import os
import json
import faiss
import numpy as np
from fastapi import FastAPI, HTTPException, Depends
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
from fastapi.security import HTTPBasic, HTTPBasicCredentials
from pydantic import BaseModel
from sentence_transformers import SentenceTransformer
from starlette.status import HTTP_401_UNAUTHORIZED

app = FastAPI()
security = HTTPBasic()

# CORS support
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Auth config
USERNAME = os.getenv("API_USER", "bodha")
PASSWORD = os.getenv("API_PASS", "securepass123")

def authenticate(credentials: HTTPBasicCredentials = Depends(security)):
    if credentials.username != USERNAME or credentials.password != PASSWORD:
        raise HTTPException(
            status_code=HTTP_401_UNAUTHORIZED,
            detail="Incorrect username or password",
            headers={"WWW-Authenticate": "Basic"},
        )

# Load model and vector index
model = SentenceTransformer("./local_model")
faiss_index = faiss.read_index("index_combined.faiss")
with open("metadata_combined.json", "r", encoding="utf-8") as f:
    metadata = json.load(f)

# JSON schema for request body
class SearchBody(BaseModel):
    query: str

@app.get("/")
def root():
    return {"message": "BodhaGPT Vector API is live!"}

@app.post("/vector-api/search")
def search(body: SearchBody, credentials: HTTPBasicCredentials = Depends(authenticate)):
    query = body.query.strip()
    if not query:
        return JSONResponse(status_code=400, content={"error": "Query is required"})

    embedding = model.encode([query])[0]
    D, I = faiss_index.search(np.array([embedding]), k=5)

    results = [metadata[idx] for idx in I[0] if idx < len(metadata)]
    return results