This release adds 3 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Summary
AI summarypgvector HNSW indexing replaces the 500‑row in‑app scan, making all memories searchable by semantic similarity.
Full changelog
Headline
Central Intelligence scores 44.4% on LifeBench, the hardest published memory benchmark (2026, Nanjing University + Huawei). The key: pgvector HNSW indexing replaced the 500-row in-app vector scan, making all memories searchable by semantic similarity.
What Changed
pgvector ANN Search
The retrieval engine now uses PostgreSQL's pgvector extension with an HNSW index instead of fetching the 500 most recent memories and computing cosine similarity in JavaScript. This means all memories are searchable, not just the most recent 500.
migrate-pgvector.ts: enables extension, addsembedding_vec vector(1536)column, backfills from JSONB, creates HNSW index- Graceful fallback: if pgvector isn't installed, the old in-app cosine similarity still works
store()now writes both JSONB and native vector columns
Cross-Encoder Reranking (optional)
New rerank.ts service calls the Cohere Rerank API to re-score the top 100 retrieval candidates. Disabled by default — add COHERE_API_KEY as a Fly secret to enable. Falls back to passthrough scoring without the key.
Temporal Filtering
The /memories/recall endpoint now accepts date_from and date_to parameters. Both vector search and BM25 search apply the date range as a WHERE clause before scoring.
LifeBench Results on Landing Page & README
- New benchmark section on centralintelligence.online with CI's per-category scores
- LifeBench and AMB badges on GitHub README
- Links to the arxiv paper and the open-source evaluation harness
LifeBench Scores
| Category | Accuracy |
|----------|----------|
| Information Extraction | 50.0% |
| Multi-hop Reasoning | 45.6% |
| Temporal & Knowledge Updating | 28.6% |
| Nondeclarative | 43.6% |
| Overall | 44.4% |
Tested on 1 user (14,910 memories, 207 questions). Evaluation harness: lifebench-eval
Files Changed
packages/api/src/db/migrate-pgvector.ts— NEW pgvector migrationpackages/api/src/services/rerank.ts— NEW Cohere reranking servicepackages/api/src/services/memories.ts— pgvector search path, reranking integration, temporal filteringpackages/api/src/routes/memories.ts—date_from/date_toparams on recallpackages/api/src/index.ts— register pgvector migration on startupREADME.md— LifeBench + AMB badges, benchmark resultslanding/index.html— LifeBench results section
Upgrade Notes
- pgvector migration runs automatically on startup. If the extension isn't available, the API falls back to the previous retrieval method.
- Existing memories are backfilled from JSONB to native vector format on first startup (~30s for 15K memories).
- No breaking API changes.
date_from/date_toare optional new parameters.
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About AlekseiMarchenko/central-intelligence
Persistent memory for AI agents. Five tools (remember, recall, context, forget, share) with semantic search via vector embeddings and agent/user/org scoping. Works with Claude Code, Cursor, Windsurf, and any MCP client.
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Beta — feedback welcome: [email protected]