> ## 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 (add + cognify + improve) > 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. - **raw_data** (Optional[List[str]]): String inputs, one entry each: raw text, a local file or directory path on the server (requires ACCEPT_LOCAL_FILE_PATH), a web URL fetched as a page (requires ALLOW_HTTP_REQUESTS), or a GitHub/GitLab repository URL, shallow-cloned and indexed as a code graph. Uploads come first, then raw_data entries; labels and external_metadata pair with that combined order. Normal ingestion only — rejected with content_type. At least one of data or raw_data is required for normal ingestion. - **labels** (Optional[str]): JSON array of per-file labels, e.g. ["finance", "people", ""], paired positionally with the uploaded files (one entry per file; an empty entry skips that file). Stored on each file's data record. Normal ingestion only — rejected with session_id or content_type. - **external_metadata** (Optional[str]): JSON array of per-file metadata objects, e.g. [\{"source": "crm"\}, null], paired positionally with the uploaded files (one entry per file; null or \{\} skips that file). Merged into each file's stored external_metadata. Normal ingestion only — rejected with session_id or content_type. - **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). - **self_improvement** (Optional[bool]): Run the improve loop after cognify (default: True). False gives a plain add + cognify ingestion. - **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, or "code" to index whole repositories — each raw_data entry is then a git URL or server-local repo path and one code graph is built per entry (poll progress via GET /v1/datasets/status?pipeline=code_graph_pipeline); omit for normal ingestion. - **index_vectors** (Optional[bool]): content_type="code" only — also embed the extracted code facts for semantic retrievers (default false, no LLM/embedding calls otherwise). Either datasetName or datasetId must be provided. - **import_mode** (Optional[str]): COGX archive imports only: 'preserve' (default), 'hybrid', or 're-derive'. - **skill_name** (Optional[str]): content_type='skills' + skills_text only: name/slug for the inline skill (defaults to 'skill'). - **skills_text** (Optional[str]): 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. ## Error Codes - **400 Bad Request**: Neither datasetId nor datasetName provided, unsupported content_type, invalid graph_model JSON/schema, or invalid code-ingestion combination (no raw_data repository specs, file uploads or session_id with content_type="code", index_vectors without it, or local repo paths while ACCEPT_LOCAL_FILE_PATH=false) - **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://{tenant}.aws.cognee.ai description: 'Cognee Cloud: your tenant pod, named in the platform.cognee.ai dashboard' variables: tenant: default: your-tenant description: Your tenant name, shown in the Cognee Cloud dashboard - url: http://localhost:8000 description: 'Self-hosted: a locally running cognee server' security: - BearerAuth: [] - ApiKeyAuth: [] tags: - name: activity description: >- Activity endpoints for inspecting pipeline runs, traced spans, tenant users, agents, and dataset exports. - name: add description: Data ingestion endpoints for adding text, files, and structured data. - name: agent connections description: >- Endpoints for registering, unregistering, and inspecting agent connections to the instance. - name: agent management description: Endpoints for creating, listing, retrieving, and deleting agents. - name: auth description: >- Authentication endpoints for user registration, login, and token management. - name: checks description: >- Diagnostic endpoint for validating a Cognee Cloud API key supplied in the X-Api-Key header. - name: cognify description: >- Knowledge processing endpoints to transform raw data into knowledge graphs. - name: configuration description: >- Endpoints for storing, retrieving, and listing a user's saved configurations. - 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: Endpoint for removing data from the knowledge graph. - name: health description: Liveness, readiness, and component health checks. - name: improve description: Endpoint for enriching and improving an existing knowledge graph. - name: integrations description: >- Endpoints for connecting, provisioning, and disconnecting OAuth providers and plugins. - name: llm description: >- LLM-backed endpoints for inferring graph schemas and generating custom extraction prompts. - name: memify description: >- Endpoint for running enrichment pipelines over existing graphs or supplied data. - name: ontologies description: >- Endpoints for uploading, listing, and deleting ontology files used during cognify. - name: permissions description: Permission management for multi-user access control. - name: recall description: >- Endpoints for querying the knowledge graph and reviewing past recall history. - name: remember description: >- Endpoints for ingesting data into the knowledge graph and storing session memory entries. - name: responses description: Response generation endpoints using the knowledge graph. - name: schema description: >- Schema inspection endpoints for a dataset's derived schema inventory and the caller-wide memory provenance graph. - name: search description: Search endpoints for querying the knowledge graph. - name: sessions description: >- Endpoints for listing sessions and reporting usage, cost, and token statistics. - name: settings description: Configuration endpoints for managing Cognee settings. - name: skills description: >- Skill management endpoints for ingesting, listing, retrieving, and deleting dataset skills, plus read-only retrieval of improvement proposals. - name: slack description: >- Endpoints for listing workspace channels, setting channel allowlists, and linking Slack accounts. - name: sync description: Endpoints for syncing local data to Cognee Cloud and checking sync status. - name: update description: Endpoint for updating existing data in a dataset. - name: users description: User management