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Rust core for Entroly: Context Receipts, deterministic ingestion/ranking, dependency audits, and local context optimization

Project description

entroly-core

Rust core for Entroly, the information-theoretic context optimization engine for AI coding agents.

Provides high-performance PyO3 bindings for:

  • Knapsack optimizer - 0/1 DP context selection within token budget
  • Shannon entropy scorer - boilerplate detection, information density
  • SimHash deduplication - near-duplicate fragment detection
  • Query analysis - TF-IDF vagueness scoring, heuristic refinement
  • SAST scanner - security rules for common vulnerability classes
  • LSH index - approximate nearest-neighbor semantic recall
  • PRISM RL optimizer - online feedback-driven fragment weight learning

Install

python -m pip install --upgrade pip
python -m pip install --no-cache-dir -U "entroly-core>=0.19.13"

Prebuilt abi3 wheels are published for Linux, macOS, and Windows. One wheel per platform covers Python 3.10+ including Python 3.14. If pip tries to compile an old source distribution such as 0.2.0, upgrade pip and retry with --no-cache-dir; the intended path is the prebuilt wheel, not a local PyO3 build.

Usage

Usually used via the higher-level entroly package:

python -m pip install entroly
entroly  # starts the MCP server

Or directly:

from entroly_core import ContextFragment, py_knapsack_optimize, py_shannon_entropy

License

Apache-2.0

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