What it is

FastGPT is an open-source AI knowledge base platform built on large language models (LLMs). It provides integrated tools for data ingestion, vector retrieval (RAG), and visual workflow orchestration, enabling users to construct and deploy question-answering applications without writing extensive backend code. The platform runs on Next.js and supports integration with multiple LLM providers including OpenAI, Claude, DeepSeek, Qwen, and others.

It solves the problem of high-friction AI application development by abstracting away infrastructure complexity. Developers and teams can avoid building custom data pipelines, embedding services, or retrieval logic from scratch, and instead use its visual editor (Flow) to assemble AI workflows. This reduces time-to-deployment for knowledge-intensive applications like internal chatbots, documentation assistants, or customer support agents.

Key capabilities

• Ingest and preprocess multiple document formats (PDF, DOCX, HTML, Markdown, etc.) into structured knowledge bases
• Perform hybrid retrieval using vector search and keyword matching via RAG
• Visual workflow orchestration with Flow editor for chaining LLM calls, tools, and conditional logic
• Support for multi-model routing and fallback with integrated proxy (AI Proxy) for cost and latency optimization
• Expose APIs for integration with external systems via OpenAPI-compliant endpoints
• Deploy as a self-hosted service using Docker or via Sealos cloud infrastructure
• Support for agent-style interactions with tool-calling capabilities (MCP, function calling)

Who uses it and how

• Internal teams build enterprise knowledge bases for employee-facing Q&A systems using company documents
• Startups and developers prototype AI chatbots and automated agents without managing vector DB or LLM integrations
• SaaS vendors embed FastGPT as a backend for customer support or onboarding bots, using its API layer

Getting started

Install via Docker using the official image and run bash to pull and configure the service; alternatively deploy to Sealos for managed hosting. The project is available on npm and GitHub, with local development guided by documented setup steps.

When to use it — and when not to

FastGPT replaces paid platforms like Notion AI or custom RAG stacks by offering similar functionality with self-hosting control, but requires managing infrastructure (PostgreSQL, vector store, object storage, SMTP if email notifications needed). It is unsuitable for users needing fully managed SaaS without self-operation or those requiring strict compliance with non-commercial licenses (the license prohibits SaaS redistribution). For simple single-model chat apps, lighter frameworks may suffice; FastGPT shines when complex, multi-step AI workflows and knowledge grounding are needed.

# 输入命令拉取配置文件
bash <(curl -fsSL https://doc.fastgpt.io/deploy/install.sh)
# 启动
docker compose up -d

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