Update Project_notes.md: grailed-embedding-search status and TODOs (June 2025)

This commit is contained in:
nightwing
2026-02-11 17:54:47 -07:00
parent 07501bef14
commit fc792a4be9

View File

@@ -1,6 +1,6 @@
# Project Notes
*Maintained by Hermes — last updated February 2025*
*Maintained by Hermes — last updated June 2025*
---
@@ -58,13 +58,17 @@
## 5. Grailed Embedding Search
- **Repo:** https://github.com/samherring99/grailed-embedding-search
- **Local path:** `~/Desktop/Projects/grailed-embedding-search`
- **Description:** Embedding-based semantic search over Grailed fashion listings. Uses vector similarity to find related items.
- **Status:** Very early — has a basic similarity search implementation. Previously had a more complex version that's being reworked.
- **Description:** Semantic similarity search over Grailed fashion listings using CLIP embeddings and FAISS. Search by image URL or text description to find visually similar products.
- **Status:** Functional core pipeline. CLIP ViT-B/32 embeds product cover photos into 512-dim vectors, indexed with FAISS cosine similarity. Has CLI, batch embedding, persistent index save/load, and logging.
- **Recent work (June 2025):**
- PR #1 — Initial cleanup: docstrings, type hints, `.gitignore`, `requirements.txt`, README rewrite
- PR #2 — Feature improvements: persistent FAISS save/load, batch embedding, CLI (`cli.py`), proper logging throughout, lazy Grailed client, `fetch_details` toggle
- **TODO:**
- Build out the search pipeline
- Add scraping/indexing for listings
- Improve embedding approach
- Add UI or CLI for exploring results
- Embedding cache (avoid re-embedding known product URLs)
- Async/threaded image downloads for faster batch indexing
- Search result visualization (matplotlib grid of cover photos)
- Filter by category, designer, price range before search
- Web UI (Gradio or Streamlit)
---
@@ -134,3 +138,5 @@
| Gov Auction Scraper | Concept | 🔵 Future |
| Stable Audio Explorer | Dead | ⚫ None |