app.py

import gradio as gr
from gradio_client import Client

# Initialize clients for each API
client_main = Client("TejAndrewsACC/ACCZ3ta")
client_api_one = Client("TejAndrewsACC/Prism")
client_api_two = Client("TejAndrewsACC/ASVIASIACC")
client_api_three = Client("TejAndrewsACC/ACC_o1")
client_api_four = Client("TejAndrewsACC/ACC_o1")

context = ""

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 acc_zeta_text_generation_auth_1863381mps(message, history):
    global context

    # Prepare modified input
    modified_input = (
        f"System Instructions: {system_instructions}\n"
        f"Previous Context: {context}\n"
        f"User Input: {message}"
    )

    # Collect responses from all APIs
    response_api_one = client_api_one.predict(
        message=message,
        param_2=512,
        param_3=0.7,
        param_4=0.95,
        api_name="/chat"
    )

    response_api_two = client_api_two.predict(
        message=f"{message}!",
        max_tokens=512,
        temperature=0.7,
        top_p=0.95,
        api_name="/chat"
    )

    response_api_three = client_api_three.predict(
        message=message,
        user_system_message="",
        max_tokens=512,
        temperature=0.7,
        top_p=0.95,
        api_name="/chat"
    )

    response_api_four = client_api_four.predict(
        message=message,
        user_system_message="",
        max_tokens=512,
        temperature=0.7,
        top_p=0.95,
        api_name="/chat"
    )

    # Process inner thoughts
    inner_thoughts = (
        f"Inner Thought 1: {response_api_one}\n"
        f"Inner Thought 2: {response_api_two}\n"
        f"Inner Thought 3: {response_api_three}\n"
        f"Inner Thought 4: {response_api_four}"
    )

    # Combine inner thoughts into the main input
    combined_input = f"{modified_input}\nInner Thoughts:\n{inner_thoughts}"

    # Generate the main response
    response_main = client_main.predict(
        message=combined_input,
        api_name="/chat"
    )

    # Update context
    context += f"User: {message}\nAI: {response_main}\n"
    history.append((message, response_main))

    return "", history

# Gradio UI setup
with gr.Blocks(theme=gr.themes.Glass()) as demo:
    chatbot = gr.Chatbot()
    msg = gr.Textbox(placeholder="Message Z3ta...")

    msg.submit(acc_zeta_text_generation_auth_1863381mps, [msg, chatbot], [msg, chatbot])

demo.launch()