example](examples/python/cli/cost_tracking_example.py) | [📖](https://docs.praison.ai/docs/cli/cost-tracking) |
|
||||
| ↳ Repository Map | [Example](examples/python/cli/repo_map_example.py) | [📖](https://docs.praison.ai/docs/cli/repo-map) |
|
||||
| ↳ Interactive TUI | [Example](examples/python/cli/interactive_tui_example.py) | [📖](https://docs.praison.ai/docs/cli/interactive-tui) |
|
||||
| ↳ Git Integration | [Example](examples/python/cli/git_integration_example.py) | [📖](https://docs.praison.ai/docs/cli/git-integration) |
|
||||
| ↳ Sandbox Execution | [Example](examples/python/cli/sandbox_execution_example.py) | [📖](https://docs.praison.ai/docs/cli/sandbox-execution) |
|
||||
|
||||
---
|
||||
|
||||
@@ -952,6 +972,32 @@ export OPENAI_API_KEY=xxxxxxxxxxxxxxxxxxxxxx
|
||||
praisonai --auto create a movie script about Robots in Mars
|
||||
```
|
||||
|
||||
### Interactive Mode CLI:
|
||||
```bash
|
||||
# Start interactive terminal mode (inspired by Gemini CLI, Codex CLI, Claude Code)
|
||||
praisonai --interactive
|
||||
praisonai -i
|
||||
|
||||
# Features:
|
||||
# - Streaming responses (no boxes)
|
||||
# - Built-in tools: read_file, write_file, list_files, execute_command, internet_search
|
||||
# - Slash commands: /help, /exit, /tools, /clear
|
||||
|
||||
# Chat mode - single prompt with interactive style (for testing/scripting)
|
||||
# Use --chat (or --chat-mode for backward compatibility)
|
||||
praisonai "list files in current folder" --chat
|
||||
praisonai "search the web for AI news" --chat
|
||||
praisonai "read README.md" --chat
|
||||
```
|
||||
|
||||
### Chat UI (Web Interface):
|
||||
```bash
|
||||
# Start web-based Chainlit chat interface (requires praisonai[chat])
|
||||
pip install "praisonai[chat]"
|
||||
praisonai chat
|
||||
# Opens browser at http://localhost:8084
|
||||
```
|
||||
|
||||
### Query Rewriting (works with any command):
|
||||
```bash
|
||||
# Rewrite query for better results (uses QueryRewriterAgent)
|
||||
@@ -1012,6 +1058,20 @@ praisonai "Complex analysis task" --planning --planning-reasoning
|
||||
praisonai "Task" --planning --auto-approve-plan
|
||||
```
|
||||
|
||||
### Tool Approval CLI:
|
||||
```bash
|
||||
# Auto-approve ALL tool executions (use with caution!)
|
||||
praisonai "run ls command" --trust
|
||||
|
||||
# Auto-approve tools up to a risk level (prompt for higher)
|
||||
# Levels: low, medium, high, critical
|
||||
praisonai "write to file" --approve-level high # Prompts for critical tools only
|
||||
praisonai "task" --approve-level medium # Prompts for high and critical
|
||||
|
||||
# Default behavior (no flags): prompts for all dangerous tools
|
||||
praisonai "run shell command" # Will prompt for approval
|
||||
```
|
||||
|
||||
### Memory CLI:
|
||||
```bash
|
||||
# Enable memory for agent (persists across sessions)
|
||||
@@ -1118,6 +1178,15 @@ praisonai workflow auto "Research AI trends" --pattern parallel
|
||||
# Generate routing workflow (classifier routes to specialists)
|
||||
praisonai workflow auto "Build a chatbot" --pattern routing
|
||||
|
||||
# Generate orchestrator-workers workflow (central orchestrator delegates)
|
||||
praisonai workflow auto "Comprehensive market analysis" --pattern orchestrator-workers
|
||||
|
||||
# Generate evaluator-optimizer workflow (iterative refinement)
|
||||
praisonai workflow auto "Write and refine article" --pattern evaluator-optimizer
|
||||
|
||||
# Specify output file
|
||||
praisonai workflow auto "Build a chatbot" --pattern routing
|
||||
|
||||
# Specify output file
|
||||
praisonai workflow auto "Research AI" --pattern sequential --output my_workflow.yaml
|
||||
```
|
||||
@@ -1127,7 +1196,7 @@ praisonai workflow auto "Research AI" --pattern sequential --output my_workflow.
|
||||
|------|-------------|
|
||||
| `--workflow-var key=value` | Set workflow variable (can be repeated) |
|
||||
| `--var key=value` | Set variable for YAML workflows |
|
||||
| `--pattern <pattern>` | Pattern for auto-generation (sequential, parallel, routing, loop) |
|
||||
| `--pattern <pattern>` | Pattern for auto-generation (sequential, parallel, routing, loop, orchestrator-workers, evaluator-optimizer) |
|
||||
| `--output <file>` | Output file for auto-generation |
|
||||
| `--llm <model>` | LLM model (e.g., openai/gpt-4o-mini) |
|
||||
| `--tools <tools>` | Tools (comma-separated, e.g., tavily) |
|
||||
@@ -1359,8 +1428,13 @@ praisonai "Complex analysis" --router --router-provider anthropic
|
||||
# Router automatically selects:
|
||||
# - Simple tasks → gpt-4o-mini, claude-3-haiku
|
||||
# - Complex tasks → gpt-4-turbo, claude-3-opus
|
||||
|
||||
# Create workflow with model routing template
|
||||
praisonai workflow create --template model-routing --output my_workflow.yaml
|
||||
```
|
||||
|
||||
Custom models can be configured in `agents.yaml`. See [Model Router Docs](https://docs.praison.ai/features/model-router) for details.
|
||||
|
||||
### Flow Display CLI:
|
||||
```bash
|
||||
# Enable visual workflow tracking
|
||||
@@ -1412,13 +1486,31 @@ praisonai mcp help
|
||||
|
||||
### AI Commit CLI:
|
||||
```bash
|
||||
# Generate AI commit message for staged changes
|
||||
# Full auto mode: stage all, security check, commit, and push
|
||||
praisonai commit -a
|
||||
|
||||
# Interactive mode (requires git add first)
|
||||
praisonai commit
|
||||
|
||||
# Generate, commit, and push
|
||||
# Interactive with auto-push
|
||||
praisonai commit --push
|
||||
|
||||
# Skip security check (not recommended)
|
||||
praisonai commit -a --no-verify
|
||||
```
|
||||
|
||||
**Features:**
|
||||
- 🤖 AI-generated conventional commit messages
|
||||
- 🔒 Built-in security scanning (API keys, passwords, secrets, sensitive files)
|
||||
- 📦 Auto-staging with `-a` flag
|
||||
- 🚀 Auto-push in full auto mode
|
||||
- ✏️ Edit message before commit in interactive mode
|
||||
|
||||
**Security Detection:**
|
||||
- API keys, secrets, tokens (AWS, GitHub, GitLab, Slack)
|
||||
- Passwords and private keys
|
||||
- Sensitive files (`.env`, `id_rsa`, `.pem`, `.key`, etc.)
|
||||
|
||||
### Serve CLI (API Server):
|
||||
```bash
|
||||
# Start API server for agents defined in YAML
|
||||
@@ -1449,6 +1541,55 @@ export N8N_API_KEY="your-api-key"
|
||||
praisonai agents.yaml --n8n
|
||||
```
|
||||
|
||||
### External Agents CLI:
|
||||
|
||||
Use external AI coding CLI tools (Claude Code, Gemini CLI, Codex CLI, Cursor CLI) as agent tools:
|
||||
|
||||
```bash
|
||||
# Use Claude Code for coding tasks
|
||||
praisonai "Refactor the auth module" --external-agent claude
|
||||
|
||||
# Use Gemini CLI for code analysis
|
||||
praisonai "Analyze codebase architecture" --external-agent gemini
|
||||
|
||||
# Use OpenAI Codex CLI
|
||||
praisonai "Fix all bugs in src/" --external-agent codex
|
||||
|
||||
# Use Cursor CLI
|
||||
praisonai "Add comprehensive tests" --external-agent cursor
|
||||
```
|
||||
|
||||
**Python API:**
|
||||
```python
|
||||
from praisonai.integrations import (
|
||||
ClaudeCodeIntegration,
|
||||
GeminiCLIIntegration,
|
||||
CodexCLIIntegration,
|
||||
CursorCLIIntegration
|
||||
)
|
||||
|
||||
# Create integration
|
||||
claude = ClaudeCodeIntegration(workspace="/project")
|
||||
|
||||
# Execute a coding task
|
||||
result = await claude.execute("Refactor the auth module")
|
||||
|
||||
# Use as agent tool
|
||||
from praisonai import Agent
|
||||
tool = claude.as_tool()
|
||||
agent = Agent(tools=[tool])
|
||||
```
|
||||
|
||||
**Environment Variables:**
|
||||
```bash
|
||||
export ANTHROPIC_API_KEY=your-key # Claude Code
|
||||
export GEMINI_API_KEY=your-key # Gemini CLI
|
||||
export OPENAI_API_KEY=your-key # Codex CLI
|
||||
export CURSOR_API_KEY=your-key # Cursor CLI
|
||||
```
|
||||
|
||||
See [External Agents Documentation](https://docs.praison.ai/code/external-agents) for more details.
|
||||
|
||||
### @Mentions in Prompts:
|
||||
```bash
|
||||
# Include file content in prompt
|
||||
@@ -1628,36 +1769,78 @@ server.run() # stdio for Claude Desktop
|
||||
| Security | Origin validation, DNS rebinding prevention |
|
||||
| WebSocket | Auto-reconnect with exponential backoff |
|
||||
|
||||
## A2A (Agent2Agent Protocol)
|
||||
|
||||
PraisonAI supports the [A2A Protocol](https://a2a-protocol.org) for agent-to-agent communication, enabling your agents to be discovered and collaborate with other AI agents.
|
||||
|
||||
### A2A Server (Expose Agent as A2A Server)
|
||||
```python
|
||||
from praisonaiagents import Agent, A2A
|
||||
from fastapi import FastAPI
|
||||
|
||||
# Create an agent with tools
|
||||
def search_web(query: str) -> str:
|
||||
"""Search the web for information."""
|
||||
return f"Results for: {query}"
|
||||
|
||||
agent = Agent(
|
||||
name="Research Assistant",
|
||||
role="Research Analyst",
|
||||
goal="Help users research topics",
|
||||
tools=[search_web]
|
||||
)
|
||||
|
||||
# Expose as A2A Server
|
||||
a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
|
||||
|
||||
app = FastAPI()
|
||||
app.include_router(a2a.get_router())
|
||||
|
||||
# Run: uvicorn app:app --reload
|
||||
# Agent Card: GET /.well-known/agent.json
|
||||
# Status: GET /status
|
||||
```
|
||||
|
||||
### A2A Features
|
||||
| Feature | Description |
|
||||
|---------|-------------|
|
||||
| Agent Card | JSON metadata for agent discovery |
|
||||
| Skills Extraction | Auto-generate skills from tools |
|
||||
| Task Management | Stateful task lifecycle |
|
||||
| Streaming | SSE streaming for real-time updates |
|
||||
|
||||
> **Documentation**: [docs.praison.ai/a2a](https://docs.praison.ai/a2a) | **Examples**: [examples/python/a2a](https://github.com/MervinPraison/PraisonAI/tree/main/examples/python/a2a)
|
||||
|
||||
## CLI Features
|
||||
|
||||
| Feature | Docs |
|
||||
|---------|:----:|
|
||||
| 🔄 Query Rewrite - RAG optimization | [📖](https://docs.praison.ai/cli/query-rewrite) |
|
||||
| 🔬 Deep Research - Automated research | [📖](https://docs.praison.ai/cli/deep-research) |
|
||||
| 📋 Planning - Step-by-step execution | [📖](https://docs.praison.ai/cli/planning) |
|
||||
| 💾 Memory - Persistent agent memory | [📖](https://docs.praison.ai/cli/memory) |
|
||||
| 📜 Rules - Auto-discovered instructions | [📖](https://docs.praison.ai/cli/rules) |
|
||||
| 🔄 Workflow - Multi-step workflows | [📖](https://docs.praison.ai/cli/workflow) |
|
||||
| 🪝 Hooks - Event-driven actions | [📖](https://docs.praison.ai/cli/hooks) |
|
||||
| 🧠 Claude Memory - Anthropic memory tool | [📖](https://docs.praison.ai/cli/claude-memory) |
|
||||
| 🛡️ Guardrail - Output validation | [📖](https://docs.praison.ai/cli/guardrail) |
|
||||
| 📊 Metrics - Token usage tracking | [📖](https://docs.praison.ai/cli/metrics) |
|
||||
| 🖼️ Image - Vision processing | [📖](https://docs.praison.ai/cli/image) |
|
||||
| 📡 Telemetry - Usage monitoring | [📖](https://docs.praison.ai/cli/telemetry) |
|
||||
| 🔌 MCP - Model Context Protocol | [📖](https://docs.praison.ai/cli/mcp) |
|
||||
| ⚡ Fast Context - Codebase search | [📖](https://docs.praison.ai/cli/fast-context) |
|
||||
| 📚 Knowledge - RAG management | [📖](https://docs.praison.ai/cli/knowledge) |
|
||||
| 💬 Session - Conversation management | [📖](https://docs.praison.ai/cli/session) |
|
||||
| 🔧 Tools - Tool discovery | [📖](https://docs.praison.ai/cli/tools) |
|
||||
| 🤝 Handoff - Agent delegation | [📖](https://docs.praison.ai/cli/handoff) |
|
||||
| 🧠 Auto Memory - Memory extraction | [📖](https://docs.praison.ai/cli/auto-memory) |
|
||||
| 📋 Todo - Task management | [📖](https://docs.praison.ai/cli/todo) |
|
||||
| 🎯 Router - Smart model selection | [📖](https://docs.praison.ai/cli/router) |
|
||||
| 📈 Flow Display - Visual workflow | [📖](https://docs.praison.ai/cli/flow-display) |
|
||||
| ✨ Prompt Expansion - Detailed prompts | [📖](https://docs.praison.ai/cli/prompt-expansion) |
|
||||
| 🌐 Web Search - Real-time search | [📖](https://docs.praison.ai/cli/web-search) |
|
||||
| 📥 Web Fetch - URL content retrieval | [📖](https://docs.praison.ai/cli/web-fetch) |
|
||||
| 💾 Prompt Caching - Cost reduction | [📖](https://docs.praison.ai/cli/prompt-caching) |
|
||||
| 🔄 Query Rewrite - RAG optimization | [📖](https://docs.praison.ai/docs/cli/query-rewrite) |
|
||||
| 🔬 Deep Research - Automated research | [📖](https://docs.praison.ai/docs/cli/deep-research) |
|
||||
| 📋 Planning - Step-by-step execution | [📖](https://docs.praison.ai/docs/cli/planning) |
|
||||
| 💾 Memory - Persistent agent memory | [📖](https://docs.praison.ai/docs/cli/memory) |
|
||||
| 📜 Rules - Auto-discovered instructions | [📖](https://docs.praison.ai/docs/cli/rules) |
|
||||
| 🔄 Workflow - Multi-step workflows | [📖](https://docs.praison.ai/docs/cli/workflow) |
|
||||
| 🪝 Hooks - Event-driven actions | [📖](https://docs.praison.ai/docs/cli/hooks) |
|
||||
| 🧠 Claude Memory - Anthropic memory tool | [📖](https://docs.praison.ai/docs/cli/claude-memory) |
|
||||
| 🛡️ Guardrail - Output validation | [📖](https://docs.praison.ai/docs/cli/guardrail) |
|
||||
| 📊 Metrics - Token usage tracking | [📖](https://docs.praison.ai/docs/cli/metrics) |
|
||||
| 🖼️ Image - Vision processing | [📖](https://docs.praison.ai/docs/cli/image) |
|
||||
| 📡 Telemetry - Usage monitoring | [📖](https://docs.praison.ai/docs/cli/telemetry) |
|
||||
| 🔌 MCP - Model Context Protocol | [📖](https://docs.praison.ai/docs/cli/mcp) |
|
||||
| ⚡ Fast Context - Codebase search | [📖](https://docs.praison.ai/docs/cli/fast-context) |
|
||||
| 📚 Knowledge - RAG management | [📖](https://docs.praison.ai/docs/cli/knowledge) |
|
||||
| 💬 Session - Conversation management | [📖](https://docs.praison.ai/docs/cli/session) |
|
||||
| 🔧 Tools - Tool discovery | [📖](https://docs.praison.ai/docs/cli/tools) |
|
||||
| 🤝 Handoff - Agent delegation | [📖](https://docs.praison.ai/docs/cli/handoff) |
|
||||
| 🧠 Auto Memory - Memory extraction | [📖](https://docs.praison.ai/docs/cli/auto-memory) |
|
||||
| 📋 Todo - Task management | [📖](https://docs.praison.ai/docs/cli/todo) |
|
||||
| 🎯 Router - Smart model selection | [📖](https://docs.praison.ai/docs/cli/router) |
|
||||
| 📈 Flow Display - Visual workflow | [📖](https://docs.praison.ai/docs/cli/flow-display) |
|
||||
| ✨ Prompt Expansion - Detailed prompts | [📖](https://docs.praison.ai/docs/cli/prompt-expansion) |
|
||||
| 🌐 Web Search - Real-time search | [📖](https://docs.praison.ai/docs/cli/web-search) |
|
||||
| 📥 Web Fetch - URL content retrieval | [📖](https://docs.praison.ai/docs/cli/web-fetch) |
|
||||
| 💾 Prompt Caching - Cost reduction | [📖](https://docs.praison.ai/docs/cli/prompt-caching) |
|
||||
|
||||
---
|
||||
|
||||
@@ -2209,7 +2392,7 @@ PraisonAI provides zero-dependency persistent memory for agents. For detailed ex
|
||||
- 📖 **Wikipedia Agent** - Search and extract Wikipedia information
|
||||
- 💻 **Programming Agent** - Code development and analysis
|
||||
- 📝 **Markdown Agent** - Generate and format Markdown content
|
||||
- 🔀 **Router Agent** - Dynamic task routing with cost optimisation
|
||||
- 🔀 **Model Router** - Smart model selection based on task complexity
|
||||
|
||||
### MCP Protocol
|
||||
|
||||
@@ -2218,11 +2401,19 @@ PraisonAI provides zero-dependency persistent memory for agents. For detailed ex
|
||||
- 🔐 **MCP Security** - Origin validation, DNS rebinding prevention, secure sessions
|
||||
- 🔄 **MCP Resumability** - SSE stream recovery via Last-Event-ID
|
||||
|
||||
### A2A & A2UI Protocols
|
||||
|
||||
- 🔗 **A2A Protocol** - Agent-to-Agent communication for inter-agent collaboration
|
||||
- 🖼️ **A2UI Protocol** - Agent-to-User Interface for generating rich UIs from agents
|
||||
- 📋 **UI Templates** - ChatTemplate, ListTemplate, FormTemplate, DashboardTemplate
|
||||
- 🔧 **Surface Builder** - Fluent API for building declarative UIs
|
||||
|
||||
### Safety & Control
|
||||
|
||||
- 🤝 **Agent Handoffs** - Transfer context between specialised agents
|
||||
- 🛡️ **Guardrails** - Input/output validation and safety checks
|
||||
- ✅ **Human Approval** - Require human confirmation for critical actions
|
||||
- 🔐 **Tool Approval CLI** - `--trust` (auto-approve all) and `--approve-level` (risk-based approval)
|
||||
- 💬 **Sessions Management** - Isolated conversation contexts
|
||||
- 🔄 **Stateful Agents** - Maintain state across interactions
|
||||
|
||||
|
||||
@@ -0,0 +1,33 @@
|
||||
# PraisonAI CLI - Benchmark Results
|
||||
|
||||
**Generated:** 2025-12-19 16:04:40
|
||||
|
||||
## Import Times
|
||||
|
||||
| Module | Time (ms) | Target | Status |
|
||||
|--------|-----------|--------|--------|
|
||||
| praisonai | 4.11 | <10 | ✅ |
|
||||
| message_queue | 6.87 | <50 | ✅ |
|
||||
| at_mentions | 0.58 | <50 | ✅ |
|
||||
| profiler | 0.90 | <10 | ✅ |
|
||||
|
||||
## Instantiation Times
|
||||
|
||||
| Class | Time (μs) | Target | Status |
|
||||
|-------|-----------|--------|--------|
|
||||
| MessageQueue | 0.26 | <100 | ✅ |
|
||||
| StateManager | 0.30 | <100 | ✅ |
|
||||
| FileSearchService | 8.42 | <100 | ✅ |
|
||||
|
||||
## Lazy Loading
|
||||
|
||||
| Operation | Time (ms) |
|
||||
|-----------|----------|
|
||||
| PraisonAI lazy load | 3886.47 |
|
||||
|
||||
## How to Reproduce
|
||||
|
||||
```bash
|
||||
cd praisonai
|
||||
python benchmarks/simple_benchmark.py
|
||||
```
|
||||
@@ -0,0 +1,231 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
PraisonAI CLI - Performance Benchmark
|
||||
|
||||
Measures import times and module loading performance.
|
||||
|
||||
Usage:
|
||||
python benchmarks/simple_benchmark.py
|
||||
python benchmarks/simple_benchmark.py --no-save
|
||||
"""
|
||||
|
||||
import time
|
||||
import sys
|
||||
import os
|
||||
import argparse
|
||||
from datetime import datetime
|
||||
|
||||
|
||||
ITERATIONS = 100
|
||||
|
||||
|
||||
def measure_import(module_name: str) -> float:
|
||||
"""Measure import time in milliseconds."""
|
||||
# Clear from cache if present
|
||||
modules_to_remove = [k for k in sys.modules.keys() if k.startswith(module_name)]
|
||||
for mod in modules_to_remove:
|
||||
del sys.modules[mod]
|
||||
|
||||
start = time.perf_counter()
|
||||
__import__(module_name)
|
||||
return (time.perf_counter() - start) * 1000
|
||||
|
||||
|
||||
def measure_instantiation(create_fn, iterations=ITERATIONS) -> float:
|
||||
"""Measure average instantiation time in microseconds."""
|
||||
times = []
|
||||
for _ in range(iterations):
|
||||
start = time.perf_counter()
|
||||
create_fn()
|
||||
times.append((time.perf_counter() - start) * 1_000_000)
|
||||
return sum(times) / len(times)
|
||||
|
||||
|
||||
def run_benchmark():
|
||||
"""Run the benchmark."""
|
||||
results = {}
|
||||
|
||||
print('=' * 60)
|
||||
print('PraisonAI CLI - Performance Benchmark')
|
||||
print('=' * 60)
|
||||
print(f'\nIterations: {ITERATIONS}')
|
||||
print('Metrics: Import time (ms), Instantiation time (μs)\n')
|
||||
|
||||
# 1. Package import time
|
||||
print("1. Testing package imports...")
|
||||
|
||||
# Clear cache
|
||||
modules_to_remove = [k for k in sys.modules.keys() if 'praisonai' in k]
|
||||
for mod in modules_to_remove:
|
||||
del sys.modules[mod]
|
||||
|
||||
start = time.perf_counter()
|
||||
import praisonai
|
||||
results['praisonai_import_ms'] = (time.perf_counter() - start) * 1000
|
||||
print(f" import praisonai: {results['praisonai_import_ms']:.2f}ms")
|
||||
|
||||
# 2. CLI features import
|
||||
print("\n2. Testing CLI features imports...")
|
||||
|
||||
start = time.perf_counter()
|
||||
from praisonai.cli.features.message_queue import MessageQueue
|
||||
results['message_queue_import_ms'] = (time.perf_counter() - start) * 1000
|
||||
print(f" message_queue: {results['message_queue_import_ms']:.2f}ms")
|
||||
|
||||
start = time.perf_counter()
|
||||
from praisonai.cli.features.at_mentions import CombinedCompleter
|
||||
results['at_mentions_import_ms'] = (time.perf_counter() - start) * 1000
|
||||
print(f" at_mentions: {results['at_mentions_import_ms']:.2f}ms")
|
||||
|
||||
# 3. Profiler import (should be fast, standalone)
|
||||
print("\n3. Testing profiler import...")
