Jonnathan20202/AURRA

import os import asyncio import gradio as gr from groq import AsyncGroq # Changed to the asynchronous client

Secure API key loading

API_KEY = os.environ.get("GROQ_API_KEY", "YOUR_FALLBACK_KEY_HERE") client = AsyncGroq(api_key=API_KEY) # Initialized as AsyncGroq

Valid models available on Groq

MODELS = [ "llama-3.3-70b-versatile", "llama-3.1-8b-instant", "deepseek-r1-distill-llama-70b", "qwen/qwen3.6-27b" ]

Changed to an async generator function

async def chat_groq(message, history, model_name, system_prompt, temperature): messages = [{"role": "system", "content": system_prompt}]

# Add conversation history
for user_msg, assistant_msg in history:
    messages.append({"role": "user", "content": user_msg})
    messages.append({"role": "assistant", "content": assistant_msg})

# Add current user prompt
messages.append({"role": "user", "content": message})

try:
    # Await the async streaming completion creation
    response_stream = await client.chat.completions.create(
        model=model_name,
        messages=messages,
        temperature=temperature,
        max_tokens=2048,
        stream=True
    )

    partial_response = ""
    # Use async for to safely iterate over the asynchronous stream chunks
    async for chunk in response_stream:
        if chunk.choices and len(chunk.choices) > 0:
            token = chunk.choices[0].delta.content or ""
            partial_response += token
            yield partial_response
            
except Exception as e:
    yield f"An error occurred: {str(e)}"

with gr.Blocks(title="Groq AI Chatbot") as demo: gr.Markdown("## ⚡ Groq Ultra-Fast AI Assistant")

with gr.Row():
    with gr.Column(scale=1):
        model_selector = gr.Dropdown(
            choices=MODELS,
            value="llama-3.3-70b-versatile",
            label="Select Groq Model"
        )
        temp_slider = gr.Slider(
            minimum=0.0, maximum=1.0, value=0.7, step=0.1, label="Temperature"
        )
        system_box = gr.Textbox(
            value="You are a helpful and concise AI assistant.",
            label="System Prompt",
            lines=3
        )
    with gr.Column(scale=3):
        chatbot = gr.ChatInterface(
            fn=chat_groq,
            additional_inputs=[model_selector, system_box, temp_slider]
        )

demo.launch(debug=True)