import os, json, asyncio
from fastapi import FastAPI, Request, HTTPException
from fastapi.responses import StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
from prompts import build_system_prompt
from search_engine import search_web

app = FastAPI()
app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])

MODEL_REPO = "bartowski/Qwen_Qwen3.6-35B-A3B-GGUF"
MODEL_FILE = "Qwen_Qwen3.6-35B-A3B-IQ3_M.gguf"
llm = None

def load_model():
    global llm
    if llm is None:
        print("⬇️ جاري تحميل النموذج...")
        model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILE)
        llm = Llama(
            model_path=model_path,
            n_ctx=1536,
            n_threads=4,
            n_gpu_layers=0,
            use_mmap=True,
            verbose=False
        )
        print("✅ تم تحميل النموذج بنجاح.")

@app.on_event("startup")
def startup():
    load_model()

async def generate_stream(messages: list, mode: str):
    system_prompt = build_system_prompt(mode)
    user_msg = messages[-1]['content']
    prompt = f"<|system|>\n{system_prompt}\n<|user|>\n{user_msg}\n<|assistant|>\n"
    
    if mode == "search":
        search_res = search_web(user_msg)
        prompt = f"<|system|>\n{system_prompt}\n<|user|>\n{user_msg}\n[SEARCH RESULTS]\n{search_res}\n<|assistant|>\n"

    for token in llm(prompt, max_tokens=1200, stop=["<|user|>", "<|end|>"], stream=True, temperature=0.7):
        yield json.dumps({"token": token["choices"][0]["text"]}) + "\n"
        await asyncio.sleep(0.01)

@app.post("/v1/chat/completions")
async def chat_completions(request: Request):
    data = await request.json()
    messages = data.get("messages", [])
    mode = data.get("mode", "chat")
    if not messages:
        raise HTTPException(400, "No messages provided")
    return StreamingResponse(generate_stream(messages, mode), media_type="application/json")

@app.get("/health")
def health():
    return {"status": "ok", "model": MODEL_FILE}