import gradio as gr
from pipeline import run_with_chain  # Import the updated pipeline function

# Define a function that connects the Gradio interface to the pipeline
def ask_dailywellness(query: str) -> str:
    try:
        # Call the run_with_chain function that processes the query
        response = run_with_chain(query)
        return response
    except Exception as e:
        return f"Error processing your request: {str(e)}"

# Define the Gradio interface
interface = gr.Interface(
    fn=ask_dailywellness,
    inputs=gr.Textbox(lines=2, label="Ask DailyWellnessAI"),
    outputs=gr.Textbox(label="DailyWellnessAI Answer"),
    title="DailyWellnessAI",
    description="Ask about wellness or DailyWellnessAI brand. Out-of-scope queries will be redirected with relevant information."
)

if __name__ == "__main__":
    # Launch the Gradio interface with a server
    interface.launch(server_name="0.0.0.0", server_port=7860, share=True)