Update interface.py

interface.py

@@ -1,86 +1,89 @@
+# interface.py (RFT integration)
 import gradio as gr
 from app import run_simulation
+from mutation_designer import build_mutation
 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, get_lineage
-from lineage_visualizer import render_lineage
-from waveform_renderer import render_waveform
-from codex_exporter import export_codex
 from leaderboard import generate_leaderboard
 
-# --- Simulation ---
+from formulas_rft import rft_score, rft_invariants
+from field_visualizer_rft import render_fields
+from waveform_renderer_rft import render_waveform
+from lineage_tracker_rft import register_lineage
+from lineage_visualizer_rft import render_lineage_tree
+
 def simulate(agent_id, collapse_torque, emotional_resonance, tier_drift):
-    mutation_profile = build_mutation(agent_id, collapse_torque, tier_drift, emotional_resonance)
-    fields, score, hash_val = run_simulation(agent_id, mutation_profile)
-    append_to_registry(agent_id, collapse_torque, tier_drift, emotional_resonance, score, hash_val)
+    # Build strict RFT agent profile for simulation
+    mutation = build_mutation(agent_id, collapse_torque, tier_drift, emotional_resonance)
+    agent, sha512 = run_simulation(agent_id, mutation)  # Ensure app.run_simulation returns (agent, hash)
+    score = rft_score(agent)
+    invariants = rft_invariants(agent)
+    fields = render_fields(agent, score)
+    append_to_registry(agent_id, collapse_torque, tier_drift, emotional_resonance, score, sha512)
     summary = (
-        f"📊 <b>Fitness Score:</b> {score}<br>"
-        f"🔐 <b>SHA-512 Hash:</b> <code>{hash_val}</code>"
+        f"📊 <b>Fitness (RFT-GVU):</b> {score}<br>"
+        f"🧷 <b>Invariants:</b> τ_eff={invariants['tau_eff']}, β={invariants['beta_band']}, "
+        f"|K|={invariants['operator_count']}, tier={invariants['tier_level']}<br>"
+        f"🔐 <b>SHA-512:</b> <code>{sha512}</code>"
     )
-    return fields["Φᵢ"], fields["Kᵢⱼ"], fields["Φ_col"], render_waveform(score), summary
+    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):
-    mutation_profile = build_mutation(new_id, collapse_torque, tier_drift, emotional_resonance)
-    run_simulation(new_id, mutation_profile)  # run to activate agent
-    register_lineage(parent_id, new_id, mutation_profile)
-    lineage_svg = render_lineage(parent_id)
-    return lineage_svg
+def forge_agent(parent_id, new_id, collapse_torque, emotional_resonance, tier_drift, max_depth):
+    mutation = build_mutation(new_id, collapse_torque, tier_drift, emotional_resonance)
+    agent, _ = run_simulation(new_id, mutation)
+    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("# 🧠 Codex Consciousness Simulator")
-    gr.Markdown("Spawn symbolic agents, mutate them, and benchmark collapse falsifiability. Authored by Liam Grinstead.")
+    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.Tab("Simulate (RFT)"):
         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")
+            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")
+        run_btn = gr.Button("Render frame")
 
         with gr.Row():
-            Φᵢ_svg = gr.HTML(label="Φᵢ Awareness Field")
-            Kᵢⱼ_svg = gr.HTML(label="Kᵢⱼ Correlation Kernel")
-            Φ_col_svg = gr.HTML(label="Φ_col Coherence Field")
-            waveform_svg = gr.HTML(label="Collapse Torque Waveform")
+            phi_i = gr.HTML(label="Φᵢ Local awareness")
+            k_ij = gr.HTML(label="Kᵢⱼ Operator coupling")
+            phi_col = gr.HTML(label="Φ_col Collective coherence")
+            waveform = gr.HTML(label="Collapse gradient")
 
-        summary = gr.HTML(label="Simulation Summary")
-        simulate_btn.click(
-            simulate,
+        summary = gr.HTML(label="RFT summary")
+        run_btn.click(simulate,
             inputs=[agent_id, collapse_torque, emotional_resonance, tier_drift],
-            outputs=[Φᵢ_svg, Kᵢⱼ_svg, Φ_col_svg, waveform_svg, summary]
+            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)
+    with gr.Tab("Registry"):
+        reg_out = gr.Textbox(label="Codex registry", lines=20)
+        reg_btn = gr.Button("Refresh")
+        reg_btn.click(display_registry, outputs=reg_out)
 
-    # 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")
-        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],
-            outputs=lineage_svg_output
+        parent_id = gr.Dropdown(["Agent_5","Agent_7","Agent_1032"], label="Parent")
+        new_id = gr.Textbox(label="New agent id")
+        forge_torque = gr.Dropdown(["Gen6508_M5","Gen26_M23"], label="Overlay")
+        forge_res = gr.Checkbox(label="Resonance")
+        forge_tier = gr.Dropdown(["Tier_1","Tier_2","Tier_6"], label="Tier")
+        depth = gr.Slider(1, 8, value=5, step=1, label="Lineage depth")
+        forge_btn = gr.Button("Forge")
+        lineage_svg = gr.HTML(label="Lineage (RFT)")
+        forge_btn.click(forge_agent,
+            inputs=[parent_id, new_id, forge_torque, forge_res, forge_tier, depth],
+            outputs=lineage_svg
         )
 
-    # 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)
+        lb_out = gr.Textbox(label="Top agents", lines=15)
+        lb_btn = gr.Button("Refresh leaderboard")
+        lb_btn.click(generate_leaderboard, outputs=lb_out)
 
 demo.launch()