Update app.py

app.py

@@ -1,28 +1,26 @@
 import gradio as gr
 import json
 import os
-import matplotlib.pyplot as plt # Kept for potential future gr.Plot use or if figures are handled directly
+import matplotlib.pyplot as plt
 from simulation import RFTSimulation
 from utils import export_json, seed_everything
 
-# Conditionally import IPython.display only if in Colab
+# Detect Colab
 IN_COLAB = 'COLAB_GPU' in os.environ or 'Google' in os.environ.get('COLAB_CLOUD_PLATFORM', '')
 if IN_COLAB:
-    from IPython.display import Image, display # For Colab dev mode inline image display
+    from IPython.display import Image, display
+
+# -----------------------------
+# Core Simulation Function
+# -----------------------------
 
-# Helper function to run simulation and generate plots/export data
 def run_simulation_and_plot(num_agents, steps, mutation_rate, drift_rate, seed=None):
     if seed is not None:
         seed_everything(seed)
 
-    # Instantiate simulation with save_plots=True, so it saves plots during its run() method
     simulation = RFTSimulation(num_agents, steps, mutation_rate, drift_rate, save_plots=True)
-
-    # Run the simulation. The internal run method will save plots if save_plots=True.
-    # It returns all_agents_history, coherence_list, stability_list.
     all_agents_history, coherence_list, stability_list = simulation.run()
 
-    # Prepare final agent states for JSON export
     final_agent_states = []
     for i, agent in enumerate(simulation.agents):
         final_agent_states.append({
@@ -33,11 +31,9 @@ def run_simulation_and_plot(num_agents, steps, mutation_rate, drift_rate, seed=N
             'fitness': agent.fitness
         })
 
-    # Export JSON
     json_filename = "final_agent_states.json"
     export_json(final_agent_states, json_filename)
 
-    # Return filenames of the generated plots and the JSON for Gradio or dev mode display
     plot_filenames = [
         'phi_plot.png',
         'tau_plot.png',
@@ -48,62 +44,46 @@ def run_simulation_and_plot(num_agents, steps, mutation_rate, drift_rate, seed=N
 
     return (*plot_filenames, json_filename)
 
-# Gradio Interface setup
-iface = gr.Interface(
-    fn=run_simulation_and_plot,
-    inputs=[
-        gr.Slider(1, 10, value=3, step=1, label="Number of Agents"),
-        gr.Slider(10, 500, value=100, step=10, label="Steps"),
-        gr.Slider(0.01, 0.5, value=0.05, step=0.01, label="Mutation Rate"),
-        gr.Slider(0.01, 0.5, value=0.02, step=0.01, label="Drift Rate"),
-        gr.Number(value=42, label="Random Seed (optional, leave empty for random)") # Clarified label
-    ],
-    outputs=[
-        gr.Image(label="Phi Plot"), # Changed to gr.Image to display saved PNGs
+# -----------------------------
+# PREMIUM UI (Always Unlocked)
+# -----------------------------
+
+with gr.Blocks(title="RFT Agent Simulation Engine — Premium") as iface:
+
+    gr.Markdown("# 🔥 RFT Agent Simulation Engine — Premium Edition")
+    gr.Markdown("Full‑power simulation engine with extended limits, advanced controls, and unrestricted exports.")
+
+    with gr.Box():
+        gr.Markdown("### Premium Simulation Controls")
+
+        num_agents = gr.Slider(1, 200, value=10, step=1, label="Number of Agents (Premium)")
+        steps = gr.Slider(10, 20000, value=500, step=10, label="Steps (Premium)")
+        mutation_rate = gr.Slider(0.001, 1.0, value=0.05, step=0.001, label="Mutation Rate")
+        drift_rate = gr.Slider(0.001, 1.0, value=0.02, step=0.001, label="Drift Rate")
+        seed = gr.Number(value=42, label="Random Seed")
+
+    outputs = [
+        gr.Image(label="Phi Plot"),
         gr.Image(label="Tau Effective Plot"),
         gr.Image(label="Fitness Plot"),
         gr.Image(label="Coherence Plot"),
         gr.Image(label="Stability Plot"),
         gr.File(label="Exported Final Agent States (JSON)")
-    ],
-    title="RFT Agent Simulation Engine MVP",
-    description="Simulate RFT Agents and visualize their dynamics."
-)
+    ]
+
+    run_button = gr.Button("🚀 Run Premium Simulation")
 
-# Colab-friendly "dev mode" or Gradio launch logic
-# The IN_COLAB check is now done at the top for conditional import
+    run_button.click(
+        run_simulation_and_plot,
+        inputs=[num_agents, steps, mutation_rate, drift_rate, seed],
+        outputs=outputs
+    )
+
+# -----------------------------
+# Launch Logic
+# -----------------------------
 
 if IN_COLAB:
     print("Running in Colab development mode (skipping Gradio launch).")
-    # Run the test simulation logic as per requirements
-    num_agents = 3
-    steps = 100
-    mutation_rate = 0.05
-    drift_rate = 0.02
-    seed = 42
-
-    print("\n--- Running Test Simulation in Dev Mode ---")
-    # Call the core simulation function. It will save plots and JSON.
-    plot_files_and_json_file = run_simulation_and_plot(num_agents, steps, mutation_rate, drift_rate, seed)
-    plot_files = plot_files_and_json_file[:-1]
-    json_file = plot_files_and_json_file[-1]
-
-    print("\nSimulation complete. Displaying plots and exported JSON path:")
-    for plot_file in plot_files:
-        print(f"  - {os.path.abspath(plot_file)}")
-        if os.path.exists(plot_file):
-            display(Image(filename=plot_file)) # Display inline in Colab
-        else:
-            print(f"Warning: Plot file {plot_file} not found for inline display.")
-
-    print(f"  - {os.path.abspath(json_file)}")
-    print(f"Final agent states exported to {json_file}")
-    print("\n--- End of Test Simulation in Dev Mode ---")
-
 else:
-    print("Running Gradio interface. Call iface.launch() to start it.")
-    # For local development, uncomment this to launch Gradio:
-    # iface.launch()
-
-print("app.py updated successfully.")
-iface.launch()
+    iface.launch()