shcherbak-ai/contextgem

Health v2 · maintenance only

Adoption not part of the score

1993 stars · 183 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

ContextGem is an open-source Python LLM framework for extracting structured data and insights from documents with minimal code. It provides declarative APIs for defining aspects and concepts, reusable extraction pipelines, and support for cloud and local LLM providers.

Use cases

• extract structured data from contracts with an LLM
• pull specific clauses out of legal agreements
• extract dates, numbers, and JSON objects from documents
• analyze long PDFs and reports for key sections
• build reusable document extraction pipelines
• parse unstructured text into structured fields without prompt engineering
• identify topics and sections in research papers or financial reports

When to choose

• you need structured extraction (aspects, concepts, typed fields) from documents with minimal boilerplate
• you want automatic prompting and justification/reference mapping out of the box
• you work with legal, financial, or other long-form documents and need semantic segmentation rather than naive chunking
• you want a Python library that works with multiple cloud and local LLM providers

When to avoid

• you need a general-purpose RAG system with vector search and retrieval over a corpus
• you need high-throughput bulk document OCR or image processing rather than LLM-based extraction
• you want a no-code UI or hosted service instead of a Python library
• your extraction tasks are simple regex or template parsing that doesn't need an LLM

Facets

library · maturity active

llm-inference nlp rag prompt-engineering serialization large-language-models artificial-intelligence legal data-science python cross-platform document-intelligence information-extraction aspect-extraction concept-extraction contract-analysis structured-data llm-framework legaltech zero-shot-extraction multimodal natural-language-processing documents

Member repositories

For agents

markdown · JSON · MCP: product_card(name="shcherbak-ai/contextgem")