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."
)

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"
        f"User Input: {message}"
    )

    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
        history.append({"role": "user", "content": message})
        history.append({"role": "assistant", "content": response})

        return response, history

    except Exception as e:
        return f"Error: {e}", history

# 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()