FastGPT is an AI Agent construction platform written in TypeScript that enables users to build and deploy complex question-answering systems with minimal setup. The platform provides out-of-the-box capabilities including data processing, RAG retrieval, and visual workflow orchestration, allowing developers to create sophisticated applications without extensive configuration.
The repository is actively maintained with significant community engagement.
The platform supports multiple large language models including OpenAI, Claude, Deepseek, and Qwen, with integration capabilities for various AI services. Core features include Agent Skill orchestration, conversation workflows, and plugin workflows with basic RPA nodes. The knowledge base functionality supports multiple file formats including txt, md, html, pdf, docx, pptx, csv, and xlsx, with capabilities for URL reading and CSV batch imports. Users can perform hybrid retrieval with reranking and access knowledge bases through an API interface.
FastGPT offers three deployment options: a cloud service version at fastgpt.io, a community self-hosted version deployable via Docker or Sealos Cloud, and a commercial version with additional features and professional support. The platform includes debugging capabilities such as single-point knowledge base search testing, conversation feedback with citation modification and deletion, and complete call chain logging. Application evaluation and testing features are built in, with plans for advanced orchestration debug modes and application node logging.
FastGPT operates under the FastGPT Open Source License, which permits backend service commercialization but prohibits SaaS offerings without commercial authorization. The platform includes operational capabilities such as login-free sharing windows, iframe embedding, unified conversation record review with data annotation, and application operation logging.
The repository is classified across multiple machine learning and AI development categories including text generation, NLP tools, model deployment, inference optimization, and language model serving. Documentation is available in multiple languages including English, Simplified Chinese, Indonesian, Thai, Vietnamese, and Japanese, reflecting the project's international user base and commitment to accessibility.
