赛道情报 / 全球
检索增强 / RAG.
让模型回答有知识依据。
数据分类
存量红海
项目较密集，搜索需求未达到持续快速增长标准。切入前需要验证具体的用户迁移优势。
报告日期 · 方法版本 1.0.2 · 高 证据置信度
- 在公开的 GitHub 检索范围内，匹配到 459 个活跃项目。
- 关键词“retrieval augmented generation”有 104 个完整周，其中 0% 的周数据被报告为零。
- 匹配的活跃 GitHub 项目
- 459
- 搜索热度增速
- -73% · 最近 8 个完整周与此前 8 周对比
- 关键词与地区
- retrieval augmented generation · 全球
- 完整周观测数
- 104
判断依据
- 相邻两个 8 周窗口的搜索热度中位数下降 73%。
- 匹配到 459 个活跃仓库；公开的供给密集门槛为 50 个。
原始证据
GitHub 仓库搜索 · topic:retrieval-augmented-generation fork:false archived:false stars:>=5 pushed:>=2026-03-19
采集于 2026-09-15T16:35:44.822Z
Google Trends 搜索热度 · 采集于 2026-09-15T16:30:22.275Z
主要仓库
| 仓库 | Star 数 | 简介 |
|---|---|---|
| infiniflow/ragflow | 90,741 | RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs |
| pathwaycom/llm-app | 58,930 | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more. |
| HKUDS/LightRAG | 39,666 | [EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation |
| VectifyAI/PageIndex | 35,653 | 📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG |
| NirDiamant/RAG_Techniques | 29,490 | This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial. |
| deepset-ai/haystack | 26,514 | Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems. |
| HKUDS/RAG-Anything | 23,329 | "RAG-Anything: All-in-One RAG Framework" |
| memvid/memvid | 16,542 | 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. |
| llmware-ai/llmware | 14,844 | Unified framework for building enterprise RAG pipelines with small, specialized models |
| neuml/txtai | 12,949 | 💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows |
结果的适用范围
- Google Trends 衡量相对搜索关注度，不能直接代表客户数、收入或付费意愿。
- 供给统计覆盖所选 GitHub 主题下的活跃仓库，不包含未标注主题的项目或闭源竞品。
搜索热度反映关注度，不能代表付费客户。分类门槛为公开的启发式规则，仍需实证校准。
