new update fix

app.py

@@ -645,29 +645,24 @@ input[type="range"]::-webkit-slider-thumb {
 BASE_MODEL_ID = "black-forest-labs/FLUX.2-klein-4B"
 LORA_ID = "AnimeOverlord/flux2-klein-4b-mc"
 
-# Model paths with fallback: check local repo first, then HF cache
-_LOCAL_MODELS = os.path.join(os.path.dirname(__file__), "models")
-_HF_CACHE = os.path.join(
-    os.environ.get("HF_HOME", os.path.join(os.path.expanduser("~"), ".cache", "huggingface")),
-    "hub"
-)
+# Mount this path in the Space settings
+SPACE_DATA_DIR = "/data"
+
+# Put Hugging Face cache on persistent storage too
+HF_HOME = os.path.join(SPACE_DATA_DIR, ".huggingface")
+HF_HUB_CACHE = os.path.join(HF_HOME, "hub")
+
+# Store the downloaded model files here
+MODEL_ROOT = os.path.join(SPACE_DATA_DIR, "models")
+MODEL_DIR = os.path.join(MODEL_ROOT, "FLUX.2-klein-4B")
+LORA_DIR = os.path.join(MODEL_ROOT, "flux2-klein-4b-mc")
 
-def _get_model_path(repo_name: str, fallback_name: str) -> str:
-    """Get model path with fallback from local repo to HF cache."""
-    local_path = os.path.join(_LOCAL_MODELS, repo_name)
-    hf_path = os.path.join(_HF_CACHE, f"models--{fallback_name}")
-    
-    # Check local first
-    if os.path.exists(local_path):
-        log_event(f"Using local model: {local_path}")
-        return local_path
-    
-    # Fallback to HF cache
-    log_event(f"Model not in local repo, will use HF cache: {hf_path}")
-    return hf_path
-
-MODEL_DIR = _get_model_path("FLUX.2-klein-4B", "black-forest-labs--FLUX.2-klein-4B")
-LORA_DIR = _get_model_path("flux2-klein-4b-mc", "AnimeOverlord--flux2-klein-4b-mc")
+# Set these before any HF downloads happen
+os.environ["HF_HOME"] = HF_HOME
+os.environ["HF_HUB_CACHE"] = HF_HUB_CACHE
+
+os.makedirs(MODEL_DIR, exist_ok=True)
+os.makedirs(LORA_DIR, exist_ok=True)
 
 _pipe = None
 _pipe_ready = False
@@ -700,46 +695,17 @@ log_event(f"Gradio version detected: {gr.__version__}")
 log_event(f"Blocks kwargs: {BLOCKS_KWARGS}")
 log_event(f"Launch kwargs: {LAUNCH_KWARGS}")
 
-
-def _setup_models_on_spaces():
-    """Auto-download and commit models on Spaces (runs once on first deploy)."""
-    if not os.environ.get("SPACE_ID"):
-        return  # Not running on Spaces
-    
-    try:
-        log_event("Detected Spaces environment, setting up models...")
-        os.system("git config user.email 'space@bot.local'")
-        os.system("git config user.name 'Space Bot'")
-        os.system("git lfs install")
-        
-        # Track large files
-        os.system("git lfs track 'models/**/*.bin' 'models/**/*.safetensors' 'models/**/*.json' 2>/dev/null || true")
-        os.system("git add .gitattributes 2>/dev/null || true")
-        
-        # Commit models if they exist
-        os.system("git add models/ 2>/dev/null || true")
-        result = os.system("git commit -m 'Add pre-downloaded models' 2>/dev/null || true")
-        
-        if result == 0:
-            log_event("Attempting to push models to repo...")
-            os.system("git push 2>/dev/null || true")
-            log_event("Models committed to repo (if any changes)")
-    except Exception as e:
-        log_event(f"Warning: Could not commit models to Spaces repo: {e}")
-
-
 def _ensure_model_files():
     """Download models if not already cached."""
-    global MODEL_DIR, LORA_DIR
-    
     log_event("Checking model files...")
-    
-    # Ensure directories exist
+
     os.makedirs(MODEL_DIR, exist_ok=True)
     os.makedirs(LORA_DIR, exist_ok=True)
 
-    # Download base model on first run
-    if not os.path.exists(os.path.join(MODEL_DIR, "model_index.json")):
+    base_marker = os.path.join(MODEL_DIR, "model_index.json")
+    lora_marker = os.path.join(LORA_DIR, "pytorch_lora_weights.safetensors")
+
+    if not os.path.exists(base_marker):
         log_event(f"Downloading base model: {BASE_MODEL_ID}")
         snapshot_download(
             repo_id=BASE_MODEL_ID,
@@ -750,8 +716,7 @@ def _ensure_model_files():
     else:
         log_event(f"Base model already cached at {MODEL_DIR}")
 
-    # Download LoRA on first run
-    if not os.path.exists(os.path.join(LORA_DIR, "pytorch_lora_weights.safetensors")):
+    if not os.path.exists(lora_marker):
         log_event(f"Downloading LoRA: {LORA_ID}")
         snapshot_download(
             repo_id=LORA_ID,
@@ -762,9 +727,6 @@ def _ensure_model_files():
         log_event(f"LoRA downloaded to {LORA_DIR}")
     else:
         log_event(f"LoRA already cached at {LORA_DIR}")
-    
-    # Auto-commit to repo on Spaces after first download
-    _setup_models_on_spaces()
 
 
 def _load_pipe():
@@ -841,6 +803,8 @@ def _minecraftify_image(
             num_inference_steps=int(steps),
             guidance_scale=float(guidance_scale),
             generator=generator,
+            height=360,
+            width=640
         )
 
     log_event("Inference complete")
@@ -1011,7 +975,7 @@ with gr.Blocks(**BLOCKS_KWARGS) as demo:
                         elem_classes="image-upload mc-upload-area",
                         height=400,
                     )
-                    gr.HTML('<div style="color: var(--mc-gold); font-family: VT323; text-align: center; margin-top: 10px;">▶ Click Record to start capturing and auto-process live frames</div>')
+                    gr.HTML('<div style="color: var(--mc-gold); font-family: VT323; text-align: center; margin-top: 10px;">▶ Click Record to start MINECRAFTIFICATION OF LIVE FRAMES</div>')
 
                 extra_details = gr.Textbox(
                     label="🗒️ Extra scene details (optional)",