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RAG Tools

Open-source retrieval-augmented generation (RAG) tools — vector databases, document chunking, hybrid search, reranking, and RAG evaluation. Compare options for building high-quality private-knowledge Q&A and document retrieval apps.

185 projects

LangChain

144.4k · Python
Active A+

LangChain is the open-source agent engineering platform that unifies model IO, tool calling, RAG, memory and observability under one composable framework.

agent-frameworkragorchestration +2
  • · Unified model abstraction — ChatModel interface covers OpenAI, Anthropic, Bedrock, Vertex and 100+ providers
  • · Tool calling & agents — tool calling, ReAct, OpenAI Tools, Plan-and-Execute agent paradigms
  • · RAG as a first-class citizen — Document Loader, Text Splitter, Retriever and Index abstractions

Awesome LLM Apps

132.9k · Python
Active A+

100+ AI Agent and RAG apps you can actually run — clone, customize, and ship. A great reference for quickly building LLM-powered applications.

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  • · 100+ runnable templates — Original, end-to-end tested projects, not a curated link collection
  • · 14 categories — AI Agents, Multi-agent, MCP Agents, Voice AI, RAG, Agent Skills, Fine-tuning, and more
  • · Multi-model compatible — Supports Claude, Gemini, OpenAI, xAI, Qwen, Llama with config-only switching

llama.cpp

124.2k · C++
Active A+

llama.cpp is a lightweight C/C++ inference engine that runs a wide range of open-source large language models efficiently on consumer hardware.

llm-inferencellamagguf +2
  • · Ultra-lightweight inference — pure C/C++ with zero dependencies, runs quantized LLMs on CPU
  • · GGUF format — unified quantized model format that is cross-platform and supports partial loading
  • · Hardware acceleration — Apple Silicon Metal, NVIDIA CUDA, AMD ROCm, Vulkan and OpenCL backends

vLLM

89.2k · Python
Active A

A high-throughput and memory-efficient inference and serving engine for LLMs, featuring PagedAttention, continuous batching, and optimized KV cache management for production deployments.

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  • · PagedAttention memory management - Efficiently manages attention KV cache via paging, dramatically reducing memory usage
  • · Continuous batching and chunked prefill - Supports continuous batching, chunked prefill, and prefix caching for high-throughput inference
  • · Multi-quantization support - Covers FP8, INT8, INT4, GPTQ/AWQ, GGUF, compressed-tensors, and more quantization formats

RAGFlow

88.6k · Go
Active A+

A leading open-source RAG engine that fuses cutting-edge retrieval-augmented generation with agent capabilities to create a superior context layer for LLMs.

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  • · Deep document understanding - Extracts knowledge from complex unstructured data via deepdoc, supporting PDF, Word, PPT, Excel, images, and more
  • · Template-based chunking - Multiple intelligent chunking templates for explainable document segmentation and knowledge organization
  • · Traceable citations with reduced hallucinations - Visualizes text chunks for human intervention, answers include key reference sources

MinerU

77.7k · Python
Active A+

Transforms complex documents like PDFs into LLM-ready markdown/JSON for Agentic workflows, supporting layout analysis, formula recognition, and table extraction.

data-processingragpython +2
  • · Multi-format document parsing - Native support for PDF, DOCX, PPTX, XLSX, and images with Markdown/JSON output
  • · VLM + OCR dual engine - Vision-language model combined with OCR, 109-language recognition, 95+ accuracy on OmniDocBench
  • · Formula and table extraction - Auto-convert formulas to LaTeX, tables to HTML, with cross-page table merging and chart parsing

Prompt Engineering Guide

77.5k · MDX
Stale A

Comprehensive guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.

