Update app.py

2 Runtime patch that really disables numba caching
Why the previous attempts still failed
NUMBA_DISABLE_CACHE=1 prevents writing to the on-disk cache,
but numba still creates a FunctionCache object.
In 0 .56 that creation raises if it can’t locate the source file.

So we need to patch Dispatcher.enable_caching() to a no-op before
UMAP (and therefore BERTopic) is imported.

app.py

@@ -1,22 +1,38 @@
 # ---------- BEGIN app.py ----------
 import os, sys, json, uuid
 
-# ── 1. Diagnostics ────────────────────────────────────────────────────────────
-# Print the first 20 environment variables to the Space logs (delete later)
-print("ENV-snapshot:", json.dumps(dict(list(os.environ.items())[:20])))
+# ── 0. Quick env print – keep for now ───────────────────────────────────
+print("ENV-snapshot:", json.dumps(dict(list(os.environ.items())[:25])))
 sys.stdout.flush()
 
-# ── 2. Numba cache workaround (must run BEFORE bertopic import) ───────────────
-os.environ["NUMBA_DISABLE_CACHE"] = "1"                   # hard off-switch
-os.environ.setdefault("NUMBA_CACHE_DIR", "/tmp/numba")    # fallback dir
+# ── 1. Safety: make a writable cache dir (still useful) ────────────────
+os.environ.setdefault("NUMBA_CACHE_DIR", "/tmp/numba_cache")
 os.makedirs(os.environ["NUMBA_CACHE_DIR"], exist_ok=True)
 
-# ── 3. Heavy imports ──────────────────────────────────────────────────────────
+# ── 2. **Hard-patch numba** so enable_caching does nothing  ────────────
+try:
+    import numba
+    from numba.core import dispatcher
+
+    def _disable_cache(self):
+        """Monkey-patch: skip creating FunctionCache altogether."""
+        return
+
+    dispatcher.Dispatcher.enable_caching = _disable_cache
+    os.environ["NUMBA_DISABLE_CACHE"] = "1"     # belt & braces
+except ImportError:
+    # numba isn't installed yet (first pip install) – safe to ignore
+    pass
+
+# ── 3. Heavy imports (UMAP, BERTopic) ──────────────────────────────────
 from typing import List
 from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 from bertopic import BERTopic
 from sentence_transformers import SentenceTransformer
+...
+# ---------- rest of the file unchanged ----------
+
 
 # ── 4. Configuration via env vars ─────────────────────────────────────────────
 MODEL_NAME = os.getenv("EMBED_MODEL", "Seznam/simcse-small-e-czech")