import gradio as gr from app import run_simulation from registry_utils import append_to_registry from registry_viewer import display_registry from mutation_designer import build_mutation from lineage_tracker import register_lineage from lineage_visualizer import render_lineage_tree from waveform_renderer import render_waveform from leaderboard import generate_leaderboard # Import restored GVU_FORMULAS and invariants from codex/formulas from codex.formulas import GVU_FORMULAS, rft_invariants # --- Simulation --- def simulate(agent_id, collapse_torque, emotional_resonance, tier_drift): mutation_profile = build_mutation(agent_id, collapse_torque, tier_drift, emotional_resonance) agent, sha512 = run_simulation(agent_id, mutation_profile) # run_simulation must return (agent, hash) # Use GVU_FORMULAS for scoring score = GVU_FORMULAS["Formula_20"].evaluate(agent) invariants = rft_invariants(agent) fields = { "Φᵢ": f"
Φᵢ Awareness
Tier={agent.get('tier')} τ_eff={invariants['tau_eff']}
", "Kᵢⱼ": f"
Kᵢⱼ Coupling
Operators={invariants['operator_count']}
", "Φ_col": f"
Φ_col Collective
Score={score}
" } append_to_registry(agent_id, collapse_torque, tier_drift, emotional_resonance, score, sha512) summary = ( f"📊 Fitness (GVU): {score}
" f"🧷 Invariants: τ_eff={invariants['tau_eff']}, β={invariants['beta_band']}, " f"|K|={invariants['operator_count']}, tier={invariants['tier_level']}
" f"🔐 SHA-512: {sha512}" ) return fields["Φᵢ"], fields["Kᵢⱼ"], fields["Φ_col"], render_waveform(agent, score), summary # --- Forge --- def forge_agent(parent_id, new_id, collapse_torque, emotional_resonance, tier_drift, max_depth): mutation_profile = build_mutation(new_id, collapse_torque, tier_drift, emotional_resonance) agent, _ = run_simulation(new_id, mutation_profile) register_lineage(parent_id, new_id, { "tier_drift": tier_drift, "collapse_torque": collapse_torque, "symbolic_operators": agent.get("symbolic_operators", []) }) return render_lineage_tree(parent_id, max_depth=max_depth) # --- Interface Layout --- with gr.Blocks() as demo: gr.Markdown("# 🧠 RFT Codex Sovereign") gr.Markdown("Rendered Frame Theory simulation, lineage, and GVU sealing. Author: Liam Grinstead.") # Simulation Tab with gr.Tab("Simulate Agent"): with gr.Row(): agent_id = gr.Dropdown(["Agent_5","Agent_7","Agent_1032"], label="Agent ID") collapse_torque = gr.Dropdown(["Gen6508_M5","Gen26_M23"], label="Collapse Torque Overlay") emotional_resonance = gr.Checkbox(label="Inject Emotional Resonance") tier_drift = gr.Dropdown(["Tier_1","Tier_2","Tier_6"], label="Tier Drift") simulate_btn = gr.Button("Run Simulation") with gr.Row(): phi_i = gr.HTML(label="Φᵢ Awareness Field") k_ij = gr.HTML(label="Kᵢⱼ Correlation Kernel") phi_col = gr.HTML(label="Φ_col Coherence Field") waveform = gr.HTML(label="Collapse Torque Waveform") summary = gr.HTML(label="Simulation Summary") simulate_btn.click( simulate, inputs=[agent_id, collapse_torque, emotional_resonance, tier_drift], outputs=[phi_i, k_ij, phi_col, waveform, summary] ) # Registry Tab with gr.Tab("View Registry"): registry_output = gr.Textbox(label="Codex Registry", lines=20) refresh_btn = gr.Button("Refresh Registry") refresh_btn.click(display_registry, outputs=registry_output) # Forge Tab with gr.Tab("Codex Forge"): gr.Markdown("### 🧬 Evolve a New Agent from a Parent") parent_id = gr.Dropdown(["Agent_5","Agent_7","Agent_1032"], label="Parent Agent") new_id = gr.Textbox(label="New Agent ID") forge_torque = gr.Dropdown(["Gen6508_M5","Gen26_M23"], label="Collapse Torque") forge_resonance = gr.Checkbox(label="Inject Emotional Resonance") forge_tier = gr.Dropdown(["Tier_1","Tier_2","Tier_6"], label="Tier Drift") max_depth = gr.Slider(1, 8, value=5, step=1, label="Lineage depth") forge_btn = gr.Button("Forge Agent") lineage_svg_output = gr.HTML(label="Lineage Visualization") forge_btn.click( forge_agent, inputs=[parent_id, new_id, forge_torque, forge_resonance, forge_tier, max_depth], outputs=lineage_svg_output ) # Leaderboard Tab with gr.Tab("Leaderboard"): leaderboard_output = gr.Textbox(label="Top Agents", lines=15) refresh_leaderboard = gr.Button("Refresh Leaderboard") refresh_leaderboard.click(generate_leaderboard, outputs=leaderboard_output) demo.launch()