Update space

app.py

@@ -1,169 +1,160 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import pandas as pd
 import requests
 from bs4 import BeautifulSoup
-import pandas as pd
-
-client = InferenceClient("meta-llama/Llama-3.2-3B-Instruct")
 
-data = []  # Global variable to store table data
+# Initialize HF client
+client = InferenceClient("meta-llama/Llama-2-7b-chat-hf")
 
-def respond(message, history, system_message, max_tokens=2048, temperature=0.7, top_p=0.9):
-    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,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
+def respond(message, history, max_tokens=512, temperature=0.7, top_p=0.95):
+    try:
+        # Format messages including history
+        messages = []
+        for user_msg, assistant_msg in history:
+            messages.append({"role": "user", "content": user_msg})
+            messages.append({"role": "assistant", "content": assistant_msg})
+        messages.append({"role": "user", "content": message})
+        
+        # Generate response
+        response = ""
+        for chunk in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            temperature=temperature,
+            top_p=top_p,
+            stream=True,
+        ):
+            if hasattr(chunk.choices[0].delta, 'content'):
+                token = chunk.choices[0].delta.content
+                if token:
+                    response += token
+        return response
+        
+    except Exception as e:
+        return f"Error: {str(e)}"
 
-def extract_table(url):
-    global data
+def extract_schedule(url):
     try:
+        # Fetch and parse webpage
         response = requests.get(url)
         response.raise_for_status()
-        soup = BeautifulSoup(response.text, "html.parser")
-        table = soup.find("table")
+        soup = BeautifulSoup(response.text, 'html.parser')
+        
+        # Find table and extract data
+        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:]):  # Skip header row
-            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 that trigger Gradio events
-        html_rows = ""
-        for row in data:
-            html_rows += f"""
-                <tr>
-                    <td>{row['Date']}</td>
-                    <td>{row['Topic']}</td>
-                    <td><button class="gr-button gr-button-lg" onclick="handle_topic_click({row['Index']})">Prepare</button></td>
-                </tr>
-            """
-        html_table = f"""
-            <table border="1">
-                <tr>
-                    <th>Date</th>
-                    <th>Topic</th>
-                    <th>Action</th>
-                </tr>
-                {html_rows}
-            </table>
-            <script>
-                function handle_topic_click(index) {{
-                    const prepareInput = document.querySelector('#prepareInput textarea');
-                    if (prepareInput) {{
-                        prepareInput.value = index;
-                        prepareInput.dispatchEvent(new Event('input'));
-                        document.querySelector('#prepareSubmit').click();
+            
+        schedule_data = []
+        rows = table.find_all('tr')
+        for row in rows[1:]:
+            cells = row.find_all('td')
+            if len(cells) >= 4:
+                date = cells[0].text.strip()
+                topic = cells[1].text.strip()
+                
+                if date and topic and not topic.startswith('See Canvas'):
+                    schedule_data.append({
+                        'Date': date[:10],
+                        'Topic': topic,
+                        'Action': f"""
+                        <button 
+                            onclick="triggerChatbotPreparation('{topic.replace("'", "")}')" 
+                            class="prepare-btn">
+                            Prepare
+                        </button>
+                        """
+                    })
+
+        df = pd.DataFrame(schedule_data)
+        
+        # Convert to HTML with styling and JavaScript
+        html = f"""
+        <style>
+        table {{ 
+            border-collapse: collapse; 
+            width: 100%;
+            font-size: 12px;
+        }}
+        th, td {{ 
+            border: 1px solid black;
+            padding: 6px;
+            text-align: left;
+            font-family: Arial, sans-serif;
+        }}
+        .prepare-btn {{
+            padding: 4px 8px;
+            font-size: 11px;
+            cursor: pointer;
+        }}
+        </style>
+        <script>
+        function triggerChatbotPreparation(topic) {{
+            // Find all Gradio textareas
+            const textareas = document.querySelectorAll('.gradio-container textarea');
+            
+            // Find the first textarea (assuming it's the input)
+            const textbox = textareas[0];
+            
+            if (textbox) {{
+                // Set the value
+                const preparationMessage = `prepare 5 minutes reading important parts related to ${topic}`;
+                textbox.value = preparationMessage;
+                
+                // Trigger input and change events
+                const inputEvent = new Event('input', {{ bubbles: true }});
+                const changeEvent = new Event('change', {{ bubbles: true }});
+                textbox.dispatchEvent(inputEvent);
+                textbox.dispatchEvent(changeEvent);
+                
+                // Find and click the send button
+                const sendButtons = document.querySelectorAll('.gradio-container button');
+                for (let button of sendButtons) {{
+                    if (button.getAttribute('aria-label') === 'Send') {{
+                        button.click();
+                        break;
                     }}
                 }}
-            </script>
+            }}
+        }}
+        </script>
+        {df.to_html(index=False, escape=False)}
         """
-        return html_table
+        return html
+        
     except Exception as e:
         return f"<p>Error: {str(e)}</p>"
 
