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| import streamlit as st | |
| import requests | |
| import io | |
| # Hugging Face API setup | |
| API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo" | |
| # Prompt the user for their Hugging Face API key | |
| my_key = st.text_input('Enter your Hugging Face API Key', type='password') | |
| # Set up headers with the provided API key | |
| headers = {"Authorization": f"Bearer {my_key}"} | |
| # Function to send the file to the API and get the transcription result | |
| def query(file_data): | |
| try: | |
| response = requests.post(API_URL, headers=headers, files={'file': file_data}) | |
| return response.json() | |
| except requests.exceptions.RequestException as e: | |
| return {"error": str(e)} | |
| # File uploader widget for audio files | |
| uploaded_files = st.file_uploader("Choose an audio file", type=["mp3", "wav", "flac"], accept_multiple_files=True) | |
| # Handle file uploads and process them if API key is provided | |
| if my_key: # Proceed only if the API key is provided | |
| if uploaded_files: | |
| results = {} | |
| for uploaded_file in uploaded_files: | |
| st.write(f"Processing file: {uploaded_file.name}") | |
| # Validate file type and check if it's in the correct format | |
| file_type = uploaded_file.type | |
| st.write(f"File type: {file_type}") | |
| if file_type not in ["audio/mpeg", "audio/wav", "audio/flac"]: | |
| st.write(f"Unsupported file type: {file_type}. Please upload an MP3, WAV, or FLAC file.") | |
| continue | |
| # Send the file to the Hugging Face API | |
| output = query(uploaded_file) | |
| # Store and display the result | |
| results[uploaded_file.name] = output | |
| # Show results for all files | |
| st.write("Results:") | |
| for file, result in results.items(): | |
| st.write(f"**Results for {file}:**") | |
| st.json(result) | |
| else: | |
| st.write("Please upload an audio file to transcribe.") | |
| else: | |
| st.write("Please enter your Hugging Face API key to proceed.") | |