app.py

import gradio as gr
import pandas as pd
import os

# Fixed path to Excel file
EXCEL_FILE_PATH = "data.xlsx"

def search_excel(query):
    """
    Search for a query string in all columns of the Excel file
    and return matching rows as a DataFrame
    """
    try:
        # Return empty dataframe if no query
        if not query:
            return pd.DataFrame()
        
        # Check if file exists
        if not os.path.exists(EXCEL_FILE_PATH):
            return pd.DataFrame({"Error": [f"File not found: {EXCEL_FILE_PATH}"]})
            
        # Read Excel file
        df = pd.read_excel(EXCEL_FILE_PATH)
        
        # Convert all columns to string for searching
        df_str = df.astype(str)
        
        # Create a mask for rows where any column contains the query (case-insensitive)
        mask = df_str.apply(lambda x: x.str.contains(query, case=False, na=False)).any(axis=1)
        
        # Filter the dataframe using the mask
        result_df = df[mask]
        
        if len(result_df) == 0:
            return pd.DataFrame({"Results": ["No matches found"]})
        
        return result_df
    
    except Exception as e:
        return pd.DataFrame({"Error": [str(e)]})

# Create Gradio interface
with gr.Blocks() as app:
    gr.Markdown(f"# Excel File Search App")
    
    with gr.Row():
        # Search input - will trigger search on typing
        search_input = gr.Textbox(label="Search Text", placeholder="Start typing to search...")
    
    with gr.Row():
        # Output table
        output_table = gr.Dataframe(label="Search Results")
    
    # Define action when text is typed (real-time search)
    search_input.change(
        fn=search_excel,
        inputs=[search_input],
        outputs=output_table
    )

# Launch the app
if __name__ == "__main__":
    app.launch()