# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. import json import logging import shutil import uuid from collections.abc import AsyncGenerator from llama_stack.apis.agents import ( Agent, AgentConfig, AgentCreateResponse, Agents, AgentSessionCreateResponse, AgentStepResponse, AgentToolGroup, AgentTurnCreateRequest, AgentTurnResumeRequest, Document, ListAgentSessionsResponse, ListAgentsResponse, OpenAIResponseInputMessage, OpenAIResponseInputTool, OpenAIResponseObject, Session, Turn, ) from llama_stack.apis.inference import ( Inference, ToolConfig, ToolResponse, ToolResponseMessage, UserMessage, ) from llama_stack.apis.safety import Safety from llama_stack.apis.tools import ToolGroups, ToolRuntime from llama_stack.apis.vector_io import VectorIO from llama_stack.providers.utils.kvstore import InmemoryKVStoreImpl, kvstore_impl from .agent_instance import ChatAgent from .config import MetaReferenceAgentsImplConfig from .openai_responses import OpenAIResponsesImpl logger = logging.getLogger() logger.setLevel(logging.INFO) class MetaReferenceAgentsImpl(Agents): def __init__( self, config: MetaReferenceAgentsImplConfig, inference_api: Inference, vector_io_api: VectorIO, safety_api: Safety, tool_runtime_api: ToolRuntime, tool_groups_api: ToolGroups, ): self.config = config self.inference_api = inference_api self.vector_io_api = vector_io_api self.safety_api = safety_api self.tool_runtime_api = tool_runtime_api self.tool_groups_api = tool_groups_api self.in_memory_store = InmemoryKVStoreImpl() self.openai_responses_impl = None async def initialize(self) -> None: self.persistence_store = await kvstore_impl(self.config.persistence_store) self.openai_responses_impl = OpenAIResponsesImpl( self.persistence_store, inference_api=self.inference_api, tool_groups_api=self.tool_groups_api, tool_runtime_api=self.tool_runtime_api, ) # check if "bwrap" is available if not shutil.which("bwrap"): logger.warning("Warning: `bwrap` is not available. Code interpreter tool will not work correctly.") async def create_agent( self, agent_config: AgentConfig, ) -> AgentCreateResponse: agent_id = str(uuid.uuid4()) await self.persistence_store.set( key=f"agent:{agent_id}", value=agent_config.model_dump_json(), ) return AgentCreateResponse( agent_id=agent_id, ) async def _get_agent_impl(self, agent_id: str) -> ChatAgent: agent_config = await self.persistence_store.get( key=f"agent:{agent_id}", ) if not agent_config: raise ValueError(f"Could not find agent config for {agent_id}") try: agent_config = json.loads(agent_config) except json.JSONDecodeError as e: raise ValueError(f"Could not JSON decode agent config for {agent_id}") from e try: agent_config = AgentConfig(**agent_config) except Exception as e: raise ValueError(f"Could not validate(?) agent config for {agent_id}") from e return ChatAgent( agent_id=agent_id, agent_config=agent_config, inference_api=self.inference_api, safety_api=self.safety_api, vector_io_api=self.vector_io_api, tool_runtime_api=self.tool_runtime_api, tool_groups_api=self.tool_groups_api, persistence_store=( self.persistence_store if agent_config.enable_session_persistence else self.in_memory_store ), ) async def create_agent_session( self, agent_id: str, session_name: str, ) -> AgentSessionCreateResponse: agent = await self._get_agent_impl(agent_id) session_id = await agent.create_session(session_name) return AgentSessionCreateResponse( session_id=session_id, ) async def create_agent_turn( self, agent_id: str, session_id: str, messages: list[UserMessage | ToolResponseMessage], toolgroups: list[AgentToolGroup] | None = None, documents: list[Document] | None = None, stream: bool | None = False, tool_config: ToolConfig | None = None, ) -> AsyncGenerator: request = AgentTurnCreateRequest( agent_id=agent_id, session_id=session_id, messages=messages, stream=True, toolgroups=toolgroups, documents=documents, tool_config=tool_config, ) if stream: return self._create_agent_turn_streaming(request) else: raise NotImplementedError("Non-streaming agent turns not yet implemented") async def _create_agent_turn_streaming( self, request: AgentTurnCreateRequest, ) -> AsyncGenerator: agent = await self._get_agent_impl(request.agent_id) async for event in agent.create_and_execute_turn(request): yield event async def resume_agent_turn( self, agent_id: str, session_id: str, turn_id: str, tool_responses: list[ToolResponse], stream: bool | None = False, ) -> AsyncGenerator: request = AgentTurnResumeRequest( agent_id=agent_id, session_id=session_id, turn_id=turn_id, tool_responses=tool_responses, stream=stream, ) if stream: return self._continue_agent_turn_streaming(request) else: raise NotImplementedError("Non-streaming agent turns not yet implemented") async def _continue_agent_turn_streaming( self, request: AgentTurnResumeRequest, ) -> AsyncGenerator: agent = await self._get_agent_impl(request.agent_id) async for event in agent.resume_turn(request): yield event async def get_agents_turn(self, agent_id: str, session_id: str, turn_id: str) -> Turn: agent = await self._get_agent_impl(agent_id) turn = await agent.storage.get_session_turn(session_id, turn_id) return turn async def get_agents_step(self, agent_id: str, session_id: str, turn_id: str, step_id: str) -> AgentStepResponse: turn = await self.get_agents_turn(agent_id, session_id, turn_id) for step in turn.steps: if step.step_id == step_id: return AgentStepResponse(step=step) raise ValueError(f"Provided step_id {step_id} could not be found") async def get_agents_session( self, agent_id: str, session_id: str, turn_ids: list[str] | None = None, ) -> Session: agent = await self._get_agent_impl(agent_id) session_info = await agent.storage.get_session_info(session_id) if session_info is None: raise ValueError(f"Session {session_id} not found") turns = await agent.storage.get_session_turns(session_id) if turn_ids: turns = [turn for turn in turns if turn.turn_id in turn_ids] return Session( session_name=session_info.session_name, session_id=session_id, turns=turns, started_at=session_info.started_at, ) async def delete_agents_session(self, agent_id: str, session_id: str) -> None: await self.persistence_store.delete(f"session:{agent_id}:{session_id}") async def delete_agent(self, agent_id: str) -> None: await self.persistence_store.delete(f"agent:{agent_id}") async def shutdown(self) -> None: pass async def list_agents(self) -> ListAgentsResponse: pass async def get_agent(self, agent_id: str) -> Agent: pass async def list_agent_sessions( self, agent_id: str, ) -> ListAgentSessionsResponse: pass # OpenAI responses async def get_openai_response( self, id: str, ) -> OpenAIResponseObject: return await self.openai_responses_impl.get_openai_response(id) async def create_openai_response( self, input: str | list[OpenAIResponseInputMessage], model: str, previous_response_id: str | None = None, store: bool | None = True, stream: bool | None = False, temperature: float | None = None, tools: list[OpenAIResponseInputTool] | None = None, ) -> OpenAIResponseObject: return await self.openai_responses_impl.create_openai_response( input, model, previous_response_id, store, stream, temperature, tools )