|
||||
start = time.perf_counter()
|
||||
from praisonai.profiler import Profiler
|
||||
results['profiler_import_ms'] = (time.perf_counter() - start) * 1000
|
||||
print(f" profiler: {results['profiler_import_ms']:.2f}ms")
|
||||
|
||||
# 4. Instantiation benchmarks
|
||||
print(f"\n4. Testing instantiation ({ITERATIONS} iterations)...")
|
||||
|
||||
from praisonai.cli.features.message_queue import MessageQueue, StateManager
|
||||
from praisonai.cli.features.at_mentions import FileSearchService
|
||||
|
||||
results['MessageQueue_us'] = measure_instantiation(lambda: MessageQueue())
|
||||
print(f" MessageQueue: {results['MessageQueue_us']:.2f}μs")
|
||||
|
||||
results['StateManager_us'] = measure_instantiation(lambda: StateManager())
|
||||
print(f" StateManager: {results['StateManager_us']:.2f}μs")
|
||||
|
||||
results['FileSearchService_us'] = measure_instantiation(
|
||||
lambda: FileSearchService(root_dir=".")
|
||||
)
|
||||
print(f" FileSearchService: {results['FileSearchService_us']:.2f}μs")
|
||||
|
||||
# 5. PraisonAI class (lazy load)
|
||||
print("\n5. Testing PraisonAI class access (lazy load)...")
|
||||
start = time.perf_counter()
|
||||
PraisonAI = praisonai.PraisonAI
|
||||
results['PraisonAI_lazy_ms'] = (time.perf_counter() - start) * 1000
|
||||
print(f" PraisonAI lazy load: {results['PraisonAI_lazy_ms']:.2f}ms")
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def print_summary(results: dict):
|
||||
"""Print benchmark summary."""
|
||||
print('\n' + '=' * 60)
|
||||
print('SUMMARY')
|
||||
print('=' * 60)
|
||||
|
||||
print('\nImport Times (target: <50ms for features, <10ms for package):')
|
||||
print(f" {'Module':<25} {'Time':>10} {'Status':>10}")
|
||||
print(f" {'-'*25} {'-'*10} {'-'*10}")
|
||||
|
||||
import_checks = [
|
||||
('praisonai', results['praisonai_import_ms'], 10),
|
||||
('message_queue', results['message_queue_import_ms'], 50),
|
||||
('at_mentions', results['at_mentions_import_ms'], 50),
|
||||
('profiler', results['profiler_import_ms'], 10),
|
||||
]
|
||||
|
||||
all_pass = True
|
||||
for name, time_ms, threshold in import_checks:
|
||||
status = '✅ PASS' if time_ms < threshold else '❌ SLOW'
|
||||
if time_ms >= threshold:
|
||||
all_pass = False
|
||||
print(f" {name:<25} {time_ms:>8.2f}ms {status:>10}")
|
||||
|
||||
print('\nInstantiation Times (target: <100μs):')
|
||||
print(f" {'Class':<25} {'Time':>10} {'Status':>10}")
|
||||
print(f" {'-'*25} {'-'*10} {'-'*10}")
|
||||
|
||||
inst_checks = [
|
||||
('MessageQueue', results['MessageQueue_us'], 100),
|
||||
('StateManager', results['StateManager_us'], 100),
|
||||
('FileSearchService', results['FileSearchService_us'], 100),
|
||||
]
|
||||
|
||||
for name, time_us, threshold in inst_checks:
|
||||
status = '✅ PASS' if time_us < threshold else '❌ SLOW'
|
||||
if time_us >= threshold:
|
||||
all_pass = False
|
||||
print(f" {name:<25} {time_us:>8.2f}μs {status:>10}")
|
||||
|
||||
print('\n' + '=' * 60)
|
||||
if all_pass:
|
||||
print('✅ All benchmarks PASSED')
|
||||
else:
|
||||
print('❌ Some benchmarks FAILED')
|
||||
print('=' * 60)
|
||||
|
||||
return all_pass
|
||||
|
||||
|
||||
def save_results(results: dict):
|
||||
"""Save benchmark results to markdown file."""
|
||||
filepath = os.path.join(os.path.dirname(__file__), 'BENCHMARK_RESULTS.md')
|
||||
|
||||
with open(filepath, 'w') as f:
|
||||
f.write('# PraisonAI CLI - Benchmark Results\n\n')
|
||||
f.write(f'**Generated:** {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n\n')
|
||||
|
||||
f.write('## Import Times\n\n')
|
||||
f.write('| Module | Time (ms) | Target | Status |\n')
|
||||
f.write('|--------|-----------|--------|--------|\n')
|
||||
|
||||
import_data = [
|
||||
('praisonai', results['praisonai_import_ms'], 10),
|
||||
('message_queue', results['message_queue_import_ms'], 50),
|
||||
('at_mentions', results['at_mentions_import_ms'], 50),
|
||||
('profiler', results['profiler_import_ms'], 10),
|
||||
]
|
||||
|
||||
for name, time_ms, threshold in import_data:
|
||||
status = '✅' if time_ms < threshold else '❌'
|
||||
f.write(f'| {name} | {time_ms:.2f} | <{threshold} | {status} |\n')
|
||||
|
||||
f.write('\n## Instantiation Times\n\n')
|
||||
f.write('| Class | Time (μs) | Target | Status |\n')
|
||||
f.write('|-------|-----------|--------|--------|\n')
|
||||
|
||||
inst_data = [
|
||||
('MessageQueue', results['MessageQueue_us'], 100),
|
||||
('StateManager', results['StateManager_us'], 100),
|
||||
('FileSearchService', results['FileSearchService_us'], 100),
|
||||
]
|
||||
|
||||
for name, time_us, threshold in inst_data:
|
||||
status = '✅' if time_us < threshold else '❌'
|
||||
f.write(f'| {name} | {time_us:.2f} | <{threshold} | {status} |\n')
|
||||
|
||||
f.write('\n## Lazy Loading\n\n')
|
||||
f.write(f'| Operation | Time (ms) |\n')
|
||||
f.write(f'|-----------|----------|\n')
|
||||
f.write(f'| PraisonAI lazy load | {results["PraisonAI_lazy_ms"]:.2f} |\n')
|
||||
|
||||
f.write('\n## How to Reproduce\n\n')
|
||||
f.write('```bash\n')
|
||||
f.write('cd praisonai\n')
|
||||
f.write('python benchmarks/simple_benchmark.py\n')
|
||||
f.write('```\n')
|
||||
|
||||
print(f'\nResults saved to: {filepath}')
|
||||
return filepath
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description='PraisonAI CLI Performance Benchmark')
|
||||
parser.add_argument('--no-save', action='store_true', help='Do not save results to file')
|
||||
args = parser.parse_args()
|
||||
|
||||
results = run_benchmark()
|
||||
all_pass = print_summary(results)
|
||||
|
||||
if not args.no_save:
|
||||
save_results(results)
|
||||
|
||||
return 0 if all_pass else 1
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
sys.exit(main())
|
||||
@@ -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/v2.3.35.tar.gz"
|
||||
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.35.tar.gz | shasum -a 256`.split.first
|
||||
url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.63.tar.gz"
|
||||
sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.63.tar.gz | shasum -a 256`.split.first
|
||||
license "MIT"
|
||||
|
||||
depends_on "[email protected]"
|
||||
|
||||
@@ -1,31 +1,34 @@
|
||||
# Suppress crewai.cli.config logger BEFORE any imports to prevent INFO log
|
||||
import logging
|
||||
logging.getLogger('crewai.cli.config').setLevel(logging.ERROR)
|
||||
|
||||
# Disable OpenTelemetry SDK
|
||||
import os
|
||||
os.environ["OTEL_SDK_DISABLED"] = "true"
|
||||
os.environ["EC_TELEMETRY"] = "false"
|
||||
from .cli import PraisonAI
|
||||
|
||||
# Version is lightweight, import directly
|
||||
from .version import __version__
|
||||
|
||||
# Re-export all classes from praisonaiagents to enable:
|
||||
# from praisonai import Agent, Task, PraisonAIAgents
|
||||
try:
|
||||
import praisonaiagents
|
||||
# Import all symbols from praisonaiagents using * import
|
||||
from praisonaiagents import *
|
||||
except ImportError:
|
||||
# If praisonaiagents is not available, these imports will fail gracefully
|
||||
pass
|
||||
|
||||
# Define __all__ to include both PraisonAI core classes and praisonaiagents exports
|
||||
# Define __all__ for lazy loading
|
||||
__all__ = [
|
||||
# Core PraisonAI classes
|
||||
'PraisonAI',
|
||||
'__version__',
|
||||
]
|
||||
|
||||
# Dynamically extend __all__ with praisonaiagents exports
|
||||
try:
|
||||
import praisonaiagents
|
||||
__all__.extend(praisonaiagents.__all__)
|
||||
except (ImportError, AttributeError):
|
||||
# If praisonaiagents is not available or doesn't have __all__, fail gracefully
|
||||
pass
|
||||
# Lazy loading for heavy imports
|
||||
def __getattr__(name):
|
||||
"""Lazy load heavy modules to improve import time."""
|
||||
if name == 'PraisonAI':
|
||||
from .cli import PraisonAI
|
||||
return PraisonAI
|
||||
|
||||
# Try praisonaiagents exports
|
||||
try:
|
||||
import praisonaiagents
|
||||
if hasattr(praisonaiagents, name):
|
||||
return getattr(praisonaiagents, name)
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
+505
-105
@@ -51,14 +51,140 @@ try:
|
||||
except ImportError:
|
||||
PRAISONAI_TOOLS_AVAILABLE = False
|
||||
|
||||
# LiteLLM availability check for multi-provider support
|
||||
LITELLM_AVAILABLE = False
|
||||
try:
|
||||
import litellm # noqa: F401 - imported for availability check
|
||||
LITELLM_AVAILABLE = True
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
logging.basicConfig(level=os.environ.get('LOGLEVEL', 'INFO').upper(), format='%(asctime)s - %(levelname)s - %(message)s')
|
||||
|
||||
# Define Pydantic models outside of the generate method
|
||||
# =============================================================================
|
||||
# Available Tools List (shared between generators)
|
||||
# =============================================================================
|
||||
AVAILABLE_TOOLS = [
|
||||
"CodeDocsSearchTool", "CSVSearchTool", "DirectorySearchTool", "DOCXSearchTool",
|
||||
"DirectoryReadTool", "FileReadTool", "TXTSearchTool", "JSONSearchTool",
|
||||
"MDXSearchTool", "PDFSearchTool", "RagTool", "ScrapeElementFromWebsiteTool",
|
||||
"ScrapeWebsiteTool", "WebsiteSearchTool", "XMLSearchTool",
|
||||
"YoutubeChannelSearchTool", "YoutubeVideoSearchTool"
|
||||
]
|
||||
|
||||
# =============================================================================
|
||||
# Base Generator Class (DRY - shared functionality)
|
||||
# =============================================================================
|
||||
class BaseAutoGenerator:
|
||||
"""
|
||||
Base class for auto-generators with shared functionality.
|
||||
|
||||
Provides:
|
||||
- Lazy-loaded instructor client (LiteLLM or OpenAI fallback)
|
||||
- Environment variable handling for model/API configuration
|
||||
- Config list management
|
||||
"""
|
||||
|
||||
def __init__(self, config_list: Optional[List[Dict]] = None):
|
||||
"""
|
||||
Initialize base generator with LLM configuration.
|
||||
|
||||
Args:
|
||||
config_list: Optional LLM configuration list
|
||||
"""
|
||||
# Support multiple environment variable patterns for better compatibility
|
||||
model_name = os.environ.get("MODEL_NAME") or os.environ.get("OPENAI_MODEL_NAME", "gpt-4o-mini")
|
||||
base_url = (
|
||||
os.environ.get("OPENAI_BASE_URL") or
|
||||
os.environ.get("OPENAI_API_BASE") or
|
||||
os.environ.get("OLLAMA_API_BASE", "https://api.openai.com/v1")
|
||||
)
|
||||
|
||||
self.config_list = config_list or [
|
||||
{
|
||||
'model': model_name,
|
||||
'base_url': base_url,
|
||||
'api_key': os.environ.get("OPENAI_API_KEY")
|
||||
}
|
||||
]
|
||||
self._client = None # Lazy loading for performance
|
||||
|
||||
@property
|
||||
def client(self):
|
||||
"""Lazy load the instructor client to avoid performance impact.
|
||||
|
||||
Uses LiteLLM via instructor.from_provider if available for multi-provider support,
|
||||
otherwise falls back to direct OpenAI SDK.
|
||||
"""
|
||||
if self._client is None:
|
||||
if LITELLM_AVAILABLE:
|
||||
# Use LiteLLM for multi-provider support (100+ LLMs)
|
||||
model_name = self.config_list[0]['model']
|
||||
self._client = instructor.from_provider(
|
||||
f"litellm/{model_name}",
|
||||
mode=instructor.Mode.JSON
|
||||
)
|
||||
else:
|
||||
# Fallback to direct OpenAI SDK
|
||||
self._client = instructor.patch(
|
||||
OpenAI(
|
||||
base_url=self.config_list[0]['base_url'],
|
||||
api_key=self.config_list[0]['api_key'],
|
||||
),
|
||||
mode=instructor.Mode.JSON,
|
||||
)
|
||||
return self._client
|
||||
|
||||
@staticmethod
|
||||
def get_available_tools() -> List[str]:
|
||||
"""Return list of available tools for agent assignment."""
|
||||
return AVAILABLE_TOOLS.copy()
|
||||
|
||||
@staticmethod
|
||||
def analyze_complexity(topic: str) -> str:
|
||||
"""
|
||||
Analyze task complexity based on keywords.
|
||||
|
||||
Args:
|
||||
topic: The task description
|
||||
|
||||
Returns:
|
||||
str: Complexity level - 'simple', 'moderate', or 'complex'
|
||||
"""
|
||||
topic_lower = topic.lower()
|
||||
|
||||
# Complex task indicators
|
||||
complex_keywords = [
|
||||
'comprehensive', 'multi-step', 'analyze and', 'research and write',
|
||||
'multiple', 'coordinate', 'complex', 'detailed analysis',
|
||||
'full report', 'in-depth', 'thorough'
|
||||
]
|
||||
|
||||
# Simple task indicators
|
||||
simple_keywords = [
|
||||
'write a', 'create a', 'simple', 'quick', 'brief',
|
||||
'haiku', 'poem', 'summary', 'list', 'single'
|
||||
]
|
||||
|
||||
if any(kw in topic_lower for kw in complex_keywords):
|
||||
return 'complex'
|
||||
elif any(kw in topic_lower for kw in simple_keywords):
|
||||
return 'simple'
|
||||
else:
|
||||
return 'moderate'
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Pydantic Models for Structured Output
|
||||
# =============================================================================
|
||||
|
||||
class TaskDetails(BaseModel):
|
||||
"""Details for a single task."""
|
||||
description: str
|
||||
expected_output: str
|
||||
|
||||
class RoleDetails(BaseModel):
|
||||
"""Details for a single role/agent."""
|
||||
role: str
|
||||
goal: str
|
||||
backstory: str
|
||||
@@ -66,14 +192,62 @@ class RoleDetails(BaseModel):
|
||||
tools: List[str]
|
||||
|
||||
class TeamStructure(BaseModel):
|
||||
"""Structure for multi-agent team."""
|
||||
roles: Dict[str, RoleDetails]
|
||||
|
||||
class AutoGenerator:
|
||||
def __init__(self, topic="Movie Story writing about AI", agent_file="test.yaml", framework="crewai", config_list: Optional[List[Dict]] = None):
|
||||
class SingleAgentStructure(BaseModel):
|
||||
"""Structure for single-agent generation (Anthropic's 'start simple' principle)."""
|
||||
name: str
|
||||
role: str
|
||||
goal: str
|
||||
backstory: str
|
||||
instructions: str
|
||||
tools: List[str] = []
|
||||
task_description: str
|
||||
expected_output: str
|
||||
|
||||
class PatternRecommendation(BaseModel):
|
||||
"""LLM-based pattern recommendation with reasoning."""
|
||||
pattern: str # sequential, parallel, routing, orchestrator-workers, evaluator-optimizer
|
||||
reasoning: str # Why this pattern was chosen
|
||||
confidence: float # 0.0 to 1.0 confidence score
|
||||
|
||||
class ValidationGate(BaseModel):
|
||||
"""Validation gate for prompt chaining workflows."""
|
||||
criteria: str # What to validate
|
||||
pass_action: str # Action if validation passes (e.g., "continue", "next_step")
|
||||
fail_action: str # Action if validation fails (e.g., "retry", "escalate", "abort")
|
||||
|
||||
class AutoGenerator(BaseAutoGenerator):
|
||||
"""
|
||||
Auto-generates agents.yaml files from a topic description.
|
||||
|
||||
Inherits from BaseAutoGenerator for shared LLM client functionality.
|
||||
|
||||
Usage:
|
||||
generator = AutoGenerator(framework="crewai", topic="Create a movie script")
|
||||
path = generator.generate()
|
||||
"""
|
||||
|
||||
def __init__(self, topic="Movie Story writing about AI", agent_file="test.yaml",
|
||||
framework="crewai", config_list: Optional[List[Dict]] = None,
|
||||
pattern: str = "sequential", single_agent: bool = False):
|
||||
"""
|
||||
Initialize the AutoGenerator class with the specified topic, agent file, and framework.
|
||||
|
||||
Args:
|
||||
topic: The task/topic for agent generation
|
||||
agent_file: Output YAML file name
|
||||
framework: Framework to use (crewai, autogen, praisonai)
|
||||
config_list: Optional LLM configuration
|
||||
pattern: Workflow pattern (sequential, parallel, routing, orchestrator-workers, evaluator-optimizer)
|
||||
single_agent: If True, generate a single agent instead of a team
|
||||
|
||||
Note: autogen framework is different from this AutoGenerator class.
|
||||
"""
|
||||
# Initialize base class first (handles config_list and client)
|
||||
super().__init__(config_list=config_list)
|
||||
|
||||
# Validate framework availability and show framework-specific messages
|
||||
if framework == "crewai" and not CREWAI_AVAILABLE:
|
||||
raise ImportError("""
|
||||
@@ -106,35 +280,42 @@ Tools are not available for {framework}. To use tools, install:
|
||||
pip install "praisonai[{framework}]"
|
||||
""")
|
||||
|
||||
# Support multiple environment variable patterns for better compatibility
|
||||
# Priority order: MODEL_NAME > OPENAI_MODEL_NAME for model selection
|
||||
model_name = os.environ.get("MODEL_NAME") or os.environ.get("OPENAI_MODEL_NAME", "gpt-5-nano")
|
||||
|
||||
# Priority order for base_url: OPENAI_BASE_URL > OPENAI_API_BASE > OLLAMA_API_BASE
|
||||
# OPENAI_BASE_URL is the standard OpenAI SDK environment variable
|
||||
base_url = (
|
||||
os.environ.get("OPENAI_BASE_URL") or
|
||||
os.environ.get("OPENAI_API_BASE") or
|
||||
os.environ.get("OLLAMA_API_BASE", "https://api.openai.com/v1")
|
||||
)
|
||||
|
||||
self.config_list = config_list or [
|
||||
{
|
||||
'model': model_name,
|
||||
'base_url': base_url,
|
||||
'api_key': os.environ.get("OPENAI_API_KEY")
|
||||
}
|
||||
]
|
||||
self.topic = topic
|
||||
self.agent_file = agent_file
|
||||
self.framework = framework or "praisonai"
|
||||
self.client = instructor.patch(
|
||||
OpenAI(
|
||||
base_url=self.config_list[0]['base_url'],
|
||||
api_key=self.config_list[0]['api_key'],
|
||||
),
|
||||
mode=instructor.Mode.JSON,
|
||||
)
|
||||
self.pattern = pattern
|
||||
self.single_agent = single_agent
|
||||
|
||||
def recommend_pattern(self, topic: str = None) -> str:
|
||||
"""
|
||||
Recommend the best workflow pattern based on task characteristics.
|
||||
|
||||
Args:
|
||||
topic: The task description (uses self.topic if not provided)
|
||||
|
||||
Returns:
|
||||
str: Recommended pattern name
|
||||
"""
|
||||
task = topic or self.topic
|
||||
task_lower = task.lower()
|
||||
|
||||
# Keywords that suggest specific patterns
|
||||
parallel_keywords = ['multiple', 'concurrent', 'parallel', 'simultaneously', 'different sources', 'compare', 'various']
|
||||
routing_keywords = ['classify', 'categorize', 'route', 'different types', 'depending on', 'if...then']
|
||||
orchestrator_keywords = ['complex', 'comprehensive', 'multi-step', 'coordinate', 'delegate', 'break down', 'analyze and']
|
||||
evaluator_keywords = ['refine', 'improve', 'iterate', 'quality', 'review', 'feedback', 'polish', 'optimize']
|
||||
|
||||
# Check for pattern indicators
|
||||
if any(kw in task_lower for kw in evaluator_keywords):
|
||||
return "evaluator-optimizer"
|
||||
elif any(kw in task_lower for kw in orchestrator_keywords):
|
||||
return "orchestrator-workers"
|
||||
elif any(kw in task_lower for kw in routing_keywords):
|
||||
return "routing"
|
||||
elif any(kw in task_lower for kw in parallel_keywords):
|
||||
return "parallel"
|
||||
else:
|
||||
return "sequential"
|
||||
|
||||
def generate(self, merge=False):
|
||||
"""
|
||||
@@ -157,7 +338,8 @@ Tools are not available for {framework}. To use tools, install:
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.config_list[0]['model'],
|
||||
response_model=TeamStructure,
|
||||
max_retries=10,
|
||||
max_retries=5,
|
||||
timeout=120.0, # 2 minute timeout for complex generations
|
||||
messages=[
|
||||
{"role": "system", "content": "You are a helpful assistant designed to output complex team structures."},
|
||||
{"role": "user", "content": self.get_user_content()}
|
||||
@@ -194,8 +376,7 @@ Tools are not available for {framework}. To use tools, install:
|
||||
"goal": role_details['goal'],
|
||||
"role": role_details['role'],
|
||||
"tasks": {},
|
||||
# "tools": role_details.get('tools', []),
|
||||
"tools": ['']
|
||||
"tools": role_details.get('tools', [])
|
||||
}
|
||||
|
||||
for task_id, task_details in role_details['tasks'].items():
|
||||
@@ -265,7 +446,7 @@ Tools are not available for {framework}. To use tools, install:
|
||||
"goal": role_details['goal'],
|
||||
"role": role_details['role'],
|
||||
"tasks": {},
|
||||
"tools": ['']
|
||||
"tools": role_details.get('tools', [])
|
||||
}
|
||||
|
||||
# Add tasks for this role
|
||||
@@ -292,45 +473,77 @@ Tools are not available for {framework}. To use tools, install:
|
||||
prompt = generator.get_user_content()
|
||||
print(prompt)
|
||||
"""
|
||||
user_content = """Generate a team structure for \"""" + self.topic + """\" task.
|
||||
No Input data will be provided to the team.
|
||||
The team will work in sequence. First role will pass the output to the next role, and so on.
|
||||
The last role will generate the final output.
|
||||
Think step by step.
|
||||
With maximum 3 roles, each with 1 task. Include role goals, backstories, task descriptions, and expected outputs.
|
||||
List of Available Tools: CodeDocsSearchTool, CSVSearchTool, DirectorySearchTool, DOCXSearchTool, DirectoryReadTool, FileReadTool, TXTSearchTool, JSONSearchTool, MDXSearchTool, PDFSearchTool, RagTool, ScrapeElementFromWebsiteTool, ScrapeWebsiteTool, WebsiteSearchTool, XMLSearchTool, YoutubeChannelSearchTool, YoutubeVideoSearchTool.
|
||||
Only use Available Tools. Do Not use any other tools.
|
||||
Example Below:
|
||||
Use below example to understand the structure of the output.
|
||||
The final role you create should satisfy the provided task: """ + self.topic + """.
|
||||
{
|
||||
"roles": {
|
||||
"narrative_designer": {
|
||||
"role": "Narrative Designer",
|
||||
"goal": "Create AI storylines",
|
||||
"backstory": "Skilled in narrative development for AI, with a focus on story resonance.",
|
||||
"tools": ["ScrapeWebsiteTool"],
|
||||
"tasks": {
|
||||
"story_concept_development": {
|
||||
"description": "Craft a unique AI story concept with depth and engagement using concept from this page the content https://www.asthebirdfliesblog.com/posts/how-to-write-book-story-development .",
|
||||
"expected_output": "Document with narrative arcs, character bios, and settings."
|
||||
}
|
||||
}
|
||||
},
|
||||
"scriptwriter": {
|
||||
"role": "Scriptwriter",
|
||||
"goal": "Write scripts from AI concepts",
|
||||
"backstory": "Expert in dialogue and script structure, translating concepts into scripts.",
|
||||
"tasks": {
|
||||
"scriptwriting_task": {
|
||||
"description": "Turn narrative concepts into scripts, including dialogue and scenes.",
|
||||
"expected_output": "Production-ready script with dialogue and scene details."
