RAG

A platform that pairs a Rete rule engine with retrieval-augmented generation, so deterministic rules decide an outcome and grounded retrieval explains the decision in plain language.

• RAG

A hybrid retrieval engine for retrieval-augmented generation, written in Rust to run on-device on a phone or a laptop, combining lexical BM25 search, dense embedding search, reciprocal-rank fusion and cross-encoder re-ranking with no server.

• RAG

A .NET library that turns PDF, DOCX, HWP and other documents into optimized chunks for RAG systems, through a five-stage pipeline built on high-performance Rust FFI readers.

• RAG

A hands-on, notebook-first repository that builds six retrieval-augmented-generation architectures step by step with LangChain and LangGraph, from a simple retrieve-then-generate pipeline up to self-correcting, agentic and multimodal systems.

• RAG
• Tutorials

A fully generated C# SDK for the Jina API, covering embeddings, reranking and search, with Microsoft.Extensions.AI integration and support for .NET Framework, .NET Standard and modern .NET features such as trimming and NativeAOT.

• RAG
• Libraries

A self-hosted, Java-based knowledge base for small and mid-sized organizations, turning internal documents into a searchable, question-answerable and audit-exportable knowledge asset with hybrid retrieval and Docker deployment.

• RAG
• Databases

Agent memory built on a developer's own PostgreSQL and pgvector, where every retrieved result carries a verdict, a confidence score and provenance, and a query that cannot clear a calibrated trust threshold is refused instead of answered from the nearest match.

• Agent memory
• RAG

A full-stack, educational retrieval-augmented-generation demo: upload a PDF, the FastAPI backend chunks and embeds it into a per-session FAISS index, and a React app streams LLM answers grounded in the retrieved passages.

• RAG
• Tutorials

An open-source, vendor-agnostic enterprise AI and retrieval-augmented-generation platform that connects to widely used enterprise systems and a wide range of cloud or on-premise model providers.

• RAG

An open-source, local-first contract layer and runtime for applications that need canonical data storage, retrieval and RAG, and durable execution, without locking application code to one cloud provider.

• RAG
• Backend

An MCP server for hybrid semantic and full-text search over a Markdown knowledge base, with optional support for plain text, PDF, Office documents and source code.

• MCP servers
• RAG

A .NET 10 RAG library for building semantic search and retrieval systems, combining vector and keyword hybrid search with pluggable storage backends.

• RAG

A 1,350-image benchmark for evaluating document-parsing robustness against real-world captured pages, derived from OmniDocBench with physical printing, deformation and photography.

• RAG
• AI evals

Runs the same document corpus and question set through 19 retrieval architectures and reports citable, statistically tested evidence for which one fits a given dataset best.

• RAG
• AI evals

A full-stack retrieval-augmented-generation template covering authentication, knowledge-base management, document parsing and vectorization, hybrid retrieval, streaming chat and evaluation in one repository.

• RAG

A Docker image for a self-hosted document-parsing server, powered by IBM Docling, that converts PDF, DOCX, PPTX, HTML and more to Markdown or JSON with optional GPU acceleration.

• RAG
• Containers

A Chrome extension paired with a local Python backend that indexes the pages a user actually reads and lets them search their browsing history in plain English using local retrieval-augmented generation.

• RAG

A reference implementation of production-style retrieval-augmented generation for document question answering, combining hybrid retrieval, citation grounding and a streaming chat API.

• RAG

A self-hosted knowledge base where an AI agent not only answers questions over retrieval-augmented generation but also searches the web, fetches pages and writes newly found knowledge back into the index automatically.

• RAG

An open-source application that turns long-form ESG corporate disclosures into searchable, cited evidence through retrieval-augmented generation and an optional knowledge graph.

• RAG

A self-hostable AI hub for enterprise knowledge that combines hybrid retrieval-augmented generation, a typed knowledge graph and agentic tool use behind a Laravel platform, positioned as an on-premises alternative to hosted knowledge assistants.

• RAG

A local-first CLI that packs a codebase into a compact, lossless, searchable archive that can be queried and restored byte-for-byte, for agent memory and local RAG.

• Agent memory
• RAG

A full-stack web chat application that lets users switch between five language models, ask questions grounded in uploaded documents through retrieval-augmented generation, search the web in real time, and analyze images, with streaming responses.

• RAG
• Inference

A local retrieval-augmented-generation engine that fuses vector similarity, BM25 keyword search, knowledge-graph traversal and metadata filtering, running entirely on ONNX Runtime with no PyTorch or GPU required.

• MCP servers
• RAG