sphinx-spladex 0.1.1

Static hybrid SPLADE and BM25 search for Sphinx documentation.

Sphinx SpladeX

SpladeX adds static, client-side hybrid search to Sphinx HTML documentation. At build time it extracts pages and documented objects, creates SPLADE sparse vectors plus a BM25 index, and writes assets into _static. At search time the browser loads only those assets: it does not run or download a model.

Install

pip install sphinx-spladex

Development

Install the test and release tools, then run the release check:

pip install -e ".[dev]"
scripts/release-check.sh

Enable

Add the extension to conf.py:

extensions = ["spladex"]

The default model is Arvind0101/static-query-splade-code-docs. The model must include a static_query_weights.pt file containing a one-dimensional query_weights tensor matching the tokenizer vocabulary.

spladex_model_name = "Arvind0101/static-query-splade-code-docs"
spladex_device = "cpu"
spladex_max_length = 256
spladex_top_k_terms = 96
spladex_min_weight = 0.0
spladex_semantic_weight = 0.6
spladex_bm25_weight = 0.4
spladex_rrf_k = 60

After sphinx-build -b html docs docs/_build/html, the generated site includes _static/model_semantic_index.json and _static/model_static_query_assets.json.

SpladeX reads tokenizer.json, tokenizer_config.json, and static_query_weights.pt during the documentation build. It bundles their tokenization rules and aligned weights into the local query-assets file; search never requests those source files or a model from Hugging Face.

SpladeX replaces the standard Sphinx results with semantic hybrid results while retaining the usual Sphinx search-page presentation. It does not show relevance scores or provide a mode switch.