RAG Frameworks, Parsers and Vector Databases

Weaviate is a vector database for developers building search, recommendation and RAG applications. It stores data alongside embeddings so applications can retrieve related content and apply structured filters.

LEANN is a local vector database for people building AI search over personal data or knowledge collections. It reduces index storage by computing embeddings on demand rather than keeping every embedding on disk.

Rig is a Rust library for developers building AI agents and LLM applications. It provides a shared interface across model providers and vector stores for applications that need to work with different backends.

ThinkRAG answers questions about your own documents using a knowledge base on your laptop. It's for researchers, students and other knowledge workers who want to find information across their files, with particular attention to Chinese text.

OpenContracts is a self-hosted document intelligence platform for teams working with legal archives, research libraries or internal policies. It connects documents through citations and annotations, giving people and AI agents a shared record of how source material relates. The code is open source under the MIT license; the public website also provides collections readers can browse.

txtai is a Python framework for developers building search, chat with their data, and AI agents on their own hardware. It combines a searchable knowledge store with model workflows, so applications can retrieve context and act on it.

LlamaIndex is a Python framework for developers building AI agents and applications that answer questions using their own data. It provides the connections and retrieval tools needed to give a language model relevant context from documents and other sources.

FastGPT is an AI agent builder for teams creating document-based assistants and business workflows. It suits internal knowledge search, customer support and applications that combine answers with actions.

Kiln is a desktop workbench for teams building and testing AI applications. Engineers, QA staff and subject matter experts can work with the same tasks and datasets, including contributing ratings and examples without writing code.

Qdrant is a vector database for developers building semantic search, retrieval-augmented generation (RAG), recommendations and AI agent memory. It stores embeddings with metadata so applications can find similar items within a relevant subset of their data.

Marker is a local document converter for developers and teams preparing PDFs, scans and Office files for document processing or AI workflows. It extracts text while retaining structure such as tables, equations and page layout.

Haystack is a Python framework for developers building AI agents, document search and applications that answer questions using their own data. Its pipelines give teams control over the information a model receives and the steps that produce an answer.

Kwipu helps people query a document folder or Obsidian vault and trace answers back to their notes. It connects information across documents so you can investigate project decisions, people and their roles, or relationships between ideas.

Code Graph RAG helps developers understand and change unfamiliar repositories, including monorepos that mix languages. It maps code relationships into a knowledge graph so questions and edits can use context across files.

Vald is a distributed vector search engine for developers building similarity search into applications. It runs on a self-hosted Kubernetes cluster and finds approximate nearest neighbors in dense vectors using NGT. It's open source under the Apache 2.0 license, with an architecture designed to spread large vector collections across multiple machines.

Docling turns documents into structured content for developers building search, retrieval and AI applications. It handles page structure and scanned text so applications can work with more than a file's plain text.

RuoYi AI is a self-hosted AI assistant platform for teams building assistants that answer questions about their documents or perform tasks with external tools. It has separate user and admin interfaces.

OGX, formerly Llama Stack, is an AI application server for developers building chat apps, document search and AI agents. It brings model access and the services those applications need into a server you can host yourself.

Flexible GraphRAG is a self-hosted platform for teams building document search and AI chat that use both text and relationships between entities. It extracts knowledge graphs from documents and combines graph retrieval with vector similarity and full-text search. You can run it standalone or in Docker. It's open source under Apache 2.0.

SurrealDB is a database for developers building AI agents, knowledge graphs and applications with several kinds of data. It lets application records and retrieval data share one engine.

Langflow is a visual builder for developers creating AI agents and applications that answer questions using connected data. It lets you assemble workflows visually and customize their components in Python.

funes gives coding agents a searchable memory of past work. It's for developers who want earlier decisions, reasoning and findings to remain available when they start another session or switch agents.

Chonkie is a library for developers preparing documents for retrieval-augmented generation (RAG). It brings document preparation and ingestion into one pipeline, with optional components to keep dependencies small.

GROBID turns scientific and technical PDFs into structured TEI XML on your own machine or server. It's for researchers and developers who need article metadata, full text and bibliographical references for search, analysis or document collections. The software is open source under Apache 2.0.

RocketRide is an AI pipeline builder and runtime for developers creating document processing, search, and agent workflows. Its visual editor sits in VS Code, alongside the application code that uses those workflows.

LangChain4j is a Java library for building chatbots, assistants and AI agents that use local models through Ollama. It runs within JVM applications, while Ollama handles model inference on your hardware using a CPU or GPU. You can also connect to OpenAI or Google Vertex AI, in which case model requests go to the remote provider.

PocketFlow is a Python framework for developers building AI agents and workflows with their own model connections. Its utility examples include an Ollama function for local LLM calls. Developers supply that function rather than using a built-in model wrapper. Cloud API examples send model requests to their providers. FastAPI examples show chat applications with streamed responses and background jobs.

PaddleOCR is an OCR and document parsing toolkit for developers turning PDFs and images into data for document search, RAG systems and AI agents. Its local models cover both structured pages and text found in photographs.

MLX Omni Server lets developers use local models through both OpenAI-compatible and Anthropic-compatible APIs on an Apple Silicon Mac. It's for applications built around those SDKs that need inference on hardware the developer controls. Apple's MLX framework provides hardware acceleration, and all AI processing stays on the Mac.

PyTerrier is a Python framework for researchers and developers building search systems or the retrieval part of a RAG application. It builds on Terrier and lets you combine retrieval and reranking components into pipelines, then compare their search effectiveness on standard datasets.

GrapeRoot is a local MCP context tool for developers using AI coding assistants on projects that require repeated file exploration. It selects relevant code before each prompt reaches the assistant and remembers earlier work.

Unlimited-OCR is an OCR model for developers building document extraction workflows on their own hardware or servers. It handles individual document images and multi-page inputs, including PDFs converted to page images.

RepoRelay makes Git repositories searchable by AI coding assistants across projects and versions. It's for developers who want a shared code index on their own infrastructure, accessible from different editors.

FastEmbed is a Python library for developers building semantic search and retrieval-augmented generation (RAG). It turns text into vectors and evaluates search results on your own hardware without requiring a cloud embedding API.