RAG

A local-first agentic RAG system that turns PDFs, scans, DOCX, PPTX and XLSX into a searchable team knowledge base with enterprise access control, exposed through both an HTTP question-answering API and an MCP interface an agent can reason over.

• MCP servers
• RAG

A local-first personal research agent that organizes messy private document collections into a library with metadata, then reads the relevant original file sections before writing a cited answer instead of relying only on vector search over chunks.

• RAG

A native macOS app that indexes text, code, PDFs, images, audio and video into one vector space for semantic search across a Mac's entire local filesystem, running fully on-device with no network connection required.

• RAG
• Desktop utilities

A learning project that implements a local knowledge base and retrieval-augmented question answering system with Streamlit, LangChain and Chroma, letting a user upload text files and then chat with answers grounded in that uploaded content.

• RAG
• Tutorials

A tutorial project that builds a multi-agent research assistant: a main agent delegates a task to web search, database and private knowledge base sub-agents, then merges their findings into a Markdown or PDF report streamed over WebSocket.

• RAG
• Tutorials

A local research assistant that runs on a laptop using small models, recursively exploring a query with a Monte Carlo search strategy and compiling what it finds into a structured, cited report.

• RAG

A library that defines one universal file format for vector datasets, so data can be exported from one vector database, re-embedded with a different model, and imported into another, without writing custom conversion code for each pair.

• RAG
• Databases

A curated, weekly-audited list of tools, frameworks and practices for building retrieval-augmented-generation systems at production scale, with reference architectures, real case studies and source-tagged benchmark numbers.

• RAG
• Curated lists

A benchmarking library for retrieval-augmented generation systems, focused on question answering, that standardizes how retrievers, rerankers and language models are compared across many datasets.

• RAG
• AI evals

A local-first desktop AI chat client, built with Tauri and Next.js, that connects to cloud providers such as OpenAI or Anthropic or to local models through Ollama or LM Studio, with document parsing and a local retrieval-augmented knowledge base.

• RAG
• Inference

An iOS app that answers questions by combining Apple's on-device FoundationModels with a local vector-search knowledge base and real-time web search, so responses can draw on both stored documents and current information.

• RAG

An experimental Streamlit application in which a locally run Ollama model decides for itself when to search a folder of the user's documents, rather than always retrieving text on a fixed schedule.

• RAG

A local retrieval-augmented-generation server exposed over MCP that lets Claude Code, Cursor and other agent hosts search a project's documents through hybrid semantic and keyword search, with no external service or API key.

• MCP servers
• RAG

A graph foundation model-powered retrieval-augmented generation pipeline that uses a pre-trained graph neural network to reason over a knowledge graph built from a user's documents and retrieve passages for question answering.

• RAG

A local deep-research tool that turns a folder of PDF, Word, PowerPoint, image and text files into a structured Markdown report, using a judgment model to check evidence coverage alongside the generative LLM.

• RAG

A solution accelerator, no longer maintained, that shows how to build a custom copilot for customer-facing teams using Azure OpenAI and Azure AI Search over an organization's own conversation data.

• RAG
• Tutorials

A config-driven tool for running experiments and evaluations of RAG search-and-response quality, testing different Azure AI Search and Azure OpenAI hyperparameters to find the best combination.

• RAG
• AI evals

An open-source, extensible agent framework for chatting with data, turning natural language into SQL, charts, dashboards and reports.

• RAG
• Data engineering

A hypergraph-driven retrieval-augmented generation method that models beyond-pairwise relationships between entities in domain-specific knowledge, to reduce hallucinations in medical LLM answers.

• RAG
• Papers

A TypeScript sample application demonstrating the Retrieval Augmented Generation pattern on Azure, using Azure AI Search for retrieval and Azure OpenAI to power a ChatGPT-style Q&A experience over a company's own documents.

• RAG
• Tutorials

An enterprise knowledge-base platform that combines retrieval-augmented generation with an AI agent, answering questions from uploaded documents with citations back to their sources.

• RAG

A chat tool for exploring and understanding GitHub repositories or locally uploaded source trees using a local or hosted LLM, with a code graph for navigation.

• Agent memory
• RAG

A no-code tool for building RAG applications by crawling websites or processing documents, then deploying to Vespa for hybrid search with an integrated chat UI and support for any OpenAI-compatible LLM.

• RAG

A modular React Native library for building private, local retrieval-augmented-generation apps, with pluggable LLM, embeddings, vector-store and text-splitter components and on-device inference through ExecuTorch.

• RAG
• Mobile