whisper.py

import os
import requests
from fastapi import APIRouter
from pydantic import BaseModel
from dotenv import load_dotenv
from models import *

class WhisperX(BaseModel):
    filename: str

router = APIRouter()

load_dotenv()
HUGGING_TOKEN = os.environ["HUGGING_TOKEN"]

async def whsiper_to_text(filename):
    if not os.path.isfile(filename):
        print(f"Error: File {filename} does not exist.")
        return None

    API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3"
    headers = {"Authorization": f"Bearer {HUGGING_TOKEN}"}
    
    with open(filename, "rb") as f:
        files = {'file': f}
        response = requests.post(API_URL, headers=headers, files=files)

    if response.status_code != 200:
        print(f"Error status {response.status_code}")
        return None
    return response.json()

@router.post("/akeno/whsiper", response_model=SuccessResponse, responses={422: {"model": SuccessResponse}})
async def whsiper_new(payload: WhisperX):
    try:
        response_data = await whsiper_to_text(payload.filename)
        if response_data is None:
            return SuccessResponse(
                status="False",
                randydev={"error": f"Failed to whisper the filename '{payload.filename}'"}
            )
            
        return SuccessResponse(
                status="True",
                randydev={"message": response_data.get("text")}
            )
    except Exception as e:
        return SuccessResponse(
            status="False",
            randydev={"error": f"An error occurred: {str(e)}"}
        )