Complete PicoGent implementation with ReAct agent loop
- Implemented full ReAct loop in agent.py with 20 iteration limit - Added Anthropic provider using httpx (no SDK dependency) - Created complete tool system: read, write, edit, bash - Added session management with JSONL format - Updated README with usage examples - Fixed tool registry imports and methods - All core functionality working
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README.md
20
README.md
@ -41,22 +41,24 @@ pip install -e .
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3. **Use the agent**:
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```python
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import asyncio
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from picogent import Agent, Config
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from picogent import run_agent, Config
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# Load configuration
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config = Config.from_file("config.json")
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# Create agent
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agent = Agent(config)
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# Run a task
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async def main():
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response = await agent.chat("Create a hello world Python script")
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# Load configuration
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config = Config.from_file("config.json")
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# Run agent with prompt
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response = await run_agent("List all files in the current directory", config)
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print(response)
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asyncio.run(main())
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```
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Or use the CLI:
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```bash
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python -m picogent.cli "Create a hello world Python script"
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```
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## Architecture
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### Core Components
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@ -1,15 +1,16 @@
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"""
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Main agent loop with ReAct pattern
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Main agent with ReAct loop
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"""
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import uuid
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import asyncio
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from typing import Dict, Any, Optional, List
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import uuid
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from typing import Dict, Any, List, Optional
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from .config import Config
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from .session import Session
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from .context import Context
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from .context import ContextBuilder
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from .providers.anthropic import AnthropicProvider
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from .tools.registry import registry
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from .tools.registry import ToolRegistry
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from .tools.read import ReadTool
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from .tools.write import WriteTool
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from .tools.edit import EditTool
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@ -17,136 +18,136 @@ from .tools.bash import BashTool
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class Agent:
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"""Main PicoGent agent with ReAct loop"""
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"""AI coding agent with ReAct loop"""
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def __init__(self, config: Config, context: Optional[Context] = None):
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def __init__(self, config: Config):
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self.config = config
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self.context = context or Context(config.workspace)
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self.provider = None
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self.session = Session()
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self.context_builder = ContextBuilder(config.workspace)
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# Initialize provider
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if config.provider == "anthropic":
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self.provider = AnthropicProvider(config.api_key, config.model)
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else:
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raise ValueError(f"Unknown provider: {config.provider}")
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# Initialize tools
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self._initialize_tools()
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self.tool_registry = ToolRegistry()
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self._register_default_tools()
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def _initialize_tools(self):
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"""Initialize and register all tools"""
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# Register tools with workspace context
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registry.register(ReadTool())
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registry.register(WriteTool())
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registry.register(EditTool())
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registry.register(BashTool(self.context.get_workspace()))
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def _register_default_tools(self):
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"""Register default tools"""
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self.tool_registry.register(ReadTool())
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self.tool_registry.register(WriteTool())
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self.tool_registry.register(EditTool())
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self.tool_registry.register(BashTool())
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async def __aenter__(self):
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"""Async context manager entry"""
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self.provider = AnthropicProvider(self.config)
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await self.provider.__aenter__()
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return self
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async def __aexit__(self, exc_type, exc_val, exc_tb):
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"""Async context manager exit"""
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if self.provider:
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await self.provider.__aexit__(exc_type, exc_val, exc_tb)
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async def run_agent(self, prompt: str, session: Optional[Session] = None) -> str:
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"""
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Main ReAct loop
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Args:
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prompt: User prompt/question
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session: Optional session for conversation history
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Returns:
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Final response from the agent
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"""
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# Create session if not provided
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if session is None:
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session = Session()
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async def run(self, user_message: str, session_file: Optional[str] = None) -> str:
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"""Run the agent with ReAct loop"""
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# Load session if specified
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if session_file:
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self.session.session_file = session_file
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self.session.load()
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# Add user message to session
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session.add_message("user", prompt)
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self.session.add_message("user", user_message)
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# Build system prompt
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system_prompt = self.context_builder.build_system_prompt(self.config.system_prompt)
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# Add working directory info to system prompt
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system_prompt += "\n\n" + self.context_builder.get_working_directory_info()
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# ReAct loop
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for iteration in range(self.config.max_iterations):
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try:
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# Get messages and system prompt
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messages = session.get_anthropic_messages()
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system_prompt = self.context.get_system_prompt()
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tools = registry.get_tool_definitions()
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iteration = 0
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max_iterations = self.config.max_iterations
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# Call LLM
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response = await self.provider.chat_completion(
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while iteration < max_iterations:
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iteration += 1
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# Get messages for API
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messages = self.session.get_anthropic_messages()
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# Get available tools
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tools = self.tool_registry.get_anthropic_tools()
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try:
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# Generate response
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response = await self.provider.generate_response(
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messages=messages,
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system_prompt=system_prompt,
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tools=tools,
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system_prompt=system_prompt
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max_tokens=self.config.max_tokens
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)
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# Handle errors
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if "error" in response:
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error_msg = f"Provider error: {response['error']}"
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session.add_message("assistant", error_msg)
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return error_msg
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# Check if there are tool calls
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tool_calls = response.get("tool_calls", [])
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# Get content and tool calls
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content = response.get("content", "").strip()
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tool_calls = self.provider.parse_tool_calls(response)
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# No tool calls - return text response
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if not tool_calls:
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if content:
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session.add_message("assistant", content)
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return content
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else:
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error_msg = "Empty response from provider"
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session.add_message("assistant", error_msg)
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return error_msg
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# No tool calls, return text response
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response_text = response.get("content", "").strip()
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if response_text:
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self.session.add_message("assistant", response_text)
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# Add assistant message with tool calls
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if content:
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# Add text content if present
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session.add_message("assistant", content)
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# Save session if file specified
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if session_file:
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self.session.save()
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return response_text or "I apologize, but I didn't generate a response."
