from fastapi import APIRouter, Body, Depends from fastapi.responses import StreamingResponse from openai import OpenAI from pydantic import BaseModel import json import asyncio from api.dependencies import get_llm_client from agents import get as get_agent, list_all as list_all_agents router = APIRouter() class ChatRequest(BaseModel): message: str session_id: str | None = None agent_id: str | None = None # which agent to use ("naked", "media-agent", …) class ChatCompletionRequest(BaseModel): messages: list[dict] stream: bool = False model: str = "deepseek-chat" # --------------------------------------------------------------------------- # Core helpers # --------------------------------------------------------------------------- def _resolve_agent(agent_id: str | None = None, model: str | None = None): """ Look up the agent. Resolution order: 1. explicit agent_id 2. model name (OpenWebUI sends this — maps to agent_id if registered) 3. fallback to "naked" """ lookup = agent_id or model if lookup is None: agent = get_agent("naked") else: agent = get_agent(lookup) if agent is None: agent = get_agent("naked") return agent def run_agent( client: OpenAI, message: str, session_id: str | None = None, agent_id: str | None = None, model: str | None = None, ) -> str: """Non-streaming: uses the chosen agent's system prompt.""" agent = _resolve_agent(agent_id, model) response = client.chat.completions.create( model="deepseek-chat", messages=[ {"role": "system", "content": agent.build_system_prompt()}, {"role": "user", "content": message}, ], ) return response.choices[0].message.content async def run_agent_stream( client: OpenAI, message: str, session_id: str | None = None, agent_id: str | None = None, model: str | None = None, ): """Async generator — yields tokens using the chosen agent's system prompt.""" agent = _resolve_agent(agent_id, model) system_prompt = agent.build_system_prompt() loop = asyncio.get_running_loop() def _sync_stream(): stream = client.chat.completions.create( model="deepseek-chat", messages=[ {"role": "system", "content": system_prompt}, {"role": "user", "content": message}, ], stream=True, ) for chunk in stream: delta = chunk.choices[0].delta if delta and delta.content: yield delta.content gen = _sync_stream() while True: token = await loop.run_in_executor(None, next, gen, None) if token is None: break yield token # --------------------------------------------------------------------------- # Endpoints # --------------------------------------------------------------------------- @router.get("/") def root(): return {"status": "ok"} @router.post("/chat") async def chat(req: ChatRequest, client: OpenAI = Depends(get_llm_client)): """Streaming chat endpoint — returns Server-Sent Events.""" async def event_stream(): async for token in run_agent_stream( client, req.message, req.session_id, req.agent_id, ): payload = json.dumps({"token": token, "session_id": req.session_id}) yield f"data: {payload}\n\n" yield f"data: {json.dumps({'done': True, 'session_id': req.session_id})}\n\n" return StreamingResponse( event_stream(), media_type="text/event-stream", headers={ "Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no", }, ) @router.post("/chat/sync") def chat_sync(req: ChatRequest, client: OpenAI = Depends(get_llm_client)): """Non-streaming fallback — returns the full response at once.""" response = run_agent(client, req.message, req.session_id, req.agent_id) return {"response": response, "session_id": req.session_id} @router.get("/agents") def list_agents(): """Return all registered agents with their ids, descriptions, and skills.""" return { "agents": [ { "agent_id": a.agent_id, "description": a.description, "skills": a.skills, } for a in list_all_agents().values() ] } @router.get("/models") def list_models(): """Return all registered agents as selectable models for OpenWebUI.""" return { "object": "list", "data": [ { "id": a.agent_id, "object": "model", "created": 0, "owned_by": "local-agent", } for a in list_all_agents().values() ], } @router.post("/chat/completions") async def chat_completions( req: ChatCompletionRequest, client: OpenAI = Depends(get_llm_client), ): """OpenAI-compatible /chat/completions — supports stream=True. The last message's content is used as the user prompt; defaults to 'naked' agent. """ user_message = req.messages[-1]["content"] # Resolve agent from the model field (OpenWebUI sends this) agent = _resolve_agent(model=req.model) if req.stream: async def sse_stream(): async for token in run_agent_stream(client, user_message, agent_id=agent.agent_id): chunk = { "id": "chatcmpl-local", "object": "chat.completion.chunk", "choices": [ { "index": 0, "delta": {"content": token}, "finish_reason": None, } ], } yield f"data: {json.dumps(chunk)}\n\n" final_chunk = { "id": "chatcmpl-local", "object": "chat.completion.chunk", "choices": [ { "index": 0, "delta": {}, "finish_reason": "stop", } ], } yield f"data: {json.dumps(final_chunk)}\n\n" yield "data: [DONE]\n\n" return StreamingResponse( sse_stream(), media_type="text/event-stream", headers={ "Cache-Control": "no-cache", "Connection": "keep-alive", }, ) # Non-streaming path — resolve agent from model field agent = _resolve_agent(model=req.model) response = run_agent(client, user_message, agent_id=agent.agent_id) return { "id": "chatcmpl-local", "object": "chat.completion", "created": 0, "model": req.model, "choices": [ { "index": 0, "message": {"role": "assistant", "content": response}, "finish_reason": "stop", } ], }