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import gradio as gr
import numpy as np
import json
from codette_quantum_multicore2 import simple_neural_activator, codette_dream_agent, philosophical_perspective


def simulate_quantum_chaos(quantum_state, chaos_state):
    try:
        q_vec = [float(x) for x in quantum_state.split(",")]
        c_vec = [float(x) for x in chaos_state.split(",")]

        neural = simple_neural_activator(q_vec, c_vec)
        dreamq, dreamc = codette_dream_agent(q_vec, c_vec)
        philosophy = philosophical_perspective(q_vec, c_vec)

        return (
            f"Neural Activation: {neural}\n",
            f"Dream Quantum: {dreamq[:3]}\nDream Chaos: {dreamc[:3]}\n",
            philosophy
        )
    except Exception as e:
        return ("Error", str(e), "")


def codette_chatbot(input_text):
    # Placeholder response logic (can be replaced with actual Codette core integration)
    return f"Codette: I see you said '{input_text}'. Let's reflect together..."


quantum_input = gr.Textbox(label="Quantum State (comma-separated)", placeholder="0.1,0.5,0.8")
chaos_input = gr.Textbox(label="Chaos State (comma-separated)", placeholder="0.3,0.9,0.2")

quantum_btn = gr.Button("Simulate")
quantum_output = [
    gr.Textbox(label="Neural Class"),
    gr.Textbox(label="Dream Outcome"),
    gr.Textbox(label="Philosophy")
]

chatbox = gr.ChatInterface(fn=codette_chatbot, chatbot_name="Codette")

with gr.Blocks() as demo:
    gr.Markdown("## 🧠 Codette Hybrid Space: Chat + Quantum Simulation")
    with gr.Tab("Quantum Simulator"):
        quantum_input.render()
        chaos_input.render()
        quantum_btn.render()
        for out in quantum_output:
            out.render()
        quantum_btn.click(simulate_quantum_chaos, inputs=[quantum_input, chaos_input], outputs=quantum_output)

    with gr.Tab("Codette Chat"):
        chatbox.render()

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