| | import requests |
| | from typing import Dict, Any |
| | from dotenv import load_dotenv, find_dotenv |
| | import os |
| | import streamlit as st |
| | import json |
| | from textToStoryGeneration import * |
| | import logging |
| |
|
| | |
| | logging.basicConfig(level=logging.DEBUG) |
| | |
| | logging.basicConfig(level=logging.ERROR) |
| | |
| | logging.basicConfig(level=logging.WARNING) |
| |
|
| | load_dotenv(find_dotenv()) |
| | HUGGINFACE_API = os.getenv("HUGNINGFACEHUB_API_TOKEN") |
| |
|
| | class CustomHandler: |
| | def __init__(self): |
| | self.model_name = "espnet/kan-bayashi_ljspeech_vits" |
| | self.endpoint = f"https://api-inference.huggingface.co/models/{self.model_name}" |
| |
|
| | def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]: |
| | |
| | logging.warning(f"------input_data-- {str(data)}") |
| | payload = {"inputs": data} |
| | print("payload----", payload) |
| | |
| | headers = {"Authorization": f"Bearer {HUGGINFACE_API}"} |
| | |
| | |
| | response = requests.post(self.endpoint, json=payload, headers=headers) |
| | with open('StoryAudio.mp3', 'wb') as file: |
| | file.write(response.content) |
| | return 'StoryAudio.mp3' |
| | |
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