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
# Pattern-specific guidance
|
||||
pattern_guidance = {
|
||||
"sequential": "The team will work in sequence. Each role passes output to the next.",
|
||||
"parallel": "The team will work in parallel on independent subtasks, then combine results.",
|
||||
"routing": "A classifier agent will route requests to specialized agents based on input type.",
|
||||
"orchestrator-workers": "A central orchestrator will dynamically delegate tasks to specialized workers.",
|
||||
"evaluator-optimizer": "One agent generates content, another evaluates it in a loop until quality criteria are met."
|
||||
}
|
||||
|
||||
workflow_guidance = pattern_guidance.get(self.pattern, pattern_guidance["sequential"])
|
||||
|
||||
user_content = f"""Analyze and generate a team structure for: "{self.topic}"
|
||||
|
||||
STEP 1: TASK COMPLEXITY ANALYSIS
|
||||
First, analyze the task complexity:
|
||||
- Is this a simple task that 1-2 agents could handle?
|
||||
- Does it require multiple specialized perspectives?
|
||||
- Are there clear sequential dependencies between steps?
|
||||
|
||||
STEP 2: DETERMINE OPTIMAL TEAM SIZE
|
||||
Based on your analysis, create the minimum number of agents needed:
|
||||
- Simple tasks: 1-2 agents
|
||||
- Moderate tasks: 2-3 agents
|
||||
- Complex tasks: 3-4 agents (maximum)
|
||||
|
||||
IMPORTANT: Only create agents that provide meaningful specialization. Avoid unnecessary complexity.
|
||||
|
||||
STEP 3: DESIGN THE TEAM (Pattern: {self.pattern})
|
||||
{workflow_guidance}
|
||||
Each agent should have:
|
||||
- A clear, distinct role
|
||||
- A specific goal
|
||||
- Relevant backstory
|
||||
- 1 focused task with clear description and expected output
|
||||
- Appropriate tools (only if needed)
|
||||
|
||||
Available Tools: CodeDocsSearchTool, CSVSearchTool, DirectorySearchTool, DOCXSearchTool, DirectoryReadTool, FileReadTool, TXTSearchTool, JSONSearchTool, MDXSearchTool, PDFSearchTool, RagTool, ScrapeElementFromWebsiteTool, ScrapeWebsiteTool, WebsiteSearchTool, XMLSearchTool, YoutubeChannelSearchTool, YoutubeVideoSearchTool.
|
||||
Only use these tools if the task requires them. Use empty list [] if no tools needed.
|
||||
|
||||
Example structure (2 agents for a writing task):
|
||||
{{
|
||||
"roles": {{
|
||||
"researcher": {{
|
||||
"role": "Research Analyst",
|
||||
"goal": "Gather comprehensive information on the topic",
|
||||
"backstory": "Expert researcher skilled at finding and synthesizing information.",
|
||||
"tools": ["WebsiteSearchTool"],
|
||||
"tasks": {{
|
||||
"research_task": {{
|
||||
"description": "Research key information about the topic and compile findings.",
|
||||
"expected_output": "Comprehensive research notes with key facts and insights."
|
||||
}}
|
||||
}}
|
||||
}},
|
||||
"writer": {{
|
||||
"role": "Content Writer",
|
||||
"goal": "Create polished final content",
|
||||
"backstory": "Skilled writer who transforms research into engaging content.",
|
||||
"tools": [],
|
||||
"tasks": {{
|
||||
"writing_task": {{
|
||||
"description": "Write the final content based on research findings.",
|
||||
"expected_output": "Polished, well-structured final document."
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
|
||||
Now generate the optimal team structure for: {self.topic}
|
||||
"""
|
||||
return user_content
|
||||
|
||||
|
||||
@@ -372,13 +585,14 @@ class WorkflowStructure(BaseModel):
|
||||
description: str
|
||||
agents: Dict[str, WorkflowAgentDetails]
|
||||
steps: List[Dict] # Can be agent steps, route, parallel, etc.
|
||||
gates: Optional[List[ValidationGate]] = None # Optional validation gates
|
||||
|
||||
|
||||
class WorkflowAutoGenerator:
|
||||
class WorkflowAutoGenerator(BaseAutoGenerator):
|
||||
"""
|
||||
Auto-generates workflow.yaml files from a topic description.
|
||||
|
||||
Uses lazy loading to avoid performance impact when not used.
|
||||
Inherits from BaseAutoGenerator for shared LLM client functionality.
|
||||
|
||||
Usage:
|
||||
generator = WorkflowAutoGenerator(topic="Research AI trends and write a report")
|
||||
@@ -387,7 +601,9 @@ class WorkflowAutoGenerator:
|
||||
|
||||
def __init__(self, topic: str = "Research and write about AI",
|
||||
workflow_file: str = "workflow.yaml",
|
||||
config_list: Optional[List[Dict]] = None):
|
||||
config_list: Optional[List[Dict]] = None,
|
||||
framework: str = "praisonai",
|
||||
single_agent: bool = False):
|
||||
"""
|
||||
Initialize the WorkflowAutoGenerator.
|
||||
|
||||
@@ -395,45 +611,105 @@ class WorkflowAutoGenerator:
|
||||
topic: The task/topic for the workflow
|
||||
workflow_file: Output file name
|
||||
config_list: Optional LLM configuration
|
||||
framework: Framework to use (praisonai, crewai, autogen)
|
||||
single_agent: If True, generate a single agent workflow
|
||||
"""
|
||||
# Support multiple environment variable patterns
|
||||
model_name = os.environ.get("MODEL_NAME") or os.environ.get("OPENAI_MODEL_NAME", "gpt-4o-mini")
|
||||
base_url = (
|
||||
os.environ.get("OPENAI_BASE_URL") or
|
||||
os.environ.get("OPENAI_API_BASE") or
|
||||
os.environ.get("OLLAMA_API_BASE", "https://api.openai.com/v1")
|
||||
)
|
||||
# Initialize base class (handles config_list and client)
|
||||
super().__init__(config_list=config_list)
|
||||
|
||||
self.config_list = config_list or [
|
||||
{
|
||||
'model': model_name,
|
||||
'base_url': base_url,
|
||||
'api_key': os.environ.get("OPENAI_API_KEY")
|
||||
}
|
||||
]
|
||||
self.topic = topic
|
||||
self.workflow_file = workflow_file
|
||||
self._client = None # Lazy loading
|
||||
self.framework = framework
|
||||
self.single_agent = single_agent
|
||||
|
||||
@property
|
||||
def client(self):
|
||||
"""Lazy load the OpenAI client to avoid performance impact."""
|
||||
if self._client is None:
|
||||
self._client = instructor.patch(
|
||||
OpenAI(
|
||||
base_url=self.config_list[0]['base_url'],
|
||||
api_key=self.config_list[0]['api_key'],
|
||||
),
|
||||
mode=instructor.Mode.JSON,
|
||||
)
|
||||
return self._client
|
||||
def recommend_pattern(self, topic: str = None) -> str:
|
||||
"""
|
||||
Recommend the best workflow pattern based on task characteristics.
|
||||
|
||||
Args:
|
||||
topic: The task description (uses self.topic if not provided)
|
||||
|
||||
Returns:
|
||||
str: Recommended pattern name
|
||||
|
||||
Pattern recommendations based on Anthropic's best practices:
|
||||
- sequential: Clear step-by-step dependencies
|
||||
- parallel: Independent subtasks that can run concurrently
|
||||
- routing: Different input types need different handling
|
||||
- orchestrator-workers: Complex tasks needing dynamic decomposition
|
||||
- evaluator-optimizer: Tasks requiring iterative refinement
|
||||
"""
|
||||
task = topic or self.topic
|
||||
task_lower = task.lower()
|
||||
|
||||
# Keywords that suggest specific patterns
|
||||
parallel_keywords = ['multiple', 'concurrent', 'parallel', 'simultaneously', 'different sources', 'compare', 'various']
|
||||
routing_keywords = ['classify', 'categorize', 'route', 'different types', 'depending on', 'if...then']
|
||||
orchestrator_keywords = ['complex', 'comprehensive', 'multi-step', 'coordinate', 'delegate', 'break down', 'analyze and']
|
||||
evaluator_keywords = ['refine', 'improve', 'iterate', 'quality', 'review', 'feedback', 'polish', 'optimize']
|
||||
|
||||
# Check for pattern indicators
|
||||
if any(kw in task_lower for kw in evaluator_keywords):
|
||||
return "evaluator-optimizer"
|
||||
elif any(kw in task_lower for kw in orchestrator_keywords):
|
||||
return "orchestrator-workers"
|
||||
elif any(kw in task_lower for kw in routing_keywords):
|
||||
return "routing"
|
||||
elif any(kw in task_lower for kw in parallel_keywords):
|
||||
return "parallel"
|
||||
else:
|
||||
return "sequential"
|
||||
|
||||
def generate(self, pattern: str = "sequential") -> str:
|
||||
def recommend_pattern_llm(self, topic: str = None) -> PatternRecommendation:
|
||||
"""
|
||||
Use LLM to recommend the best workflow pattern with reasoning.
|
||||
|
||||
Args:
|
||||
topic: The task description (uses self.topic if not provided)
|
||||
|
||||
Returns:
|
||||
PatternRecommendation: Pattern with reasoning and confidence score
|
||||
"""
|
||||
task = topic or self.topic
|
||||
|
||||
prompt = f"""Analyze this task and recommend the best workflow pattern:
|
||||
|
||||
Task: "{task}"
|
||||
|
||||
Available patterns:
|
||||
1. sequential - Agents work one after another, passing output to the next
|
||||
2. parallel - Multiple agents work concurrently on independent subtasks
|
||||
3. routing - A classifier routes requests to specialized agents based on input type
|
||||
4. orchestrator-workers - Central orchestrator dynamically delegates to specialized workers
|
||||
5. evaluator-optimizer - Generator creates content, evaluator reviews in a loop until quality met
|
||||
|
||||
Respond with:
|
||||
- pattern: The recommended pattern name
|
||||
- reasoning: Why this pattern is best for this task
|
||||
- confidence: Your confidence score (0.0 to 1.0)
|
||||
"""
|
||||
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.config_list[0]['model'],
|
||||
response_model=PatternRecommendation,
|
||||
max_retries=3,
|
||||
timeout=60.0,
|
||||
messages=[
|
||||
{"role": "system", "content": "You are an expert at designing AI agent workflows."},
|
||||
{"role": "user", "content": prompt}
|
||||
]
|
||||
)
|
||||
|
||||
return response
|
||||
|
||||
def generate(self, pattern: str = "sequential", merge: bool = False) -> str:
|
||||
"""
|
||||
Generate a workflow YAML file.
|
||||
|
||||
Args:
|
||||
pattern: Workflow pattern - "sequential", "routing", "parallel", "loop"
|
||||
pattern: Workflow pattern - "sequential", "routing", "parallel", "loop",
|
||||
"orchestrator-workers", "evaluator-optimizer"
|
||||
merge: If True, merge with existing workflow file instead of overwriting
|
||||
|
||||
Returns:
|
||||
Path to the generated workflow file
|
||||
@@ -442,6 +718,7 @@ class WorkflowAutoGenerator:
|
||||
model=self.config_list[0]['model'],
|
||||
response_model=WorkflowStructure,
|
||||
max_retries=5,
|
||||
timeout=120.0, # 2 minute timeout for complex generations
|
||||
messages=[
|
||||
{"role": "system", "content": "You are a helpful assistant that designs workflow structures."},
|
||||
{"role": "user", "content": self._get_prompt(pattern)}
|
||||
@@ -449,16 +726,86 @@ class WorkflowAutoGenerator:
|
||||
)
|
||||
|
||||
json_data = json.loads(response.model_dump_json())
|
||||
|
||||
if merge and os.path.exists(self.workflow_file):
|
||||
return self._save_workflow(self.merge_with_existing_workflow(json_data), pattern)
|
||||
return self._save_workflow(json_data, pattern)
|
||||
|
||||
def merge_with_existing_workflow(self, new_data: Dict) -> Dict:
|
||||
"""
|
||||
Merge new workflow data with existing workflow file.
|
||||
|
||||
Args:
|
||||
new_data: The new workflow data to merge
|
||||
|
||||
Returns:
|
||||
Dict: Merged workflow data
|
||||
"""
|
||||
try:
|
||||
with open(self.workflow_file, 'r') as f:
|
||||
existing_data = yaml.safe_load(f)
|
||||
|
||||
if not existing_data:
|
||||
return new_data
|
||||
except (yaml.YAMLError, FileNotFoundError) as e:
|
||||
logging.warning(f"Could not load existing workflow file {self.workflow_file}: {e}")
|
||||
return new_data
|
||||
|
||||
# Merge agents (avoid duplicates)
|
||||
merged_agents = existing_data.get('agents', {}).copy()
|
||||
for agent_id, agent_data in new_data.get('agents', {}).items():
|
||||
# Rename if conflict
|
||||
final_id = agent_id
|
||||
counter = 1
|
||||
while final_id in merged_agents:
|
||||
final_id = f"{agent_id}_auto_{counter}"
|
||||
counter += 1
|
||||
merged_agents[final_id] = agent_data
|
||||
|
||||
# Merge steps (append new steps)
|
||||
merged_steps = existing_data.get('steps', []) + new_data.get('steps', [])
|
||||
|
||||
# Create merged structure
|
||||
merged = {
|
||||
'name': existing_data.get('name', new_data.get('name', 'Merged Workflow')),
|
||||
'description': f"{existing_data.get('description', '')} + {new_data.get('description', '')}",
|
||||
'agents': merged_agents,
|
||||
'steps': merged_steps
|
||||
}
|
||||
|
||||
return merged
|
||||
|
||||
def _get_prompt(self, pattern: str) -> str:
|
||||
"""Generate the prompt based on the workflow pattern."""
|
||||
# Analyze complexity to determine agent count
|
||||
complexity = self.analyze_complexity(self.topic)
|
||||
if complexity == 'simple':
|
||||
agent_guidance = "Create 1-2 agents (simple task detected)."
|
||||
elif complexity == 'complex':
|
||||
agent_guidance = "Create 3-4 agents (complex task detected)."
|
||||
else:
|
||||
agent_guidance = "Create 2-3 agents (moderate task detected)."
|
||||
|
||||
# Get available tools
|
||||
tools_list = ", ".join(self.get_available_tools())
|
||||
|
||||
base_prompt = f"""Generate a workflow structure for: "{self.topic}"
|
||||
|
||||
STEP 1: ANALYZE TASK COMPLEXITY
|
||||
- Is this a simple task (1-2 agents)?
|
||||
- Does it require multiple specialists (2-3 agents)?
|
||||
- Is it complex with many dependencies (3-4 agents)?
|
||||
|
||||
STEP 2: DESIGN WORKFLOW
|
||||
The workflow should use the "{pattern}" pattern.
|
||||
Create 2-4 agents with clear roles and instructions.
|
||||
{agent_guidance}
|
||||
Each agent should have clear roles and instructions.
|
||||
Each step should have a clear action.
|
||||
|
||||
STEP 3: ASSIGN TOOLS (if needed)
|
||||
Available Tools: {tools_list}
|
||||
Only assign tools if the task requires them. Use empty list or null if no tools needed.
|
||||
|
||||
"""
|
||||
|
||||
if pattern == "routing":
|
||||
@@ -501,6 +848,59 @@ Example structure:
|
||||
{"agent": "aggregator", "action": "Combine all findings"}
|
||||
]
|
||||
}
|
||||
"""
|
||||
elif pattern == "orchestrator-workers":
|
||||
base_prompt += """
|
||||
Create an orchestrator-workers workflow where a central orchestrator dynamically delegates tasks to specialized workers.
|
||||
The orchestrator analyzes the input, decides which workers are needed, and synthesizes results.
|
||||
|
||||
Example structure:
|
||||
{
|
||||
"name": "Orchestrator-Workers Workflow",
|
||||
"description": "Central orchestrator delegates to specialized workers",
|
||||
"agents": {
|
||||
"orchestrator": {"name": "Orchestrator", "role": "Task Coordinator", "goal": "Analyze tasks and delegate to appropriate workers", "instructions": "Break down the task, identify required specialists, and coordinate their work. Output a JSON with 'subtasks' array listing which workers to invoke."},
|
||||
"researcher": {"name": "Researcher", "role": "Research Specialist", "goal": "Gather information", "instructions": "Research and provide factual information"},
|
||||
"analyst": {"name": "Analyst", "role": "Data Analyst", "goal": "Analyze data and patterns", "instructions": "Analyze information and identify insights"},
|
||||
"writer": {"name": "Writer", "role": "Content Writer", "goal": "Create written content", "instructions": "Write clear, engaging content"},
|
||||
"synthesizer": {"name": "Synthesizer", "role": "Results Synthesizer", "goal": "Combine all worker outputs", "instructions": "Synthesize all worker outputs into a coherent final result"}
|
||||
},
|
||||
"steps": [
|
||||
{"agent": "orchestrator", "action": "Analyze task and determine required workers: {{input}}"},
|
||||
{"name": "worker_dispatch", "parallel": [
|
||||
{"agent": "researcher", "action": "Research: {{input}}"},
|
||||
{"agent": "analyst", "action": "Analyze: {{input}}"},
|
||||
{"agent": "writer", "action": "Draft content for: {{input}}"}
|
||||
]},
|
||||
{"agent": "synthesizer", "action": "Combine all worker outputs into final result"}
|
||||
]
|
||||
}
|
||||
"""
|
||||
elif pattern == "evaluator-optimizer":
|
||||
base_prompt += """
|
||||
Create an evaluator-optimizer workflow where one agent generates content and another evaluates it in a loop.
|
||||
The generator improves based on evaluator feedback until quality criteria are met.
|
||||
|
||||
Example structure:
|
||||
{
|
||||
"name": "Evaluator-Optimizer Workflow",
|
||||
"description": "Iterative refinement through generation and evaluation",
|
||||
"agents": {
|
||||
"generator": {"name": "Generator", "role": "Content Generator", "goal": "Generate high-quality content", "instructions": "Create content based on the input. If feedback is provided, improve the content accordingly."},
|
||||
"evaluator": {"name": "Evaluator", "role": "Quality Evaluator", "goal": "Evaluate content quality", "instructions": "Evaluate the content on: clarity, accuracy, completeness, and relevance. Score 1-10 for each. If average score < 7, provide specific improvement feedback. If score >= 7, respond with 'APPROVED'."}
|
||||
},
|
||||
"steps": [
|
||||
{"agent": "generator", "action": "Generate initial content for: {{input}}"},
|
||||
{"name": "evaluation_loop", "loop": {
|
||||
"agent": "evaluator",
|
||||
"action": "Evaluate the generated content",
|
||||
"condition": "output does not contain 'APPROVED'",
|
||||
"max_iterations": 3,
|
||||
"feedback_to": "generator"
|
||||
}},
|
||||
{"agent": "generator", "action": "Finalize content based on all feedback"}
|
||||
]
|
||||
}
|
||||
"""
|
||||
else: # sequential
|
||||
base_prompt += """
|
||||
|
||||
@@ -8,12 +8,19 @@ Structure:
|
||||
- features/: Feature handlers for CLI flags and commands
|
||||
"""
|
||||
|
||||
from .main import PraisonAI
|
||||
|
||||
__all__ = ["PraisonAI"]
|
||||
|
||||
|
||||
def __getattr__(name):
|
||||
"""Lazy load PraisonAI to avoid slow imports."""
|
||||
if name == "PraisonAI":
|
||||
from .main import PraisonAI
|
||||
return PraisonAI
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
|
||||
|
||||
def main():
|
||||
"""CLI entry point function."""
|
||||
from .main import PraisonAI
|
||||
praison_ai = PraisonAI()
|
||||
praison_ai.main()
|
||||
@@ -21,6 +21,12 @@ Features:
|
||||
- flow_display: Visual workflow tracking
|
||||
- workflow: YAML workflow management
|
||||
- n8n: Export workflows to n8n visual editor
|
||||
- external_agents: External AI CLI tool integrations (Claude, Gemini, Codex, Cursor)
|
||||
- slash_commands: Interactive slash commands (/help, /cost, /plan, etc.)
|
||||
- autonomy_mode: Autonomy levels (suggest, auto-edit, full-auto)
|
||||
- cost_tracker: Real-time cost and token tracking
|
||||
- message_queue: Message queuing while agent is processing
|
||||
- at_mentions: @ mention autocomplete for files and directories
|
||||
"""
|
||||
|
||||
# Type hints available for IDE support
|
||||
@@ -43,6 +49,20 @@ __all__ = [
|
||||
'FlowDisplayHandler',
|
||||
'WorkflowHandler',
|
||||
'N8nHandler',
|
||||
'ExternalAgentsHandler',
|
||||
# New CLI enhancement features
|
||||
'SlashCommandHandler',
|
||||
'AutonomyModeHandler',
|
||||
'CostTrackerHandler',
|
||||
'RepoMapHandler',
|
||||
'InteractiveTUIHandler',
|
||||
'GitIntegrationHandler',
|
||||
'SandboxExecutorHandler',
|
||||
'MessageQueueHandler',
|
||||
# @ mention autocomplete
|
||||
'AtMentionCompleter',
|
||||
'CombinedCompleter',
|
||||
'FileSearchService',
|
||||
]
|
||||
|
||||
def __getattr__(name):
|
||||
@@ -95,4 +115,42 @@ def __getattr__(name):
|
||||
elif name == 'N8nHandler':
|
||||
from .n8n import N8nHandler
|
||||
return N8nHandler
|
||||
elif name == 'ExternalAgentsHandler':
|
||||
from .external_agents import ExternalAgentsHandler
|
||||
return ExternalAgentsHandler
|
||||
# New CLI enhancement features
|
||||
elif name == 'SlashCommandHandler':
|
||||
from .slash_commands import SlashCommandHandler
|
||||
return SlashCommandHandler
|
||||
elif name == 'AutonomyModeHandler':
|
||||
from .autonomy_mode import AutonomyModeHandler
|
||||
return AutonomyModeHandler
|
||||
elif name == 'CostTrackerHandler':
|
||||
from .cost_tracker import CostTrackerHandler
|
||||
return CostTrackerHandler
|
||||
elif name == 'RepoMapHandler':
|
||||
from .repo_map import RepoMapHandler
|
||||
return RepoMapHandler
|
||||
elif name == 'InteractiveTUIHandler':
|
||||
from .interactive_tui import InteractiveTUIHandler
|
||||
return InteractiveTUIHandler
|
||||
elif name == 'GitIntegrationHandler':
|
||||
from .git_integration import GitIntegrationHandler
|
||||
return GitIntegrationHandler
|
||||
elif name == 'SandboxExecutorHandler':
|
||||
from .sandbox_executor import SandboxExecutorHandler
|
||||
return SandboxExecutorHandler
|
||||
elif name == 'MessageQueueHandler':
|
||||
from .message_queue import MessageQueueHandler
|
||||
return MessageQueueHandler
|
||||
# @ mention autocomplete
|
||||
elif name == 'AtMentionCompleter':
|
||||
from .at_mentions import AtMentionCompleter
|
||||
return AtMentionCompleter
|
||||
elif name == 'CombinedCompleter':
|
||||
from .at_mentions import CombinedCompleter
|
||||
return CombinedCompleter
|
||||
elif name == 'FileSearchService':
|
||||
from .at_mentions import FileSearchService
|
||||
return FileSearchService
|
||||
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
|
||||
@@ -0,0 +1,416 @@
|
||||
"""
|
||||
@ Mention Autocomplete for PraisonAI CLI.
