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labring/fastgpt

📈 Trending★ 28,060TypeScriptAudience · developerComplexity · 3/5ActiveSetup · moderate

TLDR

Open-source platform for building AI chatbots that answer questions from your own documents, with a visual workflow editor and support for multiple LLMs.

Mindmap

mindmap
  root((FastGPT))
    What it does
      Document processing
      Knowledge base storage
      RAG retrieval
      Chatbot deployment
    Key features
      Visual workflow editor
      Multi-LLM support
      Shareable links
      API access
    Deployment options
      Cloud hosted
      Self-hosted Docker
      Iframe embedding
    Use cases
      Customer support bots
      Internal knowledge assistants
      Document Q&A systems
    Tech stack
      TypeScript
      LLM integrations
      Docker support

Things people build with this

USE CASE 1

Build a customer support chatbot that answers questions from your company's documentation and FAQs.

USE CASE 2

Create an internal knowledge assistant that employees can query to find answers in company wikis and manuals.

USE CASE 3

Deploy a document Q&A system on your website using an embedded iframe to help visitors find information.

USE CASE 4

Connect your chatbot to external tools and APIs to automate workflows like ticket creation or data lookup.

Tech stack

TypeScriptDockerOpenAI APINode.jsReact

Getting it running

Difficulty · moderate Time to first run · 30min

Requires OpenAI API key and Docker to run the full stack locally.

License could not be detected automatically. Check the repository's LICENSE file before use.

In plain English

FastGPT is an open-source platform for building AI-powered question-answering systems using large language models (LLMs, AI models trained on vast amounts of text). It is designed so that non-technical users and developers alike can create chatbots or automated assistants that pull answers from their own documents and data, without deep technical setup. The platform handles several things automatically: it processes your documents (PDFs, Word files, spreadsheets, web pages, and more), stores them in a knowledge base, and uses RAG retrieval (short for Retrieval-Augmented Generation, a technique that fetches relevant pieces of your documents before generating an answer) to give accurate, source-backed responses. You can connect it to multiple AI models, including OpenAI-compatible services and others listed in the topics. One of FastGPT's standout features is its visual workflow editor, where you can drag and drop steps to design how the AI handles a conversation, for example, searching your knowledge base, calling external tools, or collecting user input. You can deploy finished chatbots via a shareable link, embed them as an iframe on a website, or connect them via an API. You can use the hosted cloud version at fastgpt.io or self-host it using Docker with a single command. The codebase is built with TypeScript. It is a good fit for teams or individuals who want a ready-made, customisable AI assistant powered by their own content, without building the retrieval and orchestration layer from scratch.

Copy-paste prompts

Prompt 1
How do I set up FastGPT to create a chatbot that answers questions from my PDF documents?
Prompt 2
Show me how to use the visual workflow editor to add a step that searches my knowledge base and calls an external API.
Prompt 3
What are the steps to self-host FastGPT using Docker on my own server?
Prompt 4
How do I embed a FastGPT chatbot as an iframe on my website and customize its appearance?
Prompt 5
Can I connect FastGPT to multiple LLM providers like OpenAI and others at the same time?
Open on GitHub → Explain another repo

Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.