arc53/DocsGPT

▲ 6 stars today★ 18,306⑂ 2,177

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.

About arc53/DocsGPT

arc53/DocsGPT is an open-source project on GitHub, mainly written in Python. Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support It currently holds 18,306 stars and 2,177 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).

Project Overview

AI Homed tracks it on the Today's Trending board, currently at rank #77 with 6 new stars today.

GitHub Repository Details

Repository arc53/DocsGPT · default branch - · size 0 KB · watchers 0 · source: GitHub REST API and repository README

README

DocsGPT 🦖

Open-source AI agents grounded in your docs. Private, self-hosted, any model.

https://github.com/arc53/DocsGPT/blob/HEAD/GitHub stars https://github.com/arc53/DocsGPT/blob/HEAD/MIT license https://github.com/arc53/DocsGPT/blob/HEAD/OpenSSF Best Practices https://github.com/arc53/DocsGPT/blob/HEAD/Discord https://github.com/arc53/DocsGPT/blob/HEAD/Follow on X

⚡️ Quickstart • ☁️ Cloud • 📖 Docs • 💬 Discord • 🗞 Blog

English | Deutsch | Español | 日本語 | Русский | 简体中文 | 繁體中文

[!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

https://github.com/arc53/DocsGPT/blob/HEAD/DocsGPT in 30 seconds: uploading documents, syncing GitHub, answers with sources, deep research, visual workflows, tools, the chat widget, the OpenAI-compatible API, the MCP server and self-hosting with docsgpt up

🎃 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

https://github.com/arc53/DocsGPT/blob/HEAD/Creating an agent in DocsGPT with its knowledge, tools and prompt

Agents: knowledge, tools and a prompt, published in a click

https://github.com/arc53/DocsGPT/blob/HEAD/The DocsGPT workflow builder with an AI agent node, a condition and two end nodes

Workflows: agents and logic on one canvas

https://github.com/arc53/DocsGPT/blob/HEAD/Connecting a GitHub repository to DocsGPT and choosing a daily sync

Knowledge: connect a service and keep it in sync

https://github.com/arc53/DocsGPT/blob/HEAD/The DocsGPT chat widget on a product support page answering from the handbook

Widget: your agent on any website

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

Tech stack and project structure
  • 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.

Supported by

https://github.com/arc53/DocsGPT/blob/HEAD/DigitalOcean

https://github.com/arc53/DocsGPT/blob/HEAD/Neon

GitHub Stars & Activity

18,306Stars
2,177Forks
0Open issues
PythonLanguage

GitHub Popularity

GitHub stars18,306
Forks2,177
Open issues0
Primary languagePython
License-
Stars gained today6
Created-
Last pushed-

Trending History

Daily boardrank #77 · ▲ 6 stars

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