> ## Documentation Index > Fetch the complete documentation index at: https://docs.dify.ai/llms.txt > Use this file to discover all available pages before exploring further. # Get Available Models > Retrieve the list of available models by type. Primarily used to query `text-embedding` and `rerank` models for knowledge base configuration. ## OpenAPI ````yaml /en/api-reference/openapi_knowledge.json get /workspaces/current/models/model-types/{model_type} openapi: 3.0.1 info: title: Knowledge API description: >- API for managing knowledge bases, documents, chunks, metadata, and tags, including creation, retrieval, and configuration. **Note:** A single Knowledge Base API key has permission to operate on all visible knowledge bases under the same account. Please pay attention to data security. version: 1.0.0 servers: - url: '{apiBaseUrl}' description: The base URL for the Knowledge API. variables: apiBaseUrl: default: https://api.dify.ai/v1 description: Actual base URL of the API security: - ApiKeyAuth: [] tags: - name: Knowledge Bases description: >- Operations for managing knowledge bases, including creation, configuration, and retrieval. - name: Documents description: >- Operations for creating, updating, and managing documents within a knowledge base. - name: Chunks description: Operations for managing document chunks and child chunks. - name: Metadata description: >- Operations for managing knowledge base metadata fields and document metadata values. - name: Tags description: Operations for managing knowledge base tags and tag bindings. - name: Models description: Operations for retrieving available models. - name: Knowledge Pipeline description: >- Operations for managing and running knowledge pipelines, including datasource plugins and pipeline execution. paths: /workspaces/current/models/model-types/{model_type}: get: tags: - Models summary: Get Available Models description: >- Retrieve the list of available models by type. Primarily used to query `text-embedding` and `rerank` models for knowledge base configuration. operationId: getAvailableModels parameters: - name: model_type in: path required: true schema: type: string enum: - text-embedding - rerank - llm - tts - speech2text - moderation description: >- Type of model to retrieve. For knowledge base configuration, use `text-embedding` for embedding models or `rerank` for reranking models. responses: '200': description: Available models for the specified type. content: application/json: schema: type: object properties: data: type: array description: List of model providers with their available models. items: type: object properties: provider: type: string description: Model provider identifier, e.g. `openai`, `cohere`. label: type: object description: Localized display name of the provider. properties: en_US: type: string description: English display name. zh_Hans: type: string description: Chinese display name. icon_small: type: object description: URL of the provider's small icon. properties: en_US: type: string description: Small icon URL. icon_large: type: object description: URL of the provider's large icon. properties: en_US: type: string description: Large icon URL. status: type: string description: >- Provider status. `active` when credentials are configured and valid. models: type: array description: List of available models from this provider. items: type: object properties: model: type: string description: >- Model identifier. Use this as the `embedding_model` value when creating or updating a knowledge base. label: type: object description: Localized display name of the model. properties: en_US: type: string description: English model name. zh_Hans: type: string description: Chinese model name. model_type: type: string description: >- Type of the model, matching the `model_type` path parameter. features: type: array nullable: true description: >- Supported features of the model, `null` if none. items: type: string fetch_from: type: string description: >- Where the model definition comes from. `predefined-model` for built-in models, `customizable-model` for user-configured models. model_properties: type: object description: >- Model-specific properties such as `context_size`. status: type: string description: >- Model availability status. `active` when ready to use. examples: success: summary: Response Example value: data: - provider: openai label: en_US: OpenAI zh_Hans: OpenAI icon_small: en_US: https://example.com/openai-small.svg icon_large: en_US: https://example.com/openai-large.svg status: active models: - model: text-embedding-3-small label: en_US: text-embedding-3-small zh_Hans: text-embedding-3-small model_type: text-embedding features: null fetch_from: predefined-model model_properties: context_size: 8191 status: active components: securitySchemes: ApiKeyAuth: type: http scheme: bearer bearerFormat: API_KEY description: >- API Key authentication. For all API requests, include your API Key in the `Authorization` HTTP Header, prefixed with `Bearer `. Example: `Authorization: Bearer {API_KEY}`. **Strongly recommend storing your API Key on the server-side, not shared or stored on the client-side, to avoid possible API-Key leakage that can lead to serious consequences.** ````