Seekr Vector database API

openapi: 3.2.0
info:
  title: SeekrFlow Vector database API
  description: SeekrFlow API Documentation
  termsOfService: http://www.seekr.com/support
  contact:
    name: Seekr API Support
    url: http://www.seekr.com/contact
    email: contact@seekr.com
  version: 5.108.1
servers:
- url: https://flow.seekr.com
  description: SeekrBuild server base URL
tags:
- name: Vector database
paths:
  /v1/flow/vectordb:
    post:
      tags:
      - Vector database
      summary: Create Vector Database Route
      description: Create a new vector database
      operationId: create_vector_database_route_v1_flow_vectordb_post
      security:
      - APIKeyHeader: []
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/VectorDatabaseCreate'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    get:
      tags:
      - Vector database
      summary: List Vector Databases
      description: List all vector databases for the user
      operationId: list_vector_databases_v1_flow_vectordb_get
      security:
      - APIKeyHeader: []
      parameters:
      - name: types
        in: query
        required: false
        schema:
          anyOf:
          - type: array
            items:
              $ref: '#/components/schemas/DBType'
          - type: 'null'
          title: Types
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseList'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}:
    delete:
      tags:
      - Vector database
      summary: Delete Vector Database Route
      description: Delete a vector database
      operationId: delete_vector_database_route_v1_flow_vectordb__database_id__delete
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseDeleteResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    get:
      tags:
      - Vector database
      summary: Get Vector Database Route
      description: Get a specific vector database
      operationId: get_vector_database_route_v1_flow_vectordb__database_id__get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    patch:
      tags:
      - Vector database
      summary: Update Vector Database Route
      description: Update a vector database name and/or description
      operationId: update_vector_database_route_v1_flow_vectordb__database_id__patch
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UpdateVectorDbRequest'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/tools:
    get:
      tags:
      - Vector database
      summary: Get Tools For Vector Database
      description: List IDs of FILE_SEARCH tools that reference this vector database.
      operationId: get_tools_for_vector_database_v1_flow_vectordb__database_id__tools_get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/IdList'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/data-jobs:
    get:
      tags:
      - Vector database
      summary: Get Data Jobs For Vector Database
      description: List IDs of data jobs that reference this vector database.
      operationId: get_data_jobs_for_vector_database_v1_flow_vectordb__database_id__data_jobs_get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/IdList'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/ingestion:
    post:
      tags:
      - Vector database
      summary: Create Vector Database Ingestion Job
      description: 'Create a new vector database ingestion job.


        **`method` — document extraction strategy:**

        - `accuracy-optimized` *(default)* — runs the full Seekr pipeline (up to 12 methods: bookmark-aware hybrid extraction, Seekr-SaaS OCR, LLM post-processing, PyMuPDF, and more) with no restrictions, always selecting the highest-quality result

        - `speed-optimized` — same pipeline, but skips methods that exceed per-method word-count thresholds; significantly faster on large documents


        **`chunking_method` — text splitting strategy:**

        - `markdown` *(default)* — heading-hierarchy-aware splitting with intelligent table handling (repeats table headers across continuation chunks so every chunk is self-contained)

        - `semantic` — spaCy sentence detection + paragraph embeddings + Ward hierarchical clustering; groups content by meaning rather than position for higher answer quality on complex QA workloads

        - `sliding` — fixed-size overlapping windows; fast and predictable, best for plain-text or homogeneous content


        **`token_count`** — target maximum tokens per chunk (default 800).


        **`overlap_tokens`** — tokens repeated between consecutive chunks to preserve context (default 100).


        **`metadata`** — optional flat JSON object attached to every chunk produced by this job.

        - Must be a flat object (no nested objects or arrays).

        - Values must be `string`, `number`, `boolean`, or `null`. Null values are silently dropped.

        - Maximum **20 fields**.

        - String values are trimmed of whitespace; newlines are replaced with spaces.


