Finalized Jupyterlab for the sprint

app/callbacks.py

+import os
+from datetime import datetime
+
+from dash import (
+    html, 
+    Dash
+)
+from dash.dependencies import (
+    Input, 
+    Output, 
+    State
+)
+
+from llm_utils.client import ChatGPT, get_openai_client
+
+
+def format_chat_messages(chat_history):
+    chat_messages = []
+    for message in chat_history:
+        chat_messages.append(html.Div([
+            html.P(f'{message["sender"]}: {message["message"]}'),
+            html.P(f'Sent at: {message["timestamp"]}')
+        ]))
+    return chat_messages
+
+
+def register_callbacks(app: Dash):
+    model="gpt4"
+    client = get_openai_client(
+        model=model,
+        config_path=os.environ.get("CONFIG_PATH")
+    )
+    chat_gpt = ChatGPT(
+        client=client,
+        model="gpt4"
+    )
+    
+    @app.callback(
+        [Output('chat-container', 'children'),
+        Output('chat-history', 'data')],
+        [Input('send-button', 'n_clicks')],
+        [State('user-input', 'value'),
+        State('chat-history', 'data')]
+    )
+    def update_chat(n_clicks, input_value, chat_history):
+        if chat_history is None:
+            chat_history = []
+        
+        if n_clicks > 0 and input_value:
+            chat_history.append({
+                'sender': 'User',
+                'message': input_value,
+                'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            })
+            
+            response = chat_gpt.chat_with_gpt(input_value)
+            
+            # Add response to chat history
+            chat_history.append({
+                'sender': 'Language Model',
+                'message': response,
+                'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            })
+        
+        return format_chat_messages(chat_history), chat_history