unslothai--unsloth/studio/frontend/data-designer.openapi (1).yaml

openapi: 3.1.0
info:
  title: NeMo Data Designer Microservice
  description: Service for generating synthetic data.
  version: 1.5.0
paths:
  /v1/data-designer/jobs:
    post:
      tags:
      - Data Designer
      summary: Create Job
      operationId: create_job_v1_data_designer_jobs_post
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/DataDesignerJobRequest'
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DataDesignerJob'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    get:
      tags:
      - Data Designer
      summary: List Jobs
      operationId: list_jobs_v1_data_designer_jobs_get
      parameters:
      - name: page
        in: query
        required: false
        schema:
          type: integer
          exclusiveMinimum: 0
          description: Page number.
          default: 1
          title: Page
        description: Page number.
      - name: page_size
        in: query
        required: false
        schema:
          type: integer
          exclusiveMinimum: 0
          description: Page size.
          default: 10
          title: Page Size
        description: Page size.
      - name: sort
        in: query
        required: false
        schema:
          allOf:
          - $ref: '#/components/schemas/DataDesignerJobsSortField'
          description: The field to sort by. To sort in decreasing order, use `-`
            in front of the field name.
          default: -created_at
        description: The field to sort by. To sort in decreasing order, use `-` in
          front of the field name.
      - in: query
        name: filter
        style: deepObject
        required: false
        explode: true
        schema:
          $ref: '#/components/schemas/DataDesignerJobsListFilter'
        description: Filter jobs on various criteria.
      - in: query
        name: search
        style: deepObject
        required: false
        explode: true
        schema:
          $ref: '#/components/schemas/DataDesignerJobsSearch'
        description: "\nSearch jobs using substring matching.\nYou can combine multiple\
          \ search fields and filters.\n\nFor example:\n- `?search[name]=training`:\
          \ searches all jobs with 'training' in the name.\n- `?search[project]=my-project`:\
          \ searches all jobs with 'my-project'\n  in the project field.\n- `?search[name]=training&search[name]=eval`:\
          \ searches all jobs with\n  'training' OR 'eval' in the name.\n- `?search[name]=training&search[project]=my-project`:\
          \ searches all\n  jobs with 'training' in the name AND 'my-project' in the\
          \ project.\n"
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DataDesignerJobsPage'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}:
    get:
      tags:
      - Data Designer
      summary: Get Job
      operationId: get_job_v1_data_designer_jobs__job_id__get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DataDesignerJob'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    delete:
      tags:
      - Data Designer
      summary: Delete Job
      operationId: delete_job_v1_data_designer_jobs__job_id__delete
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema: {}
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/cancel:
    post:
      tags:
      - Data Designer
      summary: Cancel Job
      operationId: cancel_job_v1_data_designer_jobs__job_id__cancel_post
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DataDesignerJob'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/logs:
    get:
      tags:
      - Data Designer
      summary: Get Job Logs
      operationId: get_job_logs_v1_data_designer_jobs__job_id__logs_get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      - name: limit
        in: query
        required: false
        schema:
          anyOf:
          - type: integer
          - type: 'null'
          title: Limit
      - name: page_cursor
        in: query
        required: false
        schema:
          anyOf:
          - type: string
          - type: 'null'
          title: Page Cursor
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PlatformJobLogPage'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/results:
    get:
      tags:
      - Data Designer
      summary: List Job Results
      operationId: list_job_results_v1_data_designer_jobs__job_id__results_get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PlatformJobListResultResponse'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/results/analysis/download:
    get:
      tags:
      - Data Designer
      summary: Download Job Result Analysis
      operationId: download_job_result_analysis_v1_data_designer_jobs__job_id__results_analysis_download_get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema: {}
        '404':
          description: Not Found
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/results/dataset/download:
    get:
      tags:
      - Data Designer
      summary: Download Job Result Dataset
