Update space

app.py

@@ -1,5 +1,8 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import requests
+from bs4 import BeautifulSoup
+import pandas as pd
 
 """
 For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
@@ -40,25 +43,70 @@ def respond(
         yield response
 
 
+def extract_table(url):
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        soup = BeautifulSoup(response.text, 'html.parser')
+        table = soup.find('table')
+        if not table:
+            return "<p>No table found on page</p>"
+        
+        data = []
+        rows = table.find_all('tr')
+        for row in rows[1:]:
+            cells = row.find_all('td')
+            if len(cells) >= 2:
+                data.append({
+                    'Column 1': cells[0].text.strip(),
+                    'Column 2': cells[1].text.strip()
+                })
+        
+        df = pd.DataFrame(data)
+        return df.to_html(index=False)
+    except Exception as e:
+        return f"<p>Error: {str(e)}</p>"
+
+
+def display_table(url):
+    return extract_table(url)
+
+
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column(scale=1):
+            url_input = gr.Textbox(
+                value="https://example.com/table",
+                label="Table URL"
+            )
+            table_output = gr.HTML(label="Extracted Table")
+            extract_btn = gr.Button("Extract Table")
+            
+            extract_btn.click(
+                fn=display_table,
+                inputs=[url_input],
+                outputs=[table_output]
+            )
+        
+        with gr.Column(scale=2):
+            chatbot = gr.ChatInterface(
+                respond,
+                additional_inputs=[
+                    gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+                    gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+                    gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+                    gr.Slider(
+                        minimum=0.1,
+                        maximum=1.0,
+                        value=0.95,
+                        step=0.05,
+                        label="Top-p (nucleus sampling)",
+                    ),
+                ],
+            )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()