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. observed · 2026-08-28
Health v2 · maintenance only
93/100
- Activity 99
- Release rhythm 86
- Longevity 91
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 2.0
- age_days: 1287
- days_rel: 12
- days_push: 7
- n_releases_24m: 149
Adoption not part of the score
29477 stars · 7279 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
FastGPT is an open-source AI agent building platform built on large language models, offering out-of-the-box knowledge base (RAG) management, data processing, and visual drag-and-drop workflow orchestration. It can be self-hosted via Docker or used as a cloud service, and supports multiple LLM providers including OpenAI, Claude, DeepSeek, and Qwen.
Use cases
- build a chatbot on my own documents
- create a knowledge base Q&A system from PDFs
- build AI agents with a visual workflow editor
- self-host a RAG platform for enterprise knowledge
- orchestrate LLM workflows without code
- add a support assistant trained on company docs
- connect AI agents to tools via MCP
- deploy a private ChatGPT alternative for my team
When to choose
- you want a low-code/visual platform for building knowledge-base chatbots and AI agents
- you need self-hosted deployment with data privacy and enterprise features like SSO and RBAC
- you want built-in document ingestion, parsing, and hybrid retrieval out of the box
- you need to integrate with multiple LLM providers and chat platforms like WeChat, Feishu, or DingTalk
When to avoid
- you only need a lightweight RAG library to embed in your own code rather than a full platform
- you require a fully permissive open-source license - the license is custom with commercial restrictions
- you want to build highly custom agent logic that doesn't fit a node-based workflow model
- you need a headless solution without a web UI
Facets
application · maturity active
rag agent-framework chatbot workflow-automation llm-inference mcp chat-interface web-framework artificial-intelligence large-language-models chatbots self-hosted self-hosted cloud knowledge-base visual-workflow low-code ai-agent-builder enterprise-ai document-parsing openai-compatible-api ai-agents retrieval-augmented-generation knowledge-management docker web-server nodejs
6 sources
- readme: https://github.com/labring/FastGPT · fetched 2026-08-28 · 9488af3a36bc
- homepage: https://fastgpt.io · fetched 2026-08-29 · 5d743bdd92b0
- site_page: https://doc.fastgpt.io/docs/introduction · fetched 2026-08-29 · 1f6f966cc6a0
- site_page: https://fastgpt.io/price · fetched 2026-08-29 · 1bf81e8c9e01
- site_page: https://doc.fastgpt.io/ · fetched 2026-08-29 · 1f6f966cc6a0
- site_page: https://fastgpt.io/faq · fetched 2026-08-29 · 76c2a3e9f40d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| labring/FastGPT | main | 93 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem