Alex
a20c83f468
`docsgpt up --native` installs services meant to outlive the shell. Development wants the opposite, and until now it meant three terminals from the guide: uvicorn, celery, and vite. `docsgpt dev` runs this checkout's API and worker as children of one terminal, both restarting when a file is saved, their output interleaved and labelled, and Ctrl-C stopping them together. `--ui` adds the Vite dev server, `--mock-llm` runs the bundled mock model so no API key is needed, and `--no-worker` leaves the worker to your editor's debugger. Celery has no reloader of its own, so the worker is wrapped in watchfiles when it is installed, and runs plain when it is not. Alongside it, the commands a dev loop keeps reaching for: - `docsgpt doctor` checks what usually breaks a new setup: PostgreSQL answering and its schema matching this version, Redis answering, a model provider being configured, and the port being free. - `docsgpt restart [api|worker]` bounces services without rewriting settings or rerunning migrations, which `down` plus `up` did. - `docsgpt logs -f` follows a native install instead of telling you to run `tail -f` yourself. - `docsgpt env set` applies itself to a running native install rather than asking you to run `docsgpt up` again to change one value. Two bugs found on the way, both older than this change: - `docsgpt api --reload` watched the working directory, which in a checkout is 178,425 files: .venv, node_modules, and the indexes/ and inputs/ the app writes to while ingesting, so the server restarted itself mid-request. It watches the package now — 1,217 files. - The VS Code "Flask Debugger" ran `flask run`, which serves only the WSGI app: /mcp, the SSE streams and artifact downloads 404 under it. The guide warned about this in prose while the debug config did it anyway. It runs uvicorn on the ASGI app now, like production.
DocsGPT 🦖
Private AI for agents, assistants and enterprise search
DocsGPT is an open-source AI platform for building intelligent agents and assistants. Features Agent Builder, deep research tools, document analysis (PDF, Office, web content, and audio), Multi-model support (choose your provider or run locally), and rich API connectivity for agents with actionable tools and integrations. Deploy anywhere with complete privacy control.
Key Features:
- 🗂️ Wide Format Support: Reads PDF, DOCX, CSV, XLSX, EPUB, MD, RST, HTML, MDX, JSON, PPTX, images, and audio files such as MP3, WAV, M4A, OGG, and WebM.
- 🎙️ Speech Workflows: Record voice input into chat, transcribe audio on the backend, and ingest meeting recordings or voice notes as searchable knowledge.
- 🌐 Web & Data Integration: Ingests from URLs, sitemaps, Reddit, GitHub and web crawlers.
- ✅ Reliable Answers: Get accurate, hallucination-free responses with source citations viewable in a clean UI.
- 🔑 Streamlined API Keys: Generate keys linked to your settings, documents, and models, simplifying chatbot and integration setup.
- 🔗 Actionable Tooling: Connect to APIs, tools, and other services to enable LLM actions.
- 🧩 Pre-built Integrations: Use readily available HTML/React chat widgets, search tools, Discord/Telegram bots, and more.
- 🔌 Flexible Deployment: Works with major LLMs (OpenAI, Google, Anthropic) and local models (Ollama, llama_cpp).
- 🏢 Secure & Scalable: Run privately and securely with Kubernetes support, designed for enterprise-grade reliability.
Roadmap
- Agent Workflow Builder with conditional nodes ( February 2026 )
- Research mode ( March 2026 )
- SharePoint & Confluence connectors ( March – April 2026 )
- Postgres migration for user data ( April 2026 )
- OpenTelemetry observability ( April 2026 )
- Bring Your Own Model (BYOM) ( April 2026 )
- Agent scheduling (RedBeat-backed) ( April 2026 )
- Notifications & conversation search ( May 2026 )
- Analytics & logs revamp with per-agent attribution ( June 2026 )
- OIDC / SSO login with SCIM provisioning & groups ( June 2026 )
- Admin dashboard & role-based access control (RBAC) ( June 2026 )
- Agent import / export ( June 2026 )
- Teams with team-scoped sharing & roles ( June 2026 )
You can find our full roadmap here. Please don't hesitate to contribute or create issues, it helps us improve DocsGPT!
Production Support / Help for Companies:
We're eager to provide personalized assistance when deploying your DocsGPT to a live environment.
Join the Lighthouse Program 🌟
Calling all developers and GenAI innovators! The DocsGPT Lighthouse Program connects technical leaders actively deploying or extending DocsGPT in real-world scenarios. Collaborate directly with our team to shape the roadmap, access priority support, and build enterprise-ready solutions with exclusive community insights.
QuickStart
Note
DocsGPT runs on Docker. The installer checks for it first.
macOS and Linux:
curl -fsSL https://docs.ac/install | bash
Windows (PowerShell):
irm https://docs.ac/install.ps1 | iex
The installer gets uv, installs the docsgpt Python package with it, and runs docsgpt up. That asks who should reach DocsGPT (only this computer, your network, or a domain with HTTPS) and which model provider to use, then starts it, at http://localhost:7091 for a local install. Afterwards, docsgpt status, docsgpt logs, docsgpt upgrade, docsgpt down and docsgpt uninstall manage it.
To read the script before running it:
curl -fsSL https://docs.ac/install -o install.sh
less install.sh
bash install.sh
A more detailed Quickstart is available in our documentation.
From a clone, with the setup script
-
Clone the repository:
git clone https://github.com/arc53/DocsGPT.git cd DocsGPT
For macOS and Linux:
-
Run the setup script:
./setup.sh
For Windows:
-
Run the PowerShell setup script:
PowerShell -ExecutionPolicy Bypass -File .\setup.ps1
Either script will guide you through setting up DocsGPT. Five options are available: using the public API, running locally, connecting to a local inference engine, using a cloud API provider, or building the docker image locally. The scripts will automatically configure your .env file and handle necessary downloads and installations based on your chosen option.
Navigate to http://localhost:5173/
To stop DocsGPT, open a terminal in the DocsGPT directory and run:
docker compose -f deployment/docker-compose.yaml down
(or use the specific docker compose down command shown after running the setup script).
Note
For development environment setup instructions, please refer to the Development Environment Guide.
Contributing
Please refer to the CONTRIBUTING.md file for information about how to get involved. We welcome issues, questions, and pull requests.
Architecture
Project Structure
-
docsgpt - Backend Flask application (the
docsgptPython package). -
Extensions - Integrations and widgets (e.g., Chatwoot, React widget).
-
Scripts - Miscellaneous utility scripts.
Code Of Conduct
We as members, contributors, and leaders, pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. Please refer to the CODE_OF_CONDUCT.md file for more information about contributing.
Many Thanks To Our Contributors⚡
License
The source code license is MIT, as described in the LICENSE file.
This project is supported by:
