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Elias Stepanik
164e5a2f1d
- Implement space assignment queue and worker for BullMQ - Add native Cypher cosine similarity function to replace GDS dependency - Make Trigger.dev environment variables optional (only required when QUEUE_PROVIDER=trigger) - Add EMBEDDING_MODEL_SIZE configuration for vector index management - Update vector search queries to use native Neo4j vector search with score - Add Neo4j utility scripts for index management and troubleshooting - Update documentation with embedding model configuration and vector index recreation steps
23 lines
1.2 KiB
Plaintext
23 lines
1.2 KiB
Plaintext
// Drop existing vector indexes if they exist (to handle dimension mismatches)
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DROP INDEX entity_embedding IF EXISTS;
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DROP INDEX statement_embedding IF EXISTS;
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DROP INDEX episode_embedding IF EXISTS;
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// Create vector indexes with 1536 dimensions (for text-embedding-3-small)
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// Change the vector.dimensions value if using a different embedding model:
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// - text-embedding-3-small: 1536
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// - text-embedding-3-large: 3072
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// - mxbai-embed-large (Ollama): 1024
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CREATE VECTOR INDEX entity_embedding IF NOT EXISTS FOR (n:Entity) ON n.nameEmbedding
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OPTIONS {indexConfig: {`vector.dimensions`: 1536, `vector.similarity_function`: 'cosine', `vector.hnsw.ef_construction`: 400, `vector.hnsw.m`: 32}};
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CREATE VECTOR INDEX statement_embedding IF NOT EXISTS FOR (n:Statement) ON n.factEmbedding
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OPTIONS {indexConfig: {`vector.dimensions`: 1536, `vector.similarity_function`: 'cosine', `vector.hnsw.ef_construction`: 400, `vector.hnsw.m`: 32}};
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CREATE VECTOR INDEX episode_embedding IF NOT EXISTS FOR (n:Episode) ON n.contentEmbedding
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OPTIONS {indexConfig: {`vector.dimensions`: 1536, `vector.similarity_function`: 'cosine', `vector.hnsw.ef_construction`: 400, `vector.hnsw.m`: 32}};
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// Verify indexes were created
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SHOW INDEXES YIELD name, type WHERE type = 'VECTOR' RETURN name, type;
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