        Returns 400 if metadata fails validation. The job is not started until validation passes.'
      operationId: create_vector_database_ingestion_job_v1_flow_vectordb__database_id__ingestion_post
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/VectorDatabaseIngestionRequest'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseIngestionResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    get:
      tags:
      - Vector database
      summary: List Vector Database Ingestion Jobs
      description: List all vector database ingestion jobs
      operationId: list_vector_database_ingestion_jobs_v1_flow_vectordb__database_id__ingestion_get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseIngestionList'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/ingestion/{job_id}:
    get:
      tags:
      - Vector database
      summary: Get Vector Database Ingestion Job
      description: Get status of a vector database ingestion job
      operationId: get_vector_database_ingestion_job_v1_flow_vectordb__database_id__ingestion__job_id__get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseIngestionResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/files:
    get:
      tags:
      - Vector database
      summary: List Vector Database Files
      description: List files in vector database with queue positions
      operationId: list_vector_database_files_v1_flow_vectordb__database_id__files_get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseFileList'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/chunk/{chunk_id}:
    get:
      tags:
      - Vector database
      summary: Get Vector Database Chunk
      description: Retrieve provenance details for a chunk in a vector database.
      operationId: get_vector_database_chunk_v1_flow_vectordb__database_id__chunk__chunk_id__get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      - name: chunk_id
        in: path
        required: true
        schema:
          type: string
          title: Chunk Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseChunkResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/chunks:
    post:
      tags:
      - Vector database
      summary: List Vector Database Chunks
      description: "Search/list chunks in a vector database with optional filtering.\n\nSupports filtering by `file_id`, `chunk_ids`, and `metadata` fields.\nMetadata filters support operator syntax: `$gt`, `$gte`, `$lt`, `$lte`, `$in`.\nUnknown operators return 400.\n\nRequest body example:\n```json\n{\n  \"file_id\": \"file-abc123\",\n  \"metadata\": {\"year\": {\"$gte\": 2023}, \"doc_type\": \"SOP\"},\n  \"limit\": 20,\n  \"offset\": 0\n}\n```"
      operationId: list_vector_database_chunks_v1_flow_vectordb__database_id__chunks_post
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/VectorDatabaseChunkSearchRequest'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseChunkListResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/files/{file_id}:
    delete:
      tags:
      - Vector database
      summary: Delete Vector Database File
      description: Delete a file from a vector database
      operationId: delete_vector_database_file_v1_flow_vectordb__database_id__files__file_id__delete
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      - name: file_id
        in: path
        required: true
        schema:
          type: string
          title: File Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseFileDeleteResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/flow/vectordb/{database_id}/metadata:
    patch:
      tags:
      - Vector database
      summary: Update Vector Database Metadata
      description: 'Overwrite metadata on chunks within a vector database, targeted by file_ids or chunk_ids.


        This operation is **destructive**: the provided `metadata` object **replaces** all existing

        metadata on every targeted chunk. Previous metadata fields that are not included in the

        new object are permanently removed.


        To preserve existing fields, include them explicitly in the new `metadata` object.


        **Metadata constraints:**

        - Must be a flat object (no nested objects or arrays).

        - Values must be `string`, `number`, `boolean`, or `datetime`. Null is rejected (422).

        - Maximum **20 fields**.

        - String values are trimmed of whitespace; newlines are replaced with spaces.


        Returns 422 if metadata is invalid or the database is not found, and 404 if the

        provided file_ids/chunk_ids match no chunks in the database.'
      operationId: update_vector_database_metadata_v1_flow_vectordb__database_id__metadata_patch
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/VectorDatabaseMetadataUpdateRequest'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseMetadataUpdateResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    post:
      tags:
      - Vector database
      summary: Generate Vector Database Metadata Snapshot
      description: 'Generate (or refresh) the metadata snapshot for a vector database.


        Samples up to 10,000 random chunks from the index, ranks the top 100 metadata keys

        by frequency, and for each key records the top 10 most common values along with an

        inferred type. The snapshot is stored in Postgres and returned by GET on this path.


        Retrying is safe — each call replaces the prior snapshot.


        Errors:

        - 422 if the vector database is not found.

        - 502 with `SnapshotGenerationFailed` if the ingestion service cannot produce the snapshot.'
      operationId: generate_vector_database_metadata_snapshot_v1_flow_vectordb__database_id__metadata_post
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseMetadataSnapshotGenerateResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    get:
      tags:
      - Vector database
      summary: Get Vector Database Metadata Snapshot
      description: 'Return the current metadata snapshot for a vector database.


        The snapshot is automatically refreshed whenever an ingestion job completes or a

        file is deleted from the database (both are best-effort and asynchronous, so the

        refresh may briefly lag the change), and can be regenerated on demand via POST on

        this path. A snapshot with no metadata returns 200 with `keys: []`. Returns 404 if

