#!/usr/bin/env python3
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import logging, json
from pathlib import Path

logging.basicConfig(level=logging.INFO)

STATUS_FILE = Path('/tmp/setup_status.json')
READY_FLAG = Path('/tmp/faiss_ready')

def get_status():
    if not STATUS_FILE.exists():
        return {'status': 'init', 'progress': 0}
    with open(STATUS_FILE) as f:
        return json.load(f)

query_engine = None

def get_engine():
    global query_engine
    if query_engine is None:
        if not READY_FLAG.exists():
            raise HTTPException(503, "Em construção")
        from query_engine import QueryEngine
        query_engine = QueryEngine()
    return query_engine

app = FastAPI(title="Para.AI RAG", version="3.5.0")

class SearchRequest(BaseModel):
    query: str
    top_k: int = 10

@app.get("/")
async def root():
    return {"status": "online", "rag_ready": READY_FLAG.exists(), "setup": get_status()}

@app.get("/setup/status")
async def status():
    return get_status()

@app.get("/setup/logs")
async def logs():
    try:
        with open('/tmp/setup_debug.log') as f:
            return {"logs": f.read()}
    except:
        return {"logs": "N/A"}

@app.post("/search/embedding")
async def search(req: SearchRequest):
    return get_engine().search_by_embedding(req.query, req.top_k)