Update space

app.py

@@ -1,51 +1,121 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import pandas as pd
+import requests
+from bs4 import BeautifulSoup
 
-client = InferenceClient("meta-llama/Llama-3.2-3B-Instruct")
+# Initialize HF client
+client = InferenceClient("meta-llama/Llama-2-7b-chat-hf")
 
-def respond(message, history: list[tuple[str, str]], 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,
-        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,  # Changed back to 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_schedule(url):
+    try:
+        # Fetch and parse webpage
+        response = requests.get(url)
+        response.raise_for_status()
+        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>"
+            
+        schedule_data = []
+        rows = table.find_all('tr')
+        
+        for row in rows[1:]:  # Skip header row
+            cells = row.find_all('td')
+            if len(cells) >= 4:  # Only process rows with enough columns
+                date = cells[0].text.strip()
+                topic = cells[1].text.strip()
+                
+                # Skip empty rows and non-lecture entries
+                if date and topic and not topic.startswith('See Canvas'):
+                    schedule_data.append({
+                        'Date': date[:10],  # Only YYYY-MM-DD
+                        'Topic': topic
+                    })
+        
+        # Create DataFrame
+        df = pd.DataFrame(schedule_data)
+        
+        # Convert to HTML with styling
+        html = f"""
+        <style>
+        table {{ border-collapse: collapse; width: 100%; }}
+        th, td {{ 
+            border: 1px solid black;
+            padding: 8px;
+            text-align: left;
+        }}
+        th {{ background-color: #f2f2f2; }}
+        </style>
+        {df.to_html(index=False)}
+        """
+        return html
+        
+    except Exception as e:
+        return f"<p>Error: {str(e)}</p>"
 
-def upload_schedule(files):
-    # Process the uploaded files here
-    return f"Uploaded {len(files)} file(s)"
+def display_schedule(url):
+    try:
+        html_table = extract_schedule(url)
+        return html_table  # Already HTML string
+    except Exception as e:
+        return str(e)
 
 with gr.Blocks() as demo:
     with gr.Row():
+        # Left Column - Schedule
         with gr.Column(scale=1):
-            gr.File(label="Upload Schedule", file_count="multiple", type="file", fn=upload_schedule)
-        with gr.Column(scale=3):
-            gr.ChatInterface(
+            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")
+            
+            extract_btn.click(
+                fn=display_schedule,
+                inputs=[url_input],
+                outputs=[schedule_output]
+            )
+        
+        # Right Column - Chatbot
+        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)",
-                    ),
-                ],
+                #additional_inputs=[
+                #    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__":