        a snapshot has never been generated for this database.'
      operationId: get_vector_database_metadata_snapshot_v1_flow_vectordb__database_id__metadata_get
      security:
      - APIKeyHeader: []
      parameters:
      - name: database_id
        in: path
        required: true
        schema:
          type: string
          title: Database Id
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorDatabaseMetadataSnapshotResponse'
        '422':
          description: Invalid request parameters
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
components:
  schemas:
    VectorDatabaseFileResponse:
      properties:
        id:
          type: string
          title: Id
        record_id:
          type: string
          title: Record Id
        vector_database_id:
          type: string
          title: Vector Database Id
        filename:
          type: string
          title: Filename
        method:
          anyOf:
          - type: string
          - type: 'null'
          title: Method
        chunk_method:
          anyOf:
          - type: string
          - type: 'null'
          title: Chunk Method
        token_count:
          anyOf:
          - type: integer
          - type: 'null'
          title: Token Count
        overlap_tokens:
          anyOf:
          - type: integer
          - type: 'null'
          title: Overlap Tokens
        created_at:
          type: string
          format: date-time
          title: Created At
        ingestion_job_id:
          anyOf:
          - type: string
          - type: 'null'
          title: Ingestion Job Id
        status:
          type: string
          title: Status
        error_message:
          anyOf:
          - type: string
          - type: 'null'
          title: Error Message
        suggested_fix:
          anyOf:
          - type: string
          - type: 'null'
          title: Suggested Fix
        processing_at:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          title: Processing At
        completed_at:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          title: Completed At
        failed_at:
          anyOf:
          - type: string
            format: date-time
          - type: 'null'
          title: Failed At
        file_size_in_bytes:
          anyOf:
          - type: integer
          - type: 'null'
          title: File Size In Bytes
        queue_position:
          anyOf:
          - type: integer
          - type: 'null'
          title: Queue Position
          description: Position in queue if status is queued
        metadata:
          anyOf:
          - additionalProperties: true
            type: object
          - type: 'null'
          title: Metadata
          description: User-defined metadata associated with this file's chunks. Set at ingestion time or updated via PATCH /vectordb/{database_id}/metadata.
      type: object
      required:
      - id
      - record_id
      - vector_database_id
      - filename
      - created_at
      - status
      title: VectorDatabaseFileResponse
      description: Response model for a vector database file
    VectorDatabaseChunkListItem:
      properties:
        chunk_id:
          type: string
          title: Chunk Id
        file_id:
          type: string
          title: File Id
        text:
          type: string
          title: Text
        metadata:
          anyOf:
          - additionalProperties: true
            type: object
          - type: 'null'
          title: Metadata
        hierarchy:
          anyOf:
          - items:
              type: string
            type: array
          - type: 'null'
          title: Hierarchy
        locations:
          anyOf:
          - items:
              $ref: '#/components/schemas/VectorDatabaseMarkdownLocation'
            type: array
          - type: 'null'
          title: Locations
      type: object
      required:
      - chunk_id
      - file_id
      - text
      title: VectorDatabaseChunkListItem
    VectorDatabaseMetadataUpdateResponse:
      properties:
        metadata:
          additionalProperties: true
          type: object
          title: Metadata
          description: The metadata object that was written to all matching chunks.
      type: object
      required:
      - metadata
      title: VectorDatabaseMetadataUpdateResponse
    VectorDatabaseChunkSearchRequest:
      properties:
        file_id:
          anyOf:
          - type: string
          - type: 'null'
          title: File Id
          description: Filter to chunks from a specific file
        chunk_ids:
          anyOf:
          - items:
              type: string
            type: array
          - type: 'null'
          title: Chunk Ids
          description: Chunk IDs to retrieve
        metadata:
          anyOf:
          - additionalProperties: true
            type: object
          - type: 'null'
          title: Metadata
          description: 'Metadata key-value filters with optional operators ($gt, $gte, $lt, $lte, $in). Example: {"year": {"$gte": 2023}, "doc_type": "SOP"}'
        limit:
          type: integer
          maximum: 100
          minimum: 1
          title: Limit
          description: Max results to return
          default: 20
        offset:
          type: integer
          minimum: 0
          title: Offset
          description: Pagination offset
          default: 0
      type: object
      title: VectorDatabaseChunkSearchRequest
      description: Request body for searching/listing chunks in a vector database.
    VectorDatabaseFileList:
      properties:
        object:
          type: string
          title: Object
          default: list
        data:
          items:
            $ref: '#/components/schemas/VectorDatabaseFileResponse'
          type: array
          title: Data
      type: object
      required:
      - data
      title: VectorDatabaseFileList
      description: Response model for a list of vector database files
    IdList:
      properties:
        object:
          type: string
          const: list
          title: Object
          default: list
        data:
          items:
            type: string
          type: array
          title: Data