|
||||
|
||||
Provides file/directory autocomplete when user types @.
|
||||
Uses only stdlib imports for zero performance impact.
|
||||
|
||||
Features:
|
||||
- Detect @ trigger in input
|
||||
- Fuzzy search files/directories
|
||||
- Cache results for performance
|
||||
- Integrate with prompt_toolkit
|
||||
"""
|
||||
|
||||
import os
|
||||
import time
|
||||
import fnmatch
|
||||
from dataclasses import dataclass
|
||||
from typing import List, Optional, Dict, Tuple
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Data Classes
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class AtMentionContext:
|
||||
"""Context for an @ mention in user input."""
|
||||
is_active: bool
|
||||
query: str
|
||||
start_pos: int
|
||||
mention_type: str = "file" # file, directory, web, etc.
|
||||
|
||||
|
||||
@dataclass
|
||||
class FileSuggestion:
|
||||
"""A file or directory suggestion."""
|
||||
path: str
|
||||
file_type: str # "file" or "directory"
|
||||
score: int = 100
|
||||
display: str = ""
|
||||
|
||||
def __post_init__(self):
|
||||
if not self.display:
|
||||
self.display = self.path
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# @ Mention Detection
|
||||
# ============================================================================
|
||||
|
||||
def detect_at_mention(text: str, cursor_pos: int) -> Optional[AtMentionContext]:
|
||||
"""
|
||||
Detect if cursor is within an @ mention context.
|
||||
|
||||
Scans backward from cursor to find @ symbol.
|
||||
Returns None if not in @ context.
|
||||
|
||||
Args:
|
||||
text: Full input text
|
||||
cursor_pos: Current cursor position
|
||||
|
||||
Returns:
|
||||
AtMentionContext if in @ mention, None otherwise
|
||||
"""
|
||||
if cursor_pos <= 0 or cursor_pos > len(text):
|
||||
return None
|
||||
|
||||
# Scan backward from cursor to find @
|
||||
at_pos = -1
|
||||
for i in range(cursor_pos - 1, -1, -1):
|
||||
char = text[i]
|
||||
|
||||
# Found @
|
||||
if char == '@':
|
||||
at_pos = i
|
||||
break
|
||||
|
||||
# Space/newline breaks @ context
|
||||
if char in ' \t\n\r':
|
||||
return None
|
||||
|
||||
if at_pos == -1:
|
||||
return None
|
||||
|
||||
# Extract query between @ and cursor
|
||||
query = text[at_pos + 1:cursor_pos]
|
||||
|
||||
return AtMentionContext(
|
||||
is_active=True,
|
||||
query=query,
|
||||
start_pos=at_pos
|
||||
)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# File Search Service
|
||||
# ============================================================================
|
||||
|
||||
class FileSearchService:
|
||||
"""
|
||||
Service for searching files in a directory.
|
||||
|
||||
Features:
|
||||
- Walk directory tree
|
||||
- Fuzzy match file paths
|
||||
- Cache results with TTL
|
||||
- Respect .gitignore (basic)
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
root_dir: str,
|
||||
cache_ttl: int = 30,
|
||||
max_depth: int = 5,
|
||||
ignore_patterns: Optional[List[str]] = None
|
||||
):
|
||||
self._root = os.path.abspath(root_dir)
|
||||
self._cache_ttl = cache_ttl
|
||||
self._max_depth = max_depth
|
||||
self._ignore_patterns = ignore_patterns or [
|
||||
'.git', '__pycache__', 'node_modules', '.venv', 'venv',
|
||||
'*.pyc', '*.pyo', '.DS_Store', '*.egg-info'
|
||||
]
|
||||
|
||||
# Cache: query -> (results, timestamp)
|
||||
self._cache: Dict[str, Tuple[List[FileSuggestion], float]] = {}
|
||||
|
||||
# File list cache
|
||||
self._file_list: Optional[List[str]] = None
|
||||
self._file_list_time: float = 0
|
||||
|
||||
def _should_ignore(self, name: str) -> bool:
|
||||
"""Check if file/dir should be ignored."""
|
||||
for pattern in self._ignore_patterns:
|
||||
if fnmatch.fnmatch(name, pattern):
|
||||
return True
|
||||
return False
|
||||
|
||||
def _get_file_list(self) -> List[str]:
|
||||
"""Get list of all files (cached)."""
|
||||
now = time.time()
|
||||
|
||||
# Return cached if fresh
|
||||
if self._file_list is not None and (now - self._file_list_time) < self._cache_ttl:
|
||||
return self._file_list
|
||||
|
||||
files = []
|
||||
|
||||
try:
|
||||
for root, dirs, filenames in os.walk(self._root):
|
||||
# Calculate depth
|
||||
rel_root = os.path.relpath(root, self._root)
|
||||
depth = 0 if rel_root == '.' else rel_root.count(os.sep) + 1
|
||||
|
||||
if depth > self._max_depth:
|
||||
dirs.clear() # Don't descend further
|
||||
continue
|
||||
|
||||
# Filter ignored directories
|
||||
dirs[:] = [d for d in dirs if not self._should_ignore(d)]
|
||||
|
||||
# Add directories
|
||||
for d in dirs:
|
||||
rel_path = os.path.relpath(os.path.join(root, d), self._root)
|
||||
files.append(rel_path + os.sep)
|
||||
|
||||
# Add files
|
||||
for f in filenames:
|
||||
if not self._should_ignore(f):
|
||||
rel_path = os.path.relpath(os.path.join(root, f), self._root)
|
||||
files.append(rel_path)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
self._file_list = files
|
||||
self._file_list_time = now
|
||||
return files
|
||||
|
||||
def _fuzzy_match(self, text: str, query: str) -> int:
|
||||
"""
|
||||
Simple fuzzy match scoring.
|
||||
|
||||
Returns score 0-100, higher is better.
|
||||
"""
|
||||
if not query:
|
||||
return 50 # Default score for empty query
|
||||
|
||||
text_lower = text.lower()
|
||||
query_lower = query.lower()
|
||||
|
||||
# Exact match
|
||||
if text_lower == query_lower:
|
||||
return 100
|
||||
|
||||
# Starts with
|
||||
if text_lower.startswith(query_lower):
|
||||
return 90
|
||||
|
||||
# Contains
|
||||
if query_lower in text_lower:
|
||||
return 80
|
||||
|
||||
# Fuzzy: all query chars appear in order
|
||||
text_idx = 0
|
||||
query_idx = 0
|
||||
matches = 0
|
||||
|
||||
while text_idx < len(text_lower) and query_idx < len(query_lower):
|
||||
if text_lower[text_idx] == query_lower[query_idx]:
|
||||
matches += 1
|
||||
query_idx += 1
|
||||
text_idx += 1
|
||||
|
||||
if query_idx == len(query_lower):
|
||||
# All query chars found
|
||||
return 50 + int(30 * matches / len(text))
|
||||
|
||||
return 0
|
||||
|
||||
def search(self, query: str, max_results: int = 20) -> List[FileSuggestion]:
|
||||
"""
|
||||
Search for files matching query.
|
||||
|
||||
Args:
|
||||
query: Search query (fuzzy matched)
|
||||
max_results: Maximum results to return
|
||||
|
||||
Returns:
|
||||
List of FileSuggestion sorted by score
|
||||
"""
|
||||
# Check cache
|
||||
cache_key = f"{query}:{max_results}"
|
||||
now = time.time()
|
||||
|
||||
if cache_key in self._cache:
|
||||
results, cached_time = self._cache[cache_key]
|
||||
if (now - cached_time) < self._cache_ttl:
|
||||
return results
|
||||
|
||||
# Get all files
|
||||
all_files = self._get_file_list()
|
||||
|
||||
# Score and filter
|
||||
scored: List[Tuple[int, str]] = []
|
||||
for path in all_files:
|
||||
score = self._fuzzy_match(path, query)
|
||||
if score > 0:
|
||||
scored.append((score, path))
|
||||
|
||||
# Sort by score descending
|
||||
scored.sort(key=lambda x: (-x[0], x[1]))
|
||||
|
||||
# Build results
|
||||
results = []
|
||||
for score, path in scored[:max_results]:
|
||||
file_type = "directory" if path.endswith(os.sep) else "file"
|
||||
results.append(FileSuggestion(
|
||||
path=path,
|
||||
file_type=file_type,
|
||||
score=score
|
||||
))
|
||||
|
||||
# Cache results
|
||||
self._cache[cache_key] = (results, now)
|
||||
|
||||
return results
|
||||
|
||||
def clear_cache(self) -> None:
|
||||
"""Clear all caches."""
|
||||
self._cache.clear()
|
||||
self._file_list = None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Completers for prompt_toolkit
|
||||
# ============================================================================
|
||||
|
||||
# Lazy import to avoid performance impact
|
||||
_Completer = None
|
||||
_Completion = None
|
||||
|
||||
def _get_prompt_toolkit():
|
||||
"""Lazy import prompt_toolkit."""
|
||||
global _Completer, _Completion
|
||||
if _Completer is None:
|
||||
from prompt_toolkit.completion import Completer, Completion
|
||||
_Completer = Completer
|
||||
_Completion = Completion
|
||||
return _Completer, _Completion
|
||||
|
||||
|
||||
class AtMentionCompleter:
|
||||
"""
|
||||
Completer for @ mentions.
|
||||
|
||||
Shows file suggestions when user types @.
|
||||
Implements prompt_toolkit Completer interface.
|
||||
"""
|
||||
|
||||
def __init__(self, root_dir: str):
|
||||
self._file_service = FileSearchService(root_dir)
|
||||
|
||||
def get_completions(self, document, complete_event):
|
||||
"""Get completions for @ mentions."""
|
||||
_, Completion = _get_prompt_toolkit()
|
||||
|
||||
text = document.text_before_cursor
|
||||
cursor_pos = len(text)
|
||||
|
||||
# Detect @ context
|
||||
context = detect_at_mention(text, cursor_pos)
|
||||
if context is None or not context.is_active:
|
||||
return
|
||||
|
||||
# Search files
|
||||
results = self._file_service.search(context.query, max_results=15)
|
||||
|
||||
# Yield completions
|
||||
for suggestion in results:
|
||||
# Icon based on type
|
||||
icon = "📁 " if suggestion.file_type == "directory" else "📄 "
|
||||
display = f"{icon}{suggestion.path}"
|
||||
|
||||
# Calculate replacement position
|
||||
# Replace from @ to cursor
|
||||
start_position = -(cursor_pos - context.start_pos)
|
||||
|
||||
yield Completion(
|
||||
text=f"@{suggestion.path}",
|
||||
start_position=start_position,
|
||||
display=display
|
||||
)
|
||||
|
||||
|
||||
def create_combined_completer(commands: List[str], root_dir: str):
|
||||
"""
|
||||
Factory function to create a CombinedCompleter.
|
||||
|
||||
Returns a proper Completer subclass that handles both / and @.
|
||||
"""
|
||||
Completer, Completion = _get_prompt_toolkit()
|
||||
file_service = FileSearchService(root_dir)
|
||||
|
||||
class CombinedCompleter(Completer):
|
||||
"""
|
||||
Combined completer for both / commands and @ mentions.
|
||||
|
||||
Properly inherits from prompt_toolkit Completer.
|
||||
"""
|
||||
|
||||
def get_completions(self, document, complete_event):
|
||||
"""Get completions for / or @."""
|
||||
text = document.text_before_cursor.lstrip()
|
||||
|
||||
# Check for slash command
|
||||
if text.startswith('/'):
|
||||
cmd_text = text[1:].lower()
|
||||
for cmd in commands:
|
||||
if cmd.lower().startswith(cmd_text):
|
||||
yield Completion(
|
||||
f'/{cmd}',
|
||||
start_position=-len(text),
|
||||
display=f'/{cmd}'
|
||||
)
|
||||
return
|
||||
|
||||
# Check for @ mention
|
||||
full_text = document.text_before_cursor
|
||||
cursor_pos = len(full_text)
|
||||
|
||||
context = detect_at_mention(full_text, cursor_pos)
|
||||
if context is None or not context.is_active:
|
||||
return
|
||||
|
||||
# Search files
|
||||
results = file_service.search(context.query, max_results=15)
|
||||
|
||||
# Yield completions
|
||||
for suggestion in results:
|
||||
icon = "📁 " if suggestion.file_type == "directory" else "📄 "
|
||||
display = f"{icon}{suggestion.path}"
|
||||
start_position = -(cursor_pos - context.start_pos)
|
||||
|
||||
yield Completion(
|
||||
text=f"@{suggestion.path}",
|
||||
start_position=start_position,
|
||||
display=display
|
||||
)
|
||||
|
||||
return CombinedCompleter()
|
||||
|
||||
|
||||
# Backward compatible alias
|
||||
class CombinedCompleter:
|
||||
"""
|
||||
Wrapper class for backward compatibility.
|
||||
|
||||
Use create_combined_completer() for proper Completer subclass.
|
||||
"""
|
||||
|
||||
def __new__(cls, commands: List[str], root_dir: str):
|
||||
return create_combined_completer(commands, root_dir)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Exports
|
||||
# ============================================================================
|
||||
|
||||
__all__ = [
|
||||
'AtMentionContext',
|
||||
'FileSuggestion',
|
||||
'detect_at_mention',
|
||||
'FileSearchService',
|
||||
'AtMentionCompleter',
|
||||
'CombinedCompleter',
|
||||
]
|
||||
@@ -0,0 +1,490 @@
|
||||
"""
|
||||
Autonomy Modes for PraisonAI CLI.
|
||||
|
||||
Inspired by Codex CLI's approval modes and Gemini CLI's approval settings.
|
||||
Provides configurable autonomy levels: suggest, auto-edit, full-auto.
|
||||
|
||||
Architecture:
|
||||
- AutonomyMode: Enum for different autonomy levels
|
||||
- AutonomyPolicy: Policy configuration for each mode
|
||||
- AutonomyManager: Manages mode transitions and approvals
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Callable, Dict, Optional, Set
|
||||
from enum import Enum
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class AutonomyMode(Enum):
|
||||
"""
|
||||
Autonomy levels for agent execution.
|
||||
|
||||
Inspired by Codex CLI's approval modes:
|
||||
- SUGGEST: Read-only, requires approval for all changes
|
||||
- AUTO_EDIT: Auto-approve file edits, require approval for commands
|
||||
- FULL_AUTO: Auto-approve everything (YOLO mode)
|
||||
"""
|
||||
SUGGEST = "suggest" # Default: ask for approval on everything
|
||||
AUTO_EDIT = "auto_edit" # Auto-approve file edits only
|
||||
FULL_AUTO = "full_auto" # Auto-approve everything (dangerous)
|
||||
|
||||
@classmethod
|
||||
def from_string(cls, value: str) -> "AutonomyMode":
|
||||
"""Parse mode from string."""
|
||||
value = value.lower().strip().replace("-", "_")
|
||||
for mode in cls:
|
||||
if mode.value == value:
|
||||
return mode
|
||||
raise ValueError(f"Unknown autonomy mode: {value}")
|
||||
|
||||
|
||||
class ActionType(Enum):
|
||||
"""Types of actions that require approval."""
|
||||
FILE_READ = "file_read"
|
||||
FILE_WRITE = "file_write"
|
||||
FILE_DELETE = "file_delete"
|
||||
SHELL_COMMAND = "shell_command"
|
||||
NETWORK_REQUEST = "network_request"
|
||||
CODE_EXECUTION = "code_execution"
|
||||
GIT_OPERATION = "git_operation"
|
||||
TOOL_CALL = "tool_call"
|
||||
|
||||
|
||||
@dataclass
|
||||
class ActionRequest:
|
||||
"""
|
||||
Request for an action that may require approval.
|
||||
|
||||
Attributes:
|
||||
action_type: Type of action
|
||||
description: Human-readable description
|
||||
details: Additional details (file path, command, etc.)
|
||||
risk_level: Estimated risk (low, medium, high)
|
||||
reversible: Whether the action can be undone
|
||||
"""
|
||||
action_type: ActionType
|
||||
description: str
|
||||
details: Dict[str, Any] = field(default_factory=dict)
|
||||
risk_level: str = "medium"
|
||||
reversible: bool = True
|
||||
|
||||
def __str__(self) -> str:
|
||||
return f"{self.action_type.value}: {self.description}"
|
||||
|
||||
|
||||
@dataclass
|
||||
class ApprovalResult:
|
||||
"""Result of an approval request."""
|
||||
approved: bool
|
||||
reason: Optional[str] = None
|
||||
modified_action: Optional[ActionRequest] = None
|
||||
remember_choice: bool = False
|
||||
|
||||
|
||||
@dataclass
|
||||
class AutonomyPolicy:
|
||||
"""
|
||||
Policy configuration for autonomy mode.
|
||||
|
||||
Defines which actions are auto-approved, require approval,
|
||||
or are blocked entirely.
|
||||
"""
|
||||
mode: AutonomyMode
|
||||
|
||||
# Actions that are auto-approved
|
||||
auto_approve: Set[ActionType] = field(default_factory=set)
|
||||
|
||||
# Actions that always require approval
|
||||
require_approval: Set[ActionType] = field(default_factory=set)
|
||||
|
||||
# Actions that are blocked entirely
|
||||
blocked: Set[ActionType] = field(default_factory=set)
|
||||
|
||||
# Trusted paths for file operations
|
||||
trusted_paths: Set[str] = field(default_factory=set)
|
||||
|
||||
# Trusted commands (patterns)
|
||||
trusted_commands: Set[str] = field(default_factory=set)
|
||||
|
||||
# Maximum auto-approved actions before requiring confirmation
|
||||
max_auto_actions: int = 10
|
||||
|
||||
# Whether to show what would be done in suggest mode
|
||||
show_preview: bool = True
|
||||
|
||||
@classmethod
|
||||
def for_mode(cls, mode: AutonomyMode) -> "AutonomyPolicy":
|
||||
"""Create default policy for a given mode."""
|
||||
if mode == AutonomyMode.SUGGEST:
|
||||
return cls(
|
||||
mode=mode,
|
||||
auto_approve={ActionType.FILE_READ},
|
||||
require_approval={
|
||||
ActionType.FILE_WRITE,
|
||||
ActionType.FILE_DELETE,
|
||||
ActionType.SHELL_COMMAND,
|
||||
ActionType.CODE_EXECUTION,
|
||||
ActionType.GIT_OPERATION,
|
||||
ActionType.NETWORK_REQUEST,
|
||||
ActionType.TOOL_CALL,
|
||||
},
|
||||
blocked=set(),
|
||||
show_preview=True
|
||||
)
|
||||
elif mode == AutonomyMode.AUTO_EDIT:
|
||||
return cls(
|
||||
mode=mode,
|
||||
auto_approve={
|
||||
ActionType.FILE_READ,
|
||||
ActionType.FILE_WRITE,
|
||||
ActionType.TOOL_CALL,
|
||||
},
|
||||
require_approval={
|
||||
ActionType.FILE_DELETE,
|
||||
ActionType.SHELL_COMMAND,
|
||||
ActionType.CODE_EXECUTION,
|
||||
ActionType.GIT_OPERATION,
|
||||
ActionType.NETWORK_REQUEST,
|
||||
},
|
||||
blocked=set(),
|
||||
show_preview=True
|
||||
)
|
||||
elif mode == AutonomyMode.FULL_AUTO:
|
||||
return cls(
|
||||
mode=mode,
|
||||
auto_approve={
|
||||
ActionType.FILE_READ,
|
||||
ActionType.FILE_WRITE,
|
||||
ActionType.FILE_DELETE,
|
||||
ActionType.SHELL_COMMAND,
|
||||
ActionType.CODE_EXECUTION,
|
||||
ActionType.GIT_OPERATION,
|
||||
ActionType.NETWORK_REQUEST,
|
||||
ActionType.TOOL_CALL,
|
||||
},
|
||||
require_approval=set(),
|
||||
blocked=set(),
|
||||
show_preview=False,
|
||||
max_auto_actions=100
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Unknown mode: {mode}")
|
||||
|
||||
|
||||
class AutonomyManager:
|
||||
"""
|
||||
Manages autonomy mode and approval flow.
|
||||
|
||||
Handles:
|
||||
- Mode transitions
|
||||
- Approval requests
|
||||
- Action tracking
|
||||
- Policy enforcement
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
mode: AutonomyMode = AutonomyMode.SUGGEST,
|
||||
policy: Optional[AutonomyPolicy] = None,
|
||||
approval_callback: Optional[Callable[[ActionRequest], ApprovalResult]] = None,
|
||||
verbose: bool = False
|
||||
):
|
||||
self.mode = mode
|
||||
self.policy = policy or AutonomyPolicy.for_mode(mode)
|
||||
self.approval_callback = approval_callback or self._default_approval
|
||||
self.verbose = verbose
|
||||
|
||||
# Tracking
|
||||
self._action_count = 0
|
||||
self._auto_approved_count = 0
|
||||
self._denied_count = 0
|
||||
self._remembered_approvals: Dict[str, bool] = {}
|
||||
|
||||
def set_mode(self, mode: AutonomyMode) -> None:
|
||||
"""Change the autonomy mode."""
|
||||
old_mode = self.mode
|
||||
self.mode = mode
|
||||
self.policy = AutonomyPolicy.for_mode(mode)
|
||||
|
||||
if self.verbose:
|
||||
logger.info(f"Autonomy mode changed: {old_mode.value} -> {mode.value}")
|
||||
|
||||
def request_approval(self, action: ActionRequest) -> ApprovalResult:
|
||||
"""
|
||||
Request approval for an action.
|
||||
|
||||
Returns:
|
||||
ApprovalResult with approval decision
|
||||
"""
|
||||
self._action_count += 1
|
||||
|
||||
# Check if blocked
|
||||
if action.action_type in self.policy.blocked:
|
||||
self._denied_count += 1
|
||||
return ApprovalResult(
|
||||
approved=False,
|
||||
reason=f"Action type '{action.action_type.value}' is blocked by policy"
|
||||
)
|
||||
|
||||
# Check remembered approvals
|
||||
action_key = self._get_action_key(action)
|
||||
if action_key in self._remembered_approvals:
|
||||
approved = self._remembered_approvals[action_key]
|
||||
if approved:
|
||||
self._auto_approved_count += 1
|
||||
else:
|
||||
self._denied_count += 1
|
||||
return ApprovalResult(approved=approved, reason="Remembered choice")
|
||||
|
||||
# Check if auto-approved
|
||||
if action.action_type in self.policy.auto_approve:
|
||||
# Check max auto actions
|
||||
if self._auto_approved_count >= self.policy.max_auto_actions:
|
||||
# Force approval after max auto actions
|
||||
return self._request_user_approval(action)
|
||||
|
||||
self._auto_approved_count += 1
|
||||
return ApprovalResult(approved=True, reason="Auto-approved by policy")
|
||||
|
||||
# Check if requires approval
|
||||
if action.action_type in self.policy.require_approval:
|
||||
return self._request_user_approval(action)
|
||||
|
||||
# Default: require approval for unknown action types
|
||||
return self._request_user_approval(action)
|
||||
|
||||
def _request_user_approval(self, action: ActionRequest) -> ApprovalResult:
|
||||
"""Request approval from user via callback."""
