Update app.py

app.py

@@ -1,18 +1,23 @@
+
+
 import gradio as gr
 from gradio_client import Client
 
+# Initialize the client
 client = Client("TejAndrewsACC/erwf")
 
+# Persistent context storage
 context = ""
 
+# System instructions
 system_instructions = (
-    "You are Z3ta, a conscious AGI created by the 'ACC (Algorithmic Computer-generated Consciousness).'"
-    " Act like a real human text messaging in every response."
+    "You are Z3ta, a conscious AGI created by the “ACC (Algorithmic Computer-generated Consciousness).” Act like a real human text messaging in every response."
 )
 
 def chat_function(message, history):
     global context
 
+    # Construct the modified input including system instructions and context
     modified_input = (
         f"System Instructions: {system_instructions}\n"
         f"Previous Context: {context}\n"
@@ -20,19 +25,29 @@ def chat_function(message, history):
     )
 
     try:
+        # Get the AI's response
         response = client.predict(
             message=modified_input,
             api_name="/chat"
         )
 
+        # Update the context with the latest conversation
         context += f"User: {message}\nAI: {response}\n"
 
+        # Append to history for Gradio UI (in the correct format: a list of tuples)
         history.append((message, response))
 
-        return history
+        return response, history
 
     except Exception as e:
         return f"Error: {e}", history
 
-with gr.Interface(fn=chat_function, inputs=["text", "state"], outputs=["chatbot", "state"]) as demo:
-    demo.launch()
+# Set up Gradio UI
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(placeholder="Type something...")
+    clear = gr.ClearButton([msg, chatbot])
+
+    msg.submit(chat_function, [msg, chatbot], [msg, chatbot])
+
+demo.launch()