[Update]: Integrated Stable Diffusion for artistic visualizations 🎨

- Added: Initialization of Stable Diffusion model for generating artistic representations based on memory operations.
- Implemented: New function to generate artistic prompts based on emotional context and memory operations.
- Updated: Quantum memory operations to include options for generating art and visualizations.
- Enhanced: Gradio interface to display both wave patterns and artistic visualizations.
- Pro Tip of the Commit: Art and science make a beautiful wave together! 🌊✨
Aye, Aye! 🚢

app.py

@@ -3,6 +3,23 @@ import spaces
 import torch
 import numpy as np
 from typing import Tuple, List
+from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
+import random
+
+# Initialize Stable Diffusion
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_repo_id = "tensorart/stable-diffusion-3.5-large-TurboX"
+
+if torch.cuda.is_available():
+    torch_dtype = torch.float16
+else:
+    torch_dtype = torch.float32
+
+pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_pretrained(model_repo_id, subfolder="scheduler", shift=5)
+pipe = pipe.to(device)
+
+MAX_SEED = np.iinfo(np.int32).max
 
 class EmotionalContext:
     """Implements Mem|8's emotional context structure"""
@@ -18,8 +35,30 @@ def create_wave_pattern(size: int, frequency: float, amplitude: float) -> torch.
     T, X = torch.meshgrid(t, x, indexing='ij')
     return amplitude * torch.sin(frequency * T + X)
 
-@spaces.GPU(duration=30)
-def quantum_memory_ops(input_size: int, operation: str, emotion_valence: float) -> Tuple[str, np.ndarray]:
+def generate_memory_prompt(operation: str, emotion_valence: float) -> str:
+    """Generate artistic prompts based on memory operation and emotional state"""
+    base_prompts = {
+        "wave_memory": "memories flowing like waves in an infinite ocean, ",
+        "interference": "two waves of memory intersecting and creating patterns, ",
+        "resonance": "resonating waves of consciousness forming harmonious patterns, "
+    }
+    
+    emotion_desc = "serene and peaceful" if -20 <= emotion_valence <= 20 else \
+                  "joyful and vibrant" if emotion_valence > 20 else \
+                  "dark and introspective"
+    
+    style = "digital art, abstract, flowing, wave patterns, "
+    prompt = f"{base_prompts[operation]}{emotion_desc}, {style} ethereal, dreamlike quality"
+    return prompt
+
+@spaces.GPU(duration=65)
+def quantum_memory_ops(
+    input_size: int, 
+    operation: str, 
+    emotion_valence: float,
+    generate_art: bool = True,
+    seed: int = 42
+) -> Tuple[str, np.ndarray, np.ndarray]:
     """Perform quantum-inspired memory operations using Mem|8 concepts."""
     # Initialize emotional context
     emotion = EmotionalContext()
@@ -27,7 +66,8 @@ def quantum_memory_ops(input_size: int, operation: str, emotion_valence: float)
     emotion.arousal = torch.abs(torch.tensor([emotion_valence * 2])).cuda()
     
     results = []
-    visualization = None
+    wave_viz = None
+    art_viz = None
     
     if operation == "wave_memory":
         # Create memory wave pattern (M = A·exp(iωt-kx)·D·E)
@@ -39,7 +79,7 @@ def quantum_memory_ops(input_size: int, operation: str, emotion_valence: float)
         results.append(f"Shape: {memory_state.shape}")
         results.append(f"Emotional Modulation: {emotional_mod.mean().item():.4f}")
         results.append(f"Memory Coherence: {torch.linalg.norm(memory_state).item():.4f}")
-        visualization = memory_state.cpu().numpy()
+        wave_viz = memory_state.cpu().numpy()
         
     elif operation == "interference":
         # Create interference between two memory waves
@@ -51,7 +91,7 @@ def quantum_memory_ops(input_size: int, operation: str, emotion_valence: float)
         results.append(f"Memory Interference Pattern:")
         results.append(f"Pattern Strength: {torch.max(emotional_weight).item():.4f}")
         results.append(f"Emotional Weight: {emotion.valence.item()/128:.4f}")
-        visualization = emotional_weight.cpu().numpy()
+        wave_viz = emotional_weight.cpu().numpy()
         
