app.py

import gradio as gr

MODELS = ["Mixtral-8x7B-Instruct-v0.1"]

def chat_with_ai(message, chat_history, system_prompt):
    """Formats the chat history for processing."""
    history = [{"role": "system", "content": system_prompt}]
    history.extend(chat_history)
    history.append({"role": "user", "content": message})
    return history

def generate(message, chat_history, model, system_prompt, thinking_budget):
    """Simulates response generation."""
    # Dummy logic for simulating a response
    response = f"Simulated response for: {message}"
    
    # Update chat history
    chat_history.append({"role": "user", "content": message})
    chat_history.append({"role": "assistant", "content": response})

    return chat_history, ""

DEFAULT_SYSTEM_PROMPT = """
You are a helpful assistant in normal conversation.
When given a problem to solve, you are an expert problem-solving assistant.
Your task is to provide a detailed, step-by-step solution to a given question.
...
"""

with gr.Blocks() as demo:
    gr.Markdown("# Custom Chat Interface")
    
    with gr.Row():
        model = gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[0])
        thinking_budget = gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Thinking Budget")
    
    system_prompt = gr.Textbox(value=DEFAULT_SYSTEM_PROMPT, lines=15, label="System Prompt")
    chatbot = gr.Chatbot(label="Chat")
    msg = gr.Textbox(label="Type your message here...", placeholder="Enter your message...")
    
    def clear_chat():
        return [], ""
    
    gr.Button("Clear Chat").click(clear_chat, inputs=None, outputs=[chatbot, msg])

    msg.submit(generate, inputs=[msg, chatbot, model, system_prompt, thinking_budget], outputs=[chatbot, msg])

demo.launch()