""" Agent Runner Core orchestrator for AI agent execution with tool calling support. Manages the full request cycle: LLM generation → tool execution → final response. """ import logging from typing import List, Dict, Any, Optional import asyncio from .agent_config import AgentConfiguration from .providers.base import LLMProvider from .providers.gemini import GeminiProvider from .providers.openrouter import OpenRouterProvider from .providers.cohere import CohereProvider from ..mcp.tool_registry import MCPToolRegistry, ToolExecutionResult logger = logging.getLogger(__name__) class AgentRunner: """ Agent execution orchestrator with tool calling support. This class manages the full agent request cycle: 1. Generate LLM response with tool definitions 2. If tool calls requested, execute tools with user context injection 3. Generate final response with tool results 4. Handle rate limiting with fallback providers """ def __init__(self, config: AgentConfiguration, tool_registry: MCPToolRegistry): """ Initialize the agent runner. Args: config: Agent configuration tool_registry: MCP tool registry """ self.config = config self.tool_registry = tool_registry self.primary_provider = self._create_provider(config.provider) self.fallback_provider = None if config.fallback_provider: self.fallback_provider = self._create_provider(config.fallback_provider) logger.info(f"Initialized AgentRunner with provider: {config.provider}") def _create_provider(self, provider_name: str) -> LLMProvider: """ Create an LLM provider instance. Args: provider_name: Provider name (gemini, openrouter, cohere) Returns: LLMProvider instance Raises: ValueError: If provider is not supported or API key is missing """ api_key = self.config.get_provider_api_key(provider_name) if not api_key: raise ValueError(f"API key not configured for provider: {provider_name}") model = self.config.get_provider_model(provider_name) if provider_name == "gemini": return GeminiProvider( api_key=api_key, model=model, temperature=self.config.temperature, max_tokens=self.config.max_tokens ) elif provider_name == "openrouter": return OpenRouterProvider( api_key=api_key, model=model, temperature=self.config.temperature, max_tokens=self.config.max_tokens ) elif provider_name == "cohere": return CohereProvider( api_key=api_key, model=model, temperature=self.config.temperature, max_tokens=self.config.max_tokens ) else: raise ValueError(f"Unsupported provider: {provider_name}") async def execute( self, messages: List[Dict[str, str]], user_id: int, system_prompt: Optional[str] = None ) -> Dict[str, Any]: """ Execute agent request with tool calling support. SECURITY: user_id is injected by backend, never from LLM output. Args: messages: Conversation history [{"role": "user", "content": "..."}] user_id: User ID (injected by backend for security) system_prompt: Optional system prompt (uses config default if not provided) Returns: Dict with response content and metadata """ prompt = system_prompt or self.config.system_prompt provider = self.primary_provider try: # Get tool definitions tool_definitions = self.tool_registry.get_tool_definitions() logger.info(f"Executing agent for user {user_id} with {len(tool_definitions)} tools") # Generate initial response with tool definitions response = await provider.generate_response_with_tools( messages=messages, system_prompt=prompt, tools=tool_definitions ) # Check if tool calls were requested if response.tool_calls: logger.info(f"Agent requested {len(response.tool_calls)} tool calls") # Execute all tool calls tool_results = [] for tool_call in response.tool_calls: result = await self.tool_registry.execute_tool( tool_name=tool_call["name"], arguments=tool_call["arguments"], user_id=user_id # Inject user context for security ) tool_results.append(result) # Generate final response with tool results final_response = await provider.generate_response_with_tool_results( messages=messages, tool_calls=response.tool_calls, tool_results=tool_results ) return { "content": final_response.content, "tool_calls": response.tool_calls, "tool_results": tool_results, "provider": provider.get_provider_name() } # No tool calls, return direct response logger.info("Agent generated direct response (no tool calls)") return { "content": response.content, "tool_calls": None, "tool_results": None, "provider": provider.get_provider_name() } except Exception as e: logger.error(f"Agent execution failed with primary provider: {str(e)}") # Try fallback provider if configured if self.fallback_provider: logger.info("Attempting fallback provider") try: return await self._execute_with_provider( provider=self.fallback_provider, messages=messages, user_id=user_id, system_prompt=prompt ) except Exception as fallback_error: logger.error(f"Fallback provider also failed: {str(fallback_error)}") raise raise async def _execute_with_provider( self, provider: LLMProvider, messages: List[Dict[str, str]], user_id: int, system_prompt: str ) -> Dict[str, Any]: """ Execute agent request with a specific provider. Args: provider: LLM provider to use messages: Conversation history user_id: User ID system_prompt: System prompt Returns: Dict with response content and metadata """ tool_definitions = self.tool_registry.get_tool_definitions() # Generate initial response response = await provider.generate_response_with_tools( messages=messages, system_prompt=system_prompt, tools=tool_definitions ) # Handle tool calls if response.tool_calls: tool_results = [] for tool_call in response.tool_calls: result = await self.tool_registry.execute_tool( tool_name=tool_call["name"], arguments=tool_call["arguments"], user_id=user_id ) tool_results.append(result) final_response = await provider.generate_response_with_tool_results( messages=messages, tool_calls=response.tool_calls, tool_results=tool_results ) return { "content": final_response.content, "tool_calls": response.tool_calls, "tool_results": tool_results, "provider": provider.get_provider_name() } return { "content": response.content, "tool_calls": None, "tool_results": None, "provider": provider.get_provider_name() } async def execute_simple( self, messages: List[Dict[str, str]], system_prompt: Optional[str] = None ) -> str: """ Execute a simple agent request without tool calling. Args: messages: Conversation history system_prompt: Optional system prompt Returns: Response content as string """ prompt = system_prompt or self.config.system_prompt provider = self.primary_provider try: response = await provider.generate_simple_response( messages=messages, system_prompt=prompt ) return response.content or "" except Exception as e: logger.error(f"Simple execution failed: {str(e)}") # Try fallback provider if self.fallback_provider: logger.info("Attempting fallback provider for simple execution") response = await self.fallback_provider.generate_simple_response( messages=messages, system_prompt=prompt ) return response.content or "" raise