semsift

Building blocks for hybrid retrieval: chunk text, embed it, store vectors and a keyword index together in SQLite or memory, search both, fuse the ranked results and rerank them. It retrieves and ranks; it never generates text.

Status: Implemented, not yet released. See docs/design.md for the blocks and their contracts, and docs/features.md for what was taken from other projects.

import sqlite3

from semsift.embed import StaticEncoder
from semsift.search import KeywordSource, Search, VectorSource
from semsift.store import Field, Item, Store

conn = sqlite3.connect(":memory:", isolation_level=None)
store = Store(conn, "notes", [Field("source", "text")],
              encoder=StaticEncoder("minishlab/potion-base-8M"))

items = [Item(1, "Rent is due on the first of the month.", {"source": "lease.md"}),
         Item(2, "The boiler service is booked for Tuesday.", {"source": "home.md"})]
vectors = store.embed(items)          # encode before opening the transaction
conn.execute("BEGIN")
store.upsert(items, vectors)          # the store never commits; you do
conn.execute("COMMIT")

search = Search(store, sources=[VectorSource(store), KeywordSource(store)],
                citation=("source",))
for hit in search.run("when is rent due", k=1).hits:
    print(hit.citation["source"], hit.text)

Install extras for what you use: static (model2vec encoders), onnx, webgpu, tree-sitter (syntax-aware chunking).

Development

uv venv .venv && uv pip install --python .venv/bin/python -e ".[static,onnx,tree-sitter]"
HF_HUB_OFFLINE=1 .venv/bin/python -m unittest discover -s tests -t .
.venv/bin/python benchmarks/run.py

To use an unreleased semsift from another project, depend on the checkout (uv add --editable ../semsift, or pip install -e ../semsift), or build it (uv build) and install the wheel from dist/.

Releasing

The version lives only in semsift.__version__. Bump it, commit, and push a matching tag (v0.0.1). The release workflow runs the tests, builds, refuses to publish unless the tag, __version__, the sdist and the wheel agree, publishes to PyPI through trusted publishing, and creates the GitHub release. PyPI must list this repository's release.yml as a trusted publisher for the semsift project.