      operationId: download_job_result_dataset_v1_data_designer_jobs__job_id__results_dataset_download_get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/octet-stream:
              schema:
                type: string
                format: binary
        '404':
          description: Not Found
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/results/{result_name}:
    get:
      tags:
      - Data Designer
      summary: Get Job Result
      operationId: get_job_result_v1_data_designer_jobs__job_id__results__result_name__get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      - name: result_name
        in: path
        required: true
        schema:
          type: string
          title: Result Name
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PlatformJobResultResponse'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/results/{result_name}/download:
    get:
      tags:
      - Data Designer
      summary: Download Job Result
      operationId: download_job_result_v1_data_designer_jobs__job_id__results__result_name__download_get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      - name: result_name
        in: path
        required: true
        schema:
          type: string
          title: Result Name
      responses:
        '200':
          description: Successful Response
          content:
            application/octet-stream:
              schema:
                type: string
                format: binary
        '404':
          description: Not Found
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/jobs/{job_id}/status:
    get:
      tags:
      - Data Designer
      summary: Get Job Status
      operationId: get_job_status_v1_data_designer_jobs__job_id__status_get
      parameters:
      - name: job_id
        in: path
        required: true
        schema:
          type: string
          title: Job Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PlatformJobStatusResponse'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/preview:
    post:
      tags:
      - Data Designer
      summary: Generate preview Data Designer
      operationId: preview_v1_data_designer_preview_post
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PreviewRequest'
        required: true
      responses:
        '200':
          description: Successful Response
          content:
            application/jsonl:
              schema:
                $ref: '#/components/schemas/PreviewMessage'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
  /v1/data-designer/settings:
    get:
      tags:
      - Data Designer
      summary: Get Data Designer settings
      description: Returns the settings available for Data Designer.
      operationId: get_settings_v1_data_designer_settings_get
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/SettingsResponse'
components:
  schemas:
    BernoulliMixtureSamplerParams:
      properties:
        p:
          type: number
          maximum: 1.0
          minimum: 0.0
          title: P
          description: Bernoulli distribution probability of success.
        dist_name:
          type: string
          title: Dist Name
          description: Mixture distribution name. Samples will be equal to the distribution
            sample with probability `p`, otherwise equal to 0. Must be a valid scipy.stats
            distribution name.
        dist_params:
          additionalProperties: true
          type: object
          title: Dist Params
          description: Parameters of the scipy.stats distribution given in `dist_name`.
        sampler_type:
          type: string
          const: bernoulli_mixture
          title: Sampler Type
          default: bernoulli_mixture
      additionalProperties: false
      type: object
      required:
      - p
      - dist_name
      - dist_params
      title: BernoulliMixtureSamplerParams
      description: "Parameters for sampling from a Bernoulli mixture distribution.\n\
        \nCombines a Bernoulli distribution with another continuous distribution,\
        \ creating a mixture\nwhere values are either 0 (with probability 1-p) or\
        \ sampled from the specified distribution\n(with probability p). This is useful\
        \ for modeling scenarios with many zero values mixed with\na continuous distribution\
        \ of non-zero values.\n\nCommon use cases include modeling sparse events,\
        \ zero-inflated data, or situations where\nan outcome either doesn't occur\
        \ (0) or follows a specific distribution when it does occur.\n\nAttributes:\n\
        \    p: Probability of sampling from the mixture distribution (non-zero outcome).\n\
        \        Must be between 0.0 and 1.0 (inclusive). With probability 1-p, the\
        \ sample is 0.\n    dist_name: Name of the scipy.stats distribution to sample\
        \ from when outcome is non-zero.\n        Must be a valid scipy.stats distribution\
        \ name (e.g., \"norm\", \"gamma\", \"expon\").\n    dist_params: Parameters\
        \ for the specified scipy.stats distribution."