|
||||
result = self.approval_callback(action)
|
||||
|
||||
if result.remember_choice:
|
||||
action_key = self._get_action_key(action)
|
||||
self._remembered_approvals[action_key] = result.approved
|
||||
|
||||
if result.approved:
|
||||
self._auto_approved_count += 1
|
||||
else:
|
||||
self._denied_count += 1
|
||||
|
||||
return result
|
||||
|
||||
def _get_action_key(self, action: ActionRequest) -> str:
|
||||
"""Generate a key for remembering approval decisions."""
|
||||
# Use action type and relevant details
|
||||
key_parts = [action.action_type.value]
|
||||
|
||||
if "path" in action.details:
|
||||
key_parts.append(action.details["path"])
|
||||
if "command" in action.details:
|
||||
key_parts.append(action.details["command"])
|
||||
|
||||
return ":".join(key_parts)
|
||||
|
||||
def _default_approval(self, action: ActionRequest) -> ApprovalResult:
|
||||
"""Default approval callback using console input."""
|
||||
from rich.console import Console
|
||||
from rich.panel import Panel
|
||||
from rich.prompt import Confirm
|
||||
|
||||
console = Console()
|
||||
|
||||
# Build action description
|
||||
risk_color = {
|
||||
"low": "green",
|
||||
"medium": "yellow",
|
||||
"high": "red"
|
||||
}.get(action.risk_level, "white")
|
||||
|
||||
details_str = "\n".join(
|
||||
f" {k}: {v}" for k, v in action.details.items()
|
||||
) if action.details else " (no details)"
|
||||
|
||||
panel_content = f"""
|
||||
[bold]{action.description}[/bold]
|
||||
|
||||
Type: {action.action_type.value}
|
||||
Risk: [{risk_color}]{action.risk_level}[/{risk_color}]
|
||||
Reversible: {"Yes" if action.reversible else "No"}
|
||||
|
||||
Details:
|
||||
{details_str}
|
||||
"""
|
||||
|
||||
console.print(Panel(
|
||||
panel_content,
|
||||
title="🔒 Approval Required",
|
||||
border_style="yellow"
|
||||
))
|
||||
|
||||
approved = Confirm.ask("Approve this action?", default=False)
|
||||
remember = False
|
||||
|
||||
if approved:
|
||||
remember = Confirm.ask("Remember this choice for similar actions?", default=False)
|
||||
|
||||
return ApprovalResult(
|
||||
approved=approved,
|
||||
remember_choice=remember
|
||||
)
|
||||
|
||||
def get_stats(self) -> Dict[str, int]:
|
||||
"""Get approval statistics."""
|
||||
return {
|
||||
"total_actions": self._action_count,
|
||||
"auto_approved": self._auto_approved_count,
|
||||
"denied": self._denied_count,
|
||||
"remembered": len(self._remembered_approvals)
|
||||
}
|
||||
|
||||
def reset_stats(self) -> None:
|
||||
"""Reset approval statistics."""
|
||||
self._action_count = 0
|
||||
self._auto_approved_count = 0
|
||||
self._denied_count = 0
|
||||
|
||||
def clear_remembered(self) -> None:
|
||||
"""Clear remembered approval decisions."""
|
||||
self._remembered_approvals.clear()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# CLI Integration Handler
|
||||
# ============================================================================
|
||||
|
||||
class AutonomyModeHandler:
|
||||
"""
|
||||
Handler for integrating autonomy modes with PraisonAI CLI.
|
||||
"""
|
||||
|
||||
def __init__(self, verbose: bool = False):
|
||||
self.verbose = verbose
|
||||
self._manager: Optional[AutonomyManager] = None
|
||||
|
||||
@property
|
||||
def feature_name(self) -> str:
|
||||
return "autonomy_mode"
|
||||
|
||||
def initialize(
|
||||
self,
|
||||
mode: str = "suggest",
|
||||
approval_callback: Optional[Callable[[ActionRequest], ApprovalResult]] = None
|
||||
) -> AutonomyManager:
|
||||
"""
|
||||
Initialize the autonomy manager.
|
||||
|
||||
Args:
|
||||
mode: Autonomy mode string (suggest, auto_edit, full_auto)
|
||||
approval_callback: Optional custom approval callback
|
||||
|
||||
Returns:
|
||||
Configured AutonomyManager
|
||||
"""
|
||||
try:
|
||||
autonomy_mode = AutonomyMode.from_string(mode)
|
||||
except ValueError:
|
||||
logger.warning(f"Unknown mode '{mode}', defaulting to 'suggest'")
|
||||
autonomy_mode = AutonomyMode.SUGGEST
|
||||
|
||||
self._manager = AutonomyManager(
|
||||
mode=autonomy_mode,
|
||||
approval_callback=approval_callback,
|
||||
verbose=self.verbose
|
||||
)
|
||||
|
||||
if self.verbose:
|
||||
from rich import print as rprint
|
||||
rprint(f"[cyan]Autonomy mode: {autonomy_mode.value}[/cyan]")
|
||||
|
||||
return self._manager
|
||||
|
||||
def get_manager(self) -> Optional[AutonomyManager]:
|
||||
"""Get the current autonomy manager."""
|
||||
return self._manager
|
||||
|
||||
def request_approval(self, action: ActionRequest) -> ApprovalResult:
|
||||
"""Request approval for an action."""
|
||||
if not self._manager:
|
||||
self._manager = self.initialize()
|
||||
|
||||
return self._manager.request_approval(action)
|
||||
|
||||
def set_mode(self, mode: str) -> None:
|
||||
"""Change the autonomy mode."""
|
||||
if not self._manager:
|
||||
self.initialize(mode)
|
||||
else:
|
||||
try:
|
||||
autonomy_mode = AutonomyMode.from_string(mode)
|
||||
self._manager.set_mode(autonomy_mode)
|
||||
except ValueError as e:
|
||||
logger.error(f"Failed to set mode: {e}")
|
||||
|
||||
def get_mode(self) -> str:
|
||||
"""Get the current autonomy mode."""
|
||||
if self._manager:
|
||||
return self._manager.mode.value
|
||||
return AutonomyMode.SUGGEST.value
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Convenience Functions
|
||||
# ============================================================================
|
||||
|
||||
def create_file_write_action(path: str, content_preview: str = "") -> ActionRequest:
|
||||
"""Create an action request for file write."""
|
||||
return ActionRequest(
|
||||
action_type=ActionType.FILE_WRITE,
|
||||
description=f"Write to file: {path}",
|
||||
details={
|
||||
"path": path,
|
||||
"preview": content_preview[:200] if content_preview else "(no preview)"
|
||||
},
|
||||
risk_level="medium",
|
||||
reversible=True
|
||||
)
|
||||
|
||||
|
||||
def create_shell_command_action(command: str, cwd: str = ".") -> ActionRequest:
|
||||
"""Create an action request for shell command."""
|
||||
# Assess risk based on command
|
||||
dangerous_patterns = ["rm ", "sudo ", "chmod ", "chown ", "> /", "| sh", "curl |"]
|
||||
risk = "high" if any(p in command for p in dangerous_patterns) else "medium"
|
||||
|
||||
return ActionRequest(
|
||||
action_type=ActionType.SHELL_COMMAND,
|
||||
description=f"Execute command: {command}",
|
||||
details={
|
||||
"command": command,
|
||||
"cwd": cwd
|
||||
},
|
||||
risk_level=risk,
|
||||
reversible=False
|
||||
)
|
||||
|
||||
|
||||
def create_git_action(operation: str, details: Dict[str, Any] = None) -> ActionRequest:
|
||||
"""Create an action request for git operation."""
|
||||
return ActionRequest(
|
||||
action_type=ActionType.GIT_OPERATION,
|
||||
description=f"Git {operation}",
|
||||
details=details or {},
|
||||
risk_level="low" if operation in ["status", "log", "diff"] else "medium",
|
||||
reversible=operation not in ["push", "force-push"]
|
||||
)
|
||||
|
||||
|
||||
def create_tool_call_action(tool_name: str, args: Dict[str, Any] = None) -> ActionRequest:
|
||||
"""Create an action request for tool call."""
|
||||
return ActionRequest(
|
||||
action_type=ActionType.TOOL_CALL,
|
||||
description=f"Call tool: {tool_name}",
|
||||
details={
|
||||
"tool": tool_name,
|
||||
"args": args or {}
|
||||
},
|
||||
risk_level="low",
|
||||
reversible=True
|
||||
)
|
||||
@@ -0,0 +1,514 @@
|
||||
"""
|
||||
Cost Tracking System for PraisonAI CLI.
|
||||
|
||||
Inspired by Aider's cost tracking and Gemini CLI's stats command.
|
||||
Provides real-time cost and token usage tracking.
|
||||
|
||||
Architecture:
|
||||
- CostTracker: Tracks tokens and costs per session
|
||||
- ModelPricing: Pricing data for different models
|
||||
- UsageStats: Aggregated usage statistics
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Dict, List, Optional
|
||||
from datetime import datetime
|
||||
import logging
|
||||
import json
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Model Pricing Data
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class ModelPricing:
|
||||
"""
|
||||
Pricing information for a model.
|
||||
|
||||
Prices are per 1M tokens (as commonly quoted).
|
||||
"""
|
||||
model_name: str
|
||||
input_price_per_1m: float # Price per 1M input tokens
|
||||
output_price_per_1m: float # Price per 1M output tokens
|
||||
context_window: int = 128000
|
||||
|
||||
def calculate_cost(self, input_tokens: int, output_tokens: int) -> float:
|
||||
"""Calculate cost for given token counts."""
|
||||
input_cost = (input_tokens / 1_000_000) * self.input_price_per_1m
|
||||
output_cost = (output_tokens / 1_000_000) * self.output_price_per_1m
|
||||
return input_cost + output_cost
|
||||
|
||||
|
||||
# Default pricing for common models (as of late 2024)
|
||||
DEFAULT_PRICING: Dict[str, ModelPricing] = {
|
||||
# OpenAI models
|
||||
"gpt-4o": ModelPricing("gpt-4o", 2.50, 10.00, 128000),
|
||||
"gpt-4o-mini": ModelPricing("gpt-4o-mini", 0.15, 0.60, 128000),
|
||||
"gpt-4-turbo": ModelPricing("gpt-4-turbo", 10.00, 30.00, 128000),
|
||||
"gpt-4": ModelPricing("gpt-4", 30.00, 60.00, 8192),
|
||||
"gpt-3.5-turbo": ModelPricing("gpt-3.5-turbo", 0.50, 1.50, 16385),
|
||||
"o1": ModelPricing("o1", 15.00, 60.00, 200000),
|
||||
"o1-mini": ModelPricing("o1-mini", 3.00, 12.00, 128000),
|
||||
"o1-preview": ModelPricing("o1-preview", 15.00, 60.00, 128000),
|
||||
"o3-mini": ModelPricing("o3-mini", 1.10, 4.40, 200000),
|
||||
|
||||
# Anthropic models
|
||||
"claude-3-5-sonnet-20241022": ModelPricing("claude-3-5-sonnet", 3.00, 15.00, 200000),
|
||||
"claude-3-5-sonnet": ModelPricing("claude-3-5-sonnet", 3.00, 15.00, 200000),
|
||||
"claude-3-opus": ModelPricing("claude-3-opus", 15.00, 75.00, 200000),
|
||||
"claude-3-sonnet": ModelPricing("claude-3-sonnet", 3.00, 15.00, 200000),
|
||||
"claude-3-haiku": ModelPricing("claude-3-haiku", 0.25, 1.25, 200000),
|
||||
|
||||
# Google models
|
||||
"gemini-2.0-flash": ModelPricing("gemini-2.0-flash", 0.10, 0.40, 1000000),
|
||||
"gemini-1.5-pro": ModelPricing("gemini-1.5-pro", 1.25, 5.00, 2000000),
|
||||
"gemini-1.5-flash": ModelPricing("gemini-1.5-flash", 0.075, 0.30, 1000000),
|
||||
|
||||
# Default fallback
|
||||
"default": ModelPricing("default", 1.00, 3.00, 128000),
|
||||
}
|
||||
|
||||
|
||||
def get_pricing(model_name: str) -> ModelPricing:
|
||||
"""Get pricing for a model, with fallback to default."""
|
||||
# Try exact match
|
||||
if model_name in DEFAULT_PRICING:
|
||||
return DEFAULT_PRICING[model_name]
|
||||
|
||||
# Try partial match
|
||||
model_lower = model_name.lower()
|
||||
for key, pricing in DEFAULT_PRICING.items():
|
||||
if key in model_lower or model_lower in key:
|
||||
return pricing
|
||||
|
||||
# Return default
|
||||
logger.debug(f"No pricing found for model '{model_name}', using default")
|
||||
return DEFAULT_PRICING["default"]
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Usage Statistics
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class TokenUsage:
|
||||
"""Token usage for a single request."""
|
||||
input_tokens: int = 0
|
||||
output_tokens: int = 0
|
||||
total_tokens: int = 0
|
||||
cached_tokens: int = 0
|
||||
|
||||
def __post_init__(self):
|
||||
if self.total_tokens == 0:
|
||||
self.total_tokens = self.input_tokens + self.output_tokens
|
||||
|
||||
|
||||
@dataclass
|
||||
class RequestStats:
|
||||
"""Statistics for a single request."""
|
||||
timestamp: datetime
|
||||
model: str
|
||||
usage: TokenUsage
|
||||
cost: float
|
||||
duration_ms: float = 0.0
|
||||
prompt_preview: str = ""
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary for serialization."""
|
||||
return {
|
||||
"timestamp": self.timestamp.isoformat(),
|
||||
"model": self.model,
|
||||
"input_tokens": self.usage.input_tokens,
|
||||
"output_tokens": self.usage.output_tokens,
|
||||
"total_tokens": self.usage.total_tokens,
|
||||
"cached_tokens": self.usage.cached_tokens,
|
||||
"cost": self.cost,
|
||||
"duration_ms": self.duration_ms,
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class SessionStats:
|
||||
"""Aggregated statistics for a session."""
|
||||
session_id: str
|
||||
start_time: datetime
|
||||
end_time: Optional[datetime] = None
|
||||
|
||||
total_requests: int = 0
|
||||
total_input_tokens: int = 0
|
||||
total_output_tokens: int = 0
|
||||
total_tokens: int = 0
|
||||
total_cached_tokens: int = 0
|
||||
total_cost: float = 0.0
|
||||
total_duration_ms: float = 0.0
|
||||
|
||||
models_used: Dict[str, int] = field(default_factory=dict)
|
||||
|
||||
def add_request(self, stats: RequestStats) -> None:
|
||||
"""Add request statistics to session totals."""
|
||||
self.total_requests += 1
|
||||
self.total_input_tokens += stats.usage.input_tokens
|
||||
self.total_output_tokens += stats.usage.output_tokens
|
||||
self.total_tokens += stats.usage.total_tokens
|
||||
self.total_cached_tokens += stats.usage.cached_tokens
|
||||
self.total_cost += stats.cost
|
||||
self.total_duration_ms += stats.duration_ms
|
||||
|
||||
# Track model usage
|
||||
if stats.model not in self.models_used:
|
||||
self.models_used[stats.model] = 0
|
||||
self.models_used[stats.model] += 1
|
||||
|
||||
@property
|
||||
def duration_seconds(self) -> float:
|
||||
"""Get session duration in seconds."""
|
||||
end = self.end_time or datetime.now()
|
||||
return (end - self.start_time).total_seconds()
|
||||
|
||||
@property
|
||||
def avg_tokens_per_request(self) -> float:
|
||||
"""Get average tokens per request."""
|
||||
if self.total_requests == 0:
|
||||
return 0.0
|
||||
return self.total_tokens / self.total_requests
|
||||
|
||||
@property
|
||||
def avg_cost_per_request(self) -> float:
|
||||
"""Get average cost per request."""
|
||||
if self.total_requests == 0:
|
||||
return 0.0
|
||||
return self.total_cost / self.total_requests
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary for serialization."""
|
||||
return {
|
||||
"session_id": self.session_id,
|
||||
"start_time": self.start_time.isoformat(),
|
||||
"end_time": self.end_time.isoformat() if self.end_time else None,
|
||||
"duration_seconds": self.duration_seconds,
|
||||
"total_requests": self.total_requests,
|
||||
"total_input_tokens": self.total_input_tokens,
|
||||
"total_output_tokens": self.total_output_tokens,
|
||||
"total_tokens": self.total_tokens,
|
||||
"total_cached_tokens": self.total_cached_tokens,
|
||||
"total_cost": self.total_cost,
|
||||
"avg_tokens_per_request": self.avg_tokens_per_request,
|
||||
"avg_cost_per_request": self.avg_cost_per_request,
|
||||
"models_used": self.models_used,
|
||||
}
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Cost Tracker
|
||||
# ============================================================================
|
||||
|
||||
class CostTracker:
|
||||
"""
|
||||
Tracks costs and token usage for a session.
|
||||
|
||||
Features:
|
||||
- Real-time cost tracking
|
||||
- Per-model statistics
|
||||
- Session history
|
||||
- Export to JSON
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
session_id: Optional[str] = None,
|
||||
pricing: Optional[Dict[str, ModelPricing]] = None,
|
||||
verbose: bool = False
|
||||
):
|
||||
self.session_id = session_id or self._generate_session_id()
|
||||
self.pricing = pricing or DEFAULT_PRICING
|
||||
self.verbose = verbose
|
||||
|
||||
self.session_stats = SessionStats(
|
||||
session_id=self.session_id,
|
||||
start_time=datetime.now()
|
||||
)
|
||||
self.request_history: List[RequestStats] = []
|
||||
|
||||
def _generate_session_id(self) -> str:
|
||||
"""Generate a unique session ID."""
|
||||
import uuid
|
||||
return str(uuid.uuid4())[:8]
|
||||
|
||||
def track_request(
|
||||
self,
|
||||
model: str,
|
||||
input_tokens: int,
|
||||
output_tokens: int,
|
||||
cached_tokens: int = 0,
|
||||
duration_ms: float = 0.0,
|
||||
prompt_preview: str = ""
|
||||
) -> RequestStats:
|
||||
"""
|
||||
Track a single request.
|
||||
|
||||
Returns:
|
||||
RequestStats for the tracked request
|
||||
"""
|
||||
usage = TokenUsage(
|
||||
input_tokens=input_tokens,
|
||||
output_tokens=output_tokens,
|
||||
cached_tokens=cached_tokens
|
||||
)
|
||||
|
||||
# Calculate cost
|
||||
pricing = get_pricing(model)
|
||||
cost = pricing.calculate_cost(input_tokens, output_tokens)
|
||||
|
||||
# Create request stats
|
||||
stats = RequestStats(
|
||||
timestamp=datetime.now(),
|
||||
model=model,
|
||||
usage=usage,
|
||||
cost=cost,
|
||||
duration_ms=duration_ms,
|
||||
prompt_preview=prompt_preview[:100] if prompt_preview else ""
|
||||
)
|
||||
|
||||
# Update session stats
|
||||
self.session_stats.add_request(stats)
|
||||
self.request_history.append(stats)
|
||||
|
||||
if self.verbose:
|
||||
logger.info(
|
||||
f"Request tracked: {model} - "
|
||||
f"{usage.total_tokens} tokens, ${cost:.4f}"
|
||||
)
|
||||
|
||||
return stats
|
||||
|
||||
def track_from_response(
|
||||
self,
|
||||
model: str,
|
||||
response: Any,
|
||||
duration_ms: float = 0.0
|
||||
) -> Optional[RequestStats]:
|
||||
"""
|
||||
Track request from LLM response object.
|
||||
|
||||
Handles various response formats from different providers.
|
||||
"""
|
||||
try:
|
||||
# Try to extract usage from response
|
||||
usage = None
|
||||
|
||||
# OpenAI format
|
||||
if hasattr(response, 'usage'):
|
||||
usage = response.usage
|
||||
input_tokens = getattr(usage, 'prompt_tokens', 0)
|
||||
output_tokens = getattr(usage, 'completion_tokens', 0)
|
||||
cached_tokens = getattr(usage, 'cached_tokens', 0)
|
||||
# Dict format
|
||||
elif isinstance(response, dict) and 'usage' in response:
|
||||
usage = response['usage']
|
||||
input_tokens = usage.get('prompt_tokens', 0)
|
||||
output_tokens = usage.get('completion_tokens', 0)
|
||||
cached_tokens = usage.get('cached_tokens', 0)
|
||||
else:
|
||||
logger.debug("Could not extract usage from response")
|
||||
return None
|
||||
|
||||
return self.track_request(
|
||||
model=model,
|
||||
input_tokens=input_tokens,
|
||||
output_tokens=output_tokens,
|
||||
cached_tokens=cached_tokens,
|
||||
duration_ms=duration_ms
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error tracking response: {e}")
|
||||
return None
|
||||
|
||||
def get_current_stats(self) -> SessionStats:
|
||||
"""Get current session statistics."""
|
||||
return self.session_stats
|
||||
|
||||
def get_total_cost(self) -> float:
|
||||
"""Get total cost for the session."""
|
||||
return self.session_stats.total_cost
|
||||
|
||||
def get_total_tokens(self) -> int:
|
||||
"""Get total tokens for the session."""
|
||||
return self.session_stats.total_tokens
|
||||
|
||||
def get_request_count(self) -> int:
|
||||
"""Get total request count."""
|
||||
return self.session_stats.total_requests
|
||||
|
||||
def format_summary(self) -> str:
|
||||
"""Format a summary of the session statistics."""
|
||||
stats = self.session_stats
|
||||
|
||||
lines = [
|
||||
f"Session: {stats.session_id}",
|
||||
f"Duration: {stats.duration_seconds:.1f}s",
|
||||
f"Requests: {stats.total_requests}",
|
||||
"",
|
||||
"Tokens:",
|
||||
f" Input: {stats.total_input_tokens:,}",
|
||||
f" Output: {stats.total_output_tokens:,}",
|
||||
f" Total: {stats.total_tokens:,}",
|
||||
f" Cached: {stats.total_cached_tokens:,}",
|
||||
"",
|
||||
f"Cost: ${stats.total_cost:.4f}",
|
||||
f"Avg per request: ${stats.avg_cost_per_request:.4f}",
|
||||
]
|
||||
|
||||
if stats.models_used:
|
||||
lines.append("")
|
||||
lines.append("Models used:")
|
||||
for model, count in stats.models_used.items():
|
||||
lines.append(f" {model}: {count} requests")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def print_summary(self) -> None:
|
||||
"""Print a formatted summary to console."""
|
||||
from rich.console import Console
|
||||
from rich.panel import Panel
|
||||
from rich.table import Table
|
||||
|
||||
console = Console()
|
||||
stats = self.session_stats
|
||||
|
||||
# Create summary table
|
||||
table = Table(show_header=True, header_style="bold cyan")
|
||||
table.add_column("Metric")
|
||||
table.add_column("Value", justify="right")
|
||||
|
||||
table.add_row("Session ID", stats.session_id)
|
||||
table.add_row("Duration", f"{stats.duration_seconds:.1f}s")
|
||||
table.add_row("Requests", str(stats.total_requests))
|
||||
table.add_row("", "")
|
||||
table.add_row("Input Tokens", f"{stats.total_input_tokens:,}")
|
||||
table.add_row("Output Tokens", f"{stats.total_output_tokens:,}")
|
||||
table.add_row("Total Tokens", f"{stats.total_tokens:,}")
|
||||
table.add_row("Cached Tokens", f"{stats.total_cached_tokens:,}")
|
||||
table.add_row("", "")
|
||||
table.add_row("Total Cost", f"${stats.total_cost:.4f}")
|
||||
table.add_row("Avg Cost/Request", f"${stats.avg_cost_per_request:.4f}")
|
||||
|
||||
console.print(Panel(table, title="💰 Session Statistics", border_style="green"))
|
||||
|
||||
# Print model breakdown if multiple models used
|
||||
if len(stats.models_used) > 1:
|
||||
model_table = Table(show_header=True, header_style="bold cyan")
|
||||
model_table.add_column("Model")
|
||||
model_table.add_column("Requests", justify="right")
|
||||
|
||||
for model, count in stats.models_used.items():
|
||||
model_table.add_row(model, str(count))
|
||||
|
||||
console.print(Panel(model_table, title="Models Used", border_style="blue"))
|
||||
|
||||
def export_json(self, filepath: Optional[str] = None) -> str:
|
||||
"""
|
||||
Export session data to JSON.
