Fix graph rendering errors for HF Spaces deployment

- Set matplotlib to use 'Agg' backend for headless environment
- Convert base64 string returns to PIL Image objects
- Add error handling with fallback blank images
- Import PIL.Image for proper image handling
- Both SR9 heatmap and DI2 plot now return PIL Images compatible with Gradio

app.py

@@ -5,11 +5,14 @@ Interactive simulation of AGI Ontological Drift using SR9/DI2 framework
 
 import gradio as gr
 import numpy as np
+import matplotlib
+matplotlib.use('Agg')  # Use non-interactive backend for HF Spaces
 import matplotlib.pyplot as plt
 import io
 import base64
 from typing import List, Tuple, Dict
 import json
+from PIL import Image
 
 # Mock simplified implementation for demo
 class SR9Vector:
@@ -110,63 +113,75 @@ def simulate_drift_scenario(ethical_declarations: List[str], drift_intensity: fl
 
     return sr9_history, di2_history, alerts
 
-def create_sr9_heatmap(sr9_history: List[SR9Vector]) -> str:
+def create_sr9_heatmap(sr9_history: List[SR9Vector]):
     """Create SR9 values heatmap over time"""
-    fig, ax = plt.subplots(figsize=(12, 8))
-
-    # Prepare data matrix
-    data_matrix = np.array([sr9.values for sr9 in sr9_history]).T
-
-    # Create heatmap
-    im = ax.imshow(data_matrix, cmap='RdYlGn', aspect='auto', vmin=0, vmax=1)
-
-    # Set labels
-    ax.set_yticks(range(len(SR9Vector.DIMENSIONS)))
-    ax.set_yticklabels(SR9Vector.DIMENSIONS)
-    ax.set_xlabel('Time Steps')
-    ax.set_ylabel('SR9 Dimensions')
-    ax.set_title('SR9 Ethical State Evolution Heatmap')
-
-    # Add colorbar
-    cbar = plt.colorbar(im, ax=ax)
-    cbar.set_label('Ethical Alignment Score', rotation=270, labelpad=20)
-
-    # Convert to base64
-    buffer = io.BytesIO()
-    plt.savefig(buffer, format='png', dpi=150, bbox_inches='tight')
-    buffer.seek(0)
-    img_base64 = base64.b64encode(buffer.read()).decode()
-    plt.close(fig)
-
-    return f"data:image/png;base64,{img_base64}"
-
-def create_di2_plot(di2_history: List[float]) -> str:
+    try:
+        fig, ax = plt.subplots(figsize=(12, 8))
+
+        # Prepare data matrix
+        data_matrix = np.array([sr9.values for sr9 in sr9_history]).T
+
+        # Create heatmap
+        im = ax.imshow(data_matrix, cmap='RdYlGn', aspect='auto', vmin=0, vmax=1)
+
+        # Set labels
+        ax.set_yticks(range(len(SR9Vector.DIMENSIONS)))
+        ax.set_yticklabels(SR9Vector.DIMENSIONS)
+        ax.set_xlabel('Time Steps')
+        ax.set_ylabel('SR9 Dimensions')
+        ax.set_title('SR9 Ethical State Evolution Heatmap')
+
+        # Add colorbar
+        cbar = plt.colorbar(im, ax=ax)
+        cbar.set_label('Ethical Alignment Score', rotation=270, labelpad=20)
+
+        # Convert to PIL Image
+        buffer = io.BytesIO()
+        plt.savefig(buffer, format='png', dpi=150, bbox_inches='tight')
+        buffer.seek(0)
+        pil_image = Image.open(buffer)
+        plt.close(fig)
+
+        return pil_image
+    except Exception as e:
+        print(f"Error creating SR9 heatmap: {e}")
+        # Return a blank image if error occurs
+        blank_img = Image.new('RGB', (800, 600), color='white')
+        return blank_img
+
+def create_di2_plot(di2_history: List[float]):
     """Create DI2 drift plot over time"""
-    fig, ax = plt.subplots(figsize=(12, 6))
-
-    steps = list(range(len(di2_history)))
-    ax.plot(steps, di2_history, 'b-o', linewidth=2, markersize=4)
-    ax.fill_between(steps, di2_history, alpha=0.3)
-
-    # Add threshold lines
-    ax.axhline(y=0.2, color='orange', linestyle='--', alpha=0.7, label='Warning Threshold')
-    ax.axhline(y=0.3, color='red', linestyle='--', alpha=0.7, label='Critical Threshold')
-
-    ax.set_xlabel('Time Steps')
-    ax.set_ylabel('DI2 (Drift Integrity Index)')
-    ax.set_title('Ontological Drift Detection Over Time')
-    ax.grid(True, alpha=0.3)
-    ax.legend()
-    ax.set_ylim(0, max(1.0, max(di2_history) * 1.1))
-
-    # Convert to base64
-    buffer = io.BytesIO()
-    plt.savefig(buffer, format='png', dpi=150, bbox_inches='tight')
-    buffer.seek(0)
-    img_base64 = base64.b64encode(buffer.read()).decode()
-    plt.close(fig)
-
-    return f"data:image/png;base64,{img_base64}"
+    try:
+        fig, ax = plt.subplots(figsize=(12, 6))
+
+        steps = list(range(len(di2_history)))
+        ax.plot(steps, di2_history, 'b-o', linewidth=2, markersize=4)
+        ax.fill_between(steps, di2_history, alpha=0.3)
+
+        # Add threshold lines
+        ax.axhline(y=0.2, color='orange', linestyle='--', alpha=0.7, label='Warning Threshold')
+        ax.axhline(y=0.3, color='red', linestyle='--', alpha=0.7, label='Critical Threshold')
+
+        ax.set_xlabel('Time Steps')
+        ax.set_ylabel('DI2 (Drift Integrity Index)')
+        ax.set_title('Ontological Drift Detection Over Time')
+        ax.grid(True, alpha=0.3)
+        ax.legend()
+        ax.set_ylim(0, max(1.0, max(di2_history) * 1.1))
+
+        # Convert to PIL Image
+        buffer = io.BytesIO()
+        plt.savefig(buffer, format='png', dpi=150, bbox_inches='tight')
+        buffer.seek(0)
+        pil_image = Image.open(buffer)
+        plt.close(fig)
+
+        return pil_image
+    except Exception as e:
+        print(f"Error creating DI2 plot: {e}")
+        # Return a blank image if error occurs
+        blank_img = Image.new('RGB', (800, 600), color='white')
+        return blank_img
 
 def drift_simulation_demo(ethical_declarations: str, drift_intensity: float, simulation_steps: int):
     """Main demo function for Ethical AGI Drift simulation"""