# Import libraries
import os
import gradio as gr
from groq import Groq

# Set up Groq API client (ensure GROQ_API_KEY is set in your environment or as a Hugging Face secret for deployment)
client = Groq(api_key= apikey )


# Function to interact with the LLM using Groq's API
def chatbot(user_input):
    try:
        # Send user input to the LLM and get a response
        chat_completion = client.chat.completions.create(
            messages=[
                {
                    "role": "user",
                    "content": user_input,
                }
            ],
            model="llama3-8b-8192",  # Replace with the desired model
        )
        response = chat_completion.choices[0].message.content
        return response
    except Exception as e:
        # Handle errors gracefully
        return f"An error occurred: {str(e)}"

# Create a Gradio interface for real-time interaction
iface = gr.Interface(
    fn=chatbot,
    inputs=gr.Textbox(label="Your Message", placeholder="Type a message here..."),
    outputs=gr.Textbox(label="Response"),
    title="Real-Time Text-to-Text Chatbot - by ATIF MEHMOOD",
    description="You can Chat with the LLM in real-time using Groq's API.",
)

# Launch the Gradio app
iface.launch()