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| import os | |
| import streamlit as st | |
| from dotenv import load_dotenv | |
| from groq import Groq | |
| # Load environment variables from .env file | |
| load_dotenv() | |
| # Get the GROQ API Key from the environment | |
| api_key = os.getenv("GROQ_API_KEY") | |
| # If the API key is not found, show an error in the app | |
| if not api_key: | |
| st.error("Please set the GROQ_API_KEY in the .env file.") | |
| st.stop() | |
| # Initialize the Groq client with the API key | |
| client = Groq(api_key=api_key) | |
| # Streamlit app UI | |
| st.title("GROQ API with Llama-3.3 Integration") | |
| st.write("This app uses GROQ API to interact with Llama-3.3 for generating responses based on the user input.") | |
| # User input section | |
| user_input = st.text_area("Ask me anything about fast language models:") | |
| if st.button("Generate Response"): | |
| if user_input: | |
| # Make API call to GROQ | |
| chat_completion = client.chat.completions.create( | |
| messages=[{"role": "user", "content": user_input}], | |
| model="llama-3.3-70b-versatile", | |
| ) | |
| # Display the response from the model | |
| st.write(chat_completion.choices[0].message.content) | |
| else: | |
| st.error("Please enter a question.") | |