from fastapi import FastAPI, UploadFile, File, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from faster_whisper import WhisperModel
import anyio
import os
import tempfile
import shutil
import asyncio

app = FastAPI()

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

# Use the 'Base' model for maximum speed on Free Tier CPU
MODEL_ID = "Systran/faster-whisper-small"#Systran/faster-whisper-base
inference_lock = asyncio.Lock()
user_sessions = {}

try:
    print(f"Loading {MODEL_ID}...")
    # int8 quantization keeps it tiny and fast
    model = WhisperModel(MODEL_ID, device="cpu", compute_type="int8", download_root="./model_cache")
    print("Base Model Loaded!")
except Exception as e:
    print(f"Error: {e}")

@app.post("/whisper")
async def transcribe_audio(audio: UploadFile = File(...), session_id: str = "default",lang: str = None):
    async with inference_lock:
        if session_id not in user_sessions:
            temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".webm", dir="/tmp")
            user_sessions[session_id] = temp_file.name

        temp_path = user_sessions[session_id]
        
        try:
            with open(temp_path, "ab") as buffer:
                shutil.copyfileobj(audio.file, buffer)

            # Performance settings for the Base model
            segments, info = await anyio.to_thread.run_sync(
                lambda: model.transcribe(
                    temp_path, 
                    beam_size=1, 
                    vad_filter=True,
                    language=lang,
                    # Helping the small model with language context
                    initial_prompt="English and Arabic conversation. مرحبا بكم"
                )
            )
            
            full_text = " ".join([s.text for s in segments]).strip()
            return {"text": full_text, "language": info.language}

        except Exception as e:
            return {"text": "", "error": str(e)}

@app.get("/")
def health(): return {"status": "base-model-active"}