endpoints. - name: validate description: >- Diagnostic endpoint for checking consistency between a dataset's graph and vector stores. - name: visualize description: Graph visualization endpoints. paths: /api/v1/remember: post: tags: - remember summary: >- Remember: ingest data and build the knowledge graph (add + cognify + improve) 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. - **raw_data** (Optional[List[str]]): String inputs, one entry each: raw text, a local file or directory path on the server (requires ACCEPT_LOCAL_FILE_PATH), a web URL fetched as a page (requires ALLOW_HTTP_REQUESTS), or a GitHub/GitLab repository URL, shallow-cloned and indexed as a code graph. Uploads come first, then raw_data entries; labels and external_metadata pair with that combined order. Normal ingestion only — rejected with content_type. At least one of data or raw_data is required for normal ingestion. - **labels** (Optional[str]): JSON array of per-file labels, e.g. ["finance", "people", ""], paired positionally with the uploaded files (one entry per file; an empty entry skips that file). Stored on each file's data record. Normal ingestion only — rejected with session_id or content_type. - **external_metadata** (Optional[str]): JSON array of per-file metadata objects, e.g. [\{"source": "crm"\}, null], paired positionally with the uploaded files (one entry per file; null or \{\} skips that file). Merged into each file's stored external_metadata. Normal ingestion only — rejected with session_id or content_type. - **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). - **self_improvement** (Optional[bool]): Run the improve loop after cognify (default: True). False gives a plain add + cognify ingestion. - **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, or "code" to index whole repositories — each raw_data entry is then a git URL or server-local repo path and one code graph is built per entry (poll progress via GET /v1/datasets/status?pipeline=code_graph_pipeline); omit for normal ingestion. - **index_vectors** (Optional[bool]): content_type="code" only — also embed the extracted code facts for semantic retrievers (default false, no LLM/embedding calls otherwise). Either datasetName or datasetId must be provided. - **import_mode** (Optional[str]): COGX archive imports only: 'preserve' (default), 'hybrid', or 're-derive'. - **skill_name** (Optional[str]): content_type='skills' + skills_text only: name/slug for the inline skill (defaults to 'skill'). - **skills_text** (Optional[str]): 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. ## Error Codes - **400 Bad Request**: Neither datasetId nor datasetName provided, unsupported content_type, invalid graph_model JSON/schema, or invalid code-ingestion combination (no raw_data repository specs, file uploads or session_id with content_type="code", index_vectors without it, or local repo paths while ACCEPT_LOCAL_FILE_PATH=false) - **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 raw_data: anyOf: - items: type: string example: '' type: array - type: 'null' title: Raw Data description: >- Data given as strings instead of uploads, one entry each: raw text to remember, a local file or directory path on the server's filesystem (requires ACCEPT_LOCAL_FILE_PATH), a web URL to fetch (requires ALLOW_HTTP_REQUESTS), or a GitHub/GitLab repository URL, which is shallow-cloned and indexed as a code graph. Combined with 'data': uploads come first, then these entries; labels and external_metadata pair with that combined order. Empty entries are ignored. With content_type='code' every entry is a repository spec (git URL or server-local repo path) and one code graph is built per entry; rejected with content_type='skills' or 'cogx-archive', which take file uploads. examples: - [] labels: anyOf: - type: string - type: 'null' title: Labels description: >- Per-file labels, e.g. ["finance", "people", ""] — the Nth label applies to the Nth uploaded file, one entry per file, an empty entry skips that file. The comma-separated form "finance,people," is accepted equivalently (it is what Swagger UI sends when you type a JSON array here), so labels cannot contain commas unless the client sends real JSON. Stored on each file's data record and returned when listing dataset data. Only supported for normal ingestion — rejected when combined with session_id or content_type. examples: - '' external_metadata: anyOf: - type: string - type: 'null' title: External Metadata description: >- JSON array of per-file metadata objects, e.g. [\{"source": "crm", "ticket": 42\}, null]. Paired positionally like labels: the Nth entry applies to the Nth uploaded file (null or \{\} skips that file), and one entry per file is required when any is given. Merged into the file's stored external_metadata (your keys win over loader-derived ones; 'node_set' is reserved). Only supported for normal ingestion — rejected when combined with session_id or content_type. examples: - '' 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: - [] 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 self_improvement: anyOf: - type: boolean - type: 'null' title: Self Improvement description: >- Run the self-improvement loop (improve) after the knowledge graph is built: triplet enrichment and, for session-backed data, the session bridge. Set to false for a plain add + cognify ingestion. Ignored with session_id. default: true 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, or 'code' to index whole code repositories (pass git URLs or server-local repo paths via 'raw_data') as an architectural code graph through the enola-backed pipeline. 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: - '' index_vectors: anyOf: - type: boolean - type: 'null' title: Index Vectors description: >- content_type='code' only: also embed the extracted code facts so semantic/completion retrievers can see them (requires an embedding provider). Default false — the code graph pipeline is deterministic and makes no LLM or embedding calls, and SearchType.CODE uses graph indexes only. default: false 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 ````