Update app.py

app.py

@@ -1,4 +1,3 @@
-import gradio as gr
 from gradio_client import Client
 
 # Initialize the client
@@ -9,19 +8,17 @@ 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."
 )
 
-# Function to handle the chatbot interaction
-def chat(user_input, history=None):
-    global context
-    if history is None:
-        history = []
-
+while True:
+    # Get user input
+    user_input = input("User: ")
+    
+    # If the user types "exit," end the chat session
     if user_input.lower() == "exit":
-        # Append exit message in tuple format
-        history.append(["assistant", "Ending session. Goodbye!"])
-        return history
+        print("Ending session. Goodbye!")
+        break
 
     # Construct the modified input including system instructions and context
     modified_input = (
@@ -31,27 +28,13 @@ def chat(user_input, history=None):
     )
     
     # Get the AI's response
-    ai_response = client.predict(
+    result = client.predict(
         message=modified_input,
         api_name="/chat"
     )
     
-    # Update the context with the latest conversation
-    context += f"User: {user_input}\nAI: {ai_response}\n"
-    
-    # Append the conversation to the history in the tuple format
-    history.append(["user", user_input])
-    history.append(["assistant", ai_response])
+    # Print the result
+    print(f"Z3ta: {result}")
     
-    return history
-
-# Gradio interface using the Chatbot template
-interface = gr.Interface(
-    fn=chat,
-    inputs=["text", "state"],
-    outputs=["chatbot", "state"],
-    live=True
-)
-
-# Launch the chatbot
-interface.launch()
+    # Update the context with the latest conversation
+    context += f"User: {user_input}\nAI: {result}\n”