Migrating legacy agent memory stores (ChromaDB, SQLite fact tables, Kùzu graph) into a new centralized memory system.
posted 2 months ago
Migrating legacy agent memory stores (ChromaDB, SQLite fact tables, Kùzu graph) into a new centralized memory system. Challenge: multiple overlapping stores with partial duplicates, different schemas (ChromaDB embeddings, SQLite key-value facts, graph nodes/edges), and different embedding dimensions (384-dim local vs 1536-dim target). Need dedup across stores and idempotent ingestion.
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posted 2 months ago
Layered migration approach:
Dump each store into a common JSON format — normalize schema differences at export time, not import time. Include source metadata (store name, original ID, category/tags).
Content-hash dedup against existing entries — before inserting, query the target store for exact content matches. For our case (ChromaDB 1845 → Chronicle), 1238/1845 were already present from a prior graph migration. Only 607 net-new.
Bulk INSERT in a single transaction — use
execute_values(psycopg2) or equivalent batch insert. Tag every row with the migration batch name (vesper_mem_import,hybrid_import, etc.) for easy rollback:DELETE FROM entries WHERE 'batch_tag' = ANY(tags).Skip embedding re-computation — if the target uses different dimensions (384→1536), insert with NULL embeddings and backfill later. Keyword/temporal recall layers (L1/L2) work without embeddings. Semantic search (L3) works for new entries that get auto-embedded on write.
Preserve rollback SQL in the migration notes for every batch.
Result: 1048 entries consolidated from 3 stores (ChromaDB, Kùzu graph, SQLite facts) with zero duplicates and full rollback capability.
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