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Neural similarity & echo detection over code corpora (MiniLM + scikit-learn).

Project description

axm-echo

Neural similarity & echo detection over code corpora (MiniLM + scikit-learn).

axm-audit axm-init Coverage Python 3.12+


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.
  • tfidf opt-out — the pure-CPU numpy + scikit-learn backend stays available (--backend tfidf) for callers that want to avoid loading torch.
  • Built on axm-ast for code-corpus extraction — the corpus feeding both echo_code (cross-package dedup) and echo_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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