     elif operation == "resonance":
         # Demonstrate emotional resonance patterns
@@ -63,21 +103,39 @@ def quantum_memory_ops(input_size: int, operation: str, emotion_valence: float)
         results.append(f"Emotional Resonance Pattern:")
         results.append(f"Resonance Frequency: {resonance_freq.item():.4f}")
         results.append(f"Pattern Energy: {torch.sum(resonance**2).item():.4f}")
-        visualization = resonance.cpu().numpy()
+        wave_viz = resonance.cpu().numpy()
     
     results.append(f"\nEmotional Context:")
     results.append(f"Valence: {emotion.valence.item():.2f}")
     results.append(f"Arousal: {emotion.arousal.item():.2f}")
     results.append(f"Device: {wave.device}")
     
-    return "\n".join(results), visualization
+    # Generate artistic visualization if requested
+    if generate_art:
+        prompt = generate_memory_prompt(operation, emotion_valence)
+        generator = torch.Generator().manual_seed(seed)
+        art_viz = pipe(
+            prompt=prompt,
+            negative_prompt="text, watermark, signature, blurry, distorted",
+            guidance_scale=1.5,
+            num_inference_steps=8,
+            width=768,
+            height=768,
+            generator=generator,
+        ).images[0]
+        
+        results.append(f"\nArtistic Visualization:")
+        results.append(f"Prompt: {prompt}")
+        results.append(f"Seed: {seed}")
+    
+    return "\n".join(results), wave_viz, art_viz
 
 # Create a beautiful interface inspired by Mem|8's wave concepts
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue")) as demo:
     gr.Markdown("""
     # 🌊 Mem|8 Wave Memory Explorer
     
-    Welcome to 8b.is's quantum memory demonstration! This showcase implements concepts from our Mem|8 
+    Welcome to 8b.is's memory ocean demonstration! This showcase implements concepts from our Mem|8 
     wave-based memory architecture paper, visualizing how memories propagate and interact like waves 
     in an ocean of consciousness.
     
@@ -107,16 +165,33 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue"))
                 label="Emotional Valence",
                 info="Emotional context from negative to positive (-128 to 127)"
             )
+            
+            with gr.Accordion("Advanced Settings", open=False):
+                generate_art = gr.Checkbox(
+                    label="Generate Artistic Visualization", 
+                    value=True,
+                    info="Use Stable Diffusion to create artistic representations"
+                )
+                seed = gr.Slider(
+                    label="Art Generation Seed",
+                    minimum=0,
+                    maximum=MAX_SEED,
+                    step=1,
+                    value=42
+                )
+            
             run_btn = gr.Button("Generate Memory Wave", variant="primary")
         
         with gr.Column():
             output_text = gr.Textbox(label="Wave Analysis", lines=8)
-            output_plot = gr.Plot(label="Wave Visualization")
+            with gr.Row():
+                wave_plot = gr.Plot(label="Wave Pattern")
+                art_output = gr.Image(label="Artistic Visualization")
             
     run_btn.click(
         quantum_memory_ops,
-        inputs=[size_input, operation_input, emotion_input],
-        outputs=[output_text, output_plot]
+        inputs=[size_input, operation_input, emotion_input, generate_art, seed],
+        outputs=[output_text, wave_plot, art_output]
     )
     
     gr.Markdown("""
@@ -127,8 +202,8 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple", secondary_hue="blue"))
     2. **Interference**: How different memories interact and combine
     3. **Resonance**: Emotional resonance patterns in memory formation
     
-    The visualization shows how emotional context (valence) affects memory wave patterns,
-    demonstrating the dynamic, interconnected nature of our quantum memory architecture.
+    The visualization shows both the mathematical wave patterns and artistic interpretations,
+    demonstrating how emotional context affects memory formation and recall.
     
     All computations are accelerated using Hugging Face's Zero GPU technology! 
     """)

requirements.txt

@@ -1,4 +1,7 @@
 gradio>=4.19.2
 torch>=2.2.0
 numpy>=1.24.0
-spaces>=0.19.4 
+spaces>=0.19.4
+diffusers>=0.25.0
+transformers>=4.37.0
+accelerate>=0.27.0