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BUILDING FAISS INDEX FOR CONGRESSIONAL BIOGUIDE
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1. Loading sentence transformer model...
   ✓ Model loaded in 2.021s

2. Loading biographies from database...
   ✓ Loaded 13,047 biographies in 0.211s

3. Preparing data for encoding...
   ✓ Prepared 13,047 texts
   ✓ Time: 0.000s

4. Generating embeddings...
   (This may take several minutes...)
   Encoded 3,200/13,047 (48 texts/sec, ~207s remaining)
   Encoded 6,400/13,047 (47 texts/sec, ~141s remaining)
   Encoded 9,600/13,047 (47 texts/sec, ~74s remaining)
   Encoded 12,800/13,047 (46 texts/sec, ~5s remaining)
   ✓ Generated 13,047 embeddings in 280.6s
   ✓ Shape: (13047, 384)

5. Building FAISS index...
   Dimension: 384
   ✓ Index built in 0.009s
   ✓ Total vectors in index: 13,047

6. Saving FAISS index to disk...
   ✓ Index saved to: /Users/electron/workspace/Nanocentury AI/NIO/BioGuideMCP/congress_faiss.index
   ✓ Time: 0.004s

7. Saving bio ID mapping...
   ✓ Mapping saved to: /Users/electron/workspace/Nanocentury AI/NIO/BioGuideMCP/congress_bio_ids.pkl
   ✓ Time: 0.001s

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FAISS INDEX BUILD COMPLETE
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Total biographies indexed: 13,047
Index file size: 19.11 MB
Mapping file size: 0.12 MB
Total size: 19.24 MB

The MCP server will now load this index on startup for semantic search.
You can now use the 'semantic_search_biography' tool!