app.py

import gradio as gr

gr.load("models/Qwen/Qwen2.5-Coder-32B-Instruct").launch()

# Define the custom function with a system prompt
def chat_with_system_prompt(user_input):
    # Example of a system prompt
    system_prompt = "You are a helpful AI specialized in code-related tasks."
    response = f"{system_prompt}\n\nUser: {user_input}\n\nAI:"
    # Here, you would call your model's inference API with the full prompt
    # For example:
    # response = model_inference(f"{system_prompt}\nUser: {user_input}")
    return response  # Placeholder for now

# Build the Gradio interface
with gr.Blocks() as demo:
    with gr.Row():
        user_input = gr.Textbox(label="Your Input", placeholder="Ask something...")
    with gr.Row():
        output = gr.Textbox(label="AI Response", lines=5, interactive=False)
    user_input.submit(chat_with_system_prompt, inputs=user_input, outputs=output)

# Launch the app
demo.launch()