Update app.py

app.py

@@ -6,14 +6,12 @@ from langchain_google_genai.chat_models import ChatGoogleGenerativeAI
 os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./firm-catalyst-437006-s4-407500537db5.json"
 
 # Initialize the language model with required parameters
-# Replace 'your-model-name' with the actual model you intend to use
 llm = ChatGoogleGenerativeAI(model='gemini-1.5-pro')  
 
 def chat_with_gemini(message, chat_history):
-    # Placeholder function to simulate bot response
-    bot_response = "You said: " + message
-    chat_history.append({"role": "user", "content": message})
-    chat_history.append({"role": "bot", "content": bot_response})
+    # Generate a response using the language model
+    bot_response = llm.predict(message)  # Get the bot's response from the model
+    chat_history.append((message, bot_response))  # Append the user and bot messages as a tuple
     return chat_history, chat_history
 
 # Create a Gradio interface
@@ -21,7 +19,7 @@ with gr.Blocks() as iface:
     gr.Markdown("# Ken Chatbot")
     gr.Markdown("Ask me anything!")
 
-    chatbot = gr.Chatbot(type='messages', elem_id="chatbot")  # Initialize the chatbot with type='messages' and an element ID for styling
+    chatbot = gr.Chatbot(elem_id="chatbot")  # Initialize the chatbot with an element ID for styling
     msg = gr.Textbox(label="Type your message here...", placeholder="Enter your message and press enter to send your message...")
     state = gr.State([])  # Store chat history
 
@@ -52,4 +50,4 @@ with gr.Blocks() as iface:
     """)
 
 # Launch the interface with debugging enabled
-iface.launch(debug=True)
+iface.launch(debug=True)