Add pre-built FAISS index (87MB) for instant startup

- 29,601 vectors, 768-dim, gte-modernbert-base embeddings
- Built from updated catalog with new product types
- Eliminates ~2min+ CPU embedding at startup on HF Space
- index.faiss tracked via Git LFS

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.faiss filter=lfs diff=lfs merge=lfs -text

app.py

@@ -54,7 +54,8 @@ REAL_CATALOG_PATH = os.getenv(
 )
 REAL_INDEX_DIR = os.getenv(
     "REAL_INDEX_DIR",
-    str(ROOT / "data" / "real_catalog_index"),
+    str(_app_dir / "faiss-index") if (_app_dir / "faiss-index" / "index.faiss").is_file()
+    else str(ROOT / "data" / "real_catalog_index"),
 )
 # Fallback: original HF dataset (used if real catalog JSONL not found)
 CATALOG_PATH = os.getenv("CATALOG_PATH", str(ROOT / "data" / "amazebay-2M"))

faiss-index/index.faiss

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8cd8ad450d2d26c93efb2b22b310469ae2f1570a91a39ff59ad7649b8438e2da
+size 90934335

faiss-index/meta.json

@@ -0,0 +1,7 @@
+{
+  "model": "Alibaba-NLP/gte-modernbert-base",
+  "dim": 768,
+  "n_products": 29601,
+  "index_type": "Flat",
+  "metric": "inner_product"
+}