app.py

import gradio as gr
from groq import Groq
import os

def chatbot(message, history, api_key):
    # Initialize Groq client with the provided API key
    client = Groq(api_key=api_key)

    # Prepare the messages including the conversation history
    messages = [
        {"role": "system", "content": "You are a helpful assistant."}
    ]
    for human, assistant in history:
        messages.append({"role": "user", "content": human})
        messages.append({"role": "assistant", "content": assistant})
    messages.append({"role": "user", "content": message})

    try:
        # Create the chat completion
        completion = client.chat.completions.create(
            model="llama-3.2-90b-text-preview",
            messages=messages,
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=True,
            stop=None,
        )

        # Stream the response
        partial_message = ""
        for chunk in completion:
            if chunk.choices[0].delta.content is not None:
                partial_message += chunk.choices[0].delta.content
                yield partial_message
    except Exception as e:
        yield f"Error: {str(e)}"

# Create the Gradio interface
with gr.Blocks(theme="soft") as iface:
    gr.Markdown("# Groq LLaMA 3.2 90B Chatbot")
    gr.Markdown("Chat with the LLaMA 3.2 90B model using Groq API")
    
    with gr.Row():
        api_key_input = gr.Textbox(
            label="Enter your Groq API Key",
            placeholder="sk-...",
            type="password"
        )

    chatbot = gr.ChatInterface(
        chatbot,
        additional_inputs=[api_key_input],
        examples=[
            "Tell me a short story about a robot learning to paint.",
            "Explain quantum computing in simple terms.",
            "What are some creative ways to reduce plastic waste?",
        ],
        retry_btn=None,
        undo_btn="Delete Last",
        clear_btn="Clear",
    )

# Launch the interface
iface.launch()