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Basic Information

FastGPT is an AI agent construction platform that provides out-of-the-box building blocks for developing, deploying and operating workflow-driven AI applications. It offers visual Flow orchestration for composing dialogue flows, plugin workflows and RPA nodes, plus data processing and model-calling capabilities to implement complex agent behaviors. The project includes a knowledge-base system and mixed retrieval support for RAG scenarios, multi-model configuration options, OpenAPI-compatible endpoints for completions and CRUD operations, and deployment guides. The repository targets developers and teams who need a full stack to create conversational apps, automated workflows and agent-based services with tooling for debugging, testing and integration with vector databases and document loaders.

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App Details

Features
Visual Flow editor for workflow orchestration including dialogue, plugin and RPA nodes. Agent invocation and two-way MCP support. Knowledge-base management with multi-format ingestion, chunk editing and mixed retrieval. OpenAPI endpoints including chat-style completions and CRUD for knowledge and dialogs. Debugging and testing features such as single-point KB search tests, call-chain logging and editable dialogue references. Deployment guidance including a one-click Sealos option for scalable clusters. Multi-model management and configurable model integrations. UX and ops features like iframe embedding, shareable windows, unified conversation review and template marketplace. Voice input/output support and extensible plugin ecosystem.
Use Cases
FastGPT accelerates building end-to-end AI agent applications by supplying reusable components, visual orchestration and integrated data and retrieval tooling so teams avoid stitching many services together. Its knowledge-base and RAG features simplify ingestion of documents in many formats and enable improved retrieval-augmented responses. OpenAPI endpoints and multi-model configuration make it easier to standardize model calls and expose services. Deployment recipes and support for scalable database and vector stores reduce operational burden. Built-in debugging, conversation review and sharing tools help iterate and operate applications. Community resources, documentation and related projects provide integration and deployment options.

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