> ## Documentation Index > Fetch the complete documentation index at: https://docs.cognee.ai/llms.txt > Use this file to discover all available pages before exploring further. # Remember > Ingest data and build the knowledge graph in a single call. This endpoint combines the add and cognify steps. Data is ingested first, then automatically processed into a structured knowledge graph. ## Request Parameters - **data** (List[UploadFile]): Files to upload and process. - **datasetName** (Optional[str]): Name of the target dataset. - **datasetId** (Optional[UUID]): UUID of an existing dataset. - **session_id** (Optional[str]): Session to attribute this memory to. When set, data is stored in the session cache and bridged into the permanent graph in the background; the session is tracked in the sessions dashboard. When omitted, data is ingested directly via add + cognify. - **node_set** (Optional[List[str]]): Node identifiers for graph organisation. - **run_in_background** (Optional[bool]): Run the cognify step asynchronously (default: False). - **custom_prompt** (Optional[str]): Custom prompt for entity extraction. - **chunk_size** (Optional[int]): Maximum tokens per chunk (default: 4096). - **chunks_per_batch** (Optional[int]): Chunks per cognify batch. - **ontology_key** (Optional[List[str]]): Reference to one or more previously uploaded ontology files to use for knowledge graph construction. - **graph_model** (Optional[str]): JSON-serialised graph model schema (same dict format accepted by the cognify endpoint). - **content_type** (Optional[str]): Set to "skills" to ingest SKILL.md files as Skill nodes; omit for normal ingestion. Either datasetName or datasetId must be provided. ## Error Codes - **400 Bad Request**: Neither datasetId nor datasetName provided, unsupported content_type, or invalid graph_model JSON/schema - **409 Conflict**: Error during processing ## OpenAPI ````yaml /cognee_openapi_spec.json post /api/v1/remember openapi: 3.1.0 info: title: Cognee API description: Cognee API with Bearer token and Cookie auth version: 1.0.0 servers: - url: https://api.cognee.ai description: Production server (full functionality) - url: http://localhost:8000 description: Local development server (requires local setup) security: - BearerAuth: [] - ApiKeyAuth: [] tags: - name: activity description: '' - name: add description: Data ingestion endpoints for adding text, files, and structured data. - name: agent connections description: '' - name: agent management description: '' - name: auth description: >- Authentication endpoints for user registration, login, and token management. - name: checks description: '' - name: cognify description: >- Knowledge processing endpoints to transform raw data into knowledge graphs. - name: configuration description: '' - name: datasets description: Dataset management endpoints for listing, creating, and deleting datasets. - name: delete description: Data deletion endpoints (deprecated — use datasets endpoints instead). - name: forget description: '' - name: health description: '' - name: improve description: '' - name: llm description: '' - name: memify description: '' - name: ontologies description: '' - name: permissions description: Permission management for multi-user access control. - name: recall description: '' - name: remember description: '' - name: responses description: Response generation endpoints using the knowledge graph. - name: schema description: '' - name: search description: Search endpoints for querying the knowledge graph. - name: sessions description: '' - name: settings description: Configuration endpoints for managing Cognee settings. - name: skills description: '' - name: sync description: '' - name: update description: '' - name: users description: User management endpoints. - name: visualize description: Graph visualization endpoints. paths: /api/v1/remember: post: tags: - remember summary: Remember description: >- Ingest data and build the knowledge graph in a single call. This endpoint combines the add and cognify steps. Data is ingested first, then automatically processed into a structured knowledge graph. ## Request Parameters - **data** (List[UploadFile]): Files to upload and process. - **datasetName** (Optional[str]): Name of the target dataset. - **datasetId** (Optional[UUID]): UUID of an existing dataset. - **session_id** (Optional[str]): Session to attribute this memory to. When set, data is stored in the session cache and bridged into the permanent graph in the background; the session is tracked in the sessions dashboard. When omitted, data is ingested directly via add + cognify. - **node_set** (Optional[List[str]]): Node identifiers for graph organisation. - **run_in_background** (Optional[bool]): Run the cognify step asynchronously (default: False). - **custom_prompt** (Optional[str]): Custom prompt for entity extraction. - **chunk_size** (Optional[int]): Maximum tokens per chunk (default: 4096). - **chunks_per_batch** (Optional[int]): Chunks per cognify batch. - **ontology_key** (Optional[List[str]]): Reference to one or more previously uploaded ontology files to use for knowledge graph construction. - **graph_model** (Optional[str]): JSON-serialised graph model schema (same dict format accepted by the cognify endpoint). - **content_type** (Optional[str]): Set