> ## 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 Knowledge Base > Retrieve detailed information about a specific knowledge base, including its embedding model, retrieval configuration, and document statistics. ## OpenAPI ````yaml /en/api-reference/openapi_knowledge.json get /datasets/{dataset_id} 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: /datasets/{dataset_id}: get: tags: - Knowledge Bases summary: Get Knowledge Base description: >- Retrieve detailed information about a specific knowledge base, including its embedding model, retrieval configuration, and document statistics. operationId: getDatasetDetail parameters: - name: dataset_id in: path required: true schema: type: string format: uuid description: Knowledge base ID. responses: '200': description: Knowledge base details. content: application/json: schema: $ref: '#/components/schemas/Dataset' examples: success: summary: Response Example value: id: c42e2a6e-40b3-4330-96f8-f1e4d768e8c9 name: Product Documentation description: Technical documentation for the product API provider: vendor permission: only_me data_source_type: null indexing_technique: high_quality app_count: 0 document_count: 0 word_count: 0 created_by: ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4 author_name: admin created_at: 1741267200 updated_by: ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4 updated_at: 1741267200 embedding_model: text-embedding-3-small embedding_model_provider: openai embedding_available: true retrieval_model_dict: search_method: semantic_search reranking_enable: false reranking_mode: null reranking_model: reranking_provider_name: '' reranking_model_name: '' weights: null top_k: 3 score_threshold_enabled: false score_threshold: null tags: [] doc_form: text_model external_knowledge_info: null external_retrieval_model: null doc_metadata: [] built_in_field_enabled: true pipeline_id: null runtime_mode: null chunk_structure: null icon_info: null summary_index_setting: null is_published: false total_documents: 0 total_available_documents: 0 enable_api: true is_multimodal: false '403': description: >- `forbidden` : Insufficient permissions to access this knowledge base. content: application/json: examples: forbidden: summary: forbidden value: status: 403 code: forbidden message: Insufficient permissions to access this knowledge base. '404': description: '`not_found` : Dataset not found.' content: application/json: examples: not_found: summary: not_found value: status: 404 code: not_found message: Dataset not found. components: schemas: Dataset: type: object properties: id: type: string description: Unique identifier of the knowledge base. name: type: string description: Display name of the knowledge base. Unique within the workspace. description: type: string description: >- Optional text describing the purpose or contents of the knowledge base. provider: type: string description: >- Provider type. `vendor` for internally managed, `external` for external knowledge base connections. permission: type: string description: >- Controls who can access this knowledge base. Possible values: `only_me`, `all_team_members`, `partial_members`. data_source_type: type: string description: Data source type of the documents, `null` if not yet configured. indexing_technique: type: string description: >- `high_quality` uses embedding models for precise search; `economy` uses keyword-based indexing. app_count: type: integer description: Number of applications currently using this knowledge base. document_count: type: integer description: Total number of documents in the knowledge base. word_count: type: integer description: Total word count across all documents. created_by: type: string description: ID of the user who created the knowledge base. author_name: type: string description: Display name of the creator. created_at: type: number description: Creation timestamp (Unix epoch in seconds). updated_by: type: string description: ID of the user who last updated the knowledge base. updated_at: type: number description: Last update timestamp (Unix epoch in seconds). embedding_model: type: string description: Name of the embedding model used for indexing. embedding_model_provider: type: string description: >- Embedding model provider. Use the `provider` field from [Get Available Models](/api-reference/models/get-available-models) with `model_type=text-embedding`. embedding_available: type: boolean description: Whether the configured embedding model is currently available. retrieval_model_dict: type: object description: Retrieval configuration for the knowledge base. properties: search_method: type: string description: >- Search method used for retrieval. `keyword_search` for keyword matching, `semantic_search` for embedding-based similarity, `full_text_search` for full-text indexing, `hybrid_search` for a combination of semantic and keyword approaches. reranking_enable: type: boolean description: Whether reranking is enabled. reranking_mode: type: string nullable: true description: >- Reranking mode. `reranking_model` for model-based reranking, `weighted_score` for score-based weighting. `null` if reranking is disabled. reranking_model: type: object description: Reranking model configuration. properties: reranking_provider_name: type: string description: Provider name of the reranking model. reranking_model_name: type: string description: Name of the reranking model. weights: type: object nullable: true description: Weight configuration for hybrid search. properties: weight_type: type: string description: Strategy for balancing semantic and keyword search weights. vector_setting: type: object description: Semantic search weight settings. properties: vector_weight: type: number description: Weight assigned to semantic (vector) search results. embedding_provider_name: type: string description: Provider of the embedding model used for vector search. embedding_model_name: type: string description: Name of the embedding model used for vector search. keyword_setting: type: object description: Keyword search weight settings. properties: keyword_weight: type: number description: Weight assigned to keyword search results. top_k: type: integer description: Maximum number of results to return. score_threshold_enabled: type: boolean description: Whether score threshold filtering is enabled. score_threshold: type: number description: >- Minimum similarity score for results. Only effective when `score_threshold_enabled` is `true`. summary_index_setting: type: object nullable: true description: Summary index configuration. properties: enable: type: boolean description: Whether summary indexing is enabled. model_name: type: string description: Name of the model used for generating summaries. model_provider_name: type: string description: Provider of the summary generation model. summary_prompt: type: string description: Prompt template used for summary generation. tags: type: array description: Tags associated with this knowledge base. items: type: object properties: id: type: string description: Tag identifier. name: type: string description: Tag name. type: type: string description: Tag type. Always `knowledge` for knowledge base tags. doc_form: type: string description: >- Document chunking mode. `text_model` for standard text chunking, `hierarchical_model` for parent-child structure, `qa_model` for QA pair extraction. external_knowledge_info: type: object nullable: true description: >- Connection details for external knowledge bases. Present when `provider` is `external`. properties: external_knowledge_id: type: string description: ID of the external knowledge base. external_knowledge_api_id: type: string description: ID of the external knowledge API connection. external_knowledge_api_name: type: string description: Display name of the external knowledge API. external_knowledge_api_endpoint: type: string description: Endpoint URL of the external knowledge API. external_retrieval_model: type: object nullable: true description: >- Retrieval settings for external knowledge bases. `null` for internal knowledge bases. properties: top_k: type: integer description: >- Maximum number of results to return from the external knowledge base. score_threshold: type: number description: Minimum similarity score threshold. score_threshold_enabled: type: boolean description: Whether score threshold filtering is enabled. doc_metadata: type: array description: Metadata field definitions for the knowledge base. items: type: object properties: id: type: string description: Metadata field identifier. name: type: string description: Metadata field name. type: type: string description: Metadata field value type. built_in_field_enabled: type: boolean description: >- Whether built-in metadata fields (e.g., `document_name`, `uploader`) are enabled. pipeline_id: type: string nullable: true description: Pipeline ID, if a custom processing pipeline is configured. runtime_mode: type: string nullable: true description: Runtime processing mode. chunk_structure: type: string nullable: true description: Chunk structure configuration. icon_info: type: object nullable: true description: Icon display configuration for the knowledge base. properties: icon_type: type: string description: Type of icon. icon: type: string description: Icon identifier or emoji. icon_background: type: string description: Background color for the icon. icon_url: type: string description: URL of a custom icon image. is_published: type: boolean description: Whether the knowledge base is published. total_documents: type: integer description: Total number of documents. total_available_documents: type: integer description: Number of documents that are enabled and available. enable_api: type: boolean description: Whether API access is enabled for this knowledge base. is_multimodal: type: boolean description: Whether multimodal content processing is enabled. 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.** ````