ContextGem 1.0

ContextGem is an open-source Python framework for pulling structured data out of documents with LLMs. Version 1.0 added decision models, which answer yes/no, label and rating questions with a probability for each answer, alongside LLMs for open questions; the current release is 1.4.1.

Why it matters

For developers building contract review, compliance or document-processing tools. It handles the prompts, validation and source references for you, and lets cheaper decision models answer high-volume closed questions.

Highlights

• You describe what to extract in plain language and ContextGem writes the prompts, returning typed output (text, numbers, dates, booleans, labels, ratings, JSON).
• Every extracted item maps back to the paragraph or sentence it came from, with a justification on request.
• Model groups send each question to the model that suits it: an LLM for open answers, a decision model for closed ones, with fallbacks between models.
• Works with cloud or local LLMs through LiteLLM, and with decision models such as TypeSafe Jev and OpenAI's Decisions API.
• Recent releases (1.3 and 1.4) added refusal errors, a `ToolCallError` for tool calls in chat, and sync tool functions that run in a worker thread.

Taken from the project's own README, docs or launch page. Claims about speed or accuracy are the maker's unless stated otherwise.

Worth knowing: Upgrading from 0.x renames or removes some classes and parameters and drops Python 3.10; there's a migration guide. Smaller local LLMs may not follow its extraction instructions well, per the README.

Quick facts

Links

• Official site: https://contextgem.shcherbak.ai/
• Repository: https://github.com/shcherbak-ai/contextgem
• Release notes: https://github.com/shcherbak-ai/contextgem/releases
• Docs: https://contextgem.shcherbak.ai/

Related ranking

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Checked 2026-10-27 from the tool's own pages. Prices and star counts change, so confirm on the official site. Listing here is not a ranking or an endorsement.