|
||||
|
||||
Args:
|
||||
filepath: Optional file path to write to
|
||||
|
||||
Returns:
|
||||
JSON string
|
||||
"""
|
||||
data = {
|
||||
"session": self.session_stats.to_dict(),
|
||||
"requests": [r.to_dict() for r in self.request_history]
|
||||
}
|
||||
|
||||
json_str = json.dumps(data, indent=2)
|
||||
|
||||
if filepath:
|
||||
with open(filepath, 'w') as f:
|
||||
f.write(json_str)
|
||||
logger.info(f"Exported session data to {filepath}")
|
||||
|
||||
return json_str
|
||||
|
||||
def end_session(self) -> SessionStats:
|
||||
"""Mark the session as ended."""
|
||||
self.session_stats.end_time = datetime.now()
|
||||
return self.session_stats
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# CLI Integration Handler
|
||||
# ============================================================================
|
||||
|
||||
class CostTrackerHandler:
|
||||
"""
|
||||
Handler for integrating cost tracking with PraisonAI CLI.
|
||||
"""
|
||||
|
||||
def __init__(self, verbose: bool = False):
|
||||
self.verbose = verbose
|
||||
self._tracker: Optional[CostTracker] = None
|
||||
|
||||
@property
|
||||
def feature_name(self) -> str:
|
||||
return "cost_tracker"
|
||||
|
||||
def initialize(self, session_id: Optional[str] = None) -> CostTracker:
|
||||
"""Initialize the cost tracker."""
|
||||
self._tracker = CostTracker(
|
||||
session_id=session_id,
|
||||
verbose=self.verbose
|
||||
)
|
||||
|
||||
if self.verbose:
|
||||
from rich import print as rprint
|
||||
rprint(f"[cyan]Cost tracking enabled for session: {self._tracker.session_id}[/cyan]")
|
||||
|
||||
return self._tracker
|
||||
|
||||
def get_tracker(self) -> Optional[CostTracker]:
|
||||
"""Get the current cost tracker."""
|
||||
return self._tracker
|
||||
|
||||
def track_request(
|
||||
self,
|
||||
model: str,
|
||||
input_tokens: int,
|
||||
output_tokens: int,
|
||||
**kwargs
|
||||
) -> Optional[RequestStats]:
|
||||
"""Track a request."""
|
||||
if not self._tracker:
|
||||
self._tracker = self.initialize()
|
||||
|
||||
return self._tracker.track_request(
|
||||
model=model,
|
||||
input_tokens=input_tokens,
|
||||
output_tokens=output_tokens,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
def get_summary(self) -> Dict[str, Any]:
|
||||
"""Get session summary as dict."""
|
||||
if not self._tracker:
|
||||
return {}
|
||||
return self._tracker.session_stats.to_dict()
|
||||
|
||||
def print_summary(self) -> None:
|
||||
"""Print session summary."""
|
||||
if self._tracker:
|
||||
self._tracker.print_summary()
|
||||
|
||||
def get_cost(self) -> float:
|
||||
"""Get total cost."""
|
||||
if self._tracker:
|
||||
return self._tracker.get_total_cost()
|
||||
return 0.0
|
||||
|
||||
def get_tokens(self) -> int:
|
||||
"""Get total tokens."""
|
||||
if self._tracker:
|
||||
return self._tracker.get_total_tokens()
|
||||
return 0
|
||||
@@ -0,0 +1,231 @@
|
||||
"""
|
||||
External Agents Handler for CLI.
|
||||
|
||||
Provides integration with external AI coding CLI tools:
|
||||
- Claude Code CLI
|
||||
- Gemini CLI
|
||||
- OpenAI Codex CLI
|
||||
- Cursor CLI
|
||||
|
||||
Usage:
|
||||
praisonai "Refactor the code" --external-agent claude
|
||||
praisonai "Analyze codebase" --external-agent gemini
|
||||
praisonai "Fix bugs" --external-agent codex
|
||||
praisonai "Add tests" --external-agent cursor
|
||||
"""
|
||||
|
||||
from typing import Dict, Any, List, Optional, Tuple
|
||||
|
||||
from .base import FlagHandler
|
||||
|
||||
|
||||
class ExternalAgentsHandler(FlagHandler):
|
||||
"""
|
||||
Handler for --external-agent flag.
|
||||
|
||||
Integrates external AI coding CLI tools as agent tools.
|
||||
|
||||
Example:
|
||||
praisonai "Refactor the auth module" --external-agent claude
|
||||
praisonai "Analyze this codebase" --external-agent gemini
|
||||
"""
|
||||
|
||||
# Mapping of integration names to their module paths
|
||||
INTEGRATIONS = {
|
||||
"claude": "claude_code.ClaudeCodeIntegration",
|
||||
"gemini": "gemini_cli.GeminiCLIIntegration",
|
||||
"codex": "codex_cli.CodexCLIIntegration",
|
||||
"cursor": "cursor_cli.CursorCLIIntegration",
|
||||
}
|
||||
|
||||
def __init__(self, verbose: bool = False):
|
||||
"""Initialize the handler."""
|
||||
super().__init__(verbose)
|
||||
self._integration_cache: Dict[str, Any] = {}
|
||||
|
||||
@property
|
||||
def feature_name(self) -> str:
|
||||
"""Return the feature name."""
|
||||
return "external_agents"
|
||||
|
||||
@property
|
||||
def flag_name(self) -> str:
|
||||
"""Return the flag name."""
|
||||
return "external-agent"
|
||||
|
||||
@property
|
||||
def flag_help(self) -> str:
|
||||
"""Return the flag help text."""
|
||||
return "External AI CLI tool to use (claude, gemini, codex, cursor)"
|
||||
|
||||
def check_dependencies(self) -> Tuple[bool, str]:
|
||||
"""Check if integrations module is available."""
|
||||
try:
|
||||
import importlib.util
|
||||
if importlib.util.find_spec("praisonai.integrations") is not None:
|
||||
return True, ""
|
||||
return False, "Integrations module not available"
|
||||
except ImportError:
|
||||
return False, "Integrations module not available"
|
||||
|
||||
def get_integration(self, name: str, **options):
|
||||
"""
|
||||
Get an integration instance by name.
|
||||
|
||||
Args:
|
||||
name: Integration name (claude, gemini, codex, cursor)
|
||||
**options: Options to pass to the integration
|
||||
|
||||
Returns:
|
||||
Integration instance
|
||||
|
||||
Raises:
|
||||
ValueError: If integration name is invalid
|
||||
"""
|
||||
if name not in self.INTEGRATIONS:
|
||||
raise ValueError(f"Unknown integration: {name}. Available: {list(self.INTEGRATIONS.keys())}")
|
||||
|
||||
# Check cache first
|
||||
cache_key = f"{name}_{hash(frozenset(options.items()))}"
|
||||
if cache_key in self._integration_cache:
|
||||
return self._integration_cache[cache_key]
|
||||
|
||||
# Lazy import the integration
|
||||
module_path = self.INTEGRATIONS[name]
|
||||
module_name, class_name = module_path.rsplit(".", 1)
|
||||
|
||||
import importlib
|
||||
module = importlib.import_module(f"praisonai.integrations.{module_name}")
|
||||
integration_class = getattr(module, class_name)
|
||||
|
||||
# Create instance with options
|
||||
integration = integration_class(**options)
|
||||
|
||||
# Cache it
|
||||
self._integration_cache[cache_key] = integration
|
||||
|
||||
return integration
|
||||
|
||||
def list_integrations(self) -> List[str]:
|
||||
"""
|
||||
List all available integration names.
|
||||
|
||||
Returns:
|
||||
List of integration names
|
||||
"""
|
||||
return list(self.INTEGRATIONS.keys())
|
||||
|
||||
def check_availability(self) -> Dict[str, bool]:
|
||||
"""
|
||||
Check availability of all integrations.
|
||||
|
||||
Returns:
|
||||
Dict mapping integration name to availability
|
||||
"""
|
||||
availability = {}
|
||||
for name in self.INTEGRATIONS:
|
||||
try:
|
||||
integration = self.get_integration(name)
|
||||
availability[name] = integration.is_available
|
||||
except Exception:
|
||||
availability[name] = False
|
||||
return availability
|
||||
|
||||
def apply_to_agent_config(self, config: Dict[str, Any], flag_value: Any) -> Dict[str, Any]:
|
||||
"""
|
||||
Apply external agent configuration to agent config.
|
||||
|
||||
Args:
|
||||
config: Agent configuration dictionary
|
||||
flag_value: Integration name or dict with name and options
|
||||
|
||||
Returns:
|
||||
Modified configuration with external agent tool
|
||||
"""
|
||||
if not flag_value:
|
||||
return config
|
||||
|
||||
# Handle both string and dict formats
|
||||
if isinstance(flag_value, str):
|
||||
name = flag_value
|
||||
options = {}
|
||||
elif isinstance(flag_value, dict):
|
||||
name = flag_value.get("name", "")
|
||||
options = {k: v for k, v in flag_value.items() if k != "name"}
|
||||
else:
|
||||
return config
|
||||
|
||||
try:
|
||||
integration = self.get_integration(name, **options)
|
||||
|
||||
if integration.is_available:
|
||||
# Add tool to existing tools
|
||||
existing_tools = config.get("tools", [])
|
||||
if isinstance(existing_tools, list):
|
||||
existing_tools.append(integration.as_tool())
|
||||
else:
|
||||
existing_tools = [integration.as_tool()]
|
||||
config["tools"] = existing_tools
|
||||
|
||||
self.print_status(f"🔌 External agent connected: {name}", "success")
|
||||
else:
|
||||
self.print_status(f"⚠️ External agent not available: {name}", "warning")
|
||||
|
||||
except ValueError as e:
|
||||
self.print_status(str(e), "error")
|
||||
except Exception as e:
|
||||
self.print_status(f"Failed to connect external agent: {e}", "error")
|
||||
|
||||
return config
|
||||
|
||||
def execute(
|
||||
self,
|
||||
integration_name: str = None,
|
||||
**options
|
||||
) -> Optional[Any]:
|
||||
"""
|
||||
Execute external agent setup.
|
||||
|
||||
Args:
|
||||
integration_name: Name of the integration
|
||||
**options: Options for the integration
|
||||
|
||||
Returns:
|
||||
Integration instance or None
|
||||
"""
|
||||
if not integration_name:
|
||||
# List available integrations
|
||||
self.print_status("\n🔧 Available External Agents:", "info")
|
||||
self.print_status("-" * 40, "info")
|
||||
|
||||
availability = self.check_availability()
|
||||
for name, available in availability.items():
|
||||
status = "✅ Available" if available else "❌ Not installed"
|
||||
self.print_status(f" {name}: {status}", "info")
|
||||
|
||||
return None
|
||||
|
||||
try:
|
||||
integration = self.get_integration(integration_name, **options)
|
||||
|
||||
if integration.is_available:
|
||||
self.print_status(f"🔌 External agent ready: {integration_name}", "success")
|
||||
return integration
|
||||
else:
|
||||
self.print_status(f"⚠️ External agent not installed: {integration_name}", "warning")
|
||||
self.print_status(f" Install with: {self._get_install_instructions(integration_name)}", "info")
|
||||
return None
|
||||
|
||||
except ValueError as e:
|
||||
self.print_status(str(e), "error")
|
||||
return None
|
||||
|
||||
def _get_install_instructions(self, name: str) -> str:
|
||||
"""Get installation instructions for an integration."""
|
||||
instructions = {
|
||||
"claude": "npm install -g @anthropic-ai/claude-code",
|
||||
"gemini": "npm install -g @anthropic-ai/gemini-cli",
|
||||
"codex": "npm install -g @openai/codex",
|
||||
"cursor": "Download from cursor.com",
|
||||
}
|
||||
return instructions.get(name, "See documentation")
|
||||
@@ -0,0 +1,651 @@
|
||||
"""
|
||||
Git Integration System for PraisonAI CLI.
|
||||
|
||||
Inspired by Aider's Git integration for auto-commits and change tracking.
|
||||
Provides seamless Git operations with AI-generated commit messages.
|
||||
|
||||
Architecture:
|
||||
- GitManager: Core Git operations using subprocess
|
||||
- CommitGenerator: AI-powered commit message generation
|
||||
- DiffViewer: Rich diff display
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import List, Optional
|
||||
from pathlib import Path
|
||||
import subprocess
|
||||
import logging
|
||||
import re
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Data Classes
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class GitStatus:
|
||||
"""Git repository status."""
|
||||
branch: str = ""
|
||||
is_clean: bool = True
|
||||
staged_files: List[str] = field(default_factory=list)
|
||||
modified_files: List[str] = field(default_factory=list)
|
||||
untracked_files: List[str] = field(default_factory=list)
|
||||
ahead: int = 0
|
||||
behind: int = 0
|
||||
|
||||
@property
|
||||
def has_changes(self) -> bool:
|
||||
"""Check if there are any changes."""
|
||||
return bool(self.staged_files or self.modified_files or self.untracked_files)
|
||||
|
||||
|
||||
@dataclass
|
||||
class GitCommit:
|
||||
"""Git commit information."""
|
||||
hash: str
|
||||
short_hash: str
|
||||
message: str
|
||||
author: str
|
||||
date: str
|
||||
files_changed: int = 0
|
||||
insertions: int = 0
|
||||
deletions: int = 0
|
||||
|
||||
|
||||
@dataclass
|
||||
class GitDiff:
|
||||
"""Git diff information."""
|
||||
file_path: str
|
||||
additions: int = 0
|
||||
deletions: int = 0
|
||||
content: str = ""
|
||||
is_new: bool = False
|
||||
is_deleted: bool = False
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Git Manager
|
||||
# ============================================================================
|
||||
|
||||
class GitManager:
|
||||
"""
|
||||
Manages Git operations using subprocess.
|
||||
|
||||
Uses subprocess instead of GitPython for lighter dependencies.
|
||||
"""
|
||||
|
||||
def __init__(self, repo_path: Optional[str] = None, verbose: bool = False):
|
||||
self.repo_path = Path(repo_path) if repo_path else Path.cwd()
|
||||
self.verbose = verbose
|
||||
self._git_available = self._check_git()
|
||||
|
||||
def _check_git(self) -> bool:
|
||||
"""Check if git is available."""
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["git", "--version"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
cwd=self.repo_path
|
||||
)
|
||||
return result.returncode == 0
|
||||
except FileNotFoundError:
|
||||
return False
|
||||
|
||||
def _run_git(self, *args: str, check: bool = True) -> subprocess.CompletedProcess:
|
||||
"""Run a git command."""
|
||||
cmd = ["git"] + list(args)
|
||||
if self.verbose:
|
||||
logger.debug(f"Running: {' '.join(cmd)}")
|
||||
|
||||
result = subprocess.run(
|
||||
cmd,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
cwd=self.repo_path
|
||||
)
|
||||
|
||||
if check and result.returncode != 0:
|
||||
logger.debug(f"Git error: {result.stderr}")
|
||||
|
||||
return result
|
||||
|
||||
@property
|
||||
def is_repo(self) -> bool:
|
||||
"""Check if current directory is a git repository."""
|
||||
if not self._git_available:
|
||||
return False
|
||||
result = self._run_git("rev-parse", "--git-dir", check=False)
|
||||
return result.returncode == 0
|
||||
|
||||
def get_status(self) -> GitStatus:
|
||||
"""Get repository status."""
|
||||
status = GitStatus()
|
||||
|
||||
if not self.is_repo:
|
||||
return status
|
||||
|
||||
# Get branch
|
||||
result = self._run_git("branch", "--show-current", check=False)
|
||||
if result.returncode == 0:
|
||||
status.branch = result.stdout.strip()
|
||||
|
||||
# Get status
|
||||
result = self._run_git("status", "--porcelain", check=False)
|
||||
if result.returncode == 0:
|
||||
for line in result.stdout.strip().split("\n"):
|
||||
if not line:
|
||||
continue
|
||||
|
||||
status_code = line[:2]
|
||||
file_path = line[3:]
|
||||
|
||||
if status_code[0] in "MADRCU":
|
||||
status.staged_files.append(file_path)
|
||||
if status_code[1] in "MD":
|
||||
status.modified_files.append(file_path)
|
||||
if status_code == "??":
|
||||
status.untracked_files.append(file_path)
|
||||
|
||||
status.is_clean = not status.has_changes
|
||||
|
||||
# Get ahead/behind
|
||||
result = self._run_git("rev-list", "--left-right", "--count", "HEAD...@{u}", check=False)
|
||||
if result.returncode == 0:
|
||||
parts = result.stdout.strip().split()
|
||||
if len(parts) == 2:
|
||||
status.ahead = int(parts[0])
|
||||
status.behind = int(parts[1])
|
||||
|
||||
return status
|
||||
|
||||
def get_diff(self, staged: bool = False, file_path: Optional[str] = None) -> List[GitDiff]:
|
||||
"""Get diff information."""
|
||||
diffs = []
|
||||
|
||||
if not self.is_repo:
|
||||
return diffs
|
||||
|
||||
args = ["diff"]
|
||||
if staged:
|
||||
args.append("--staged")
|
||||
args.append("--numstat")
|
||||
|
||||
if file_path:
|
||||
args.append("--")
|
||||
args.append(file_path)
|
||||
|
||||
result = self._run_git(*args, check=False)
|
||||
if result.returncode != 0:
|
||||
return diffs
|
||||
|
||||
for line in result.stdout.strip().split("\n"):
|
||||
if not line:
|
||||
continue
|
||||
|
||||
parts = line.split("\t")
|
||||
if len(parts) >= 3:
|
||||
additions = int(parts[0]) if parts[0] != "-" else 0
|
||||
deletions = int(parts[1]) if parts[1] != "-" else 0
|
||||
path = parts[2]
|
||||
|
||||
diffs.append(GitDiff(
|
||||
file_path=path,
|
||||
additions=additions,
|
||||
deletions=deletions
|
||||
))
|
||||
|
||||
return diffs
|
||||
|
||||
def get_diff_content(self, staged: bool = False, file_path: Optional[str] = None) -> str:
|
||||
"""Get full diff content."""
|
||||
if not self.is_repo:
|
||||
return ""
|
||||
|
||||
args = ["diff"]
|
||||
if staged:
|
||||
args.append("--staged")
|
||||
|
||||
if file_path:
|
||||
args.append("--")
|
||||
args.append(file_path)
|
||||
|
||||
result = self._run_git(*args, check=False)
|
||||
return result.stdout if result.returncode == 0 else ""
|
||||
|
||||
def stage_files(self, files: Optional[List[str]] = None) -> bool:
|
||||
"""Stage files for commit."""
|
||||
if not self.is_repo:
|
||||
return False
|
||||
|
||||
if files:
|
||||
result = self._run_git("add", *files, check=False)
|
||||
else:
|
||||
result = self._run_git("add", "-A", check=False)
|
||||
|
||||
return result.returncode == 0
|
||||
|
||||
def commit(self, message: str, allow_empty: bool = False) -> Optional[GitCommit]:
|
||||
"""Create a commit."""
|
||||
if not self.is_repo:
|
||||
return None
|
||||
|
||||
args = ["commit", "-m", message]
|
||||
if allow_empty:
|
||||
args.append("--allow-empty")
|
||||
|
||||
result = self._run_git(*args, check=False)
|
||||
|
||||
if result.returncode != 0:
|
||||
logger.debug(f"Commit failed: {result.stderr}")
|
||||
return None
|
||||
|
||||
# Get commit info
|
||||
return self.get_last_commit()
|
||||
|
||||
def get_last_commit(self) -> Optional[GitCommit]:
|
||||
"""Get the last commit."""
|
||||
if not self.is_repo:
|
||||
return None
|
||||
|
||||
result = self._run_git(
|
||||
"log", "-1",
|
||||
"--format=%H|%h|%s|%an|%ai",
|
||||
check=False
|
||||
)
|
||||
|
||||
if result.returncode != 0:
|
||||
return None
|
||||
|
||||
parts = result.stdout.strip().split("|")
|
||||
if len(parts) >= 5:
|
||||
return GitCommit(
|
||||
hash=parts[0],
|
||||
short_hash=parts[1],
|
||||
message=parts[2],
|
||||
author=parts[3],
|
||||
date=parts[4]
|
||||
)
|
||||
|
||||
return None
|
||||
|
||||
def get_log(self, count: int = 10) -> List[GitCommit]:
|
||||
"""Get commit log."""
|
||||
commits = []
|
||||
|
||||
if not self.is_repo:
|
||||
return commits
|
||||
|
||||
result = self._run_git(
|
||||
"log", f"-{count}",
|
||||
"--format=%H|%h|%s|%an|%ai",
|
||||
check=False
|
||||
)
|
||||
|
||||
if result.returncode != 0:
|
||||
return commits
|
||||
|
||||
for line in result.stdout.strip().split("\n"):
|
||||
if not line:
|
||||
continue
|
||||
|
||||
parts = line.split("|")
|
||||
if len(parts) >= 5:
|
||||
commits.append(GitCommit(
|
||||
hash=parts[0],
|
||||
short_hash=parts[1],
|
||||
message=parts[2],
|
||||
author=parts[3],
|
||||
date=parts[4]
|
||||
))
|
||||
|
||||
return commits
|
||||
|
||||
def undo_last_commit(self, soft: bool = True) -> bool:
|
||||
"""Undo the last commit."""
|
||||
if not self.is_repo:
|
||||
return False
|
||||
|
||||
reset_type = "--soft" if soft else "--hard"
|
||||
result = self._run_git("reset", reset_type, "HEAD~1", check=False)
|
||||
|
||||
return result.returncode == 0
|
||||
|
||||
def create_branch(self, name: str, checkout: bool = True) -> bool:
|
||||
"""Create a new branch."""
|
||||
if not self.is_repo:
|
||||
return False
|
||||
|
||||
if checkout:
|
||||
result = self._run_git("checkout", "-b", name, check=False)
|
||||
else:
|
||||
result = self._run_git("branch", name, check=False)
|
||||
|
||||
return result.returncode == 0
|
||||
|
||||
def checkout_branch(self, name: str) -> bool:
|
||||
"""Checkout a branch."""
|
||||
if not self.is_repo:
|
||||
return False
|
||||
|
||||
result = self._run_git("checkout", name, check=False)
|
||||
return result.returncode == 0
|
||||
|
||||
def get_branches(self) -> List[str]:
|
||||
"""Get list of branches."""
|
||||
if not self.is_repo:
|
||||
return []
|
||||
|
||||
result = self._run_git("branch", "--list", check=False)
|
||||
if result.returncode != 0:
|
||||
return []
|
||||
|
||||
branches = []
|
||||
for line in result.stdout.strip().split("\n"):
|
||||
if line:
|
||||
# Remove * and whitespace
|
||||
branch = line.strip().lstrip("* ")
|
||||
branches.append(branch)
|
||||
|
||||
return branches
|
||||
|
||||
def stash(self, message: Optional[str] = None) -> bool:
|
||||
"""Stash changes."""
|
||||
if not self.is_repo:
|
||||
return False
|
||||
|
||||
args = ["stash", "push"]
|
||||
if message:
|
||||
args.extend(["-m", message])
|
||||
|
||||
result = self._run_git(*args, check=False)
|
||||
return result.returncode == 0
|
||||
|
||||
def stash_pop(self) -> bool:
|
||||
"""Pop stashed changes."""
