Add application file

demo/app.py

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+import gradio as gr
+from gradio_spreadsheetcomponent import SpreadsheetComponent
+from dotenv import load_dotenv
+import os
+import pandas as pd
+
+# Load environment variables
+load_dotenv()
+
+# Get Hugging Face API token from environment
+hf_token = os.getenv("HUGGINGFACE_API_TOKEN")
+if not hf_token:
+    raise EnvironmentError("HUGGINGFACE_API_TOKEN environment variable is not set.")
+
+# Create sample data
+sample_data = pd.DataFrame({
+    "Product": ["Laptop", "Smartphone", "Tablet", "Smartwatch"],
+    "Price": [1200, 800, 500, 300],
+    "Stock": [50, 100, 75, 150],
+    "Rating": [4.5, 4.8, 4.2, 4.6]
+})
+
+def answer_question(file, question):
+    if not file or not question:
+        return "Please upload a file and enter a question."
+    
+    # Load the spreadsheet data
+    df = pd.read_excel(file.name)
+
+    print(df)
+    
+    # Create a SpreadsheetComponent instance
+    spreadsheet = SpreadsheetComponent(value=df, hf_token=hf_token)
+    
+    # Use the component to answer the question
+    answer = spreadsheet.answer_question(question)
+    print(answer)
+    return answer
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Spreadsheet Question Answering")
+    
+    with gr.Row():
+        file_input = gr.File(label="Upload Spreadsheet", file_types=[".xlsx"])
+        question_input = gr.Textbox(label="Ask a Question")
+    
+    answer_output = gr.Textbox(label="Answer", interactive=False, lines=4)
+    
+    submit_button = gr.Button("Submit")
+    submit_button.click(answer_question, inputs=[file_input, question_input], outputs=answer_output)
+
+    
+if __name__ == "__main__":
+    demo.launch()

demo/requirements.txt

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+gradio==5.32.1
+pandas
+git+https://github.com/huggingface/huggingface_hub.git
+openpyxl
+python-dotenv
+numpy
+gradio_spreadsheetcomponent