91 lines
2.5 KiB
Python
91 lines
2.5 KiB
Python
# app.py
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import time
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import uuid
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import json
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from typing import Any, Dict
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from fastapi import FastAPI, Request
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from fastapi.responses import JSONResponse, StreamingResponse
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from agent.llm.deepseek import DeepSeekClient
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from agent.memory import Memory
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from agent.agent import Agent
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app = FastAPI(
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title="LibreChat Agent Backend",
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version="0.1.0",
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)
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llm = DeepSeekClient()
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memory = Memory()
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agent = Agent(llm=llm, memory=memory)
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def extract_last_user_content(messages: list[Dict[str, Any]]) -> str:
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last = ""
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for m in reversed(messages):
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if m.get("role") == "user":
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last = m.get("content") or ""
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break
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return last
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@app.post("/v1/chat/completions")
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async def chat_completions(request: Request):
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body = await request.json()
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model = body.get("model", "local-deepseek-agent")
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messages = body.get("messages", [])
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stream = body.get("stream", False)
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user_input = extract_last_user_content(messages)
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print("Received chat completion request, stream =", stream, "input:", user_input)
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# Process user input through the agent
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answer = agent.step(user_input)
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# Ensuite = même logique de réponse (non-stream ou stream)
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created_ts = int(time.time())
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completion_id = f"chatcmpl-{uuid.uuid4().hex}"
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if not stream:
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resp = {
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"id": completion_id,
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"object": "chat.completion",
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"created": created_ts,
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"model": model,
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"choices": [
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{
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"index": 0,
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"finish_reason": "stop",
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"message": {
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"role": "assistant",
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"content": answer or "",
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},
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}
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],
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"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
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}
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return JSONResponse(resp)
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async def event_generator():
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chunk = {
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"id": completion_id,
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"object": "chat.completion.chunk",
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"created": created_ts,
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"model": model,
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"choices": [
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{
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"index": 0,
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"delta": {
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"role": "assistant",
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"content": answer or "",
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},
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"finish_reason": "stop",
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}
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],
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}
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yield f"data: {json.dumps(chunk, ensure_ascii=False)}\n\n"
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yield "data: [DONE]\n\n"
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return StreamingResponse(event_generator(), media_type="text/event-stream")
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