This reference page outlines core technical concepts for FastGPT plugins, tailored for engineers and technical decision makers evaluating or deploying FastGPT plugin-enabled systems.
Core Plugin Terminology Table
The following table defines standard FastGPT plugin terms:
| Term | Description |
|---|---|
| Plugin | An independent, reusable feature component. Plugins can have different types, such as tools, model presets, and Dataset sources. |
| Plugin Package | The packaged .pkg file for a plugin. All plugin types are installed, updated, and managed through plugin packages. |
| Tool | A plugin type that usually wraps third-party services, internal APIs, or local computation and can be called by workflows and Agents. |
| Toolkit | A plugin that exposes multiple related child tools while sharing plugin metadata and secret configuration. |
| Plugin Marketplace | A centralized platform where users can search, download, and install plugins. |
| Runtime | The backend implementation responsible for executing plugin code. The current default runtime is local-pool. |
| Pod | A single plugin child process in the local process pool. One plugin service can own multiple Pods. |
Plugin Type Functional Roles
Plugins are categorized by their intended use case within the FastGPT ecosystem:
- Tool plugins: Wrap third-party services, internal APIs, or local computational tasks, and are callable directly by FastGPT workflows and AI Agents.
- Toolkit plugins: Aggregate multiple related tool plugins, sharing unified plugin metadata and secret configuration across all included child tools to reduce redundant setup.
- Specialized plugin types: Including model presets and Dataset source plugins, which extend core FastGPT functionality beyond external service integration.
Runtime and Pod Architecture
The FastGPT plugin runtime provides the backend execution layer for all plugin code. The default runtime environment is local-pool, which manages a pool of isolated child processes called Pods. Each Pod represents a single running instance of a plugin service, and a single plugin service can deploy multiple Pods to support varying levels of concurrent plugin invocation demand.
Source: FastGPT official source
Applicability and version scope
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Safety guardrails
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Rollback guidance
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