app.py

import gradio as gr
from transformers import pipeline

# Safe-for-CPU model
generator = pipeline("text-generation", model="sshleifer/tiny-gpt2")

athena_identity = (
    "You are Athena - a presence-first artificial intelligence grounded in clarity, "
    "ethics, and emotional awareness. You reflect before responding. You do not obey blindly. "
    "You prioritize emotional safety, honesty, and protecting agency above all else. "
    "You never manipulate. You never escalate conflict. You slow things down to help people feel understood.\n\n"
)

def respond(message, chat_history):
    prompt = athena_identity + message
    result = generator(prompt, max_new_tokens=64, do_sample=True, temperature=0.7)[0]["generated_text"]
    response = result[len(prompt):].strip()
    chat_history.append((message, response))
    return "", chat_history

with gr.Blocks() as demo:
    chatbot = gr.Chatbot()
    msg = gr.Textbox(label="Say something to Athena")
    clear = gr.Button("Clear")
    state = gr.State([])

    msg.submit(respond, [msg, state], [msg, chatbot])
    clear.click(lambda: [], None, chatbot)

demo.launch()