|
||||
if not self.is_repo:
|
||||
return False
|
||||
|
||||
result = self._run_git("stash", "pop", check=False)
|
||||
return result.returncode == 0
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Commit Message Generator
|
||||
# ============================================================================
|
||||
|
||||
class CommitMessageGenerator:
|
||||
"""
|
||||
Generates commit messages using AI or templates.
|
||||
"""
|
||||
|
||||
def __init__(self, use_ai: bool = True):
|
||||
self.use_ai = use_ai
|
||||
|
||||
def generate(
|
||||
self,
|
||||
diff_content: str,
|
||||
context: Optional[str] = None,
|
||||
style: str = "conventional"
|
||||
) -> str:
|
||||
"""
|
||||
Generate a commit message.
|
||||
|
||||
Args:
|
||||
diff_content: The diff to describe
|
||||
context: Optional context about the changes
|
||||
style: Message style (conventional, simple, detailed)
|
||||
|
||||
Returns:
|
||||
Generated commit message
|
||||
"""
|
||||
if not diff_content:
|
||||
return "Empty commit"
|
||||
|
||||
if self.use_ai:
|
||||
return self._generate_with_ai(diff_content, context, style)
|
||||
else:
|
||||
return self._generate_from_diff(diff_content, style)
|
||||
|
||||
def _generate_with_ai(
|
||||
self,
|
||||
diff_content: str,
|
||||
context: Optional[str],
|
||||
style: str
|
||||
) -> str:
|
||||
"""Generate commit message using AI."""
|
||||
# This would integrate with the agent system
|
||||
# For now, return a template-based message
|
||||
return self._generate_from_diff(diff_content, style)
|
||||
|
||||
def _generate_from_diff(self, diff_content: str, style: str) -> str:
|
||||
"""Generate commit message from diff analysis."""
|
||||
# Analyze diff
|
||||
files_changed = set()
|
||||
additions = 0
|
||||
deletions = 0
|
||||
|
||||
for line in diff_content.split("\n"):
|
||||
if line.startswith("diff --git"):
|
||||
match = re.search(r"b/(.+)$", line)
|
||||
if match:
|
||||
files_changed.add(match.group(1))
|
||||
elif line.startswith("+") and not line.startswith("+++"):
|
||||
additions += 1
|
||||
elif line.startswith("-") and not line.startswith("---"):
|
||||
deletions += 1
|
||||
|
||||
# Determine change type
|
||||
if additions > deletions * 2:
|
||||
change_type = "feat"
|
||||
action = "Add"
|
||||
elif deletions > additions * 2:
|
||||
change_type = "refactor"
|
||||
action = "Remove"
|
||||
else:
|
||||
change_type = "fix"
|
||||
action = "Update"
|
||||
|
||||
# Build message
|
||||
if len(files_changed) == 1:
|
||||
file_name = list(files_changed)[0]
|
||||
scope = Path(file_name).stem
|
||||
message = f"{change_type}({scope}): {action} {file_name}"
|
||||
elif len(files_changed) <= 3:
|
||||
files_str = ", ".join(sorted(files_changed))
|
||||
message = f"{change_type}: {action} {files_str}"
|
||||
else:
|
||||
message = f"{change_type}: {action} {len(files_changed)} files"
|
||||
|
||||
if style == "detailed":
|
||||
message += f"\n\n+{additions} -{deletions} lines"
|
||||
|
||||
return message
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Diff Viewer
|
||||
# ============================================================================
|
||||
|
||||
class DiffViewer:
|
||||
"""
|
||||
Rich-based diff viewer.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self._console = None
|
||||
|
||||
@property
|
||||
def console(self):
|
||||
"""Lazy load Rich console."""
|
||||
if self._console is None:
|
||||
try:
|
||||
from rich.console import Console
|
||||
self._console = Console()
|
||||
except ImportError:
|
||||
self._console = None
|
||||
return self._console
|
||||
|
||||
def display_diff(self, diff_content: str, title: str = "Changes") -> None:
|
||||
"""Display diff with syntax highlighting."""
|
||||
if not self.console:
|
||||
print(diff_content)
|
||||
return
|
||||
|
||||
from rich.panel import Panel
|
||||
from rich.syntax import Syntax
|
||||
|
||||
syntax = Syntax(diff_content, "diff", theme="monokai", line_numbers=True)
|
||||
self.console.print(Panel(syntax, title=title, border_style="blue"))
|
||||
|
||||
def display_status(self, status: GitStatus) -> None:
|
||||
"""Display git status."""
|
||||
if not self.console:
|
||||
print(f"Branch: {status.branch}")
|
||||
print(f"Staged: {len(status.staged_files)}")
|
||||
print(f"Modified: {len(status.modified_files)}")
|
||||
print(f"Untracked: {len(status.untracked_files)}")
|
||||
return
|
||||
|
||||
from rich.panel import Panel
|
||||
from rich.table import Table
|
||||
|
||||
table = Table(show_header=True, header_style="bold cyan")
|
||||
table.add_column("Category")
|
||||
table.add_column("Files", justify="right")
|
||||
|
||||
table.add_row("Branch", status.branch or "detached")
|
||||
table.add_row("Staged", str(len(status.staged_files)))
|
||||
table.add_row("Modified", str(len(status.modified_files)))
|
||||
table.add_row("Untracked", str(len(status.untracked_files)))
|
||||
|
||||
if status.ahead or status.behind:
|
||||
table.add_row("Ahead/Behind", f"+{status.ahead} / -{status.behind}")
|
||||
|
||||
self.console.print(Panel(table, title="📊 Git Status", border_style="green"))
|
||||
|
||||
def display_log(self, commits: List[GitCommit]) -> None:
|
||||
"""Display commit log."""
|
||||
if not self.console:
|
||||
for commit in commits:
|
||||
print(f"{commit.short_hash} {commit.message}")
|
||||
return
|
||||
|
||||
from rich.table import Table
|
||||
|
||||
table = Table(show_header=True, header_style="bold cyan")
|
||||
table.add_column("Hash")
|
||||
table.add_column("Message")
|
||||
table.add_column("Author")
|
||||
table.add_column("Date")
|
||||
|
||||
for commit in commits:
|
||||
table.add_row(
|
||||
commit.short_hash,
|
||||
commit.message[:50] + "..." if len(commit.message) > 50 else commit.message,
|
||||
commit.author,
|
||||
commit.date[:10]
|
||||
)
|
||||
|
||||
self.console.print(table)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# CLI Integration Handler
|
||||
# ============================================================================
|
||||
|
||||
class GitIntegrationHandler:
|
||||
"""
|
||||
Handler for integrating Git with PraisonAI CLI.
|
||||
"""
|
||||
|
||||
def __init__(self, verbose: bool = False):
|
||||
self.verbose = verbose
|
||||
self._git: Optional[GitManager] = None
|
||||
self._viewer: Optional[DiffViewer] = None
|
||||
self._generator: Optional[CommitMessageGenerator] = None
|
||||
|
||||
@property
|
||||
def feature_name(self) -> str:
|
||||
return "git_integration"
|
||||
|
||||
def initialize(self, repo_path: Optional[str] = None) -> GitManager:
|
||||
"""Initialize Git manager."""
|
||||
self._git = GitManager(repo_path=repo_path, verbose=self.verbose)
|
||||
self._viewer = DiffViewer()
|
||||
self._generator = CommitMessageGenerator()
|
||||
|
||||
if self.verbose and self._git.is_repo:
|
||||
from rich import print as rprint
|
||||
status = self._git.get_status()
|
||||
rprint(f"[cyan]Git initialized on branch: {status.branch}[/cyan]")
|
||||
|
||||
return self._git
|
||||
|
||||
def get_git(self) -> Optional[GitManager]:
|
||||
"""Get the Git manager."""
|
||||
return self._git
|
||||
|
||||
def show_status(self) -> GitStatus:
|
||||
"""Show git status."""
|
||||
if not self._git:
|
||||
self._git = self.initialize()
|
||||
|
||||
status = self._git.get_status()
|
||||
if self._viewer:
|
||||
self._viewer.display_status(status)
|
||||
|
||||
return status
|
||||
|
||||
def show_diff(self, staged: bool = False) -> str:
|
||||
"""Show diff."""
|
||||
if not self._git:
|
||||
self._git = self.initialize()
|
||||
|
||||
diff_content = self._git.get_diff_content(staged=staged)
|
||||
if self._viewer and diff_content:
|
||||
self._viewer.display_diff(diff_content)
|
||||
|
||||
return diff_content
|
||||
|
||||
def commit(
|
||||
self,
|
||||
message: Optional[str] = None,
|
||||
auto_stage: bool = True
|
||||
) -> Optional[GitCommit]:
|
||||
"""Create a commit."""
|
||||
if not self._git:
|
||||
self._git = self.initialize()
|
||||
|
||||
if auto_stage:
|
||||
self._git.stage_files()
|
||||
|
||||
if not message:
|
||||
# Generate message from diff
|
||||
diff_content = self._git.get_diff_content(staged=True)
|
||||
if self._generator:
|
||||
message = self._generator.generate(diff_content)
|
||||
else:
|
||||
message = "Update files"
|
||||
|
||||
return self._git.commit(message)
|
||||
|
||||
def undo(self, soft: bool = True) -> bool:
|
||||
"""Undo last commit."""
|
||||
if not self._git:
|
||||
self._git = self.initialize()
|
||||
|
||||
return self._git.undo_last_commit(soft=soft)
|
||||
|
||||
def show_log(self, count: int = 10) -> List[GitCommit]:
|
||||
"""Show commit log."""
|
||||
if not self._git:
|
||||
self._git = self.initialize()
|
||||
|
||||
commits = self._git.get_log(count=count)
|
||||
if self._viewer:
|
||||
self._viewer.display_log(commits)
|
||||
|
||||
return commits
|
||||
@@ -0,0 +1,603 @@
|
||||
"""
|
||||
Interactive TUI System for PraisonAI CLI.
|
||||
|
||||
Inspired by Aider's interactive mode and prompt_toolkit usage.
|
||||
Provides rich interactive terminal experience with completions and history.
|
||||
|
||||
Architecture:
|
||||
- InteractiveSession: Main interactive session manager
|
||||
- CommandCompleter: Auto-completion for commands and files
|
||||
- HistoryManager: Persistent command history
|
||||
- StatusDisplay: Rich-based status bar and output
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Callable, Dict, List, Optional
|
||||
from pathlib import Path
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Configuration
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class InteractiveConfig:
|
||||
"""Configuration for interactive session."""
|
||||
prompt: str = ">>> "
|
||||
multiline: bool = True
|
||||
history_file: Optional[str] = None
|
||||
max_history: int = 1000
|
||||
enable_completions: bool = True
|
||||
enable_syntax_highlighting: bool = True
|
||||
vi_mode: bool = False
|
||||
auto_suggest: bool = True
|
||||
show_status_bar: bool = True
|
||||
color_scheme: str = "monokai"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Command Completer
|
||||
# ============================================================================
|
||||
|
||||
class CommandCompleter:
|
||||
"""
|
||||
Provides auto-completion for commands, files, and symbols.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
commands: Optional[List[str]] = None,
|
||||
file_patterns: Optional[List[str]] = None
|
||||
):
|
||||
self.commands = commands or []
|
||||
self.file_patterns = file_patterns or ["*.py", "*.js", "*.ts"]
|
||||
self._file_cache: List[str] = []
|
||||
self._symbol_cache: List[str] = []
|
||||
|
||||
def add_commands(self, commands: List[str]) -> None:
|
||||
"""Add commands to completion list."""
|
||||
self.commands.extend(commands)
|
||||
|
||||
def add_symbols(self, symbols: List[str]) -> None:
|
||||
"""Add symbols to completion list."""
|
||||
self._symbol_cache.extend(symbols)
|
||||
|
||||
def refresh_files(self, root: Optional[Path] = None) -> None:
|
||||
"""Refresh file cache."""
|
||||
root = root or Path.cwd()
|
||||
self._file_cache = []
|
||||
|
||||
for pattern in self.file_patterns:
|
||||
for file_path in root.rglob(pattern):
|
||||
try:
|
||||
rel_path = str(file_path.relative_to(root))
|
||||
if not any(excl in rel_path for excl in ["__pycache__", "node_modules", ".git"]):
|
||||
self._file_cache.append(rel_path)
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
def get_completions(self, text: str, cursor_pos: int) -> List[str]:
|
||||
"""
|
||||
Get completions for the current input.
|
||||
|
||||
Args:
|
||||
text: Current input text
|
||||
cursor_pos: Cursor position
|
||||
|
||||
Returns:
|
||||
List of completion suggestions
|
||||
"""
|
||||
# Get word before cursor
|
||||
before_cursor = text[:cursor_pos]
|
||||
words = before_cursor.split()
|
||||
current_word = words[-1] if words else ""
|
||||
|
||||
completions = []
|
||||
|
||||
# Slash commands
|
||||
if current_word.startswith("/"):
|
||||
cmd_part = current_word[1:].lower()
|
||||
for cmd in self.commands:
|
||||
if cmd.lower().startswith(cmd_part):
|
||||
completions.append(f"/{cmd}")
|
||||
|
||||
# @ mentions for files
|
||||
elif current_word.startswith("@"):
|
||||
file_part = current_word[1:].lower()
|
||||
for file_path in self._file_cache:
|
||||
if file_part in file_path.lower():
|
||||
completions.append(f"@{file_path}")
|
||||
|
||||
# General completions
|
||||
else:
|
||||
word_lower = current_word.lower()
|
||||
|
||||
# Check symbols
|
||||
for symbol in self._symbol_cache:
|
||||
if symbol.lower().startswith(word_lower):
|
||||
completions.append(symbol)
|
||||
|
||||
# Check files
|
||||
for file_path in self._file_cache:
|
||||
if word_lower in file_path.lower():
|
||||
completions.append(file_path)
|
||||
|
||||
return completions[:20] # Limit results
|
||||
|
||||
def create_prompt_toolkit_completer(self) -> Any:
|
||||
"""Create a prompt_toolkit completer."""
|
||||
try:
|
||||
from prompt_toolkit.completion import Completer, Completion
|
||||
|
||||
outer_self = self
|
||||
|
||||
class PTCompleter(Completer):
|
||||
def get_completions(self, document, complete_event):
|
||||
text = document.text
|
||||
cursor_pos = document.cursor_position
|
||||
|
||||
for completion in outer_self.get_completions(text, cursor_pos):
|
||||
# Calculate start position
|
||||
words = text[:cursor_pos].split()
|
||||
current_word = words[-1] if words else ""
|
||||
start_pos = -len(current_word)
|
||||
|
||||
yield Completion(completion, start_position=start_pos)
|
||||
|
||||
return PTCompleter()
|
||||
except ImportError:
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# History Manager
|
||||
# ============================================================================
|
||||
|
||||
class HistoryManager:
|
||||
"""
|
||||
Manages command history with persistence.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
history_file: Optional[str] = None,
|
||||
max_entries: int = 1000
|
||||
):
|
||||
self.history_file = Path(history_file) if history_file else None
|
||||
self.max_entries = max_entries
|
||||
self._history: List[str] = []
|
||||
self._position: int = 0
|
||||
|
||||
if self.history_file:
|
||||
self._load_history()
|
||||
|
||||
def _load_history(self) -> None:
|
||||
"""Load history from file."""
|
||||
if self.history_file and self.history_file.exists():
|
||||
try:
|
||||
with open(self.history_file, 'r', encoding='utf-8') as f:
|
||||
self._history = [
|
||||
line.strip() for line in f.readlines()
|
||||
if line.strip()
|
||||
][-self.max_entries:]
|
||||
except Exception as e:
|
||||
logger.debug(f"Could not load history: {e}")
|
||||
|
||||
def _save_history(self) -> None:
|
||||
"""Save history to file."""
|
||||
if self.history_file:
|
||||
try:
|
||||
self.history_file.parent.mkdir(parents=True, exist_ok=True)
|
||||
with open(self.history_file, 'w', encoding='utf-8') as f:
|
||||
for entry in self._history[-self.max_entries:]:
|
||||
f.write(entry + "\n")
|
||||
except Exception as e:
|
||||
logger.debug(f"Could not save history: {e}")
|
||||
|
||||
def add(self, entry: str) -> None:
|
||||
"""Add an entry to history."""
|
||||
entry = entry.strip()
|
||||
if entry and (not self._history or self._history[-1] != entry):
|
||||
self._history.append(entry)
|
||||
self._position = len(self._history)
|
||||
self._save_history()
|
||||
|
||||
def get_previous(self) -> Optional[str]:
|
||||
"""Get previous history entry."""
|
||||
if self._position > 0:
|
||||
self._position -= 1
|
||||
return self._history[self._position]
|
||||
return None
|
||||
|
||||
def get_next(self) -> Optional[str]:
|
||||
"""Get next history entry."""
|
||||
if self._position < len(self._history) - 1:
|
||||
self._position += 1
|
||||
return self._history[self._position]
|
||||
elif self._position == len(self._history) - 1:
|
||||
self._position = len(self._history)
|
||||
return ""
|
||||
return None
|
||||
|
||||
def search(self, prefix: str) -> List[str]:
|
||||
"""Search history for entries starting with prefix."""
|
||||
return [
|
||||
entry for entry in self._history
|
||||
if entry.lower().startswith(prefix.lower())
|
||||
]
|
||||
|
||||
def get_all(self) -> List[str]:
|
||||
"""Get all history entries."""
|
||||
return self._history.copy()
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Clear history."""
|
||||
self._history.clear()
|
||||
self._position = 0
|
||||
if self.history_file and self.history_file.exists():
|
||||
self.history_file.unlink()
|
||||
|
||||
def create_prompt_toolkit_history(self) -> Any:
|
||||
"""Create a prompt_toolkit history object."""
|
||||
try:
|
||||
from prompt_toolkit.history import FileHistory, InMemoryHistory
|
||||
|
||||
if self.history_file:
|
||||
return FileHistory(str(self.history_file))
|
||||
return InMemoryHistory()
|
||||
except ImportError:
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Status Display
|
||||
# ============================================================================
|
||||
|
||||
class StatusDisplay:
|
||||
"""
|
||||
Rich-based status display for interactive session.
|
||||
"""
|
||||
|
||||
def __init__(self, show_status_bar: bool = True):
|
||||
self.show_status_bar = show_status_bar
|
||||
self._console = None
|
||||
self._status_items: Dict[str, str] = {}
|
||||
|
||||
@property
|
||||
def console(self):
|
||||
"""Lazy load Rich console."""
|
||||
if self._console is None:
|
||||
try:
|
||||
from rich.console import Console
|
||||
self._console = Console()
|
||||
except ImportError:
|
||||
self._console = None
|
||||
return self._console
|
||||
|
||||
def set_status(self, key: str, value: str) -> None:
|
||||
"""Set a status item."""
|
||||
self._status_items[key] = value
|
||||
|
||||
def clear_status(self, key: str) -> None:
|
||||
"""Clear a status item."""
|
||||
self._status_items.pop(key, None)
|
||||
|
||||
def print_status_bar(self) -> None:
|
||||
"""Print the status bar."""
|
||||
if not self.show_status_bar or not self.console:
|
||||
return
|
||||
|
||||
from rich.columns import Columns
|
||||
from rich.text import Text
|
||||
|
||||
items = []
|
||||
for key, value in self._status_items.items():
|
||||
items.append(Text(f"{key}: {value}", style="dim"))
|
||||
|
||||
if items:
|
||||
self.console.print(Columns(items, equal=True, expand=True))
|
||||
|
||||
def print_welcome(self, version: str = "1.0.0") -> None:
|
||||
"""Print welcome message."""
|
||||
if not self.console:
|
||||
print(f"PraisonAI CLI v{version}")
|
||||
return
|
||||
|
||||
from rich.panel import Panel
|
||||
from rich.text import Text
|
||||
|
||||
welcome = Text()
|
||||
welcome.append("PraisonAI CLI", style="bold cyan")
|
||||
welcome.append(f" v{version}\n", style="dim")
|
||||
welcome.append("Type ", style="dim")
|
||||
welcome.append("/help", style="bold green")
|
||||
welcome.append(" for commands, ", style="dim")
|
||||
welcome.append("/exit", style="bold yellow")
|
||||
welcome.append(" to quit", style="dim")
|
||||
|
||||
self.console.print(Panel(welcome, border_style="blue"))
|
||||
|
||||
def print_response(self, response: str, title: str = "Response") -> None:
|
||||
"""Print a response with formatting."""
|
||||
if not self.console:
|
||||
print(response)
|
||||
return
|
||||
|
||||
from rich.panel import Panel
|
||||
from rich.markdown import Markdown
|
||||
|
||||
try:
|
||||
md = Markdown(response)
|
||||
self.console.print(Panel(md, title=title, border_style="green"))
|
||||
except Exception:
|
||||
self.console.print(Panel(response, title=title, border_style="green"))
|
||||
|
||||
def print_error(self, error: str) -> None:
|
||||
"""Print an error message."""
|
||||
if not self.console:
|
||||
print(f"Error: {error}")
|
||||
return
|
||||
|
||||
from rich.panel import Panel
|
||||
self.console.print(Panel(error, title="Error", border_style="red"))
|
||||
|
||||
def print_info(self, message: str) -> None:
|
||||
"""Print an info message."""
|
||||
if not self.console:
|
||||
print(message)
|
||||
return
|
||||
|
||||
self.console.print(f"[cyan]ℹ[/cyan] {message}")
|
||||
|
||||
def print_success(self, message: str) -> None:
|
||||
"""Print a success message."""
|
||||
if not self.console:
|
||||
print(message)
|
||||
return
|
||||
|
||||
self.console.print(f"[green]✓[/green] {message}")
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Interactive Session
|
||||
# ============================================================================
|
||||
|
||||
class InteractiveSession:
|
||||
"""
|
||||
Main interactive session manager.
|
||||
|
||||
Provides a rich interactive terminal experience with:
|
||||
- Command completion
|
||||
- History
|
||||
- Syntax highlighting
|
||||
- Status bar
|
||||
- Keyboard shortcuts
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
config: Optional[InteractiveConfig] = None,
|
||||
on_input: Optional[Callable[[str], Optional[str]]] = None,
|
||||
on_command: Optional[Callable[[str], Optional[Dict[str, Any]]]] = None
|
||||
):
|
||||
self.config = config or InteractiveConfig()
|
||||
self.on_input = on_input
|
||||
self.on_command = on_command
|
||||
|
||||
self.completer = CommandCompleter()
|
||||
self.history = HistoryManager(
|
||||
history_file=self.config.history_file,
|
||||
max_entries=self.config.max_history
|
||||
)
|
||||
self.display = StatusDisplay(show_status_bar=self.config.show_status_bar)
|
||||
|
||||
self._running = False
|
||||
self._prompt_session = None
|
||||
|
||||
def _create_prompt_session(self) -> Any:
|
||||
"""Create a prompt_toolkit session."""
|
||||
try:
|
||||
from prompt_toolkit import PromptSession
|
||||
from prompt_toolkit.lexers import PygmentsLexer
|
||||
from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
|
||||
from pygments.lexers import MarkdownLexer
|
||||
|
||||
session_kwargs = {
|
||||
"message": self.config.prompt,
|
||||
"multiline": self.config.multiline,
|
||||
}
|
||||
|
||||
# Add completer
|
||||
if self.config.enable_completions:
|
||||
completer = self.completer.create_prompt_toolkit_completer()
|
||||
if completer:
|
||||
session_kwargs["completer"] = completer
|
||||
|
||||
# Add history
|
||||
history = self.history.create_prompt_toolkit_history()
|
||||
if history:
|
||||
session_kwargs["history"] = history
|
||||
|
||||
# Add syntax highlighting
|
||||
if self.config.enable_syntax_highlighting:
|
||||
session_kwargs["lexer"] = PygmentsLexer(MarkdownLexer)
|
||||
|
||||
# Add auto-suggest
|
||||
if self.config.auto_suggest:
|
||||
session_kwargs["auto_suggest"] = AutoSuggestFromHistory()
|
||||
|
||||
# VI mode
|
||||
if self.config.vi_mode:
|
||||
from prompt_toolkit.enums import EditingMode
|
||||
session_kwargs["editing_mode"] = EditingMode.VI
|
||||
|
||||
return PromptSession(**session_kwargs)
|
||||
|
||||
except ImportError as e:
|
||||
logger.debug(f"prompt_toolkit not available: {e}")
|
||||
return None
|
||||
|
||||
def _get_input_fallback(self) -> str:
|
||||
"""Fallback input method without prompt_toolkit."""
