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| import streamlit as st | |
| import speech_recognition as sr | |
| from transformers import pipeline | |
| import requests | |
| # Load the chatbot model from Hugging Face | |
| chatbot = pipeline("conversational", model="facebook/blenderbot-400M-distill") | |
| # Function to convert speech to text using SpeechRecognition | |
| def speech_to_text(): | |
| recognizer = sr.Recognizer() | |
| with sr.Microphone() as source: | |
| st.info("Listening...") | |
| audio = recognizer.listen(source) | |
| try: | |
| text = recognizer.recognize_google(audio) | |
| return text | |
| except sr.UnknownValueError: | |
| return "Sorry, I could not understand the audio." | |
| except sr.RequestError: | |
| return "Speech recognition service is not available." | |
| # Function to generate avatar video using D-ID API | |
| def generate_avatar_video(text_response): | |
| api_url = "https://api.d-id.com/talk" | |
| headers = { | |
| "Authorization": "Bearer YOUR_API_KEY", # Replace with your D-ID API Key | |
| "Content-Type": "application/json" | |
| } | |
| payload = { | |
| "script": { | |
| "type": "text", | |
| "input": text_response | |
| }, | |
| "source": { | |
| "avatar_id": "your_avatar_id" # Replace with the desired avatar ID | |
| } | |
| } | |
| response = requests.post(api_url, headers=headers, json=payload) | |
| video_url = response.json().get("result_url") | |
| return video_url | |
| # Streamlit app interface | |
| st.title("🗣️ Voice-Enabled Live Video Chatbot") | |
| # Button to start recording | |
| if st.button("Speak"): | |
| user_input = speech_to_text() | |
| if user_input: | |
| st.write(f"**You:** {user_input}") | |
| # Generate chatbot response using NLP model | |
| bot_response = chatbot(user_input) | |
| response_text = bot_response[0]["generated_text"] | |
| st.write(f"**Bot:** {response_text}") | |
| # Generate avatar video with the bot's response | |
| video_url = generate_avatar_video(response_text) | |
| # Display the video response | |
| st.video(video_url) |