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imag vector generation with dimentionality reduction

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sriram
2026-09-18 15:26:25 +05:30
parent afa0bfa743
commit d6296bd1f0
16 changed files with 1724 additions and 48 deletions
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16
app/infrastructure/settings.py
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@@ -417,6 +417,22 @@ IMAGE_EMBED_MODEL_PATH = _dir(
# serialised by a lock (a TFLite interpreter is not thread-safe).
IMAGE_EMBED_NUM_THREADS = int(os.getenv("IMAGE_EMBED_NUM_THREADS", "2"))
# ---------------------------------------------------------------------------
# Image search - POST /api/search/image-vector and /api/search/image
# (app/services/image_search.py). Public, read-only.
# ---------------------------------------------------------------------------
IMAGE_SEARCH_DEFAULT_TOP_K = int(os.getenv("IMAGE_SEARCH_DEFAULT_TOP_K", "10"))
IMAGE_SEARCH_MAX_TOP_K = int(os.getenv("IMAGE_SEARCH_MAX_TOP_K", "50"))
# 0.0 on purpose. A simulated phone photo of Marie Gold against its catalog
# render scored 0.63; the app team's "0.7 means the same product" is a
# client-side rule of thumb for phone-vs-phone, so the server does not
# impose it - callers pass min_score when they want a floor.
IMAGE_SEARCH_DEFAULT_MIN_SCORE = float(os.getenv("IMAGE_SEARCH_DEFAULT_MIN_SCORE", "0.0"))
# Candidates fetched PER brand table before re-ranking (pack sizes of one
# product share an image and tie, so more than top_k must come back), and
# the floor for hnsw.ef_search on that query so the index does not drop them.
IMAGE_SEARCH_MAX_FETCH_K = int(os.getenv("IMAGE_SEARCH_MAX_FETCH_K", "100"))
# ---------------------------------------------------------------------------
# USDA FoodData Central - nutrition for loose, unbranded commodities
# ---------------------------------------------------------------------------