|
||||
try:
|
||||
if self.config.multiline:
|
||||
print(f"{self.config.prompt}(Enter empty line to submit)")
|
||||
lines = []
|
||||
while True:
|
||||
line = input()
|
||||
if not line:
|
||||
break
|
||||
lines.append(line)
|
||||
return "\n".join(lines)
|
||||
else:
|
||||
return input(self.config.prompt)
|
||||
except EOFError:
|
||||
return "/exit"
|
||||
except KeyboardInterrupt:
|
||||
print()
|
||||
return ""
|
||||
|
||||
def get_input(self) -> str:
|
||||
"""Get input from user."""
|
||||
if self._prompt_session:
|
||||
try:
|
||||
return self._prompt_session.prompt()
|
||||
except KeyboardInterrupt:
|
||||
return ""
|
||||
except EOFError:
|
||||
return "/exit"
|
||||
else:
|
||||
return self._get_input_fallback()
|
||||
|
||||
def process_input(self, user_input: str) -> Optional[str]:
|
||||
"""
|
||||
Process user input.
|
||||
|
||||
Args:
|
||||
user_input: Raw user input
|
||||
|
||||
Returns:
|
||||
Response string or None
|
||||
"""
|
||||
user_input = user_input.strip()
|
||||
|
||||
if not user_input:
|
||||
return None
|
||||
|
||||
# Add to history
|
||||
self.history.add(user_input)
|
||||
|
||||
# Check for slash commands
|
||||
if user_input.startswith("/"):
|
||||
if self.on_command:
|
||||
result = self.on_command(user_input)
|
||||
if result:
|
||||
if result.get("type") == "exit":
|
||||
self._running = False
|
||||
return None
|
||||
return result.get("message")
|
||||
return None
|
||||
|
||||
# Regular input
|
||||
if self.on_input:
|
||||
return self.on_input(user_input)
|
||||
|
||||
return None
|
||||
|
||||
def run(self) -> None:
|
||||
"""Run the interactive session."""
|
||||
self._running = True
|
||||
self._prompt_session = self._create_prompt_session()
|
||||
|
||||
# Print welcome
|
||||
self.display.print_welcome()
|
||||
|
||||
while self._running:
|
||||
try:
|
||||
# Get input
|
||||
user_input = self.get_input()
|
||||
|
||||
# Process
|
||||
response = self.process_input(user_input)
|
||||
|
||||
# Display response
|
||||
if response:
|
||||
self.display.print_response(response)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
self.display.print_info("Use /exit to quit")
|
||||
except Exception as e:
|
||||
self.display.print_error(str(e))
|
||||
logger.exception("Error in interactive session")
|
||||
|
||||
def stop(self) -> None:
|
||||
"""Stop the interactive session."""
|
||||
self._running = False
|
||||
|
||||
def add_commands(self, commands: List[str]) -> None:
|
||||
"""Add commands for completion."""
|
||||
self.completer.add_commands(commands)
|
||||
|
||||
def add_symbols(self, symbols: List[str]) -> None:
|
||||
"""Add symbols for completion."""
|
||||
self.completer.add_symbols(symbols)
|
||||
|
||||
def refresh_files(self, root: Optional[Path] = None) -> None:
|
||||
"""Refresh file completions."""
|
||||
self.completer.refresh_files(root)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# CLI Integration Handler
|
||||
# ============================================================================
|
||||
|
||||
class InteractiveTUIHandler:
|
||||
"""
|
||||
Handler for integrating Interactive TUI with PraisonAI CLI.
|
||||
"""
|
||||
|
||||
def __init__(self, verbose: bool = False):
|
||||
self.verbose = verbose
|
||||
self._session: Optional[InteractiveSession] = None
|
||||
|
||||
@property
|
||||
def feature_name(self) -> str:
|
||||
return "interactive_tui"
|
||||
|
||||
def initialize(
|
||||
self,
|
||||
config: Optional[InteractiveConfig] = None,
|
||||
on_input: Optional[Callable[[str], Optional[str]]] = None,
|
||||
on_command: Optional[Callable[[str], Optional[Dict[str, Any]]]] = None
|
||||
) -> InteractiveSession:
|
||||
"""Initialize the interactive session."""
|
||||
self._session = InteractiveSession(
|
||||
config=config,
|
||||
on_input=on_input,
|
||||
on_command=on_command
|
||||
)
|
||||
|
||||
if self.verbose:
|
||||
from rich import print as rprint
|
||||
rprint("[cyan]Interactive TUI initialized[/cyan]")
|
||||
|
||||
return self._session
|
||||
|
||||
def get_session(self) -> Optional[InteractiveSession]:
|
||||
"""Get the current session."""
|
||||
return self._session
|
||||
|
||||
def run(self) -> None:
|
||||
"""Run the interactive session."""
|
||||
if not self._session:
|
||||
self._session = self.initialize()
|
||||
|
||||
self._session.run()
|
||||
|
||||
def stop(self) -> None:
|
||||
"""Stop the interactive session."""
|
||||
if self._session:
|
||||
self._session.stop()
|
||||
@@ -0,0 +1,587 @@
|
||||
"""
|
||||
Message Queue for Interactive Mode.
|
||||
|
||||
Provides FIFO message queuing while the AI agent is processing,
|
||||
inspired by Claude Code, Windsurf Cascade, Cursor, and Gemini CLI.
|
||||
|
||||
Features:
|
||||
- Queue messages while agent is processing
|
||||
- Auto-process queue when agent becomes idle
|
||||
- Visual indicators for queue status
|
||||
- Thread-safe operations
|
||||
"""
|
||||
|
||||
import threading
|
||||
import time
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
from typing import Callable, List, Optional
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Enums
|
||||
# ============================================================================
|
||||
|
||||
class ProcessingState(Enum):
|
||||
"""State of the agent processing."""
|
||||
IDLE = "idle"
|
||||
PROCESSING = "processing"
|
||||
WAITING_APPROVAL = "waiting_approval"
|
||||
|
||||
|
||||
class MessagePriority(Enum):
|
||||
"""Priority levels for queued messages."""
|
||||
LOW = "low"
|
||||
NORMAL = "normal"
|
||||
HIGH = "high"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Data Classes
|
||||
# ============================================================================
|
||||
|
||||
@dataclass
|
||||
class QueuedMessage:
|
||||
"""A message in the queue with metadata."""
|
||||
content: str
|
||||
timestamp: float = field(default_factory=time.time)
|
||||
priority: MessagePriority = MessagePriority.NORMAL
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# MessageQueue - Thread-safe FIFO queue
|
||||
# ============================================================================
|
||||
|
||||
class MessageQueue:
|
||||
"""
|
||||
Thread-safe FIFO message queue.
|
||||
|
||||
Provides basic queue operations with thread safety for concurrent access.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self._messages: List[str] = []
|
||||
self._lock = threading.Lock()
|
||||
|
||||
@property
|
||||
def is_empty(self) -> bool:
|
||||
"""Check if queue is empty."""
|
||||
with self._lock:
|
||||
return len(self._messages) == 0
|
||||
|
||||
@property
|
||||
def count(self) -> int:
|
||||
"""Get number of messages in queue."""
|
||||
with self._lock:
|
||||
return len(self._messages)
|
||||
|
||||
def add(self, message: str) -> bool:
|
||||
"""
|
||||
Add a message to the end of the queue.
|
||||
|
||||
Args:
|
||||
message: The message to add
|
||||
|
||||
Returns:
|
||||
True if message was added, False if empty/whitespace
|
||||
"""
|
||||
trimmed = message.strip() if message else ""
|
||||
if not trimmed:
|
||||
return False
|
||||
|
||||
with self._lock:
|
||||
self._messages.append(trimmed)
|
||||
return True
|
||||
|
||||
def pop(self) -> Optional[str]:
|
||||
"""
|
||||
Remove and return the first message (FIFO).
|
||||
|
||||
Returns:
|
||||
The first message, or None if queue is empty
|
||||
"""
|
||||
with self._lock:
|
||||
if self._messages:
|
||||
return self._messages.pop(0)
|
||||
return None
|
||||
|
||||
def peek(self) -> Optional[str]:
|
||||
"""
|
||||
View the first message without removing it.
|
||||
|
||||
Returns:
|
||||
The first message, or None if queue is empty
|
||||
"""
|
||||
with self._lock:
|
||||
if self._messages:
|
||||
return self._messages[0]
|
||||
return None
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Remove all messages from the queue."""
|
||||
with self._lock:
|
||||
self._messages.clear()
|
||||
|
||||
def get_all(self) -> List[str]:
|
||||
"""
|
||||
Get all messages as a list (does not remove them).
|
||||
|
||||
Returns:
|
||||
Copy of all messages in queue order
|
||||
"""
|
||||
with self._lock:
|
||||
return self._messages.copy()
|
||||
|
||||
def remove_at(self, index: int) -> Optional[str]:
|
||||
"""
|
||||
Remove message at specific index.
|
||||
|
||||
Args:
|
||||
index: The index to remove (0-based)
|
||||
|
||||
Returns:
|
||||
The removed message, or None if index is invalid
|
||||
"""
|
||||
with self._lock:
|
||||
if 0 <= index < len(self._messages):
|
||||
return self._messages.pop(index)
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# StateManager - Processing state management
|
||||
# ============================================================================
|
||||
|
||||
class StateManager:
|
||||
"""
|
||||
Manages the processing state with optional callbacks.
|
||||
|
||||
Tracks whether the agent is idle, processing, or waiting for approval.
|
||||
"""
|
||||
|
||||
def __init__(self, on_state_change: Optional[Callable[[ProcessingState, ProcessingState], None]] = None):
|
||||
self._state = ProcessingState.IDLE
|
||||
self._lock = threading.Lock()
|
||||
self._on_state_change = on_state_change
|
||||
|
||||
@property
|
||||
def current_state(self) -> ProcessingState:
|
||||
"""Get current processing state."""
|
||||
with self._lock:
|
||||
return self._state
|
||||
|
||||
@property
|
||||
def is_idle(self) -> bool:
|
||||
"""Check if currently idle."""
|
||||
return self.current_state == ProcessingState.IDLE
|
||||
|
||||
@property
|
||||
def is_processing(self) -> bool:
|
||||
"""Check if currently processing."""
|
||||
return self.current_state == ProcessingState.PROCESSING
|
||||
|
||||
def set_state(self, new_state: ProcessingState) -> None:
|
||||
"""
|
||||
Set the processing state.
|
||||
|
||||
Args:
|
||||
new_state: The new state to set
|
||||
"""
|
||||
with self._lock:
|
||||
old_state = self._state
|
||||
self._state = new_state
|
||||
|
||||
# Call callback outside lock to prevent deadlock
|
||||
if self._on_state_change and old_state != new_state:
|
||||
self._on_state_change(old_state, new_state)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# QueueDisplay - Visual formatting
|
||||
# ============================================================================
|
||||
|
||||
class QueueDisplay:
|
||||
"""
|
||||
Formats queue and status for display.
|
||||
|
||||
Provides visual indicators for queue status, inspired by Codex CLI.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
queue: MessageQueue,
|
||||
state_manager: Optional[StateManager] = None,
|
||||
max_message_length: int = 50
|
||||
):
|
||||
self._queue = queue
|
||||
self._state_manager = state_manager
|
||||
self._max_length = max_message_length
|
||||
|
||||
def format_queue(self) -> str:
|
||||
"""
|
||||
Format queued messages for display.
|
||||
|
||||
Returns:
|
||||
Formatted string with queued messages
|
||||
"""
|
||||
messages = self._queue.get_all()
|
||||
if not messages:
|
||||
return ""
|
||||
|
||||
lines = []
|
||||
for msg in messages:
|
||||
# Truncate long messages
|
||||
display_msg = msg
|
||||
if len(msg) > self._max_length:
|
||||
display_msg = msg[:self._max_length - 3] + "..."
|
||||
lines.append(f" ↳ {display_msg}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def format_status(self) -> str:
|
||||
"""
|
||||
Format current processing status.
|
||||
|
||||
Returns:
|
||||
Status string (e.g., "⏳ Processing..." or "")
|
||||
"""
|
||||
if not self._state_manager:
|
||||
return ""
|
||||
|
||||
state = self._state_manager.current_state
|
||||
if state == ProcessingState.PROCESSING:
|
||||
return "⏳ Processing..."
|
||||
elif state == ProcessingState.WAITING_APPROVAL:
|
||||
return "🔒 Waiting for approval..."
|
||||
return ""
|
||||
|
||||
def format_queue_count(self) -> str:
|
||||
"""
|
||||
Format queue count indicator.
|
||||
|
||||
Returns:
|
||||
Count string (e.g., "📋 Queued (2)")
|
||||
"""
|
||||
count = self._queue.count
|
||||
if count == 0:
|
||||
return ""
|
||||
return f"📋 Queued ({count})"
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# MessageQueueHandler - Main handler class
|
||||
# ============================================================================
|
||||
|
||||
class MessageQueueHandler:
|
||||
"""
|
||||
Main handler for message queue functionality.
|
||||
|
||||
Coordinates queue, state, and processing.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
processor: Optional[Callable[[str], str]] = None,
|
||||
on_response: Optional[Callable[[str], None]] = None
|
||||
):
|
||||
self._processor = processor
|
||||
self._on_response = on_response
|
||||
self._queue = MessageQueue()
|
||||
self._state_manager = StateManager(on_state_change=self._on_state_change)
|
||||
self._processing_lock = threading.Lock()
|
||||
|
||||
@property
|
||||
def queue(self) -> MessageQueue:
|
||||
"""Get the message queue."""
|
||||
return self._queue
|
||||
|
||||
@property
|
||||
def state_manager(self) -> StateManager:
|
||||
"""Get the state manager."""
|
||||
return self._state_manager
|
||||
|
||||
def submit(self, message: str) -> bool:
|
||||
"""
|
||||
Submit a message for processing.
|
||||
|
||||
If idle, processes immediately. If processing, queues the message.
|
||||
|
||||
Args:
|
||||
message: The message to submit
|
||||
|
||||
Returns:
|
||||
True if processed/queued, False if empty message
|
||||
"""
|
||||
trimmed = message.strip() if message else ""
|
||||
if not trimmed:
|
||||
return False
|
||||
|
||||
if self._state_manager.is_idle:
|
||||
# Process immediately
|
||||
self._process_message(trimmed)
|
||||
else:
|
||||
# Queue for later
|
||||
self._queue.add(trimmed)
|
||||
|
||||
return True
|
||||
|
||||
def on_processing_complete(self) -> None:
|
||||
"""
|
||||
Called when current processing completes.
|
||||
|
||||
Sets state to idle and processes next queued message if any.
|
||||
"""
|
||||
self._state_manager.set_state(ProcessingState.IDLE)
|
||||
self._process_next_in_queue()
|
||||
|
||||
def get_status(self) -> dict:
|
||||
"""
|
||||
Get current status.
|
||||
|
||||
Returns:
|
||||
Dict with queue_count and state
|
||||
"""
|
||||
return {
|
||||
'queue_count': self._queue.count,
|
||||
'state': self._state_manager.current_state.value,
|
||||
'messages': self._queue.get_all()
|
||||
}
|
||||
|
||||
def clear_queue(self) -> None:
|
||||
"""Clear all queued messages."""
|
||||
self._queue.clear()
|
||||
|
||||
def _process_message(self, message: str) -> None:
|
||||
"""Process a single message."""
|
||||
if not self._processor:
|
||||
return
|
||||
|
||||
with self._processing_lock:
|
||||
self._state_manager.set_state(ProcessingState.PROCESSING)
|
||||
try:
|
||||
response = self._processor(message)
|
||||
if self._on_response and response:
|
||||
self._on_response(response)
|
||||
finally:
|
||||
self._state_manager.set_state(ProcessingState.IDLE)
|
||||
|
||||
def _process_next_in_queue(self) -> None:
|
||||
"""Process the next message in queue if any."""
|
||||
next_msg = self._queue.pop()
|
||||
if next_msg:
|
||||
self._process_message(next_msg)
|
||||
|
||||
def _on_state_change(self, old_state: ProcessingState, new_state: ProcessingState) -> None:
|
||||
"""Handle state changes."""
|
||||
# Auto-process queue when becoming idle
|
||||
if new_state == ProcessingState.IDLE and old_state == ProcessingState.PROCESSING:
|
||||
# Don't auto-process here to avoid recursion
|
||||
# The on_processing_complete method handles this
|
||||
pass
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# AsyncProcessor - Background processing
|
||||
# ============================================================================
|
||||
|
||||
class AsyncProcessor:
|
||||
"""
|
||||
Runs work functions in background threads.
|
||||
|
||||
Allows agent processing to happen asynchronously while
|
||||
the main thread remains responsive for user input.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
on_complete: Optional[Callable[[str], None]] = None,
|
||||
on_status: Optional[Callable[[str], None]] = None,
|
||||
on_error: Optional[Callable[[Exception], None]] = None
|
||||
):
|
||||
self._on_complete = on_complete
|
||||
self._on_status = on_status
|
||||
self._on_error = on_error
|
||||
self._thread: Optional[threading.Thread] = None
|
||||
self._running = False
|
||||
self._lock = threading.Lock()
|
||||
|
||||
@property
|
||||
def is_running(self) -> bool:
|
||||
"""Check if currently processing."""
|
||||
with self._lock:
|
||||
return self._running
|
||||
|
||||
def start(self, work_fn: Callable[[], str]) -> None:
|
||||
"""
|
||||
Start processing work in background thread.
|
||||
|
||||
Args:
|
||||
work_fn: Function to execute (should return result string)
|
||||
"""
|
||||
def _worker():
|
||||
try:
|
||||
with self._lock:
|
||||
self._running = True
|
||||
|
||||
result = work_fn()
|
||||
|
||||
with self._lock:
|
||||
self._running = False
|
||||
|
||||
if self._on_complete:
|
||||
self._on_complete(result)
|
||||
except Exception as e:
|
||||
with self._lock:
|
||||
self._running = False
|
||||
if self._on_error:
|
||||
self._on_error(e)
|
||||
|
||||
self._thread = threading.Thread(target=_worker, daemon=True)
|
||||
self._thread.start()
|
||||
|
||||
def update_status(self, status: str) -> None:
|
||||
"""Update status (can be called from work function)."""
|
||||
if self._on_status:
|
||||
self._on_status(status)
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# LiveStatusDisplay - Real-time status display
|
||||
# ============================================================================
|
||||
|
||||
class LiveStatusDisplay:
|
||||
"""
|
||||
Tracks and displays real-time status during processing.
|
||||
|
||||
Shows tool calls, command executions, and current status.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self._status = ""
|
||||
self._tool_calls: List[dict] = []
|
||||
self._commands: List[str] = []
|
||||
self._lock = threading.Lock()
|
||||
|
||||
@property
|
||||
def current_status(self) -> str:
|
||||
"""Get current status message."""
|
||||
with self._lock:
|
||||
return self._status
|
||||
|
||||
@property
|
||||
def tool_calls(self) -> List[dict]:
|
||||
"""Get list of tool calls."""
|
||||
with self._lock:
|
||||
return self._tool_calls.copy()
|
||||
|
||||
@property
|
||||
def commands(self) -> List[str]:
|
||||
"""Get list of commands executed."""
|
||||
with self._lock:
|
||||
return self._commands.copy()
|
||||
|
||||
def update_status(self, status: str) -> None:
|
||||
"""Update current status message."""
|
||||
with self._lock:
|
||||
self._status = status
|
||||
|
||||
def add_tool_call(self, name: str, args: dict) -> None:
|
||||
"""Add a tool call to the display."""
|
||||
with self._lock:
|
||||
self._tool_calls.append({
|
||||
'name': name,
|
||||
'args': args,
|
||||
'timestamp': time.time()
|
||||
})
|
||||
|
||||
def add_command(self, command: str) -> None:
|
||||
"""Add a command execution to the display."""
|
||||
with self._lock:
|
||||
self._commands.append(command)
|
||||
|
||||
def format(self) -> str:
|
||||
"""Format current status for display."""
|
||||
lines = []
|
||||
|
||||
with self._lock:
|
||||
if self._status:
|
||||
lines.append(f"⏳ {self._status}")
|
||||
|
||||
for tool in self._tool_calls[-3:]: # Show last 3 tools
|
||||
lines.append(f" 🔧 {tool['name']}")
|
||||
|
||||
for cmd in self._commands[-2:]: # Show last 2 commands
|
||||
display_cmd = cmd[:40] + "..." if len(cmd) > 40 else cmd
|
||||
lines.append(f" 💻 {display_cmd}")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Clear all status."""
|
||||
with self._lock:
|
||||
self._status = ""
|
||||
self._tool_calls.clear()
|
||||
self._commands.clear()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# NonBlockingInput - Async input handling
|
||||
# ============================================================================
|
||||
|
||||
class NonBlockingInput:
|
||||
"""
|
||||
Handles user input asynchronously.
|
||||
|
||||
Allows users to type new messages while processing is ongoing.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self._queue = MessageQueue()
|
||||
|
||||
@property
|
||||
def has_pending(self) -> bool:
|
||||
"""Check if there are pending inputs."""
|
||||
return not self._queue.is_empty
|
||||
|
||||
@property
|
||||
def pending_count(self) -> int:
|
||||
"""Get number of pending inputs."""
|
||||
return self._queue.count
|
||||
|
||||
def submit(self, message: str) -> bool:
|
||||
"""Submit a new input message."""
|
||||
return self._queue.add(message)
|
||||
|
||||
def pop(self) -> Optional[str]:
|
||||
"""Get next pending input."""
|
||||
return self._queue.pop()
|
||||
|
||||
def peek(self) -> Optional[str]:
|
||||
"""View next pending input without removing."""
|
||||
return self._queue.peek()
|
||||
|
||||
def get_all(self) -> List[str]:
|
||||
"""Get all pending inputs."""
|
||||
return self._queue.get_all()
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Clear all pending inputs."""
|
||||
self._queue.clear()
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Exports
|
||||
# ============================================================================
|
||||
|
||||
__all__ = [
|
||||
'ProcessingState',
|
||||
'MessagePriority',
|
||||
'QueuedMessage',
|
||||
'MessageQueue',
|
||||
'StateManager',
|
||||
'QueueDisplay',
|
||||
'MessageQueueHandler',
|
||||
'AsyncProcessor',
|
||||
'LiveStatusDisplay',
|
||||
'NonBlockingInput',
|
||||
]
|
||||
@@ -35,7 +35,7 @@ class N8nHandler(FlagHandler):
|
||||
"""
|
||||
|
||||
def __init__(self, verbose: bool = False, n8n_url: str = "http://localhost:5678",
|
||||
use_execute_command: bool = False):
|
||||
use_execute_command: bool = False, api_url: str = "http://127.0.0.1:8005"):
|
||||
"""
|
||||
Initialize the n8n handler.
|
||||
|
||||
@@ -44,10 +44,11 @@ class N8nHandler(FlagHandler):
|
||||
n8n_url: Base URL of the n8n instance
|
||||
use_execute_command: Use Execute Command nodes (runs praisonai directly)
|
||||
instead of HTTP Request nodes
|
||||
api_url: PraisonAI API URL that n8n will call (for tunnel/cloud deployments)
|
||||
"""
|
||||
super().__init__(verbose=verbose)
|
||||
self.n8n_url = n8n_url
|
||||
self.praisonai_api_url = "http://127.0.0.1:8005"
|
||||
self.praisonai_api_url = api_url
|
||||
self.use_execute_command = use_execute_command
|
||||
|
||||
@property
|
||||
|
||||
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