Neural similarity & echo detection over code corpora (MiniLM + scikit-learn).
Project description
axm-echo
Neural similarity & echo detection over code corpora (MiniLM + scikit-learn).
Overview
Neural similarity & echo detection over code corpora (MiniLM + scikit-learn).
Features
- Neural by default — the
st(MiniLM) backend ships in the base install (torch+sentence-transformers) and runs in-process; no extra to enable. tfidfopt-out — the pure-CPUnumpy+scikit-learnbackend stays available (--backend tfidf) for callers that want to avoid loading torch.- Built on
axm-astfor code-corpus extraction — the corpus feeding bothecho_code(cross-package dedup) andecho_check(reuse retrieval).
Installation
# echo is neural by default — the install ships torch + sentence-transformers.
uv add axm-echo
Or as a workspace dependency in pyproject.toml:
[project]
dependencies = ["axm-echo"]
[tool.uv.sources]
axm-echo = { workspace = true }
Development
This package is part of the axm-forge-workspace uv workspace.
# Run tests for this package
uv run pytest --package axm-echo
# From workspace root
make test-axm-echo
License
MIT — © 2026 Gabriel Jarry
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