    BernoulliSamplerParams:
      properties:
        p:
          type: number
          maximum: 1.0
          minimum: 0.0
          title: P
          description: Probability of success.
        sampler_type:
          type: string
          const: bernoulli
          title: Sampler Type
          default: bernoulli
      additionalProperties: false
      type: object
      required:
      - p
      title: BernoulliSamplerParams
      description: "Parameters for sampling from a Bernoulli distribution.\n\nSamples\
        \ binary values (0 or 1) representing the outcome of a single trial with a\
        \ fixed\nprobability of success. This is the simplest discrete probability\
        \ distribution, useful for\nmodeling binary outcomes like success/failure,\
        \ yes/no, or true/false.\n\nAttributes:\n    p: Probability of success (sampling\
        \ 1). Must be between 0.0 and 1.0 (inclusive).\n        The probability of\
        \ failure (sampling 0) is automatically 1 - p."
    BinomialSamplerParams:
      properties:
        n:
          type: integer
          title: N
          description: Number of trials.
        p:
          type: number
          maximum: 1.0
          minimum: 0.0
          title: P
          description: Probability of success on each trial.
        sampler_type:
          type: string
          const: binomial
          title: Sampler Type
          default: binomial
      additionalProperties: false
      type: object
      required:
      - n
      - p
      title: BinomialSamplerParams
      description: "Parameters for sampling from a Binomial distribution.\n\nSamples\
        \ integer values representing the number of successes in a fixed number of\
        \ independent\nBernoulli trials, each with the same probability of success.\
        \ Commonly used to model the number\nof successful outcomes in repeated experiments.\n\
        \nAttributes:\n    n: Number of independent trials. Must be a positive integer.\n\
        \    p: Probability of success on each trial. Must be between 0.0 and 1.0\
        \ (inclusive)."
    BuildStage:
      type: string
      enum:
      - pre_batch
      - post_batch
      - pre_generation
      - post_generation
      title: BuildStage
    CategorySamplerParams:
      properties:
        values:
          items:
            anyOf:
            - type: string
            - type: integer
            - type: number
          type: array
          minItems: 1
          title: Values
          description: List of possible categorical values that can be sampled from.
        weights:
          type: array
          items:
            type: number
          title: Weights
          description: List of unnormalized probability weights to assigned to each
            value, in order. Larger values will be sampled with higher probability.
        sampler_type:
          type: string
          const: category
          title: Sampler Type
          default: category
      additionalProperties: false
      type: object
      required:
      - values
      title: CategorySamplerParams
      description: "Parameters for categorical sampling with optional probability\
        \ weighting.\n\nSamples values from a discrete set of categories. When weights\
        \ are provided, values are\nsampled according to their assigned probabilities.\
        \ Without weights, uniform sampling is used.\n\nAttributes:\n    values: List\
        \ of possible categorical values to sample from. Can contain strings, integers,\n\
        \        or floats. Must contain at least one value.\n    weights: Optional\
        \ unnormalized probability weights for each value. If provided, must be\n\
        \        the same length as `values`. Weights are automatically normalized\
        \ to sum to 1.0.\n        Larger weights result in higher sampling probability\
        \ for the corresponding value."
    CodeLang:
      type: string
      enum:
      - go
      - javascript
      - java
      - kotlin
      - python
      - ruby
      - rust
      - scala
      - swift
      - typescript
      - sql:sqlite
      - sql:tsql
      - sql:bigquery
      - sql:mysql
      - sql:postgres
      - sql:ansi
      title: CodeLang
    CodeValidatorParams:
      properties:
        code_lang:
          allOf:
          - $ref: '#/components/schemas/CodeLang'
          description: The language of the code to validate
      additionalProperties: false
      type: object
      required:
      - code_lang
      title: CodeValidatorParams
      description: "Configuration for code validation. Supports Python and SQL code\
        \ validation.\n\nAttributes:\n    code_lang: The language of the code to validate.\
        \ Supported values include: `python`,\n        `sql:sqlite`, `sql:postgres`,\
        \ `sql:mysql`, `sql:tsql`, `sql:bigquery`, `sql:ansi`."
