andnp-searchkernel 0.3.0

Source-agnostic search/indexing kernel: domain-agnostic content ingestion, hybrid vector+keyword+graph search, pluggable embedding/LLM/reranker providers.

andnp-searchkernel

A domain-agnostic search/indexing kernel for building hybrid vector + keyword + graph search systems with pluggable embedding, LLM, and reranker providers.

Status

Pre-alpha, extraction in progress. This library is being extracted from mcp-markdown-ragdocs to enable reuse across arbitrary content sources and search backends.

Optional backends

The core package provides the domain models, ports, search pipeline, and evaluation primitives. Install only the integrations required by an application:

pip install andnp-searchkernel[pgvector,huggingface,markdown]

Available extras are faiss, pgvector, huggingface, and markdown. FAISS and pgvector implement the same record-oriented backend contracts; they can be selected independently or used together during migrations.

Integration tests

The pgvector integration tests automatically start a temporary pgvector/pgvector:pg17 Docker container when SEARCHKERNEL_PG_DSN is not set. Docker must be running:

uv run pytest tests/integration

To use an existing PostgreSQL instance instead, set SEARCHKERNEL_PG_DSN to its connection string. The database must allow the vector extension to be created.

Releases

Merges to main with feat, fix, or breaking Conventional Commits are released automatically. The release workflow bumps the SemVer version, updates pyproject.toml and uv.lock, pushes a v* tag, and dispatches the PyPI publishing workflow. Documentation, chore, and test-only commits do not create releases.

License

MIT License. See LICENSE for details.