mnestic 0.12.0

Embedded graph + vector + full-text database with Datalog — a maintained fork of CozoDB, tuned as a substrate for agentic memory.

mnestic (Python)

Embedded graph + vector + full-text database with Datalog queries — a maintained fork of CozoDB, tuned as a substrate for agentic memory. This package is the in-process Python binding (no server required).

mnestic is not the official CozoDB and is not affiliated with or endorsed by its original authors. All credit for the original design belongs to Ziyang Hu and the Cozo Project Authors. See the fork repository for provenance and licensing.

pip install mnestic

from mnestic import CozoDbPy

db = CozoDbPy("mem", "", "{}")  # engines: "mem", "sqlite" (file path), "rocksdb" (dir path)
db.run_script("?[x] <- [[1],[2],[3]]", {}, False)

# One-call hybrid retrieval (HNSW + full-text fused with Reciprocal Rank Fusion),
# over a relation that has an HNSW index and an FTS index:
hits = db.hybrid_search({
    "relation": "docs",
    "vector_index": "vec", "query_vector": [0.1, 0.9], "vector_k": 5,
    "fts_index": "fts", "query_text": "vector search", "fts_k": 5,
})
# -> {"headers": ["id", "score"], "rows": [["d3", 0.033], ...], "next": None}

# Pass "detailed": True for per-leg contributions — one row per (item, leg)
# with the within-leg rank the fusion used and the leg's raw score:
# headers ["id","score","list_id","leg_rank","leg_score"]

The "rocksdb" persistent backend now ships in the published wheel — CozoDbPy("rocksdb", "./my.db", "{}") works straight from pip install mnestic. The source distribution stays SQLite/compact-only, so the persistent engine is wheel-only.

Upgrade note (0.10.6): a persistent database whose relation catalogs were last written by a build older than 0.10.0 could fail to open with Cannot deserialize relation metadata from bytes after upgrading to 0.10.0–0.10.5. 0.10.6 fixes this — legacy catalogs open again with no migration, so upgrade to 0.10.6 if you carry a pre-0.10.0 database.

run_script takes an optional timeout= — a per-query wall-clock budget in seconds; on expiry the query raises an eval::timeout error. db.set_default_query_timeout(secs) sets a Db-wide default and db.default_query_timeout() reads it back; the effective budget for a query is the minimum of that default and any per-call timeout.

New in 0.12.0: budgeted weighted traversal, straight from the wheel. BudgetedTraversal is a new fixed rule: cheapest-first expansion from a set of seed nodes, over non-negative edge weights, under a required global budget of distinct nodes (max_nodes), with an optional cost ceiling (max_cost), an exact hop bound (max_depth), and an optional admission gate (a gate relation plus an admit: predicate — a gated-out node spends no budget and is never a bridge). It emits each admitted node's cost, parent, and depth — parent pointers reconstruct any path in plain Datalog — and it runs from the wheel through run_script with nothing to register: db.run_script("?[n, c, p, d] <~ BudgetedTraversal(*edge[f, t, w], seeds[n], max_nodes: 200)", {}, False). Admission is deterministic (total-order tie-breaking), long expansions abort cleanly via a query timeout=, and the rule can consume a cached ::graph projection (graph: 'g') instead of positional edges — measured 2–4× faster than an equivalent host-side BFS at the release's merge gate. Weights are consumed as costs (apply -ln(weight)-style transforms yourself). Purely additive — no existing query changes result.

For idiomatic LangChain / LlamaIndex usage, install the integration packages (langchain-mnestic, llama-index-vector-stores-mnestic).

The query language (CozoScript / Datalog) and engine semantics follow CozoDB; see the upstream documentation and the fork changelog.

License

Mozilla Public License 2.0. Original work © 2022 The Cozo Project Authors; fork modifications © 2026 Shan Rizvi.