RAG

An in-memory knowledge graph server for retrieval-augmented generation that stores entities, relationships and document chunks together with their embeddings so related information stays connected during retrieval.

• RAG
• Databases

A project that indexes more than 200 million academic publication abstracts from OpenAlex into a semantic search engine, using embeddings and a fast vector index.

• RAG
• Databases

A self-hosted retrieval-augmented-generation search engine that indexes 34 file formats with hybrid BM25 and semantic search, and can call Gemini, OpenAI, Claude or a local Ollama model to answer from the retrieved passages.

• RAG

A benchmark and toolkit for skill-retrieval-augmented LLM agents that treats reusable agent skills as a large corpus to retrieve from, rather than listing every skill in the prompt.

• RAG
• AI evals

A minimal FastAPI backend that demonstrates retrieval-augmented generation with vector similarity search, built for learning and for wiring into a frontend.

• RAG
• Tutorials

An example internal AI chatbot, built for a fictional investment research firm, that lets analysts query a corpus of financial filings in plain English and get sourced answers.

• RAG
• Tutorials

An enterprise Java AI agent server, built on Spring Boot and LangChain4j, combining ReAct reasoning, hybrid retrieval-augmented generation, and semantic caching for knowledge Q&A.

• Agent frameworks
• RAG

A local code search tool for developers and AI agents that combines BM25 keyword search, vector similarity and cross-encoder reranking, returning symbol-bounded results instead of whole files.

• Agent memory
• RAG

A self-hosted retrieval-augmented search platform that indexes GitHub, Notion, Google Drive, Confluence, and other sources into one AI-searchable knowledge base with cited answers.

• RAG

A research method that lets an autoregressive video generator retrieve its own earlier generated frames as extra context, reducing drift and error buildup in long videos without retraining.

• RAG
• Generative media

A vision-language model fine-tuned specifically to extract structured text from German business documents such as invoices, receipts, and forms, runnable locally or through a cloud API.

• RAG
• Models

An LLM-powered Slack bot that answers questions using a company's own Slack history, GitHub pull requests, and Linear issues, run on a Postgres and TimescaleDB backend.

• RAG
• Databases

A local knowledge engine that indexes a folder of notes, code, PDFs, and Office documents, then answers questions with citations through a CLI, web UI, REST API, or MCP.

• RAG

A tool that turns scanned PDFs and images into searchable documents by reading them with a locally run vision language model instead of traditional OCR.

• RAG
• Inference

A neural vector compression method for large-scale similarity search that predicts each quantization step's codebook from a neural network instead of using a fixed one.

• RAG

A Terraform module that deploys a generative-AI retrieval-augmented-generation solution on Google Cloud, provisioning a choice of Cloud SQL MySQL, Cloud SQL PostgreSQL, AlloyDB or Cloud Spanner as the database and prebuilt frontend and retrieval service containers.

• RAG
• Hosting

A production-ready Python and FastAPI retrieval-augmented-generation framework that swaps vector databases, language models, rerankers and caches with a one-line configuration change, running as a full Docker API server or as an offline local CLI chatbot with no API key required.

• RAG

An unofficial project that runs Japan's Digital Agency GENAI government AI entirely locally, replacing cloud dependencies with SAML authentication through Keycloak, an OpenAI-compatible backend, RAG through Qdrant, and local transcription and image generation.

• RAG
• Inference

A high-performance knowledge graph engine built for large language models and GraphRAG, using sparse matrix algebra for sub-millisecond graph traversals, with full OpenCypher query support and Python, JavaScript and Docker access.

• RAG
• Databases

A Google Cloud Platform sample that demonstrates real-time text semantic search end to end, extracting embeddings with the Universal Sentence Encoder and building an approximate nearest-neighbour index with the Annoy library.

• RAG

A Swift package for building on-device retrieval-augmented generation pipelines, combining a document-parsing library with a vector store and semantic search into one end-to-end pipeline for creating a searchable knowledge base on iOS or macOS.

• RAG

A research framework for repository-level code generation that retrieves context from external libraries as well as the local repository, using a knowledge graph over both.

• RAG
• Papers

A self-hosted semantic search and memory layer for AI coding assistants that indexes a codebase with local embeddings, aiming to cut context tokens by around 98 percent, installable via Docker or from source and integrated through an MCP client.

• Agent memory
• RAG

A repo-native agent that turns private office documents such as decks, spreadsheets, PDFs and emails into a local, evidence-first knowledge base, preserving structure like slide layout, table references and formatting so an AI agent's answers stay traceable to a source file.

• Agent memory
• RAG