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| import gradio as gr | |
| from groq import Groq | |
| import os | |
| import time | |
| import speech_recognition as sr | |
| from gtts import gTTS | |
| api_key = os.getenv('GROQ_API_KEY') | |
| # Initialize Groq client | |
| client = Groq(api_key=api_key) | |
| # Function to convert audio to text | |
| def audio_to_text(audio_file): | |
| recognizer = sr.Recognizer() | |
| with sr.AudioFile(audio_file) as source: | |
| audio_data = recognizer.record(source) | |
| text = recognizer.recognize_google(audio_data) | |
| return text | |
| # Function to convert text to audio | |
| def text_to_audio(text): | |
| tts = gTTS(text) | |
| audio_file = "output_audio.mp3" | |
| tts.save(audio_file) | |
| return audio_file | |
| # Function to generate responses with error handling | |
| def generate_response(user_input, chat_history: list): | |
| try: | |
| # Prepare messages with chat history | |
| messages = [{"role": "system", "content": "You are a mental health assistant. Your responses should be empathetic, non-judgmental, and provide helpful advice based on mental health principles. Always encourage seeking professional help when needed. Your responses should look human as well."}] | |
| # Iterate through chat history and add user and assistant messages | |
| for message in chat_history: | |
| # Ensure that each message contains only 'role' and 'content' keys | |
| if 'role' in message and 'content' in message: | |
| messages.append({"role": message["role"], "content": message["content"]}) | |
| else: | |
| print(f"Skipping invalid message: {message}") | |
| messages.append({"role": "user", "content": user_input}) # Add the current user message | |
| # Call Groq API to get a response from LLaMA | |
| chat_completion = client.chat.completions.create( | |
| messages=messages, | |
| model='llama-3.1-70b-versatile' | |
| ) | |
| # Extract response | |
| response = chat_completion.choices[0].message.content | |
| return response, chat_history # Ensure you return both response and chat_history | |
| except Exception as e: | |
| print(f"Error occurred: {e}") # Print error to console for debugging | |
| return "An error occurred while generating the response. Please try again.", chat_history | |
| # Define Gradio interface | |
| def gradio_interface(): | |
| with gr.Blocks() as demo: | |
| # Initialize chat history | |
| chat_history = [] | |
| # Create input textbox and button for clearing chat | |
| gr.Markdown("## LoserHero - A Mental Health Chatbot") | |
| chatbot = gr.Chatbot(type="messages") | |
| audio_input = gr.Audio(source="microphone", type="filepath", label="Speak your message") | |
| msg = gr.Textbox(placeholder="Type your message here...") | |
| text_output = gr.Textbox(label="Response (Text)") | |
| audio_output = gr.Audio(label="Response (Audio)") | |
| clear = gr.Button("Clear") | |
| def process_input(user_message, audio_file, history: list): | |
| if audio_file: | |
| user_message = audio_to_text(audio_file) | |
| if user_message: | |
| history.append({"role": "user", "content": user_message}) | |
| response, updated_history = generate_response(user_message, history) | |
| history = updated_history | |
| history.append({"role": "assistant", "content": response}) | |
| response_audio = text_to_audio(response) | |
| return "", None, response, response_audio, history | |
| return "", None, "Please provide a valid input.", None, history | |
| msg.submit(process_input, [msg, audio_input, chatbot], [msg, audio_input, text_output, audio_output, chatbot]) | |
| audio_input.change(process_input, [msg, audio_input, chatbot], [msg, audio_input, text_output, audio_output, chatbot]) | |
| clear.click(lambda: ("", None, "", None, []), None, [msg, audio_input, text_output, audio_output, chatbot]) | |
| demo.launch() | |
| # Run the interface | |
| gradio_interface() |