> ## Documentation Index > Fetch the complete documentation index at: https://dify-6c0370d8-fix-template-upload-size-guidance.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Update Knowledge Base > Updates a knowledge base. Only the fields included in the request body are changed. ## OpenAPI ````yaml /en/api-reference/openapi_service.json patch /datasets/{dataset_id} openapi: 3.0.1 info: description: >- REST API for Dify applications and knowledge bases. Application endpoints authenticate with an app API key; knowledge endpoints authenticate with a dataset API key. title: Dify Service API version: 1.0.0 servers: - description: >- Base URL of the Dify Service API. For self-hosted deployments, replace it with your own API base URL. url: https://{api_base_url} variables: api_base_url: default: api.dify.ai/v1 description: Host and path of the API base URL, without the `https://` prefix. security: - ApiKeyAuth: [] tags: - description: Operations related to chat messages and interactions. name: Chat Messages - description: File upload and preview operations. name: Files - description: Operations related to end user information. name: End Users - description: User feedback operations. name: Feedback - description: Operations related to managing conversations. name: Conversations - description: Text-to-Speech and Speech-to-Text operations. name: Audio - description: Operations to retrieve application settings and information. name: Applications - description: Operations related to managing annotations for direct replies. name: Annotations - description: Endpoints for resuming paused workflows that require human input. name: Human Input - description: Operations for executing and managing workflows. name: Workflow Runs - description: Operations related to text generation and completion. name: Completion Messages - description: >- Operations for managing knowledge bases, including creation, configuration, and retrieval. name: Knowledge Bases - description: >- Operations for creating, updating, and managing documents within a knowledge base. name: Documents - description: Operations for managing document chunks and child chunks. name: Chunks - description: >- Operations for managing knowledge base metadata fields and document metadata values. name: Metadata - description: Operations for managing knowledge base tags and tag bindings. name: Tags - description: Operations for retrieving available models. name: Models - description: >- Operations for managing and running knowledge pipelines, including datasource plugins and pipeline execution. name: Knowledge Pipeline paths: /datasets/{dataset_id}: patch: tags: - Knowledge Bases summary: Update Knowledge Base description: >- Updates a knowledge base. Only the fields included in the request body are changed. operationId: updateDataset parameters: - description: >- Knowledge base ID, from [List Knowledge Bases](/en/api-reference/knowledge-bases/list-knowledge-bases). in: path name: dataset_id required: true schema: format: uuid type: string requestBody: content: application/json: schema: properties: description: description: Description of the knowledge base. maxLength: 400 type: string embedding_model: description: >- Embedding model name. Use the `model` field from [Get Available Models](/en/api-reference/models/get-available-models) with `model_type=text-embedding`. type: string embedding_model_provider: description: >- Embedding model provider identifier, formatted as `organization/plugin_name/provider_name` (e.g. `langgenius/openai/openai`). A bare name like `openai` expands to `langgenius//` and works only for langgenius-published plugins. Get valid values from the `provider` field of [Get Available Models](/en/api-reference/models/get-available-models) with `model_type=text-embedding`. type: string external_knowledge_api_id: description: ID of the external knowledge API connection. type: string external_knowledge_id: description: ID of the external knowledge base. type: string external_retrieval_model: description: Retrieval settings for external knowledge bases. properties: score_threshold: description: >- Minimum similarity score threshold for filtering results. type: number score_threshold_enabled: description: Whether score threshold filtering is enabled. type: boolean top_k: description: Maximum number of results to return. type: integer type: object indexing_technique: description: >- `high_quality` uses embedding models for precise search; `economy` uses keyword-based indexing. enum: - high_quality - economy nullable: true type: string name: description: Name of the knowledge base. maxLength: 40 minLength: 1 type: string partial_member_list: description: >- List of team members with access when `permission` is `partial_members`. items: properties: user_id: description: ID of the team member to grant access. type: string type: object type: array permission: description: >- Controls who can access this knowledge base. `only_me` restricts to the creator, `all_team_members` grants access to the entire workspace, `partial_members` grants access to specified members. enum: - only_me - all_team_members - partial_members type: string retrieval_model: $ref: '#/components/schemas/RetrievalModel' description: >- Retrieval model configuration. Controls how chunks are searched and ranked when querying this knowledge base. type: object required: true responses: '200': content: application/json: examples: success: summary: Response Example value: app_count: 0 author_name: admin built_in_field_enabled: true chunk_structure: null created_at: 1741267200 created_by: ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4 data_source_type: null description: Technical documentation for the product API doc_form: text_model doc_metadata: [] document_count: 0 embedding_available: true embedding_model: text-embedding-3-small embedding_model_provider: langgenius/openai/openai enable_api: true external_knowledge_info: null external_retrieval_model: null icon_info: null id: c42e2a6e-40b3-4330-96f8-f1e4d768e8c9 indexing_technique: high_quality is_multimodal: false is_published: false maintainer: admin name: Product Documentation partial_member_list: [] permission: only_me pipeline_id: null provider: vendor retrieval_model_dict: reranking_enable: false reranking_mode: null reranking_model: reranking_model_name: '' reranking_provider_name: '' score_threshold: null score_threshold_enabled: false search_method: semantic_search top_k: 3 weights: null runtime_mode: null summary_index_setting: null tags: [] total_available_documents: 0 total_documents: 0 updated_at: 1741267200 updated_by: ad313dd6-ef04-4dd1-a5b0-c0f0b9e2e7e4 word_count: 0 schema: $ref: '#/components/schemas/Dataset' description: Knowledge base updated successfully. '400': content: application/json: examples: invalid_param: summary: invalid_param value: code: invalid_param message: >- No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider. status: 400 description: >- `invalid_param` : The embedding or reranking model you specified is not configured or available. '403': content: application/json: examples: forbidden_1: summary: forbidden (api access) value: code: forbidden message: Dataset api access is not enabled. status: 403 forbidden_2: summary: forbidden (rate limit) value: code: forbidden message: >- Sorry, you have reached the knowledge base request rate limit of your subscription. status: 403 description: >- - `forbidden` : API access is not enabled for this knowledge base. - `forbidden` : Your subscription's knowledge base request rate limit has been reached. '404': content: application/json: examples: not_found: summary: not_found value: code: not_found message: Dataset not found. status: 404 description: '`not_found` : No knowledge base matches `dataset_id`.' components: schemas: RetrievalModel: properties: metadata_filtering_conditions: description: >- Restrict retrieval to chunks whose document metadata matches the given conditions. Conditions are evaluated server-side against document metadata fields. nullable: true properties: conditions: description: List of metadata conditions to evaluate. items: properties: comparison_operator: description: >- Comparison to apply, by metadata type: - String or array metadata: `contains`, `not contains`, `start with`, `end with`, `is`, `is not`, `empty`, `not empty`, `in`, `not in` - Numeric metadata: `=`, `≠`, `>`, `<`, `≥`, `≤` - Time metadata: `before`, `after` enum: - contains - not contains - start with - end with - is - is not - empty - not empty - in - not in - '=' - ≠ - '>' - < - ≥ - ≤ - before - after type: string name: description: Metadata field name to compare against. type: string value: description: >- Value to compare against. Type depends on `comparison_operator`: string for most string operators, array of strings for `in` and `not in`, number for numeric operators, and omitted for `empty` and `not empty`. nullable: true oneOf: - type: string - items: type: string type: array - type: number required: - name - comparison_operator type: object nullable: true type: array logical_operator: default: and description: How to combine multiple conditions. enum: - and - or nullable: true type: string type: object reranking_enable: description: Whether reranking is enabled. type: boolean reranking_mode: description: Reranking mode. Required when `reranking_enable` is `true`. enum: - reranking_model - weighted_score nullable: true type: string reranking_model: description: Reranking model configuration. properties: reranking_model_name: description: Name of the reranking model. type: string reranking_provider_name: description: >- Reranking model provider identifier, formatted as `organization/plugin_name/provider_name` (e.g. `langgenius/cohere/cohere`). A bare name like `cohere` expands to `langgenius//` and works only for langgenius-published plugins. Get valid values from the `provider` field of [Get Available Models](/en/api-reference/models/get-available-models) with `model_type=rerank`. type: string type: object score_threshold: description: >- Minimum similarity score for results. Only effective when `score_threshold_enabled` is `true`. nullable: true type: number score_threshold_enabled: description: Whether score threshold filtering is enabled. type: boolean search_method: description: Search method used for retrieval. enum: - keyword_search - semantic_search - full_text_search - hybrid_search type: string top_k: description: Maximum number of results to return. type: integer weights: description: Weight configuration for hybrid search. nullable: true properties: keyword_setting: description: Keyword search weight settings. properties: keyword_weight: description: Weight assigned to keyword search results. type: number type: object vector_setting: description: Semantic search weight settings. properties: embedding_model_name: description: Name of the embedding model used for vector search. type: string embedding_provider_name: description: Provider of the embedding model used for vector search. type: string vector_weight: description: Weight assigned to semantic (vector) search results. type: number type: object weight_type: description: Strategy for balancing semantic and keyword search weights. enum: - semantic_first - keyword_first - customized type: string type: object required: - search_method - reranking_enable - top_k - score_threshold_enabled type: object Dataset: properties: app_count: description: Number of applications currently using this knowledge base. type: integer author_name: description: Display name of the creator. type: string built_in_field_enabled: description: >- Whether built-in metadata fields (e.g., `document_name`, `uploader`) are enabled. type: boolean chunk_structure: description: Chunk structure configuration. nullable: true type: string created_at: description: Creation timestamp (Unix epoch in seconds). type: number created_by: description: ID of the user who created the knowledge base. type: string data_source_type: description: Data source type of the documents, `null` if not yet configured. type: string description: description: >- Optional text describing the purpose or contents of the knowledge base. type: string doc_form: description: >- Document chunking mode. `text_model` for standard text chunking, `hierarchical_model` for parent-child structure, `qa_model` for QA pair extraction. type: string doc_metadata: description: Metadata field definitions for the knowledge base. items: properties: id: description: Metadata field identifier. type: string name: description: Metadata field name. type: string type: description: Metadata field value type. type: string type: object type: array document_count: description: Total number of documents in the knowledge base. type: integer embedding_available: description: Whether the configured embedding model is currently available. type: boolean embedding_model: description: Name of the embedding model used for indexing. type: string embedding_model_provider: description: >- Embedding model provider identifier, formatted as `organization/plugin_name/provider_name` (e.g. `langgenius/openai/openai`). Legacy knowledge bases may return the bare short form (e.g. `openai`). type: string enable_api: description: Whether API access is enabled for this knowledge base. type: boolean external_knowledge_info: description: >- Connection details for external knowledge bases. Present when `provider` is `external`. nullable: true properties: external_knowledge_api_endpoint: description: Endpoint URL of the external knowledge API. type: string external_knowledge_api_id: description: ID of the external knowledge API connection. type: string external_knowledge_api_name: description: Display name of the external knowledge API. type: string external_knowledge_id: description: ID of the external knowledge base. type: string type: object external_retrieval_model: description: >- Retrieval settings for external knowledge bases. `null` for internal knowledge bases. nullable: true properties: score_threshold: description: Minimum similarity score threshold. type: number score_threshold_enabled: description: Whether score threshold filtering is enabled. type: boolean top_k: description: >- Maximum number of results to return from the external knowledge base. type: integer type: object icon_info: description: Icon display configuration for the knowledge base. nullable: true properties: icon: description: Icon identifier or emoji. type: string icon_background: description: Background color for the icon. type: string icon_type: description: Type of icon. type: string icon_url: description: URL of a custom icon image. type: string type: object id: description: