suna/agentpress/standard_tool_executor.py

import asyncio
import json
import logging
from typing import Dict, Any, List, Set, Callable, Optional
from agentpress.base_processors import ToolExecutorBase
from agentpress.tool import ToolResult

# --- Standard Tool Executor Implementation ---

class StandardToolExecutor(ToolExecutorBase):
    """Standard implementation of tool execution with configurable strategies.
    
    Provides a flexible tool execution implementation that supports both parallel
    and sequential execution patterns, with built-in error handling and result
    formatting.
    
    Attributes:
        parallel (bool): Whether to execute tools in parallel
        
    Methods:
        execute_tool_calls: Main execution entry point
        _execute_parallel: Parallel execution implementation
        _execute_sequential: Sequential execution implementation
    """
    
    def __init__(self, parallel: bool = True):
        self.parallel = parallel
    
    async def execute_tool_calls(
        self,
        tool_calls: List[Dict[str, Any]],
        available_functions: Dict[str, Callable],
        thread_id: str,
        executed_tool_calls: Optional[Set[str]] = None
    ) -> List[Dict[str, Any]]:
        if executed_tool_calls is None:
            executed_tool_calls = set()
            
        if self.parallel:
            return await self._execute_parallel(
                tool_calls, 
                available_functions, 
                thread_id, 
                executed_tool_calls
            )
        else:
            return await self._execute_sequential(
                tool_calls, 
                available_functions, 
                thread_id, 
                executed_tool_calls
            )
    
    async def _execute_parallel(
        self,
        tool_calls: List[Dict[str, Any]],
        available_functions: Dict[str, Callable],
        thread_id: str,
        executed_tool_calls: Set[str]
    ) -> List[Dict[str, Any]]:
        async def execute_single_tool(tool_call: Dict[str, Any]) -> Dict[str, Any]:
            if tool_call['id'] in executed_tool_calls:
                return None
                
            try:
                function_name = tool_call['function']['name']
                function_args = tool_call['function']['arguments']
                if isinstance(function_args, str):
                    function_args = json.loads(function_args)
                
                function_to_call = available_functions.get(function_name)
                if not function_to_call:
                    error_msg = f"Function {function_name} not found"
                    logging.error(error_msg)
                    return {
                        "role": "tool",
                        "tool_call_id": tool_call['id'],
                        "name": function_name,
                        "content": str(ToolResult(success=False, output=error_msg))
                    }

                result = await function_to_call(**function_args)
                logging.info(f"Tool execution result for {function_name}: {result}")
                executed_tool_calls.add(tool_call['id'])
                
                return {
                    "role": "tool",
                    "tool_call_id": tool_call['id'],
                    "name": function_name,
                    "content": str(result)
                }
            except Exception as e:
                error_msg = f"Error executing {function_name}: {str(e)}"
                logging.error(error_msg)
                return {
                    "role": "tool",
                    "tool_call_id": tool_call['id'],
                    "name": function_name,
                    "content": str(ToolResult(success=False, output=error_msg))
                }

        tasks = [execute_single_tool(tool_call) for tool_call in tool_calls]
        results = await asyncio.gather(*tasks)
        return [r for r in results if r is not None]
    
    async def _execute_sequential(
        self,
        tool_calls: List[Dict[str, Any]],
        available_functions: Dict[str, Callable],
        thread_id: str,
        executed_tool_calls: Set[str]
    ) -> List[Dict[str, Any]]:
        results = []
        for tool_call in tool_calls:
            if tool_call['id'] in executed_tool_calls:
                continue
                
            try:
                function_name = tool_call['function']['name']
                function_args = tool_call['function']['arguments']
                if isinstance(function_args, str):
                    function_args = json.loads(function_args)
                
                function_to_call = available_functions.get(function_name)
                if not function_to_call:
                    error_msg = f"Function {function_name} not found"
                    logging.error(error_msg)
                    result = ToolResult(success=False, output=error_msg)
                else:
                    result = await function_to_call(**function_args)
                    logging.info(f"Tool execution result for {function_name}: {result}")
                    executed_tool_calls.add(tool_call['id'])
                
                results.append({
                    "role": "tool",
                    "tool_call_id": tool_call['id'],
                    "name": function_name,
                    "content": str(result)
                })
            except Exception as e:
                error_msg = f"Error executing {function_name}: {str(e)}"
                logging.error(error_msg)
                results.append({
                    "role": "tool",
                    "tool_call_id": tool_call['id'],
                    "name": function_name,
                    "content": str(ToolResult(success=False, output=error_msg))
                })
        
        return results