from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from datetime import datetime
import platform
import urllib.request
import json as jsonlib

app = FastAPI(title="PropFirms API", version="1.2.0")

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

OLLAMA_URL = "http://10.0.1.1:11435"

SYSTEM_PROMPT = """Tu es un assistant spécialisé dans le trading et les prop firms.
Tu résumes des transcripts de vidéos YouTube en français pour des traders.
Format de réponse :
- Contexte marché (1-2 phrases)
- Points clés (3-5 bullet points)
- Takeaways pour un trader prop firm (1-2 phrases)
Sois concis et direct."""

@app.get("/")
def root():
    return {"status": "ok", "service": "PropFirms DGX API", "version": "1.2.0"}

@app.get("/health")
def health():
    return {
        "status":    "healthy",
        "timestamp": datetime.utcnow().isoformat(),
        "host":      platform.node(),
        "ollama":    "qwen3:14b"
    }

@app.get("/ping")
def ping():
    return {"pong": True}

class SummarizeRequest(BaseModel):
    transcript: str
    video_title: str = ""

@app.post("/summarize")
async def summarize(req: SummarizeRequest):
    if not req.transcript.strip():
        raise HTTPException(status_code=400, detail="Transcript vide")

    prompt = f"Titre de la vidéo : {req.video_title}\n\nTranscript :\n{req.transcript[:4000]}"

    payload = jsonlib.dumps({
        "model":  "qwen3:14b",
        "prompt": prompt,
        "system": SYSTEM_PROMPT,
        "stream": False
    }).encode("utf-8")

    try:
        request = urllib.request.Request(
            f"{OLLAMA_URL}/api/generate",
            data=payload,
            headers={"Content-Type": "application/json"},
            method="POST"
        )
        with urllib.request.urlopen(request, timeout=120) as resp:
            result = jsonlib.loads(resp.read())
    except Exception as e:
        raise HTTPException(status_code=502, detail=f"Erreur Ollama : {str(e)}")

    return {
        "summary":     result.get("response", ""),
        "video_title": req.video_title,
        "model":       "qwen3:14b",
        "timestamp":   datetime.utcnow().isoformat()
    }

class OCRRequest(BaseModel):
    image_base64: str
    platform: str = "auto"

@app.post("/ocr")
def ocr(req: OCRRequest):
    raise HTTPException(status_code=503, detail="OCR non encore activé — disponible à l'étape 3")