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  • · Prompt engineering techniques - systematic coverage of Zero-Shot, Few-Shot, Chain-of-Thought, Tree of Thoughts and other core methods
  • · RAG and tool-use guides - detailed coverage of Retrieval Augmented Generation, ART, ReAct and other reasoning-with-tools techniques
  • · Model-specific guides - dedicated prompting strategies for ChatGPT, GPT-4, LLaMA, Gemini, Mistral, Code Llama and more

Hello Agents

73.2k · Python
Active A+

A comprehensive tutorial on AI agent principles and practice, systematically covering core concepts, framework usage and hands-on projects.

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  • · Systematic agent tutorial — complete learning path from agent definitions to multi-agent applications
  • · Classic paradigm implementations — hands-on ReAct, Plan-and-Solve, and Reflection patterns
  • · Low-code platform tutorials — practical guides for Coze, Dify, and n8n platforms

codegraph

66.6k · C
Active A

CodeGraph is a context graph for coding agents, mapping how a codebase is wired together so LLM-driven tools can navigate dependencies and produce more accurate edits.

code-intelligencemcprag +2
  • · Pre-indexed code knowledge graph that auto-syncs code changes with millisecond queries
  • · Compatible with multiple coding agents including Claude Code, Codex, Cursor, and AntiGravity
  • · Runs 100% locally with indexes and queries kept on your machine

Docling

64.9k · Python
Active A+

Docling is an open-source document processing tool by IBM that converts PDF, Word, PPT, HTML and more into structured data for AI, purpose-built for GenAI and RAG pipelines.

document-parsingpdfrag +1
  • · Multi-format document parsing — Supports PDF, DOCX, PPTX, XLSX, HTML, WAV, MP3, email, images, LaTeX, and more
  • · Advanced PDF understanding — Page layout analysis, reading order detection, table structure extraction, formula recognition, and image classification
  • · Unified DoclingDocument format — Expressive representation with export to Markdown, HTML, WebVTT, DocTags, and lossless JSON

Embedchain

63.4k · Python
Active A+

Embedchain is a universal memory layer for AI agents, enabling quick integration of diverse data sources into LLMs for context-aware AI applications.

memoryragembeddings +2
  • · Universal memory layer — quickly integrates diverse data sources (web, PDFs, YouTube, Notion) into LLMs for context
  • · Vectorized storage — auto-chunks, embeds, and stores data in vector databases with semantic retrieval support
  • · Multi-LLM backend support — compatible with OpenAI, Cohere, Ollama and other LLM and embedding models

Mem0

63.4k · Python
Active A+

Mem0 is a long-term memory layer for AI agents, supporting cross-session memory management and personalized context retrieval.

memoryragpersonalization +1
  • · Multi-level memory — seamlessly manages user, session, and agent memory states with adaptive personalization
  • · Single-pass ADD extraction — one LLM call extracts memories with no UPDATE/DELETE, memories accumulate only
  • · Entity linking — entities extracted, embedded, and linked across memories for retrieval boosting

Daily Stock Analysis

63.0k · Python
Active A+

LLM-powered stock analysis system for A/H/US markets with multi-source quotes, real-time news, LLM decision dashboard and multi-channel push notifications.

agentpythonllm +2
  • · Multi-market data aggregation — Supports A-shares, HK stocks, US ETFs with quotes, K-lines, technical indicators, fund flows, chips, news, and fundamentals
  • · AI decision dashboard — Generates core conclusions, scores, trends, buy/sell signals, risk alerts, catalysts, and action checklists
  • · Agent strategy Q&A — Multi-turn queries with 15 built-in strategies (MA, Chanlun, Wave, Trend, Hotspots, Events, Growth, Expectation), covers Web/Bot/API

Pathway

62.5k · Python
Active A+

Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG applications.