      additionalProperties: true
      type: object
      required:
      - data
      title: IdList
      description: Generic response model for a list of resource IDs.
    VectorDatabaseIngestionRequest:
      properties:
        file_ids:
          items:
            type: string
          type: array
          title: File Ids
          description: List of file ids to use for alignment
        method:
          anyOf:
          - type: string
          - type: 'null'
          title: Method
          description: 'Document extraction strategy used to convert raw files into clean markdown before chunking. `accuracy-optimized` (default) — runs the full Seekr extraction pipeline: tries up to 12 conversion methods in priority order (bookmark-aware hybrid extraction, Seekr-SaaS OCR, LLM post-processing, PyMuPDF, and more) with no word-count restrictions, selecting the highest-quality result for each document. Best for complex PDFs, tables, and documents where retrieval accuracy matters. `speed-optimized` — uses the same pipeline but skips methods that exceed per-method word-count thresholds, dramatically reducing processing time on large documents while still producing high-quality output.'
          default: accuracy-optimized
          examples:
          - accuracy-optimized
          - speed-optimized
        chunking_method:
          anyOf:
          - type: string
          - type: 'null'
          title: Chunking Method
          description: Strategy used to split the extracted markdown into chunks before embedding. `markdown` (default) — parses the heading hierarchy (`#`–`######`) to identify section boundaries, groups subsections into token-bounded chunks, and intelligently handles tables by repeating table headers across continuation chunks so every chunk is self-contained. Best for structured documents (reports, policies, manuals). `semantic` — uses spaCy sentence detection, generates paragraph-level embeddings, then applies Ward hierarchical clustering to group paragraphs by meaning rather than position. Produces topically coherent chunks even in poorly structured documents — ideal for improving answer quality on complex question-answering workloads. `sliding` — fixed-size overlapping windows with no structural awareness. Fast and predictable; best for plain-text or homogeneous content where document structure is absent.
          default: markdown
          examples:
          - markdown
          - semantic
          - sliding
        token_count:
          type: integer
          title: Token Count
          description: Target maximum tokens per chunk.
          default: 800
        overlap_tokens:
          type: integer
          title: Overlap Tokens
          description: Number of tokens repeated at the start of each chunk from the end of the previous one, preserving context across chunk boundaries.
          default: 100
        metadata:
          anyOf:
          - additionalProperties: true
            type: object
          - type: 'null'
          title: Metadata
          description: 'Optional flat JSON object attached to every chunk produced by this ingestion job. Constraints: (1) must be a flat object — no nested objects or arrays; (2) values must be string, number, boolean, or datetime (null is rejected); (3) maximum 20 fields; (4) string values are trimmed of leading/trailing whitespace and newlines are replaced with spaces. Example: {"year": 2024, "doc_type": "policy", "is_confidential": false}'
          examples:
          - doc_type: policy
            is_confidential: false
            year: 2024
      type: object
      required:
      - file_ids
      title: VectorDatabaseIngestionRequest
    VectorDatabaseIngestionResponse:
      properties:
        id:
          type: string
          title: Id
        vector_database_id:
          type: string
          title: Vector Database Id
        status:
          type: string
          title: Status
        created_at:
          type: string
          format: date-time
          title: Created At
        updated_at:
          type: string
          format: date-time
          title: Updated At
        error_message:
          anyOf:
          - type: string
          - type: 'null'
          title: Error Message
        file_ids:
          items:
            type: string
          type: array
          title: File Ids
        metaflow_run_id:
          anyOf:
          - type: string
          - type: 'null'
          title: Metaflow Run Id
        file_records:
          anyOf:
          - items:
              $ref: '#/components/schemas/VectorDatabaseFileResponse'
            type: array
          - type: 'null'
          title: File Records
      type: object
      required:
      - id
      - vector_database_id
      - status
      - created_at
      - updated_at
      - error_message
      - file_ids
      - metaflow_run_id
      title: VectorDatabaseIngestionResponse
    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
    VectorDatabaseResponse:
      properties:
        id:
          type: string
          title: Id
        name:
          type: string
          title: Name
        model:
          type: string
          title: Model
        dimension:
          type: integer
          title: Dimension
        description:
          anyOf:
          - type: string
          - type: 'null'
          title: Description
        created_at:
          type: string
          format: date-time
          title: Created At
        updated_at:
          type: string
          format: date-time
          title: Updated At
        file_count:
          type: integer
          title: File Count
        size_in_bytes:
          anyOf:
          - type: integer
          - type: 'null'
          title: Size In Bytes
        db_type:
          anyOf:
          - $ref: '#/components/schemas/DBType'
          - type: 'null'
      type: object
      required:
      - id
      - name
      - model
      - dimension
      - description
      - created_at
      - updated_at
      - file_count
 

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# Full source: https://raw.githubusercontent.com/api-evangelist/seekr/refs/heads/main/openapi/seekr-vector-database-api-openapi.yml