app.py

import os
import time
import json
import tempfile
import threading
from typing import Optional
from datetime import datetime, timezone

import httpx
import whisper
import nltk
from nltk.tokenize import sent_tokenize
from fastapi import FastAPI, UploadFile, File, Form, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from transformers import pipeline

# ---------------- Fix Whisper cache issue ----------------
os.environ["XDG_CACHE_HOME"] = "/tmp/.cache"

# ---------------- Config ----------------
UPLOAD_DIR = "uploads"
os.makedirs(UPLOAD_DIR, exist_ok=True)

# Initialize FastAPI
app = FastAPI()

# Allow CORS for all origins
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Load Whisper model (small for speed)
model = whisper.load_model("small")


@app.post("/transcribe/")
async def transcribe_audio(file: UploadFile = File(...)):
    try:
        # Save uploaded file temporarily
        file_path = os.path.join(UPLOAD_DIR, file.filename)
        with open(file_path, "wb") as f:
            f.write(await file.read())

        # Transcribe with Whisper
        result = model.transcribe(file_path)

        # Return text output
        return {"filename": file.filename, "transcription": result["text"]}

    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))