to "skills" to ingest SKILL.md files as Skill nodes; omit for normal ingestion. Either datasetName or datasetId must be provided. ## Error Codes - **400 Bad Request**: Neither datasetId nor datasetName provided, unsupported content_type, or invalid graph_model JSON/schema - **409 Conflict**: Error during processing operationId: remember_api_v1_remember_post requestBody: content: multipart/form-data: schema: $ref: '#/components/schemas/Body_remember_api_v1_remember_post' responses: '200': description: Successful Response content: application/json: schema: additionalProperties: true type: object title: Response Remember Api V1 Remember Post '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - BearerAuth: [] - ApiKeyAuth: [] components: schemas: Body_remember_api_v1_remember_post: properties: data: items: type: string format: binary type: array title: Data datasetName: anyOf: - type: string - type: 'null' title: Datasetname description: >- Name of the target dataset (created if it does not exist). Required unless datasetId is provided. examples: - default_dataset datasetId: anyOf: - type: string format: uuid - type: string const: '' - type: 'null' title: Datasetid examples: - '' session_id: anyOf: - type: string - type: 'null' title: Session Id description: >- Session to attribute this memory to (e.g. claude-code-1718000000). When set, the data is stored in the session cache (and bridged into the permanent graph in the background) and the session appears in the sessions dashboard. Leave empty for a direct add+cognify. examples: - '' node_set: anyOf: - items: type: string example: '' type: array - type: 'null' title: Node Set description: >- Tags the ingested data with named node sets (e.g. per-agent or per-project groups). Extracted graph nodes are linked to these sets, and recall/search can later be restricted to them via their node_name parameter. Leave empty to skip tagging. examples: - null run_in_background: anyOf: - type: boolean - type: 'null' title: Run In Background description: >- If true, the request returns immediately (status 'running' with a pipeline_run_id) while ingestion and graph building continue server-side — poll GET /v1/datasets/status to track completion. If false, the request blocks until the knowledge graph is fully built, which can take minutes for large files. default: false custom_prompt: anyOf: - type: string - type: 'null' title: Custom Prompt description: >- Replaces the default entity-extraction prompt used during graph building. Use it to steer which entities and relationships get extracted (e.g. focus on technical concepts, people, or contracts). Leave empty for the default prompt. default: '' chunk_size: anyOf: - type: integer - type: 'null' title: Chunk Size description: >- Maximum tokens per text chunk during ingestion (default: 4096). Each chunk is processed by the LLM separately for entity extraction: larger chunks give more context per extraction but fewer, coarser passes; smaller chunks give finer-grained extraction at higher LLM cost. default: 4096 chunks_per_batch: anyOf: - type: integer - type: 'null' title: Chunks Per Batch description: >- Number of chunks processed per cognify task batch (default: 36). Controls ingestion parallelism/throughput; rarely needs changing. default: 36 ontology_key: anyOf: - items: type: string example: '' type: array - type: 'null' title: Ontology Key description: >- Keys of previously uploaded ontologies (see /v1/ontologies) to ground entity extraction. Leave empty to ingest without an ontology. examples: - [] graph_model: anyOf: - type: string - type: 'null' title: Graph Model description: >- JSON-serialised graph model schema (same format as the cognify endpoint), e.g. {"title": "CompanyGraph", "type": "object", "properties": {...}}. Must include a top-level 'title' key. Leave empty to use the default KnowledgeGraph model — a restrictive schema here can produce an empty graph. Invalid JSON or an unconvertible schema is rejected with 400. examples: - '' content_type: anyOf: - type: string - type: 'null' title: Content Type description: >- Set to 'skills' to ingest SKILL.md files as dataset-scoped Skill nodes. Only supported value: 'skills'; leave empty for normal ingestion. examples: - '' import_mode: anyOf: - type: string - type: 'null' title: Import Mode description: >- COGX archive imports only: 'preserve' (default), 'hybrid', or 're-derive'. examples: - '' skills_text: anyOf: - type: string - type: 'null' title: Skills Text description: >- content_type='skills' only: inline SKILL.md markdown to ingest without a file upload (no-code path). When set and no files are uploaded, it is written to a temporary SKILL.md and ingested via the normal skills pipeline. Pair with skill_name to control the resulting skill name. examples: - '' skill_name: anyOf: - type: string - type: 'null' title: Skill Name description: >- content_type='skills' + skills_text only: name/slug for the inline skill (defaults to 'skill'). examples: - '' type: object title: Body_remember_api_v1_remember_post HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context type: object required: - loc - msg - type title: ValidationError securitySchemes: BearerAuth: type: http scheme: bearer bearerFormat: JWT ApiKeyAuth: type: apiKey in: header name: X-Api-Key ````