app.py

import gradio as gr

# Assuming `my_gpt_model` is your custom model's function that takes a date range and a ticker and returns a string.
def predict_with_gpt(start_date, end_date, ticker):
    # Your model would use the start_date, end_date, and ticker to generate a prediction.
    # For this example, we'll just return a dummy string.
    prediction = ", ".join([start_date, end_date, ticker])
    return prediction

# Create the Gradio app
def create_gradio_app():
    with gr.Blocks() as app:
        gr.Markdown("Enter a range of dates and a stock ticker to get predictions from the GPT model.")
        with gr.Row():
            start_date = gr.Date(label="Start Date")
            end_date = gr.Date(label="End Date")
        ticker = gr.Textbox(label="Ticker")
        output = gr.Textbox(label="GPT Model Output")

        # When the button is clicked, the `predict_with_gpt` function is called
        gr.Button("Predict").click(
            predict_with_gpt, 
            inputs=[start_date, end_date, ticker], 
            outputs=output
        )

    return app

app = create_gradio_app()
app.launch()