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# Process tool calls
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# First, add the assistant message with tool calls
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if response.get("raw_content"):
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self.session.add_message("assistant", response["raw_content"])
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else:
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# Fallback for when we don't have raw content
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self.session.add_message("assistant", f"I'll use the following tools: {[tc['name'] for tc in tool_calls]}")
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# Execute each tool call
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all_results = []
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for tool_call in tool_calls:
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tool_id = tool_call.get("id") or str(uuid.uuid4())
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tool_name = tool_call.get("name", "")
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tool_args = tool_call.get("arguments", {})
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tool_id = tool_call.get("id", str(uuid.uuid4()))
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tool_name = tool_call.get("name")
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tool_input = tool_call.get("input", {})
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# Add tool use to session
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session.add_tool_use(tool_name, tool_args, tool_id)
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try:
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# Execute the tool
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result = await self.tool_registry.execute_tool(tool_name, tool_input)
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# Execute tool
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result = await registry.execute_tool(tool_name, tool_args)
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all_results.append(result)
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# Add tool result to session
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self.session.add_tool_result(tool_id, result)
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# Add tool result to session
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session.add_tool_result(tool_id, result)
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except Exception as e:
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error_result = f"Error executing {tool_name}: {str(e)}"
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self.session.add_tool_result(tool_id, error_result)
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# Continue loop to process tool results
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continue
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# Continue the loop to get the next response
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except Exception as e:
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error_msg = f"Agent error in iteration {iteration + 1}: {str(e)}"
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session.add_message("assistant", error_msg)
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error_msg = f"Error during agent execution: {str(e)}"
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# Save session if file specified
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if session_file:
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self.session.save()
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return error_msg
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# Max iterations reached
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final_msg = f"Reached maximum iterations ({self.config.max_iterations}). Task may be incomplete."
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session.add_message("assistant", final_msg)
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return final_msg
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final_message = f"Maximum iterations ({max_iterations}) reached. The agent may need more steps to complete the task."
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# Save session if file specified
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if session_file:
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self.session.save()
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# Convenience function
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async def run_agent(prompt: str, config: Config, session: Optional[Session] = None) -> str:
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"""
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Convenience function to run agent
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return final_message
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Args:
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prompt: User prompt
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config: Agent configuration
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session: Optional session for conversation history
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async def chat(self, user_message: str) -> str:
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"""Simple chat interface without session persistence"""
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return await self.run(user_message)
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Returns:
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Agent response
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"""
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async with Agent(config) as agent:
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return await agent.run_agent(prompt, session)
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def clear_session(self):
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"""Clear the current session"""
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self.session.clear()
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def get_session_messages(self) -> List[Dict[str, Any]]:
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"""Get all messages in the current session"""
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return self.session.get_messages()
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@ -19,18 +19,22 @@ class Tool(ABC):
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"""Execute the tool with given arguments"""
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pass
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def to_anthropic_format(self) -> Dict[str, Any]:
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"""Convert tool to Anthropic API format"""
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def to_dict(self) -> Dict[str, Any]:
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"""Convert tool to dictionary for API"""
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return {
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"name": self.name,
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"description": self.description,
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"input_schema": {
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"type": "object",
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"properties": self.parameters.get("properties", {}),
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"required": self.parameters.get("required", [])
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'name': self.name,
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'description': self.description,
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'input_schema': {
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'type': 'object',
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'properties': self.parameters.get('properties', {}),
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'required': self.parameters.get('required', [])
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}
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}
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def to_anthropic_format(self) -> Dict[str, Any]:
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"""Convert tool to Anthropic API format (alias)"""
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return self.to_dict()
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class ToolRegistry:
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"""Registry for managing available tools"""
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@ -52,11 +56,22 @@ class ToolRegistry:
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"""Get all registered tools"""
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return list(self.tools.values())
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def get_tool_definitions(self) -> List[Dict[str, Any]]:
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"""Get tool definitions for API"""
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return [tool.to_dict() for tool in self.tools.values()]
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def get_anthropic_tools(self) -> List[Dict[str, Any]]:
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"""Get all tools in Anthropic API format"""
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return [tool.to_anthropic_format() for tool in self.tools.values()]
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"""Get all tools in Anthropic API format (alias)"""
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return self.get_tool_definitions()
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async def execute_tool(self, name: str, args: Dict[str, Any]) -> str:
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"""Execute a tool by name with arguments"""
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tool = self.get_tool(name)
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return await tool.execute(args)
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try:
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tool = self.get_tool(name)
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return await tool.execute(args)
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except Exception as e:
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return f"Error executing {name}: {str(e)}"
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# Global registry instance
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registry = ToolRegistry()
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