Add in-DB indexing script, benchmark results, schema names in presentation
- index_images_indb.py: new script indexing via VECTOR_EMBEDDING(CLIP_IMG) using a two-step INSERT+UPDATE to work around ORA-24816 - index_images_oracle.py / index_images.py: add timing output - Presentation: schema names VECTORS_USER/VECTOR in diagram and comparison, ONNX expansion, HNSW index note on slide 11, indexing times updated from 3-run benchmark (avg: PG 12.1s, Ora 12.1s, InDB 13.6s) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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@@ -1,4 +1,5 @@
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import os
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import time
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from dotenv import load_dotenv
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from db import get_connection
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from embedder import embed_image
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@@ -37,6 +38,7 @@ def main():
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files = [f for f in os.listdir(PHOTOS_DIR) if f.lower().endswith((".jpg", ".jpeg"))]
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print(f"Found {len(files)} photos in {PHOTOS_DIR}")
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start = time.time()
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for i, filename in enumerate(files, 1):
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filepath = os.path.join(PHOTOS_DIR, filename)
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cur.execute("SELECT 1 FROM images WHERE filename = %s", (filename,))
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@@ -50,7 +52,7 @@ def main():
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cur.close()
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conn.close()
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print("Done.")
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print(f"Done in {time.time() - start:.1f} seconds.")
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if __name__ == "__main__":
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main()
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