idkre

idkre is a software framework designed to support knowledge retrieval, indexing, and reasoning across heterogeneous data sources. It aims to provide a modular platform that can ingest structured and unstructured data, build searchable indexes, and support natural language queries in a scalable way. The project emphasizes interoperability and extensibility, allowing organizations to tailor the workflow to their data ecosystems and use cases.

Architecture and core concepts: The framework centers on a modular pipeline with components such as an indexer, a retriever, a reasoner, and an API layer. Data connectors enable integration with relational databases, document stores, graph databases, and file systems. The retrieval layer supports both traditional lexical search and vector-based semantic search, enabling accurate matching beyond keyword overlap. The reasoner component can apply rule-based logic or lightweight inference to refine results or derive new insights from retrieved items.

Data model and features: idkre supports multi-source indexing, access controls, and provenance tracking to help manage data quality and security. It offers pluggable scoring and ranking functions, support for multilingual text, and integration with external embedding models for semantic understanding. The framework is designed to be container-friendly and to work with common development stacks, including Python and JavaScript client libraries.

Development and usage: idkre originated as an open-source initiative and is released under a permissive license. The project prioritizes portability, testability, and clear documentation to facilitate adoption in research settings, knowledge bases, and AI-assisted applications.

See also: information retrieval, knowledge management, vector databases, natural language processing.