labring/FastGPT
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.
FastGPT – An AI‑Agent Building Platform
FastGPT (by the labring organization) is a self‑hosted, open‑source platform for creating and running AI agents. It bundles the usual pieces needed for a Retrieval‑Augmented Generation (RAG) or chatbot‑style application—data ingestion, vector‑store search, model calling, and a visual workflow editor—so you can assemble fairly complex AI‑driven services without writing a lot of glue code.
What it does
| Area | What FastGPT provides |
|---|---|
| Application orchestration | A Flow visual editor where you can chain together Agent Skills, dialogue workflows, plugin steps, and basic RPA nodes. The UI lets you design multi‑step interactions and expose them as a single app. |
| Debug & testing | Built‑in tools for testing knowledge‑base look‑ups, seeing the full call chain (including model prompts and responses), and annotating or editing references during a conversation. |
| Knowledge‑base handling | Supports multiple vector stores, incremental chunk updates, and a wide range of file types (txt, md, html, pdf, docx, pptx, csv, xlsx) plus URL fetching. It also offers mixed retrieval & re‑ranking and an API‑driven knowledge‑base. |
| Plugin system | Hot‑reloading of system tools, with a roadmap for hot‑updating RAG modules, agent loops, and real‑time generation plugins. |
| Operations | Shareable, no‑login chat windows, one‑click iframe embedding, unified conversation logs with labeling, and basic usage analytics. |
How to get it running
- Docker quick‑start – Run a single script that pulls a configuration file and then
docker compose up -d. After a few seconds the UI is reachable athttp://localhost:3000(default credentials:root / 1234). - Self‑hosted options – Besides Docker you can deploy on Sealos Cloud with a one‑click installer.
- Cloud SaaS – If you prefer not to manage infrastructure, FastGPT offers a hosted version at fastgpt.io.
- Commercial edition – For enterprises that need extra features or dedicated support, a paid version is available (SaaS is prohibited by the open‑source license).
Ecosystem & related projects
- fastgpt‑plugin – a repository for extending FastGPT with custom plugins.
- AI Proxy – a model‑aggregation and load‑balancing service that FastGPT can call.
- Sealos – the underlying platform used for cluster‑level deployment.
- SiliconCloud – an open‑source model‑hosting front‑end that can be hooked into FastGPT.
Who might use it?
- Product teams that want to prototype AI‑augmented workflows (e.g., customer‑support bots, internal knowledge assistants) without building the pipeline from scratch.
- Developers looking for a visual “low‑code” environment to stitch together LLM calls, vector searches, and external APIs.
- Enterprises that need a self‑hosted solution for data‑privacy reasons but still want a ready‑made UI and debugging tools.
License
FastGPT is released under the FastGPT Open Source License. Commercial use as a backend service is allowed, but providing a SaaS offering without a commercial license is prohibited; all commercial deployments must retain the copyright notice.
All information above is taken directly from the repository’s README; no additional features have been inferred.