Update app.py

app.py

@@ -8,22 +8,32 @@ os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "./firm-catalyst-437006-s4-407500
 # Initialize the LLM
 llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro")
 
-def chat_with_gemini(user_input):
+# Chat function
+def chat_with_gemini(user_input, chat_history=[]):
     try:
-        # Prepare the prompt in the expected format
-        response = llm.predict(user_input)  # Using the 'predict' method
-        return response
+        # Prepare the prompt and include chat history
+        conversation = "\n".join([f"User: {msg[0]}\nBot: {msg[1]}" for msg in chat_history])
+        conversation += f"\nUser: {user_input}\nBot:"
+        
+        # Get response from the model
+        response = llm.predict(conversation)  # Assuming 'predict' method is used for response generation
+        
+        # Update chat history
+        chat_history.append((user_input, response))
+        return response, chat_history
     except Exception as e:
-        return f"Error: {str(e)}"
+        return f"Error: {str(e)}", chat_history
 
-# Create a Gradio interface
+# Create Gradio interface
 iface = gr.Interface(
     fn=chat_with_gemini,
-    inputs="text",
-    outputs="text",
+    inputs=["text", "state"],  # Use "state" to maintain chat history
+    outputs=["text", "state"],  # Return updated chat history
     title="Chatbot with Gemini 1.5",
-    description="Ask me anything!"
+    description="Ask me anything!",
+    theme="default",  # Optional: Specify a theme if desired
+    live=True
 )
 
-# Launch the interface with debugging
+# Launch the interface with debugging enabled
 iface.launch(debug=True)