ContextGem
Gem is an innovative open-source framework aimed at streamlining the extraction of structured data from documents using large language models (LLMs). Developed by Shcherbak AI AS, it tackles the issue of needing extensive boilerplate code in document analysis by offering an intuitive, flexible framework that greatly simplifies development complexity. The framework supports both cloud-based and local LLMs via LiteLLM integration, including providers such as OpenAI, Anthropic, Google, and Azure OpenAI, with built-in converters for various file formats, especially excelling in DOCX conversions.
Visit Website- Automated Dynamic Prompting and Data ModelingAutomatically generates prompts and validates data to eliminate boilerplate code, greatly reducing development time.
- Accurate Reference LinkingOffers detailed reference alignment at both paragraph and sentence levels, along with built-in justifications for extracting information.
- Support for Multiple Large Language ModelsAllows for the creation of intricate extraction workflows that utilize multiple Large Language Models (LLMs) with specific roles and store unified, serialized result data.
- Document Format TransformationIntegrated converters for multiple document formats such as DOCX, which maintain document structure and comprehensive metadata to enhance LLM (Large Language Model) analysis performance.