Unique identifier of the knowledge base. type: string indexing_technique: description: >- `high_quality` uses embedding models for precise search; `economy` uses keyword-based indexing. type: string is_multimodal: description: Whether multimodal content processing is enabled. type: boolean is_published: description: Whether the knowledge base is published. type: boolean maintainer: description: Display name of the knowledge base maintainer. `null` if not set. nullable: true type: string name: description: Display name of the knowledge base. Unique within the workspace. type: string partial_member_list: description: >- Account IDs of members granted access when `permission` is `partial_members`. Always present on the update response; on the detail response, present only when `permission` is `partial_members`. items: type: string nullable: true type: array permission: description: >- Controls who can access this knowledge base. Possible values: `only_me`, `all_team_members`, `partial_members`. type: string pipeline_id: description: Pipeline ID, if a custom processing pipeline is configured. nullable: true type: string provider: description: >- Provider type. `vendor` for internally managed, `external` for external knowledge base connections. type: string retrieval_model_dict: description: Retrieval configuration for the knowledge base. properties: reranking_enable: description: Whether reranking is enabled. type: boolean reranking_mode: description: >- Reranking mode. `reranking_model` for model-based reranking, `weighted_score` for score-based weighting. `null` if reranking is disabled. nullable: true type: string reranking_model: description: Reranking model configuration. properties: reranking_model_name: description: Name of the reranking model. type: string reranking_provider_name: description: >- Reranking model provider identifier, formatted as `organization/plugin_name/provider_name` (e.g. `langgenius/cohere/cohere`). Legacy knowledge bases may return the bare short form (e.g. `cohere`). type: string type: object score_threshold: description: >- Minimum similarity score for results. Only effective when `score_threshold_enabled` is `true`. type: number score_threshold_enabled: description: Whether score threshold filtering is enabled. type: boolean search_method: 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. type: string top_k: description: Maximum number of results to return. type: integer weights: description: Weight configuration for hybrid search. nullable: true properties: keyword_setting: description: Keyword search weight settings. properties: keyword_weight: description: Weight assigned to keyword search results. type: number type: object vector_setting: description: Semantic search weight settings. properties: embedding_model_name: description: Name of the embedding model used for vector search. type: string embedding_provider_name: description: Provider of the embedding model used for vector search. type: string vector_weight: description: Weight assigned to semantic (vector) search results. type: number type: object weight_type: description: Strategy for balancing semantic and keyword search weights. type: string type: object type: object runtime_mode: description: Runtime processing mode. nullable: true type: string summary_index_setting: description: Summary index configuration. nullable: true properties: enable: description: Whether summary indexing is enabled. type: boolean model_name: description: Name of the model used for generating summaries. type: string model_provider_name: description: Provider of the summary generation model. type: string summary_prompt: description: Prompt template used for summary generation. type: string type: object tags: description: Tags associated with this knowledge base. items: properties: id: description: Tag identifier. type: string name: description: Tag name. type: string type: description: Tag type. Always `knowledge` for knowledge base tags. type: string type: object type: array total_available_documents: description: Number of documents that are enabled and available. type: integer total_documents: description: Total number of documents. type: integer updated_at: description: Last update timestamp (Unix epoch in seconds). type: number updated_by: description: ID of the user who last updated the knowledge base. type: string word_count: description: Total word count across all documents. type: integer type: object securitySchemes: ApiKeyAuth: bearerFormat: API_KEY description: >- Every request authenticates with an API key: `Authorization: Bearer {API_KEY}`. App endpoints take an app API key; knowledge endpoints take a knowledge base API key ([Get Started](/en/api-reference/guides/get-started)). Keep keys server-side; never embed them in client code. Requests with a missing or invalid key fail with HTTP `401` (`unauthorized`). scheme: bearer type: http ````