ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
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"""
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Comprehensive Coding Agent - Modular implementation with pure Python tools
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All tools implemented without command-line dependencies
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"""
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import os
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import json
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from typing import List, Dict, Any, Optional, Iterator
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from pathlib import Path
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from datetime import datetime
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import anthropic
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try:
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from dotenv import load_dotenv
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load_dotenv()
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except ImportError:
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pass
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from system_state import SystemState
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from tool_registry import ToolRegistry
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class CodingAgent:
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"""Main coding agent with streaming support and modular tool system"""
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def __init__(self, api_key: str, model: str = "claude-sonnet-4-20250514", base_url: Optional[str] = None):
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"""
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Initialize coding agent
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Args:
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api_key: API key for Anthropic/OpenRouter
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model: Model identifier
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base_url: Optional base URL for OpenRouter or other providers
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"""
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self.api_key = api_key
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self.model = model
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self.base_url = base_url
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self.system_state = SystemState()
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self.tool_registry = ToolRegistry()
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self.messages: List[Dict[str, Any]] = []
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self.tools = self._load_tools()
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self.system_prompt = self._load_system_prompt()
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# Initialize Anthropic client
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if base_url:
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self.client = anthropic.Anthropic(api_key=api_key, base_url=base_url)
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else:
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self.client = anthropic.Anthropic(api_key=api_key)
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def _load_tools(self) -> List[Dict[str, Any]]:
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"""Load tool definitions from tools.json"""
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tools_file = Path(__file__).parent / "tools.json"
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with open(tools_file, 'r') as f:
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data = json.load(f)
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return data["tools"]
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def _load_system_prompt(self) -> str:
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"""Load system prompt from system-prompt.md"""
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prompt_file = Path(__file__).parent / "system-prompt.md"
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with open(prompt_file, 'r') as f:
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content = f.read()
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# Inject current environment information
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content = content.replace("${Working directory}", self.system_state.current_directory)
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content = content.replace("${current_branch}", self._get_git_branch())
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content = content.replace("${main_branch}", self._get_main_branch())
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content = content.replace("${Last 5 Recent commits}", self._get_recent_commits())
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return content
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def _get_git_branch(self) -> str:
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"""Get current git branch"""
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try:
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import subprocess
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return subprocess.getoutput("git branch --show-current") or "unknown"
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except Exception:
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return "unknown"
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def _get_main_branch(self) -> str:
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"""Get main branch name"""
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try:
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import subprocess
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branches = subprocess.getoutput("git branch -a")
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if "main" in branches:
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return "main"
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elif "master" in branches:
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return "master"
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return "main"
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except Exception:
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return "main"
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def _get_git_status(self) -> str:
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"""Get git status"""
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try:
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import subprocess
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return subprocess.getoutput("git status --short") or "No changes"
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except Exception:
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return "Not a git repository"
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def _get_recent_commits(self) -> str:
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"""Get recent commits"""
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try:
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import subprocess
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return subprocess.getoutput("git log --oneline -5") or "No commits"
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except Exception:
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return "Not a git repository"
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def run(self, user_message: str, max_iterations: int = 50) -> Iterator[Dict[str, Any]]:
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"""
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Run agent with streaming output
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Args:
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user_message: User's input message
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max_iterations: Maximum number of agent iterations
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Yields:
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Streaming events with type and content
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"""
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# Add user message with timestamp
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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self.messages.append({
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"role": "user",
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"content": f"[{timestamp}] {user_message}"
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})
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yield {"type": "user_message", "content": user_message, "timestamp": timestamp}
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for iteration in range(max_iterations):
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yield {"type": "iteration_start", "iteration": iteration + 1}
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# Prepare messages with system hint
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messages_with_hint = self.messages.copy()
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# Add system hint as a user message at the end
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system_hint = self.system_state.get_system_hint()
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messages_with_hint.append({
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"role": "user",
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"content": f"<system_hint>\n{system_hint}\n</system_hint>"
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})
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# Call Claude API with streaming
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try:
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with self.client.messages.stream(
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model=self.model,
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system=self.system_prompt,
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messages=messages_with_hint,
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tools=self.tools
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) as stream:
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assistant_message = {"role": "assistant", "content": []}
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current_text = ""
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current_tool_use = None
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current_tool_json = ""
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for event in stream:
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if event.type == "content_block_start":
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if event.content_block.type == "text":
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current_text = ""
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elif event.content_block.type == "tool_use":
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current_tool_use = {
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"type": "tool_use",
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"id": event.content_block.id,
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"name": event.content_block.name,
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"input": {}
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}
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current_tool_json = ""
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elif event.type == "content_block_delta":
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if event.delta.type == "text_delta":
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current_text += event.delta.text
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yield {
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"type": "text_delta",
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"delta": event.delta.text,
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"accumulated": current_text
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}
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elif event.delta.type == "input_json_delta":
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# Accumulate tool input; partial_json is a fragment,
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# only the concatenation of all fragments parses.
