Cognita is an open source framework designed to help developers build, organize, and deploy Retrieval-Augmented Generation (RAG) applications in a structured and production-ready way. It addresses the gap between quick experimentation in notebooks and the complexity of deploying scalable AI systems by introducing a modular and API-driven architecture. Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize each stage of the RAG pipeline independently. It includes both a backend service and a frontend interface, enabling users to upload documents, experiment with configurations, and perform question-answering tasks interactively. Cognita supports incremental indexing, meaning it processes only new or updated data to reduce computational overhead and improve efficiency.

Features

  • Modular architecture with customizable RAG components like loaders and retrievers
  • Built-in API server for handling queries and scalable deployments
  • Frontend UI for uploading documents and interactive question answering
  • Incremental indexing to avoid reprocessing unchanged documents
  • Support for multiple vector databases and embedding models
  • Integration with local or external LLM providers for flexible inference

Project Samples

Project Activity

See All Activity >