    ColumnInequalityConstraint:
      properties:
        target_column:
          type: string
          title: Target Column
        rhs:
          type: string
          title: Rhs
        operator:
          $ref: '#/components/schemas/InequalityOperator'
      additionalProperties: false
      type: object
      required:
      - target_column
      - rhs
      - operator
      title: ColumnInequalityConstraint
    DataDesignerConfig:
      properties:
        columns:
          items:
            oneOf:
            - $ref: '#/components/schemas/ExpressionColumnConfig'
            - $ref: '#/components/schemas/LLMCodeColumnConfig'
            - $ref: '#/components/schemas/LLMJudgeColumnConfig'
            - $ref: '#/components/schemas/LLMStructuredColumnConfig'
            - $ref: '#/components/schemas/LLMTextColumnConfig'
            - $ref: '#/components/schemas/SamplerColumnConfig'
            - $ref: '#/components/schemas/SeedDatasetColumnConfig'
            - $ref: '#/components/schemas/ValidationColumnConfig'
            discriminator:
              propertyName: column_type
              mapping:
                expression: '#/components/schemas/ExpressionColumnConfig'
                llm-code: '#/components/schemas/LLMCodeColumnConfig-Input'
                llm-judge: '#/components/schemas/LLMJudgeColumnConfig-Input'
                llm-structured: '#/components/schemas/LLMStructuredColumnConfig-Input'
                llm-text: '#/components/schemas/LLMTextColumnConfig-Input'
                sampler: '#/components/schemas/SamplerColumnConfig'
                seed-dataset: '#/components/schemas/SeedDatasetColumnConfig'
                validation: '#/components/schemas/ValidationColumnConfig-Input'
          type: array
          minItems: 1
          title: Columns
        model_configs:
          type: array
          items:
            $ref: '#/components/schemas/ModelConfigInput'
          title: Model Configs
        seed_config:
          $ref: '#/components/schemas/SeedConfig'
        constraints:
          type: array
          items:
            anyOf:
            - $ref: '#/components/schemas/ScalarInequalityConstraint'
            - $ref: '#/components/schemas/ColumnInequalityConstraint'
          title: Constraints
        profilers:
          type: array
          items:
            $ref: '#/components/schemas/JudgeScoreProfilerConfig'
          title: Profilers
        processors:
          type: array
          items:
            $ref: '#/components/schemas/ProcessorConfig'
          title: Processors
      additionalProperties: false
      type: object
      required:
      - columns
      title: DataDesignerConfig
      description: "Configuration for NeMo Data Designer.\n\nThis class defines the\
        \ main configuration structure for NeMo Data Designer,\nwhich orchestrates\
        \ the generation of synthetic data.\n\nAttributes:\n    columns: Required\
        \ list of column configurations defining how each column\n        should be\
        \ generated. Must contain at least one column.\n    model_configs: Optional\
        \ list of model configurations for LLM-based generation.\n        Each model\
        \ config defines the model, provider, and inference parameters.\n    seed_config:\
        \ Optional seed dataset settings to use for generation.\n    constraints:\
        \ Optional list of column constraints.\n    profilers: Optional list of column\
        \ profilers for analyzing generated data characteristics."
