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LangBot provides a set of RESTful APIs for external services to integrate and automate management. These APIs are authenticated with API keys, which are a subset of the HTTP API.
Service API is currently in Beta and some APIs may change frequently.

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Get API Key

Click the API Keys button in the sidebar of the WebUI to create an API Key. create_api_key After creation, copy the API Key and save it. copy_api_key

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Authentication

All Service APIs support two authentication methods:
  • API Key: Via X-API-Key: <your-key> or Authorization: Bearer <your-key> header
  • User Token: Via Authorization: Bearer <user-token> header (obtained after login)

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Use API

The left sidebar lists all available APIs. You can fill in your instance address (the port address exposed by the backend, default is http://localhost:5300) and API Key, then click the Try it out button to call the API.

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Core Concepts

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Provider + Model Architecture

LangBot uses a Provider + Model two-layer architecture for AI model management:
  • Provider: Defines the API endpoint (base_url), requester type, and API keys. A single provider can be associated with multiple models.
  • Model: Associated with a provider (via provider_uuid), defining the specific model name and parameters. Models inherit the provider’s API endpoint and keys.
Provider (OpenAI)
├── base_url: https://api.openai.com/v1
├── api_keys: [sk-xxx]
├── LLM: gpt-4o
├── LLM: gpt-4o-mini
└── Embedding: text-embedding-3-small
This architecture allows you to manage multiple models under a single provider, sharing API configuration and avoiding redundant key entries.

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Requester

A requester defines the communication protocol with AI services. Use GET /api/v1/provider/requesters to list available requesters. Common requesters include:
  • openai-chat-completions — OpenAI-compatible chat completions API (also works with SiliconFlow, DeepSeek, etc.)
  • anthropic-messages — Anthropic Claude API
  • openai-embeddings — OpenAI-compatible embeddings API

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Async Tasks

Some operations (plugin install/delete/upgrade) run asynchronously and return a task_id. You can track progress in the WebUI.