from fastapi import FastAPI, File, UploadFile, Form
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from typing import List, Optional
import numpy as np
import io
import os
from dotenv import load_dotenv
from pydub import AudioSegment
from utils import (
    authenticate,
    split_documents,
    build_vectorstore,
    retrieve_context,
    retrieve_context_approx,
    build_prompt,
    ask_gemini,
    load_documents_gradio,
    transcribe
)

load_dotenv()

app = FastAPI()

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

client = authenticate()
store = {"value": None}

@app.post("/upload")
async def upload(files: List[UploadFile] = File(...)):
    if not files:
        return JSONResponse({"status": "error", "message": "No files uploaded."}, status_code=400)
    raw_docs = load_documents_gradio(files)
    chunks = split_documents(raw_docs)
    store["value"] = build_vectorstore(chunks)
    return {"status": "success", "message": "Document processed successfully! You can now ask questions."}

@app.post("/ask")
async def ask(
    text: Optional[str] = Form(None),
    audio: Optional[UploadFile] = File(None)
):
    transcribed = None
    if store["value"] is None:
        return JSONResponse({"status": "error", "message": "Please upload and process a document first."}, status_code=400)
    if text and text.strip():
        query = text.strip()
    elif audio is not None:
        audio_bytes = await audio.read()
        try:
            audio_io = io.BytesIO(audio_bytes)
            audio_seg = AudioSegment.from_file(audio_io)
            y = np.array(audio_seg.get_array_of_samples()).astype(np.float32)
            if audio_seg.channels == 2:
                y = y.reshape((-1, 2)).mean(axis=1)  # Convert to mono
            y /= np.max(np.abs(y))  # Normalize to [-1, 1]
            sr = audio_seg.frame_rate
            transcribed = transcribe((sr, y))
            query = transcribed
        except FileNotFoundError as e:
            return JSONResponse({"status": "error", "message": "Audio decode failed: ffmpeg is not installed or not in PATH. Please install ffmpeg."}, status_code=400)
        except Exception as e:
            return JSONResponse({"status": "error", "message": f"Audio decode failed: {str(e)}"}, status_code=400)
    else:
        return JSONResponse({"status": "error", "message": "Please provide a question by typing or speaking."}, status_code=400)
    if store["value"]["chunks"] <= 50:
        top_chunks = retrieve_context(query, store["value"])
    else:
        top_chunks = retrieve_context_approx(query, store["value"])
    prompt = build_prompt(top_chunks, query)
    answer = ask_gemini(prompt, client)
    return {"status": "success", "answer": answer.strip(), "transcribed": transcribed}