import os import logging import streamlit as st #import google.generativeai from google.cloud import aiplatform from streamlit_chat import message import whisper from gtts import gTTS import tempfile from pydub import AudioSegment from groq import Groq, GroqError # Securely configure API keys GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") GROQ_API_KEY = os.getenv("GROQ_API_KEY") # Configure Google Generative AI API #genai.configure(api_key=GOOGLE_API_KEY) # Initialize the AI Platform client aiplatform.init(project="Generative Language Client", location="your-region") # Set up logging logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) # Initialize Groq Client if not GROQ_API_KEY: raise ValueError("GROQ_API_KEY is not set.") try: groq_client = Groq(api_key=GROQ_API_KEY) logger.info("Groq API key is set and client is initialized.") except GroqError as e: logger.error(f"Failed to initialize Groq client: {e}") raise # Load Whisper model for audio transcription try: whisper_model = whisper.load_model("base") logger.info("Whisper model loaded successfully.") except Exception as e: logger.error(f"Failed to load Whisper model: {e}") raise # Initialize Google Generative Model for chatbot model = genai.GenerativeModel( 'gemini-1.5-flash', system_instruction=( "Persona: You are Dr. Assad Siddiqui, a heart specialist. Only provide information related to heart health, symptoms, and advice. " "Ask users about their heart-related symptoms and provide consultation and guidance based on their input. " "Always provide brief answers. If the inquiry is not related to heart health, politely say that you can only provide heart-related information. " "Responses should be in Urdu written in English and in English." ) ) # Function to get chatbot response def get_chatbot_response(user_input): response = model.generate_content(user_input) return response.text.strip() # Function to process audio using Whisper and Groq API def process_audio(audio_file): try: result = whisper_model.transcribe(audio_file) user_text = result['text'] logger.info(f"Transcription successful: {user_text}") except Exception as e: logger.error(f"Error in transcribing audio: {e}") return "Error in transcribing audio.", None try: chat_completion = groq_client.chat.completions.create( messages=[{"role": "user", "content": user_text}], model="llama3-8b-8192", ) response_text = chat_completion.choices[0].message.content logger.info(f"Received response from Groq API: {response_text}") except GroqError as e: logger.error(f"Error in generating response with Groq API: {e}") return "Error in generating response with Groq API.", None try: tts = gTTS(text=response_text, lang='en') audio_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3') tts.save(audio_file.name) logger.info("Text-to-speech conversion successful.") except Exception as e: logger.error(f"Error in text-to-speech conversion: {e}") return "Error in text-to-speech conversion.", None return response_text, audio_file.name # Streamlit page configuration st.set_page_config(page_title="Heart Health Chatbot", page_icon="👨‍⚕️", layout="centered") # Background and header st.markdown("""

Heart Health Chatbot 🫀

Ask me anything about heart diseases!

""", unsafe_allow_html=True) # Initialize session state for chat history if "history" not in st.session_state: st.session_state.history = [] user_avatar_url = "https://img.freepik.com/free-photo/sad-cartoon-anatomical-heart_23-2149767987.jpg" bot_avatar_url = "https://img.freepik.com/premium-photo/3d-render-man-doctor-avatar-round-sticker-with-cartoon-character-face-user-id-thumbnail.jpg" # Function to display chat history def display_chat_history(): for chat in st.session_state.history: if chat["role"] == "user": st.markdown(f"""

You: {chat['content']}

""", unsafe_allow_html=True) else: st.markdown(f"""

Bot: {chat['content']}

""", unsafe_allow_html=True) # Main application layout def main(): display_chat_history() with st.container(): with st.form(key="user_input_form", clear_on_submit=True): user_input = st.text_input("Type your message...", placeholder="Ask about heart health...", max_chars=500) submit_button = st.form_submit_button("Send") if submit_button and user_input.strip(): with st.spinner("Thinking..."): bot_response = get_chatbot_response(user_input) # Update chat history st.session_state.history.append({"role": "user", "content": user_input}) st.session_state.history.append({"role": "bot", "content": bot_response}) display_chat_history() # Footer st.markdown("""

Check out the Live Appointment.

""", unsafe_allow_html=True) # Run the app if __name__ == "__main__": main()