Update space

app.py

@@ -4,32 +4,20 @@ 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
-"""
 client = InferenceClient("meta-llama/Llama-3.2-3B-Instruct")
 
+# Global data store for the table
+data = []
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
+def respond(message, history, system_message, max_tokens, temperature, top_p):
     messages = [{"role": "system", "content": system_message}]
-
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
-
     messages.append({"role": "user", "content": message})
-
     response = ""
-
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -38,7 +26,6 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
@@ -48,31 +35,26 @@ def extract_table(url):
     try:
         response = requests.get(url)
         response.raise_for_status()
-        soup = BeautifulSoup(response.text, 'html.parser')
-        table = soup.find('table')
+        soup = BeautifulSoup(response.text, "html.parser")
+        table = soup.find("table")
         if not table:
             return "<p>No table found on page</p>"
-        
+
         # Extract data
         data = []
-        rows = table.find_all('tr')
-        for i, row in enumerate(rows[1:]):
-            cells = row.find_all('td')
+        rows = table.find_all("tr")
+        for i, row in enumerate(rows[1:]):  # Skip header
+            cells = row.find_all("td")
             if len(cells) >= 2:
-                data.append({
-                    'Index': i,
-                    'Date': cells[0].text.strip()[:10],
-                    'Topic': cells[1].text.strip(),
-                })
-        
-        # Generate HTML table with buttons
+                data.append({"Index": i, "Date": cells[0].text.strip()[:10], "Topic": cells[1].text.strip()})
+
+        # Generate HTML table without buttons
         html_rows = ""
         for row in data:
             html_rows += f"""
                 <tr>
                     <td>{row['Date']}</td>
                     <td>{row['Topic']}</td>
-                    <td><button onclick="handlePrepare({row['Index']})">Prepare</button></td>
                 </tr>
             """
         html_table = f"""
@@ -80,7 +62,6 @@ def extract_table(url):
                 <tr>
                     <th>Date</th>
                     <th>Topic</th>
-                    <th>Action</th>
                 </tr>
                 {html_rows}
             </table>
@@ -90,33 +71,24 @@ def extract_table(url):
         return f"<p>Error: {str(e)}</p>"
 
 
-
-def display_table(url):
-    return extract_table(url)
-
 def handle_prepare(index):
     topic = data[index]["Topic"]
     return f"Prepare a 10-minute reading on what I should know before the class for the topic: {topic}"
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+
+# Gradio App
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column(scale=1):
             url_input = gr.Textbox(
                 value="https://id2223kth.github.io/schedule/",
-                label="Table URL"
+                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]
-            )
-        
+
+            extract_btn.click(fn=extract_table, inputs=[url_input], outputs=[table_output])
+
         with gr.Column(scale=2):
             chatbot = gr.ChatInterface(
                 respond,
@@ -124,33 +96,24 @@ with gr.Blocks() as demo:
                     gr.Textbox(value="Student class preparation companion.", label="System message"),
                 ],
             )
-            
-            # Dynamically generate buttons for "Prepare" actions
-            prepare_buttons = gr.Column(visible=False)
 
-            def create_prepare_buttons():
-                # Create individual buttons for each topic
+            # Container for dynamically generated buttons
+            buttons_container = gr.Column(visible=True)
+
+            def create_buttons():
                 components = []
                 for i, row in enumerate(data):
                     btn = gr.Button(f"Prepare: {row['Topic']}")
                     btn.click(
                         fn=handle_prepare,
-                        inputs=[gr.State(i)],  # Pass the index of the row
-                        outputs=[],
-                    ).then(
-                        fn=lambda message: ([message],),  # Feed to chatbot
-                        inputs=[],
+                        inputs=[gr.State(i)],
                         outputs=[chatbot],
                     )
                     components.append(btn)
                 return components
 
-            extract_btn.click(
-                fn=create_prepare_buttons,
-                inputs=[],
-                outputs=[prepare_buttons],
-            )
-
+            # Create buttons when table is extracted
+            extract_btn.click(fn=create_buttons, inputs=[], outputs=[buttons_container])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()