Update README.md

README.md

@@ -1,112 +1,113 @@
----
-tags: [gradio-custom-component, SimpleTextbox, gradio-spreadsheet-custom-component]
-title: gradio_spreadsheetcomponent
-short_description: This component answers questions about spreadsheets.
-colorFrom: blue
-colorTo: yellow
-sdk: gradio
-pinned: false
-app_file: space.py
----
-
-# `gradio_spreadsheetcomponent`
-<a href="https://pypi.org/project/gradio_spreadsheetcomponent/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/gradio_spreadsheetcomponent"></a>  
-
-This component is used to answer questions about spreadsheets.
-
-## Installation
-
-```bash
-pip install gradio_spreadsheetcomponent
-```
-
-## Usage
-
-```python
-import gradio as gr
-from gradio_spreadsheetcomponent import SpreadsheetComponent
-from dotenv import load_dotenv
-import os
-import pandas as pd
-
-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)
-    
-    # Create a SpreadsheetComponent instance
-    spreadsheet = SpreadsheetComponent(value=df)
-    
-    # Use the component to answer the question
-    return spreadsheet.answer_question(question)
-
-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()
-
-```
-
-## `SpreadsheetComponent`
-
-### Initialization
-
-<table>
-<thead>
-<tr>
-<th align="left">name</th>
-<th align="left" style="width: 25%;">type</th>
-<th align="left">default</th>
-<th align="left">description</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td align="left"><code>value</code></td>
-<td align="left" style="width: 25%;">
-
-```python
-pandas.core.frame.DataFrame | list | dict | None
-```
-
-</td>
-<td align="left"><code>None</code></td>
-<td align="left">Default value to show in spreadsheet. Can be a pandas DataFrame, list of lists, or dictionary</td>
-</tr>
-</tbody></table>
-
-
-
-
-### User function
-
-The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).
-
-- When used as an Input, the component only impacts the input signature of the user function.
-- When used as an output, the component only impacts the return signature of the user function.
-
-The code snippet below is accurate in cases where the component is used as both an input and an output.
-
-- **As output:** Is passed, the preprocessed input data sent to the user's function in the backend.
-
-
- ```python
- def predict(
-     value: typing.Any
- ) -> Unknown:
-     return value
- ```
- 
+---
+tags: [gradio-custom-component, custom-component-track, gradio-spreadsheet-custom-component]
+title: gradio_spreadsheetcomponent
+short_description: This component answers questions about spreadsheets.
+colorFrom: blue
+colorTo: yellow
+sdk: gradio
+pinned: false
+app_file: space.py
+app_link: https://huggingface.co/spaces/Mustafiz996/gradio_spreadsheetcomponent
+---
+
+# `gradio_spreadsheetcomponent`
+<a href="https://pypi.org/project/gradio_spreadsheetcomponent/" target="_blank"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/gradio_spreadsheetcomponent"></a>  
+
+This component is used to answer questions about spreadsheets.
+
+## Installation
+
+```bash
+pip install gradio_spreadsheetcomponent
+```
+
+## Usage
+
+```python
+import gradio as gr
+from gradio_spreadsheetcomponent import SpreadsheetComponent
+from dotenv import load_dotenv
+import os
+import pandas as pd
+
+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)
+    
+    # Create a SpreadsheetComponent instance
+    spreadsheet = SpreadsheetComponent(value=df)
+    
+    # Use the component to answer the question
+    return spreadsheet.answer_question(question)
+
+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()
+
+```
+
+## `SpreadsheetComponent`
+
+### Initialization
+
+<table>
+<thead>
+<tr>
+<th align="left">name</th>
+<th align="left" style="width: 25%;">type</th>
+<th align="left">default</th>
+<th align="left">description</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td align="left"><code>value</code></td>
+<td align="left" style="width: 25%;">
+
+```python
+pandas.core.frame.DataFrame | list | dict | None
+```
+
+</td>
+<td align="left"><code>None</code></td>
+<td align="left">Default value to show in spreadsheet. Can be a pandas DataFrame, list of lists, or dictionary</td>
+</tr>
+</tbody></table>
+
+
+
+
+### User function
+
+The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).
+
+- When used as an Input, the component only impacts the input signature of the user function.
+- When used as an output, the component only impacts the return signature of the user function.
+
+The code snippet below is accurate in cases where the component is used as both an input and an output.
+
+- **As output:** Is passed, the preprocessed input data sent to the user's function in the backend.
+
+
+ ```python
+ def predict(
+     value: typing.Any
+ ) -> Unknown:
+     return value
+ ```
+