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if current_tool_use:
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current_tool_json += event.delta.partial_json
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elif event.type == "content_block_stop":
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if current_text:
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assistant_message["content"].append({
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"type": "text",
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"text": current_text
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})
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current_text = ""
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elif current_tool_use:
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try:
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current_tool_use["input"] = json.loads(
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current_tool_json or "{}"
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)
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except json.JSONDecodeError:
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pass
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assistant_message["content"].append(current_tool_use)
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yield {
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"type": "tool_call",
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"tool": current_tool_use["name"],
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"input": current_tool_use["input"]
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}
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current_tool_use = None
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# Add assistant message to history
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self.messages.append(assistant_message)
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# Check if we have tool calls to execute
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tool_calls = [
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block for block in assistant_message["content"]
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if block.get("type") == "tool_use"
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]
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if not tool_calls:
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# No tool calls, agent is done
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yield {"type": "done", "final_message": assistant_message}
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break
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# Execute tool calls
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tool_results = []
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for tool_call in tool_calls:
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tool_name = tool_call["name"]
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tool_input = tool_call["input"]
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yield {
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"type": "tool_execution_start",
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"tool": tool_name,
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"input": tool_input
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}
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# Get tool instance and execute
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try:
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tool = self.tool_registry.get_tool(tool_name, self.system_state)
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result = tool.execute(tool_input)
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result_dict = result.to_dict()
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except Exception as e:
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result_dict = {
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"error": str(e),
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"tool": tool_name
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}
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yield {
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"type": "tool_execution_complete",
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"tool": tool_name,
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"result": result_dict
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}
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tool_results.append({
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"type": "tool_result",
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"tool_use_id": tool_call["id"],
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"content": json.dumps(result_dict, ensure_ascii=False)
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})
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# Add tool results to messages
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self.messages.append({
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"role": "user",
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"content": tool_results
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})
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yield {"type": "iteration_end", "iteration": iteration + 1}
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except Exception as e:
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yield {"type": "error", "error": str(e)}
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break
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else:
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# Reached max iterations
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yield {"type": "max_iterations_reached", "max_iterations": max_iterations}
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def reset(self):
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"""Reset agent state"""
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self.messages = []
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self.system_state = SystemState()
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def main():
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"""Example usage"""
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api_key = os.getenv("ANTHROPIC_API_KEY")
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if not api_key:
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print("Error: ANTHROPIC_API_KEY environment variable not set")
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return
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agent = CodingAgent(api_key=api_key)
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user_query = "List all Python files in the current directory using the Glob tool"
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print(f"User: {user_query}\n")
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for event in agent.run(user_query):
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if event["type"] == "text_delta":
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print(event["delta"], end="", flush=True)
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elif event["type"] == "tool_call":
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print(f"\n[Calling tool: {event['tool']}]")
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elif event["type"] == "tool_execution_complete":
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print(f"[Tool completed]")
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elif event["type"] == "done":
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print("\n\nAgent completed successfully!")
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elif event["type"] == "error":
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print(f"\n\nError: {event['error']}")
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if __name__ == "__main__":
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main()
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