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| import os | |
| import streamlit as st | |
| from groq import Groq | |
| # Set your API key in the environment | |
| os.environ["GROQ_API_KEY"] = "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" | |
| # Initialize Groq client with the API key from the environment | |
| client = Groq( | |
| api_key=os.environ.get("GROQ_API_KEY"), | |
| ) | |
| # Function to interact with Groq API and get responses | |
| def get_chat_response(user_message): | |
| chat_completion = client.chat.completions.create( | |
| messages=[ | |
| { | |
| "role": "user", | |
| "content": user_message, | |
| } | |
| ], | |
| model="llama-3.3-70b-versatile", | |
| ) | |
| return chat_completion.choices[0].message.content | |
| # Streamlit UI setup | |
| st.title("AI-based Healthcare Chatbot") | |
| st.write("Welcome to the Healthcare Chatbot! Ask me anything about health.") | |
| # Text input for user query | |
| user_input = st.text_input("Your Question:") | |
| if user_input: | |
| # Get the response from Groq API | |
| response = get_chat_response(user_input) | |
| # Display the chatbot's response | |
| st.write("Chatbot Response:") | |
| st.write(response) | |
| # You can add more user-friendly features like history or options to rephrase responses, etc. | |