Retrieval-augmented generation (RAG) makes a language model answer from your own documents. The text is split into chunks, turned into vectors and stored in an index, and the most relevant chunks are added to the prompt when a question comes in. The projects here cover the whole pipeline or one part of it: document parsing, vector search, or a complete question-answering app.
Answer quality in RAG depends mostly on retrieval, not on the model. Compare how each project handles difficult documents such as PDFs, tables and scans, whether it supports hybrid search that combines keywords with vectors and re-ranking, and whether it shows which sources an answer came from.
GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.
A vector index built on TurboQuant, written in Rust with Python bindings.
Agent framework and applications built upon Qwen>=3.0, featuring Function Calling, MCP, Code Interpreter, RAG, Chrome extension, etc.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Open-source NotebookLM alternative. Research the open web with live data(Reddit, YT, IG, TikTok, Indeed, Google Search, Maps etc) through one platform, API or MCP server. Join our Discord: https://discord.gg/ejRNvftDp9
A lightweight, lightning-fast, in-process vector database
主要记录大语言大模型（LLMs） 算法（应用）工程师相关的知识及面试题
A powerful tool for creating datasets for LLM fine-tuning 、RAG and Eval
Unified framework for building enterprise RAG pipelines with small, specialized models
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
Comprehensive open-source library of AI research and engineering skills for any AI model. Package the skills and your claude code/codex/gemini agent will be an AI research agent with full horsepower. Maintained by Orchestra Research.
Your AI trading terminal assistant for US stocks, commodities, forex, and crypto.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
A cross-platform Markdown AI note-taking software. It is to make sure useful fragments do not disappear before you have time to turn them into something complete.
ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
Agent S: an open agentic framework that uses computers like a human
Retrieval and Retrieval-augmented LLMs
Convert any URL to an LLM-friendly input with a simple prefix https://r.jina.ai/