-def handle_prepare(index, history):
+def display_schedule(url):
     try:
-        index = int(index)
-        if 0 <= index < len(data):
-            topic = data[index]["Topic"]
-            prompt = f"Prepare a 10-minute reading on what I should know before the class for the topic: {topic}"
-            history = history or []
-            history.append((prompt, None))
-            return history
+        html_table = extract_schedule(url)
+        return html_table  # Already HTML string
     except Exception as e:
-        print(f"Error in handle_prepare: {e}")
-        return history or []
+        return str(e)
 
-def prepare_message(index, history, system_msg):
-    try:
-        index = int(index)
-        if 0 <= index < len(data):
-            topic = data[index]["Topic"]
-            return f"Prepare a 10-minute reading for topic: {topic}", history, system_msg
-    except Exception as e:
-        print(f"Error in prepare_message: {e}")
-        return "", history, system_msg
-
-def user_message(message, history):
-    history = history or []
-    history.append((message, None))
-    return "", history
-
-def clear_chat():
-    return [], []
-
-# Gradio app
 with gr.Blocks() as demo:
     with gr.Row():
+        # Left Column - Schedule
         with gr.Column(scale=1):
-            url_input = gr.Textbox(value="https://id2223kth.github.io/schedule/", label="Table URL")
-            table_output = gr.HTML(label="Extracted Table")
-            extract_btn = gr.Button("Extract Table")
+            url_input = gr.Textbox(
+                value="https://id2223kth.github.io/schedule/",
+                label="Schedule URL"
+            )
+            schedule_output = gr.HTML(label="Extracted Schedule")
+            extract_btn = gr.Button("Extract Schedule")
             
-            # Hidden components for prepare functionality
-            prepare_input = gr.Textbox(visible=False, elem_id="prepareInput")
-            prepare_submit = gr.Button("Prepare Submit", visible=False, elem_id="prepareSubmit")
-
+            extract_btn.click(
+                fn=display_schedule,
+                inputs=[url_input],
+                outputs=[schedule_output]
+            )
+        
+        # Right Column - Chatbot
         with gr.Column(scale=2):
-            chatbot = gr.Chatbot()
-            msg = gr.Textbox(label="Message")
-            system_message = gr.Textbox(
-                value="Student class preparation companion.",
-                label="System message"
+            chatbot = gr.ChatInterface(
+                respond
             )
 
-            with gr.Row():
-                submit = gr.Button("Submit")
-                clear = gr.Button("Clear")
-
-    # Event handlers
-    extract_btn.click(
-        fn=extract_table,
-        inputs=[url_input],
-        outputs=[table_output]
-    )
-
-    submit.click(
-        user_message,
-        inputs=[msg, chatbot],
-        outputs=[msg, chatbot]
-    ).then(
-        respond,
-        inputs=[msg, chatbot, system_message],
-        outputs=[chatbot]
-    )
-
-    # Handle prepare button clicks
-    prepare_submit.click(
-        handle_prepare,
-        inputs=[prepare_input, chatbot],
-        outputs=[chatbot]
-    ).then(
-        respond,
-        inputs=[prepare_input, chatbot, system_message],
-        outputs=[chatbot]
-    )
-
-    clear.click(fn=clear_chat, outputs=[chatbot, msg])
-
 if __name__ == "__main__":
     demo.launch()