app.py

import streamlit as st
from streamlit.components.v1 import html
import os
from groq import Groq

# Initialize Groq Client
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))

# Set the title of the app
st.title("AI Chatbot with Groq LLaMA Model")

# Custom CSS for a professional look
css = """
    <style>
        body {
            background-color: #f0f2f6;
            font-family: 'Arial', sans-serif;
        }
        .stTextInput, .stButton {
            margin-top: 20px;
        }
        .custom-box {
            padding: 20px;
            background-color: #ffffff;
            border-radius: 8px;
            box-shadow: 0px 4px 10px rgba(0, 0, 0, 0.1);
        }
        .error-msg {
            color: red;
            font-weight: bold;
        }
    </style>
"""

html(css)

st.markdown(
    """
    <div class='custom-box'>
    <h2>Ask anything about Data Science</h2>
    <p>Powered by Groq LLaMA 3.1 Model 🚀</p>
    </div>
    """, unsafe_allow_html=True
)

# Input for user queries
user_input = st.text_input("Ask your question here:")

# Function to handle Groq API call
def get_groq_response(query):
    try:
        chat_completion = client.chat.completions.create(
            messages=[{"role": "user", "content": query}],
            model="llama-3.1-70b-versatile",
        )
        return chat_completion.choices[0].message.content
    except Exception as e:
        return f"An error occurred: {str(e)}"

# Submit button for the chatbot
if st.button("Submit"):
    if user_input:
        with st.spinner("Fetching response..."):
            response = get_groq_response(user_input)
            st.success(response)
    else:
        st.error("Please enter a question!")

# Copy Button for User to easily copy the result
if response:
    st.code(response)
    st.button("Copy to clipboard", on_click=st.experimental_rerun)