andnp-searchkernel

andnp-searchkernel is a source-agnostic Python library for building hybrid keyword, vector, and graph search systems. Applications map their native data to canonical Record values, choose the storage and provider adapters they need, and keep source-specific lifecycle logic outside the kernel.

It supports canonical record search, checkpointed record ingestion, optional local/Postgres/FAISS/provider integrations, and bounded federation across compatible search sources. Breaking changes are documented per release in docs/upgrading.md.

Install

The core package supports Python 3.13 and newer:

pip install andnp-searchkernel

Install optional integrations only when you need them:

pip install "andnp-searchkernel[faiss]"
pip install "andnp-searchkernel[pgvector]"
pip install "andnp-searchkernel[pgvector-psycopg3]"
pip install "andnp-searchkernel[huggingface]"
pip install "andnp-searchkernel[ollama]"
pip install "andnp-searchkernel[markdown]"

First local search

The local composition helper creates durable SQLite-backed stores. This small example uses a deterministic provider so it can run without downloading a model; replace it with a real provider for semantic retrieval.

import asyncio
from datetime import UTC, datetime
from pathlib import Path

from searchkernel import Record, build_local_record_kernel


class DemoEmbeddingProvider:
    model_name = "demo"
    dim = 2

    def embed(self, texts: list[str]) -> list[list[float]]:
        return [[1.0, 0.0] for _ in texts]


async def main() -> None:
    timestamp = datetime.now(UTC)
    composition = build_local_record_kernel(
        Path("records.db"),
        embedding_provider=DemoEmbeddingProvider(),
    )
    record = Record(
        workspace_id="demo",
        source_kind="notes",
        source_id="welcome",
        title="Welcome",
        body="Canonical records can be searched locally.",
        created_at=timestamp,
        updated_at=timestamp,
    )
    composition.keyword_store.index([record])

    outcome = await composition.kernel.search("canonical records", limit=5)
    for result in outcome.results:
        print(result.record.title, result.score)


asyncio.run(main())

The result is a RecordSearchOutcome. Each result retains the complete workspace/source identity and search provenance; degraded execution is reported through outcome.failures and outcome.diagnostics.

Documentation

Start with the documentation map to choose the right guide:

Optional integrations

The core import surface does not require optional providers or backends. The available extras are faiss, pgvector, pgvector-psycopg3, huggingface, ollama, and markdown. See the getting-started guide for the selection rule and the federation guide for the HTTP source adapter.

Validation and releases

CI runs Ruff, Pyrefly, import-linter, the safe test suite, supported Python versions, and selected optional-import checks. Pgvector integration tests provision a Docker pgvector/pgvector:pg17 container; real-embedding tests are outside the default offline gate. The performance roadmap records what those checks do and do not prove.

Merges to main with release-worthy Conventional Commits are released by the repository workflows. The package and runtime __version__ are checked against each other in CI and before semantic release.

License

MIT. See LICENSE.

Project links

Data verified by PyPI on Aug 27, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.15.7)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for andnp from gravatar.com andnp

GitHub Statistics

Data verified by PyPI on Aug 27, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

Requires

Python >=3.13

Provides Extra

faiss huggingface markdown ollama pgvector pgvector-psycopg3

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

andnp_searchkernel-1.15.3.tar.gz (688.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

andnp_searchkernel-1.15.3-py3-none-any.whl (310.9 kB view details)

Uploaded Python 3

File details

Details for the file andnp_searchkernel-1.15.3.tar.gz.

File metadata

  • Download URL: andnp_searchkernel-1.15.3.tar.gz
  • Upload date:
  • Size: 688.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for andnp_searchkernel-1.15.3.tar.gz
Algorithm Hash digest
SHA256 ac34c34867be06bd66e61c0a65771fc6f7e87472e7aa8035e77be4097f139dd8
MD5 cfe7f58bd62315ddda72db1ed8009402
BLAKE2b-256 b82aa164e19ec7ade6f6ac652edba1985a3cc7443323161b5afda99fb6ed07ee

See more details on using hashes here.

Provenance

The following attestation bundles were made for andnp_searchkernel-1.15.3.tar.gz:

Publisher: publish.yml on andnp/andnp-searchkernel

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file andnp_searchkernel-1.15.3-py3-none-any.whl.

File metadata

File hashes

Hashes for andnp_searchkernel-1.15.3-py3-none-any.whl
Algorithm Hash digest
SHA256 d021b06fab061145ecbd3ea47518820f40d54ec031100c1f02431229bc8b74fb
MD5 a7b09a5cb66f79e2e07959e92598ad0b
BLAKE2b-256 369dbfc0803f6f65f89bd367ed469d0de6e3364e6fb273bf61e920881f874729

See more details on using hashes here.

Provenance

The following attestation bundles were made for andnp_searchkernel-1.15.3-py3-none-any.whl:

Publisher: publish.yml on andnp/andnp-searchkernel

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

1.15.7

2 files

1.15.6

2 files

1.15.5

2 files

1.15.4

2 files

This release

1.15.3 This release

2 files

1.15.2

2 files

1.15.1

2 files

1.15.0

2 files

1.14.0

2 files

1.13.0

2 files

1.12.0

2 files

1.11.0

2 files

1.10.0

2 files

1.9.1

2 files

1.9.0

2 files

1.8.1

2 files

1.8.0

2 files

1.7.0

2 files

1.6.3

2 files

1.6.2

2 files

1.6.1

2 files

1.6.0

2 files

1.5.2

2 files

1.5.1

2 files

1.5.0

2 files

1.4.0

2 files

1.3.0

2 files

1.2.0

2 files

1.1.0

2 files

1.0.0

2 files

0.25.0

2 files

0.24.0

2 files

0.23.0

2 files

0.22.0

2 files

0.21.0

2 files

0.20.0

2 files

0.19.0

2 files

0.18.0

2 files

0.17.0

2 files

0.16.0

2 files

0.15.8

2 files

0.15.7

2 files

0.15.6

2 files

0.15.5

2 files

0.15.4

2 files

0.15.3

2 files

0.15.2

2 files

0.15.1

2 files

0.15.0

2 files

0.14.0

2 files

0.13.3

2 files

0.13.2

2 files

0.13.1

2 files

0.13.0

2 files

0.12.0

2 files

0.11.1

2 files

0.11.0

2 files

0.10.0

2 files

0.9.1

2 files

0.9.0

2 files

0.8.0

2 files

0.7.0

2 files

0.6.0

2 files

0.5.0

2 files

0.4.1

2 files

0.4.0

2 files

0.3.0

2 files

0.2.0

2 files

0.1.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page