# app.py import os import tempfile import requests from fastapi import FastAPI, UploadFile, File, HTTPException from fastapi.responses import JSONResponse, HTMLResponse from pydantic import BaseModel from gradio_client import Client, handle_file import uvicorn app = FastAPI(title="Audio Transcription API (via URL)") # Hugging Face client try: client = Client("Ravishankarsharma/voice2text-summarizer") except Exception as e: print("Warning: Hugging Face client failed:", e) client = None # ✅ Pydantic model for URL input class AudioURL(BaseModel): url: str @app.get("/", response_class=HTMLResponse) async def home(): return HTMLResponse("""

Submit an audio URL to transcribe:

Swagger: /docs

""") # ✅ New endpoint: Accepts URL instead of file @app.post("/transcribe_url") async def transcribe_from_url(audio: AudioURL): if not client: raise HTTPException(status_code=500, detail="Hugging Face client not initialized") try: # 1. Download the audio file from given URL response = requests.get(audio.url, stream=True) if response.status_code != 200: raise HTTPException(status_code=400, detail="Failed to download audio file from URL") # 2. Save it temporarily with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp: for chunk in response.iter_content(chunk_size=8192): tmp.write(chunk) tmp_path = tmp.name # 3. Send to Hugging Face model result = client.predict(handle_file(tmp_path), api_name="/predict") os.remove(tmp_path) return { "source_url": audio.url, "transcription": result[0], "summary": result[1], "api_endpoint": result[2] } except Exception as e: raise HTTPException(status_code=500, detail=str(e)) if __name__ == "__main__": print("Server running at http://127.0.0.1:8000") uvicorn.run("app:app", host="127.0.0.1", port=8000, reload=True)