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>=1.0.21"
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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