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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) | |