AI TOOLS/AI 工具·CHAT-AGENT

ragflow

infiniflow/ragflow

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

打开仓库Open repository 官网Homepage

怎么装：Install: git clone https://github.com/infiniflow/ragflow.git

02 / 现在的位置02 / Why now

它现在处在什么位置Where it stands right now

首次发现FIRST SEEN

03 OCT 202603 OCT 2026

增长GROWTH

+0.0%+0.0%

92k → 92k stars · 2 个快照92k → 92k stars · 2 snapshots

状态STATUS

持续活跃Active

03 / 它能帮你做什么03 / What it helps you do

它能帮你做成什么What it helps you do

04 / 安装04 / Install

怎么装How to install

GIT-CLONE

$

README 里给出的安装方式。The installation method given in the README.

两种装法选一个即可 —— 上面那条给命令行用户，下面那条给写代码的用户。Pick one of the two — the first is for command-line users, the second for people writing code.

05 / 限制与风险05 / Limits and risk

限制与风险Limits and risk

风险不是警告，是可信度的一部分。以下结论只基于文档静态扫描，我们不会执行项目里的任何代码。Risk here is evidence, not an alarm. These findings come from static scanning of the docs; we never execute a project’s code.

限制LIMITS

需检查Needs review

01需要 API KeyREQUIRES API KEY: 是Yes
02需要本地环境NEEDS LOCAL RUNTIME: 是Yes
03需要 DockerNEEDS DOCKER: 未在文档中发现Not found in the docs
04难度DIFFICULTY: 需要开发经验Needs development work

PROVENANCE · 这些结论的依据是什么Where these conclusions come from

来源 URLSource URL: https://github.com/infiniflow/ragflow
原始数据哈希Raw data hash: fc5c79487d9acc9ad18ff2014cc5930e
解析时间Parsed at: 2026-10-04T09:07:01.112Z
最后一次验证Last verified: 2026-10-04T08:53:33.891Z
增长测量时间Growth measured: —
发现查询Discovery queries: focus:token:repo:topic-context-engineering
分类来源Category source: rules
焦点Focus: token (5)

静态扫描STATIC SCAN

01需要系统权限Needs system permissionsreadme
```
> sudo sysctl -w vm.max_map_count=262144
```

02读取 API KeyReads an API keyreadme

Go Docker deployment uses `docker/.env` and `docker/docker-compose.yml`, uses Kvrocks for cache and Checkpoint storage, and uses NATS JetStr

这里只做静态扫描：读 README、SKILL.md 和依赖清单，不执行代码。没有命中不代表安全。This is static scanning only: we read the README, SKILL.md and dependency list, and never execute code. No findings does not mean safe.

完整解析证据 JSONFull parse evidence JSON

{
  "agents": [],
  "apiKey": "el name, service address, and API key. #### ⚙️ Docker Configuration and Adju",
  "docker": null,
  "taxonomy": {
    "scores": {
      "design": 0,
      "ai-tools": 3,
      "dev-tools": 0,
      "indie-web": 0,
      "skill-agent": 3,
      "productivity": 3
    },
    "primary": "ai-tools",
    "secondary": "chat-agent"
  },
  "localRuntime": "install: git-clone",
  "skillMdTotal": 1,
  "skillMdErrors": [],
  "treeTruncated": false,
  "categoryScores": {
    "data": 3,
    "agent": 3,
    "media": 0,
    "design": 0,
    "browser": 0,
    "devtool": 0,
    "security": 0,
    "marketing": 0,
    "productivity": 0
  },
  "classification": [
    {
      "signal": "1 SKILL.md with name + description",
      "weight": 0.95
    },
    {
      "signal": "description mentions AI",
      "weight": 0.2
    }
  ],
  "scannedSources": [
    "readme",
    ".agents/skills/go-naming/SKILL.md"
  ],
  "skillMdFetched": 1
}