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| import streamlit as st | |
| import os | |
| import requests | |
| # Title for the Streamlit app | |
| st.title("Voice Cloning Application") | |
| # File uploader to upload a voice recording | |
| uploaded_file = st.file_uploader("Upload a voice recording (First Time)", type=["wav", "mp3"]) | |
| if uploaded_file is not None: | |
| # Save the uploaded file locally | |
| with open("user_voice.wav", "wb") as f: | |
| f.write(uploaded_file.getbuffer()) | |
| st.write("Your voice has been uploaded. Now we will clone your voice.") | |
| # Simulate storing the voice in a "database" (for simplicity, store it in the file system) | |
| user_voice_path = "user_voice.wav" | |
| # You could use Groq or other ML acceleration API here to fine-tune the model | |
| # Save user voice for future use (in real-life, this would be stored in a database) | |
| st.write(f"Voice stored at {user_voice_path}") | |
| # You can call your backend (Google Colab) to fine-tune the voice model | |
| response = requests.post("https://your-colab-backend-url", files={"file": open(user_voice_path, "rb")}) | |
| if response.status_code == 200: | |
| st.write("Voice fine-tuning completed successfully!") | |
| else: | |
| st.write("Error in fine-tuning the voice.") | |
| # File uploader for subsequent requests | |
| uploaded_file = st.file_uploader("Upload a text to clone your voice", type=["txt"]) | |
| if uploaded_file is not None: | |
| # Simulate user requesting a new cloned voice (no need to upload their voice) | |
| with open("user_text.txt", "w") as f: | |
| f.write(uploaded_file.getvalue().decode("utf-8")) | |
| # Call Google Colab model to generate cloned voice based on saved voice data | |
| cloned_voice = requests.post("https://your-colab-backend-url", files={"file": open("user_text.txt", "rb")}).content | |
| # Output the cloned voice | |
| st.audio(cloned_voice, format="audio/wav") | |
| st.write("Voice cloned successfully!") | |
| import requests | |
| def groq_accelerate(audio_file_path): | |
| url = "https://groq.api/accelerate" | |
| headers = {"Authorization": "Bearer YOUR_GROQ_API_KEY"} | |
| # Send the audio file to Groq for processing (this is a placeholder for actual implementation) | |
| audio_file = open(audio_file_path, "rb") | |
| response = requests.post(url, headers=headers, files={"file": audio_file}) | |
| # Return the accelerated result (cloned voice) | |
| return response.content | |