    DataDesignerJob:
      properties:
        id:
          type: string
          title: Id
        name:
          type: string
          title: Name
        description:
          type: string
          title: Description
        project:
          type: string
          title: Project
        namespace:
          type: string
          title: Namespace
        created_at:
          type: string
          title: Created At
        updated_at:
          type: string
          title: Updated At
        spec:
          $ref: '#/components/schemas/DataDesignerJobConfig'
        status:
          $ref: '#/components/schemas/PlatformJobStatus'
        status_details:
          type: object
          additionalProperties: true
          title: Status Details
        error_details:
          type: object
          additionalProperties: true
          title: Error Details
        ownership:
          type: object
          additionalProperties: true
          title: Ownership
        custom_fields:
          type: object
          additionalProperties: true
          title: Custom Fields
      type: object
      required:
      - name
      - spec
      title: DataDesignerJob
    DataDesignerJobConfig:
      properties:
        num_records:
          type: integer
          title: Num Records
        config:
          $ref: '#/components/schemas/DataDesignerConfig'
      type: object
      required:
      - num_records
      - config
      title: DataDesignerJobConfig
    DataDesignerJobRequest:
      properties:
        name:
          type: string
          title: Name
        description:
          type: string
          title: Description
        namespace:
          type: string
          title: Namespace
        project:
          type: string
          title: Project
        spec:
          $ref: '#/components/schemas/DataDesignerJobConfig'
        ownership:
          type: object
          additionalProperties: true
          title: Ownership
        custom_fields:
          type: object
          additionalProperties: true
          title: Custom Fields
      type: object
      required:
      - spec
      title: DataDesignerJobRequest
    DataDesignerJobsListFilter:
      properties:
        created_at:
          allOf:
          - $ref: '#/components/schemas/DatetimeFilter'
          description: Jobs created at 'gte' datetime or 'lte' datetime.
        name:
          type: string
          title: Name
          description: Name of the job.
        namespace:
          type: string
          title: Namespace
          description: Namespace of the job.
        project:
          type: string
          title: Project
          description: Project containing the job.
        status:
          allOf:
          - $ref: '#/components/schemas/PlatformJobStatus'
          description: The current status.
        updated_at:
          allOf:
          - $ref: '#/components/schemas/DatetimeFilter'
          description: Jobs updated at 'gte' datetime or 'lte' datetime.
      additionalProperties: false
      type: object
      title: DataDesignerJobsListFilter
    DataDesignerJobsPage:
      properties:
        object:
          type: string
          title: Object
          description: The type of object being returned.
          default: list
        data:
          items:
            $ref: '#/components/schemas/DataDesignerJob'
          type: array
          title: Data
        pagination:
          allOf:
          - $ref: '#/components/schemas/PaginationData'
          description: Pagination information.
        sort:
          type: string
          title: Sort
          description: The field on which the results are sorted.
        filter:
          allOf:
          - $ref: '#/components/schemas/DataDesignerJobsListFilter'
          description: Filtering information.
        search:
          allOf:
          - $ref: '#/components/schemas/DataDesignerJobsSearch'
          description: Search information.
      type: object
      required:
      - data
      title: DataDesignerJobsPage
    DataDesignerJobsSearch:
      properties:
        name:
          type: array
          items:
            type: string
          title: Name
          description: Search jobs where name contains any of these strings.
        project:
          type: array
          items:
            type: string
          title: Project
          description: Search jobs where project contains any of these strings.
      type: object
      title: DataDesignerJobsSearch
    DataDesignerJobsSortField:
      type: string
      enum:
      - created_at
      - -created_at
      - updated_at
      - -updated_at
      title: DataDesignerJobsSortField
    DatetimeFilter:
      properties:
        gte:
          type: string
          title: Gte
          description: Filter for results greater than or equal to this datetime.
        lte:
          type: string
          title: Lte
          description: Filter for results less than or equal to this datetime.
      additionalProperties: false
      type: object
      title: DatetimeFilter
    DatetimeSamplerParams:
      properties:
        start:
          type: string
          title: Start
          description: Earliest possible datetime for sampling range, inclusive.
        end:
          type: string
          title: End
          description: Latest possible datetime for sampling range, inclusive.
        unit:
          type: string
          enum:
          - Y
          - M
          - D
          - h
          - m
          - s
          title: Unit
          description: Sampling units, e.g. the smallest possible time interval between
            samples.
