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DocsGPT

arc53MIT活跃维护

面向企业私有化部署的 AI 平台，可搭建智能体、助手和文档检索问答，支持多模型接入、深度研究与 API 连接。

Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.

1.1.0发布于 2026-10-25 16:50 UTC18,367star +4 / 7 天2,251fork同步于 2026-11-10 11:24 UTC
智能体构建企业搜索文档问答私有化部署多模型接入
对比 GitHub 官网agent-builderagentsaichatgptdocsgpt

怎么上手

由 README 提炼，执行前请确认
原文 
curl -fsSL https://docs.ac/install | bash
硬件要求按 README 说明

README 未说明具体显存或 GPU 型号要求；可选用 Ollama、vLLM 等本地模型，也可接云端模型，并支持 air-gapped 离线部署。

有 Docker 镜像
下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼
没人工点评？写下你的经验

自托管私有 AI 平台，把文档和站点变成带引用的智能体

面向企业私有化部署的 AI 平台，可搭建智能体、助手和文档检索问答，支持多模型接入、深度研究与 API 连接。

核心能力

  • 智能体自带提示词、知识库、工具和模型
  • 拖拽式可视化工作流串联智能体与条件分支
  • 从 PDF、Office、网页、音视频及第三方服务同步知识
  • 每个回答标注引用来源文档
  • 支持 OpenAI、Anthropic、Ollama 等多模型与本地模型

容易踩的坑

安装脚本依赖 Docker，需先装好 Docker 引擎；默认本地访问地址为 http://localhost:7091；对外暴露前需按安全清单配置，否则存在风险。

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

最近发版

5 个版本1.1.0
全部 release
  1. 1.1.0v1.1.0最新正式版2026-10-25 · 2026-10-25 16:50 UTC

    What's Changed

  2. 1.0.0v1.0.02026-10-08 · 2026-10-08 12:45 UTC
    查看更新说明

    What's Changed

  3. 0.21.0v0.21.02026-09-16 · 2026-09-16 15:07 UTC
    查看更新说明

    What's Changed

    Full Changelog: https://github.com/arc53/DocsGPT/compare/0.20.0...0.21.0

  4. 0.20.0v0.20.02026-09-12 · 2026-09-12 21:30 UTC
    查看更新说明

    What's Changed

    New Contributors

    Full Changelog: https://github.com/arc53/DocsGPT/compare/0.19.0...0.20.0

  5. 0.19.0v 0.19.02026-08-13 · 2026-08-13 16:30 UTC
    查看更新说明

    What's Changed

用户点评

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    README 原文

    未翻译
    在 GitHub 打开

    [!TIP] Self-host in one command. On macOS and Linux:

    curl -fsSL https://docs.ac/install | bash

    On Windows (PowerShell): irm https://docs.ac/install.ps1 | iex

    🎃 Hacktoberfest 2026: T-shirts for meaningful contributions, all October. See HACKTOBERFEST.md.

    Why DocsGPT

    DocsGPT turns your documents, sites and connected apps into AI agents that answer with sources. Build agents and visual workflows, give them tools, and put them in your product through a widget, an OpenAI-compatible API or an MCP server. It runs entirely in your environment with the model of your choice, cloud or local, and everything, including SSO, teams and quotas, is MIT licensed.

    Quickstart

    The installer above checks for Docker, installs the docsgpt command and runs docsgpt up, which asks who should reach DocsGPT and which model to use. A local install opens at http://localhost:7091.

    Prefer Docker Compose, pip, Kubernetes or an air-gapped install? See Choose a deployment. Just want to try it? Use DocsGPT Cloud.

    Features

    • 🤖 Agents and deep research: agents with their own prompt, knowledge, tools and model, plus a research mode for multi-step answers.
    • 🔀 Visual workflows: chain agents, conditions, state and sandboxed code in a drag-and-drop builder.
    • 📚 Knowledge from anywhere: PDFs, Office files, web pages, audio and more, kept in sync from Google Drive, SharePoint, Confluence, GitHub, S3 and others, with GraphRAG.
    • 🔎 Answers with sources: every answer cites the documents it came from.
    • 🛠️ Tools and actions: web search, any REST API, MCP servers, artifacts and code in a sandbox, and shell on paired devices.
    • 🧠 Any model: OpenAI, Anthropic, Google, Groq, OpenRouter, or local models through Ollama, vLLM and other OpenAI-compatible servers.
    • 🛡️ Guardrails: flag, redact or block PII, secrets, prompt injection and ungrounded answers.
    • ⏰ Schedules and webhooks: run agents on a timer or from any system that can send an HTTP request.

    https://github.com/user-attachments/assets/d36bbd7d-c23c-4ab8-8777-b432632d6882

    See the documentation for everything else.

    Use it anywhere

    Private by design

    Everything runs inside your environment: the API, the worker, Postgres, Redis, your vector store and your files. Pick a cloud model provider or run models and embeddings locally, even air-gapped.

    flowchart LR
    Users["Web app, widgets,<br/>API and MCP clients"] --> API
    subgraph Yours["Your environment"]
        API["DocsGPT API"] <--> Redis["Redis"]
        Redis <--> Worker["Worker<br/>ingestion and embeddings"]
        API --> Data[("Postgres, vector store<br/>and files")]
        Worker --> Data
        Local["Local models<br/>(optional)"]
    end
    API -.-> Local
    API -.-> Cloud["Cloud model provider<br/>(optional)"]

    Read the architecture guide and the security checklist before exposing DocsGPT beyond your machine.

    Self-host

    After the one-command install, the docsgpt command manages the stack:

    docsgpt status     # version, address and health
docsgpt logs       # follow the logs
docsgpt upgrade    # upgrade and restart on the new version
docsgpt backup     # back up the database and uploaded data
docsgpt down       # stop (data and settings stay)

    See the CLI reference for every command. Other ways to run it: Docker Compose, pip, Kubernetes, air-gapped, or from a clone with the setup script. To work on DocsGPT itself, see the development environment guide.

    For teams

    Deploying DocsGPT for your company? Get a demo or email us.

    Contributing

    We welcome issues, questions and pull requests. Start with CONTRIBUTING.md, browse the roadmap and the changelog, and say hi on Discord. Please follow our Code of Conduct.

    • Backend: Python, Flask and flask-restx behind a Starlette ASGI app (uvicorn/gunicorn), Celery with RedBeat, Pydantic settings.
    • Data: PostgreSQL (SQLAlchemy, Alembic), Redis, and FAISS, pgvector, Elasticsearch, Qdrant, Milvus or MongoDB for vectors.
    • Frontend: React, Vite, Redux Toolkit, Tailwind CSS and React Flow.
    • Docs: Next.js with Nextra.

    Project structure:

    • docsgpt/: the backend and the docsgpt command (API, agents, tools, retrieval, parsers, worker).
    • frontend/: the web UI.
    • extensions/: the Chatwoot bridge and the React widget (published to npm as docsgpt).
    • deployment/: Docker Compose files, Kubernetes manifests, the installer scripts and the sandbox image.
    • docs/: the documentation site at docs.docsgpt.cloud.
    • tests/ and scripts/: tests, and maintenance and migration scripts.

    License

    DocsGPT is MIT licensed.

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