clean

.gitignore

@@ -0,0 +1,9 @@
+.venv/
+*.pyc
+*.pyo
+*.pyd
+*.pyw
+*.pyz
+*.pywz
+*.pyzw
+

app.py

@@ -3,21 +3,30 @@ 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"
+# Try importing Stable Diffusion dependencies
+try:
+    from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
+    STABLE_DIFFUSION_AVAILABLE = True
+except ImportError:
+    print("Warning: diffusers package not available. Artistic visualization will be disabled.")
+    STABLE_DIFFUSION_AVAILABLE = False
 
-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)
+# Initialize Stable Diffusion only if available
+pipe = None
+if STABLE_DIFFUSION_AVAILABLE:
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model_repo_id = "tensorart/stable-diffusion-3.5-large-TurboX"
+    torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+    
+    try:
+        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)
+    except Exception as e:
+        print(f"Warning: Could not initialize Stable Diffusion: {e}")
+        STABLE_DIFFUSION_AVAILABLE = False
 
 MAX_SEED = np.iinfo(np.int32).max
 
@@ -111,7 +120,7 @@ def quantum_memory_ops(
     results.append(f"Device: {wave.device}")
     
     # Generate artistic visualization if requested
-    if generate_art:
+    if generate_art and STABLE_DIFFUSION_AVAILABLE and pipe is not None:
         prompt = generate_memory_prompt(operation, emotion_valence)
         generator = torch.Generator().manual_seed(seed)
         art_viz = pipe(
@@ -127,6 +136,9 @@ def quantum_memory_ops(
         results.append(f"\nArtistic Visualization:")
         results.append(f"Prompt: {prompt}")
         results.append(f"Seed: {seed}")
+    elif generate_art:
+        results.append(f"\nArtistic Visualization:")
+        results.append(f"Not available - Stable Diffusion could not be initialized")
     
     return "\n".join(results), wave_viz, art_viz