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rdxtremity/
search-stack-v1

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Harrir Search Stack v1

Two-tower asymmetric GCN search for fashion retail (Harrir catalog ~28k SKUs), multilingual EN+AR. Three artifacts, version-locked together.

Layout

.
├── adapter/                      # LoRA adapter on BGE-M3 (LIVE)
├── tokenizer/                    # BGE-M3 tokenizer (LIVE)
├── gcn_head.pt                   # W_q / W_p / W_img projection heads (LIVE)
├── ltr_model.txt                 # LightGBM LambdaRank champion (LIVE)
├── ltr_idf.json                  # BM25/TF-IDF stats over catalog
├── ltr_subcat_*.{json,pt}        # subcategory embeddings (EN+AR)
├── ltr_spec_*.{json,pt}          # product spec embeddings
└── cross_encoder/                # BAAI/bge-reranker-base fine-tuned
                                  # NOT loaded by the app today (served from
                                  # Modal). Kept here for future bake-in.

Usage

The Harrir app loads these at startup. Set this repo in .env:

GCN_HF_REPO=rdxtremity/search-stack-v1
GCN_ARTIFACTS_DIR=./models/gcn_stage2

Then python download_models.py snapshot-downloads into ./models/gcn_stage2/.

Or manually:

python

from huggingface_hub import snapshot_download
snapshot_download("rdxtremity/search-stack-v1", local_dir="./models/gcn_stage2")

Eval

Baseline nDCG (golden_v1, 346 queries / 19,923 graded pairs): 0.7695 Latest with LTR+CE rerank: see Primary.GateRuns audit log in the app.