ContextGem 1.0 Pairs LLMs With Decisions

ContextGem’s strongest idea is hybrid extraction: use generative models for nuance, specialized decision models for repeatable closed questions.

• –Probability-returning answers can reduce latency and generated-text overhead for classification-heavy workflows.
• –Model groups and fallback chains let developers combine LLMs, decision models, and local or hosted providers.
• –Docling support broadens the framework from plain text to PDFs, Office files, scans, tables, and other document formats.
• –Agent tools make extraction composable, but ContextGem analyzes documents deeply rather than replacing corpus-scale RAG.
• –The 1.0 upgrade includes breaking API changes and drops Python 3.10 support.