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  • · Rust-powered engine — Scalable Rust engine based on Differential Dataflow with multithreading, multiprocessing, and distributed computation
  • · Unified batch & streaming — Same code works for local dev, batch jobs, stream replays, and live data processing
  • · Rich connectors — Built-in connectors for Kafka, GDrive, PostgreSQL, SharePoint; Airbyte connector covers 300+ data sources

TrendRadar

61.5k · Python
Active A+

AI-driven public opinion and trend monitor with multi-platform aggregation, RSS subscriptions, smart keyword filtering, AI-powered news analysis and briefings, supporting MCP integration and push notifications via WeChat, Feishu, DingTalk, Telegram and more.

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  • · Multi-platform trend aggregation — real-time scraping from 30+ sources covering tech, finance, social media
  • · AI-powered smart filtering — LLM-driven news summarization and intelligent filtering to auto-exclude irrelevant content
  • · Multi-channel push notifications — supports WeChat Work, personal WeChat, Telegram, DingTalk, Feishu, Slack and 10+ channels

Context7

60.8k · TypeScript
Active A+

Context7 is Upstash's context-engineering toolkit for agents, helping applications manage long context windows, retrieval injection, and history compression.

contextmemoryretrieval +1
  • · Real-time documentation retrieval — pulls latest version-specific library docs and code examples via MCP or CLI, injected directly into LLM context
  • · Dual-mode integration — supports CLI + Skills (ctx7 commands) and MCP Server, compatible with Cursor/Claude Code/OpenCode and other major agents
  • · Library version matching — automatically resolves library names and versions to fetch precise, version-appropriate docs

Pathway LLM App

59.0k · Jupyter Notebook
Normal A

Ready-to-run cloud templates for RAG, AI pipelines and enterprise search with live data, always in sync with Sharepoint, Google Drive, S3, Kafka and more.

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  • · Live data sync — automatically syncs incremental changes from file systems, Google Drive, Sharepoint, S3, Kafka, PostgreSQL and other sources
  • · Built-in vector index — vector search via usearch and hybrid full-text search via Tantivy, no external database required
  • · Multimodal RAG — GPT-4o parsing extracts charts, tables, and text from PDFs/DOCXs in real time

Meilisearch

59.0k · Rust
Active A

Meilisearch is a lightweight open-source search engine with typo tolerance, native vector search and instant indexing, commonly used as the retrieval layer for agents and RAG.

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  • · Typo-tolerant — forgiving search out of the box
  • · Instant indexing — new or updated docs are searchable within milliseconds
  • · Native vector search — built-in ANN vector index, hybrid with full-text

LlamaIndex

51.7k · Python
Active A+

LlamaIndex is a data framework for building LLM applications. It provides data connectors, indexing, query engines, and agent workflow orchestration — a core tool in the RAG ecosystem.

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  • · Data connectors — 300+ integration packages connecting diverse data sources (files, databases, APIs, web, etc.)
  • · Vector indexing and query engine — Supports multiple vector databases with semantic search and hybrid retrieval
  • · Agent workflow orchestration — Build complex multi-step AI agent flows with Workflows

LocalAI

48.5k · Go
Active A+

Open-source AI engine to run any model — LLMs, vision, voice, image, video — on any hardware without GPU. Provides OpenAI-compatible API for fully local, privacy-first AI inference.

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  • · Composable backend architecture — Each backend (llama.cpp, vLLM, whisper.cpp, etc.) is a separate image pulled on demand
  • · OpenAI/Anthropic/ElevenLabs-compatible API — Unified API interface across all backends for seamless cloud replacement
  • · Any modality support — LLMs, vision, voice, image, and video models behind a single unified API

SiYuan

45.8k · TypeScript
Active A+

A privacy-first, self-hosted, fully open-source personal knowledge management software with block-level references, bi-directional links, Markdown, AI enhancement and plugin extensions.

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  • · Block-level references and bi-directional links - inspired by Roam Research, blocks can be referenced from multiple places and automatically tracked
  • · Fully local-first - data stored locally on user devices, no cloud upload, optional end-to-end encrypted sync
  • · Native Markdown - supports standard Markdown plus LaTeX, Mermaid, flowcharts, syntax highlighting

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