LLMSlim
Tool-aware context, contract-safe.
What it does
v0.4.0 adds contract-safe tooling for MCP, OpenAI function, Anthropic, and generic tool schemas: provider-aware adapters, deterministic canonical JSON, SHA-256 fingerprints, exact-equivalence checks, and schema inspection. Raw execution schemas remain authoritative. Tool retrieval is research-only and is never used for authorization or execution.
Open-source Python library for extractive, rewrite, and hybrid LLM context compression with provenance-aware priority handling.
LLMSlim makes long prompts, documents, retrieval, and chat history easier to reason about—with local extractive compression, provider-aware strategies, and provenance-aware priorities. 24 curated samples stay visible in the methodology; the release story also includes categories, languages, schema contracts, security regression, and machine-readable artifacts. LLMSlim gives context a smaller, more intentional shape—without hiding the role, strategy, or boundary that produced it. Illustrative motion only. The released library exposes results—not hidden model reasoning. Local sentence selection. Deterministic, inspectable, and available without a provider. RAG text cannot gain protected…from llmslim.app
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