app.py

import gradio as gr
import numpy as np
import time
from system import DrMoagiArchitecture
from graph_cluster import GraphMoagiCluster
from trainer import SelfTrainer
from policy import PolicyController
from visualization import plot_knowledge

system = DrMoagiArchitecture(dim=16)
cluster = GraphMoagiCluster(nodes=6, dim=16)
trainer = SelfTrainer(system)
policy_controller = PolicyController(system)


def step_system(steps):
    for _ in range(int(steps)):
        Psi = np.random.randn(system.n)
        system.bounded_update(Psi)

    return diagnostics()


def diagnostics():
    return {
        "Xi_norm": float(np.linalg.norm(system.Xi)),
        "Omega_norm": float(np.linalg.norm(system.Omega)),
        "Knowledge_Field_K": float(system.archive[-1]) if system.archive else 0.0,
        "Lyapunov_Energy": float(system.lyapunov_energy()),
        "Entropy": float(system.entropy()),
        "Stability_Zone": system.stability_zone(),
        "Ticks": system.tick_counter,
    }


def reset_system(seed):
    global system, trainer, policy_controller
    system = DrMoagiArchitecture(dim=16, seed=int(seed))
    trainer = SelfTrainer(system)
    policy_controller = PolicyController(system)
    return {"status": "reset complete"}


def autonomous_loop():
    while system.running:
        Psi = np.random.randn(system.n)
        system.bounded_update(Psi)
        time.sleep(0.1)


with gr.Blocks(title="Dr Moagi Research Engine") as demo:
    gr.Markdown("## Dr Moagi Distributed Research Engine")

    steps_input = gr.Number(value=5, label="Steps")
    seed_input = gr.Number(value=42, label="Seed")

    run_btn = gr.Button("Run")
    reset_btn = gr.Button("Reset")
    start_btn = gr.Button("Start Autonomous")
    stop_btn = gr.Button("Stop Autonomous")
    cluster_btn = gr.Button("Cluster Step")
    train_btn = gr.Button("Self-Train")
    policy_btn = gr.Button("Policy Step")
    plot_btn = gr.Button("Plot Knowledge")

    output_json = gr.JSON()
    plot_output = gr.Plot()

    run_btn.click(step_system, inputs=steps_input, outputs=output_json)
    reset_btn.click(reset_system, inputs=seed_input, outputs=output_json)

    start_btn.click(lambda: system.start(), outputs=[])
    stop_btn.click(lambda: system.stop(), outputs=[])

    cluster_btn.click(lambda: cluster.graph_step(), outputs=[])
    train_btn.click(lambda: trainer.train_step(), outputs=[])
    policy_btn.click(lambda: policy_controller.policy_step(), outputs=[])

    plot_btn.click(lambda: plot_knowledge(system.archive), outputs=plot_output)

if __name__ == "__main__":
    demo.launch()