          default: D
        sampler_type:
          type: string
          const: datetime
          title: Sampler Type
          default: datetime
      additionalProperties: false
      type: object
      required:
      - start
      - end
      title: DatetimeSamplerParams
      description: "Parameters for uniform datetime sampling within a specified range.\n\
        \nSamples datetime values uniformly between a start and end date with a specified\
        \ granularity.\nThe sampling unit determines the smallest possible time interval\
        \ between consecutive samples.\n\nAttributes:\n    start: Earliest possible\
        \ datetime for the sampling range (inclusive). Must be a valid\n        datetime\
        \ string parseable by pandas.to_datetime().\n    end: Latest possible datetime\
        \ for the sampling range (inclusive). Must be a valid\n        datetime string\
        \ parseable by pandas.to_datetime().\n    unit: Time unit for sampling granularity.\
        \ Options:\n        - \"Y\": Years\n        - \"M\": Months\n        - \"\
        D\": Days (default)\n        - \"h\": Hours\n        - \"m\": Minutes\n  \
        \      - \"s\": Seconds"
    DisplayModelProvider:
      properties:
        name:
          type: string
          title: Name
        provider_type:
          type: string
          title: Provider Type
          default: openai
        extra_body:
          type: object
          additionalProperties: true
          title: Extra Body
        allowed_models:
          type: array
          items:
            type: string
          title: Allowed Models
      additionalProperties: false
      type: object
      required:
      - name
      title: DisplayModelProvider
    DistributionType:
      type: string
      enum:
      - uniform
      - manual
      title: DistributionType
    ExpressionColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: expression
          title: Column Type
          default: expression
        expr:
          type: string
          title: Expr
        dtype:
          type: string
          enum:
          - int
          - float
          - str
          - bool
          title: Dtype
          default: str
      additionalProperties: false
      type: object
      required:
      - name
      - expr
      title: ExpressionColumnConfig
      description: "Configuration for derived columns using Jinja2 expressions.\n\n\
        Expression columns compute values by evaluating Jinja2 templates that reference\
        \ other\ncolumns. Useful for transformations, concatenations, conditional\
        \ logic, and derived\nfeatures without requiring LLM generation. The expression\
        \ is evaluated row-by-row.\n\nAttributes:\n    expr: Jinja2 expression to\
        \ evaluate. Can reference other column values using\n        {{ column_name\
        \ }} syntax. Supports filters, conditionals, and arithmetic.\n        Must\
        \ be a valid, non-empty Jinja2 template.\n    dtype: Data type to cast the\
        \ result to. Must be one of \"int\", \"float\", \"str\", or \"bool\".\n  \
        \      Defaults to \"str\". Type conversion is applied after expression evaluation.\n\
        \    column_type: Discriminator field, always \"expression\" for this configuration\
        \ type."
    FileStorageType:
      type: string
      enum:
      - nds
      title: FileStorageType
    GaussianSamplerParams:
      properties:
        mean:
          type: number
          title: Mean
          description: Mean of the Gaussian distribution
        stddev:
          type: number
          title: Stddev
          description: Standard deviation of the Gaussian distribution
        decimal_places:
          type: integer
          title: Decimal Places
          description: Number of decimal places to round the sampled values to.
        sampler_type:
          type: string
          const: gaussian
          title: Sampler Type
          default: gaussian
      additionalProperties: false
      type: object
      required:
      - mean
      - stddev
      title: GaussianSamplerParams
      description: "Parameters for sampling from a Gaussian (Normal) distribution.\n\
        \nSamples continuous values from a normal distribution characterized by its\
        \ mean and standard\ndeviation. The Gaussian distribution is one of the most\
        \ commonly used probability distributions,\nappearing naturally in many real-world\
        \ phenomena due to the Central Limit Theorem.\n\nAttributes:\n    mean: Mean\
        \ (center) of the Gaussian distribution. This is the expected value and the\n\
        \        location of the distribution's peak.\n    stddev: Standard deviation\
        \ of the Gaussian distribution. Controls the spread or width\n        of the\
        \ distribution. Must be positive.\n    decimal_places: Optional number of\
        \ decimal places to round sampled values to. If None,\n        values are\
        \ not rounded."
