Fix: safe HF_HOME fallback when /data unmounted; drop risky local_files_only

app.py

@@ -16,7 +16,14 @@ ported (see BUILD_NOTES.md).
 import os
 
 # --- 1. Cache env vars FIRST, before importing torch/diffusers/etc. ---------
-os.environ.setdefault("HF_HOME", "/data/.cache/huggingface")
+# Prefer /data (persistent storage) if it's actually mounted and writable;
+# otherwise fall back to a path under /home/user (always writable on
+# ZeroGPU) so we never try to mkdir into a read-only/absent /data.
+_data_cache = "/data/.cache/huggingface"
+if os.path.isdir("/data") and os.access("/data", os.W_OK):
+    os.environ.setdefault("HF_HOME", _data_cache)
+else:
+    os.environ.setdefault("HF_HOME", "/home/user/.cache/huggingface")
 os.environ.setdefault("HF_MODULES_CACHE", "/tmp/hf_modules")
 os.environ.setdefault("MPLCONFIGDIR", "/tmp/matplotlib")
 
@@ -51,20 +58,11 @@ INTERMEDIATE_TIMESTEPS = (400, 600, 750, 900)
 # ZeroGPU (CUDA is emulated at import time); only the actual forward passes
 # need to happen inside a function decorated with @spaces.GPU.
 # -----------------------------------------------------------------------------
-try:
-    pipe = StableDiffusionPipeline.from_pretrained(
-        MODEL_ID,
-        torch_dtype=torch.float16,
-        safety_checker=None,
-        local_files_only=True,
-    ).to("cuda")
-except OSError:
-    # Fallback in case preload_from_hub cache isn't populated (e.g. local dev).
-    pipe = StableDiffusionPipeline.from_pretrained(
-        MODEL_ID,
-        torch_dtype=torch.float16,
-        safety_checker=None,
-    ).to("cuda")
+pipe = StableDiffusionPipeline.from_pretrained(
+    MODEL_ID,
+    torch_dtype=torch.float16,
+    safety_checker=None,
+).to("cuda")
 pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)