Write runtime outputs to /data bucket mount

README.md

@@ -14,8 +14,9 @@ This repository contains a self-contained Gradio demo for the
 `FINAL-ours-final_2026-05-01T12-36-12` Instruct Particulate checkpoint.
 On Hugging Face Spaces, the large model checkpoint is downloaded at startup
 from `rayli/instruct-particulate-model`.
-Runtime outputs are written under `./data` by default so the Space can use its
-mounted persistent bucket. Set `INSTRUCT_PARTICULATE_OUTPUT_ROOT` to override
+Runtime outputs are written under `/data` when that mount is available, so the
+Space can use the `rayli/instruct-particulate-results` read/write bucket. Local
+runs fall back to `./data`. Set `INSTRUCT_PARTICULATE_OUTPUT_ROOT` to override
 that location.
 
 Run:

app.py

@@ -82,9 +82,8 @@ CHECKPOINT_REPO_FILENAME = os.environ.get(
     "INSTRUCT_PARTICULATE_CHECKPOINT_REPO_FILENAME",
     "step_0080000.pt",
 )
-OUTPUT_ROOT = Path(
-    os.environ.get("INSTRUCT_PARTICULATE_OUTPUT_ROOT", str(REPO_ROOT / "data"))
-)
+DEFAULT_OUTPUT_ROOT = Path("/data") if Path("/data").exists() else REPO_ROOT / "data"
+OUTPUT_ROOT = Path(os.environ.get("INSTRUCT_PARTICULATE_OUTPUT_ROOT", str(DEFAULT_OUTPUT_ROOT)))
 UP_DIR_CHOICES = ["+X", "-X", "+Y", "-Y", "+Z", "-Z"]
 AUTO_KINEMATICS_MODEL_ID = "gemini-3.5-flash"
 AUTO_KINEMATICS_REASONING_EFFORT = "medium"