    HTTPValidationError:
      properties:
        detail:
          items:
            $ref: '#/components/schemas/ValidationError'
          type: array
          title: Detail
      type: object
      title: HTTPValidationError
    ImageContext:
      properties:
        modality:
          allOf:
          - $ref: '#/components/schemas/Modality'
          default: image
        column_name:
          type: string
          title: Column Name
        data_type:
          $ref: '#/components/schemas/ModalityDataType'
        image_format:
          $ref: '#/components/schemas/ImageFormat'
      type: object
      required:
      - column_name
      - data_type
      title: ImageContext
    ImageFormat:
      type: string
      enum:
      - png
      - jpg
      - jpeg
      - gif
      - webp
      title: ImageFormat
    IndexRange:
      properties:
        start:
          type: integer
          minimum: 0.0
          title: Start
          description: The start index of the index range (inclusive)
        end:
          type: integer
          minimum: 0.0
          title: End
          description: The end index of the index range (inclusive)
      additionalProperties: false
      type: object
      required:
      - start
      - end
      title: IndexRange
    InequalityOperator:
      type: string
      enum:
      - lt
      - le
      - gt
      - ge
      title: InequalityOperator
    InferenceParametersInput:
      properties:
        temperature:
          anyOf:
          - type: number
          - $ref: '#/components/schemas/UniformDistribution'
          - $ref: '#/components/schemas/ManualDistribution'
          - type: 'null'
          title: Temperature
        top_p:
          anyOf:
          - type: number
          - $ref: '#/components/schemas/UniformDistribution'
          - $ref: '#/components/schemas/ManualDistribution'
          - type: 'null'
          title: Top P
        max_tokens:
          type: integer
          title: Max Tokens
        max_parallel_requests:
          type: integer
          minimum: 1.0
          title: Max Parallel Requests
          default: 4
        timeout:
          type: integer
          title: Timeout
        extra_body:
          type: object
          additionalProperties: true
          title: Extra Body
      additionalProperties: false
      type: object
      title: InferenceParametersInput
    InferenceParametersOutput:
      properties:
        temperature:
          anyOf:
          - type: number
          - $ref: '#/components/schemas/UniformDistribution'
          - $ref: '#/components/schemas/ManualDistribution'
          - type: 'null'
          title: Temperature
        top_p:
          anyOf:
          - type: number
          - $ref: '#/components/schemas/UniformDistribution'
          - $ref: '#/components/schemas/ManualDistribution'
          - type: 'null'
          title: Top P
        max_tokens:
          type: integer
          title: Max Tokens
        max_parallel_requests:
          type: integer
          minimum: 1.0
          title: Max Parallel Requests
          default: 4
        timeout:
          type: integer
          title: Timeout
        extra_body:
          type: object
          additionalProperties: true
          title: Extra Body
      additionalProperties: false
      type: object
      title: InferenceParametersOutput
    JudgeScoreProfilerConfig:
      properties:
        model_alias:
          type: string
          title: Model Alias
        summary_score_sample_size:
          type: integer
          title: Summary Score Sample Size
          default: 20
      additionalProperties: false
      type: object
      required:
      - model_alias
      title: JudgeScoreProfilerConfig
    LLMCodeColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: llm-code
          title: Column Type
          default: llm-code
        prompt:
          type: string
          title: Prompt
        model_alias:
          type: string
          title: Model Alias
        system_prompt:
          type: string
          title: System Prompt
        multi_modal_context:
          type: array
          items:
            $ref: '#/components/schemas/ImageContext'
          title: Multi Modal Context
        code_lang:
          $ref: '#/components/schemas/CodeLang'
      additionalProperties: false
      type: object
      required:
      - name
      - prompt
      - model_alias
      - code_lang
      title: LLMCodeColumnConfig
      description: "Configuration for code generation columns using Large Language\
        \ Models.\n\nExtends LLMTextColumnConfig to generate code snippets in specific\
        \ programming languages\nor SQL dialects. The generated code is automatically\
        \ extracted from markdown code blocks\nfor the specified language. Inherits\
        \ all prompt templating capabilities.\n\nAttributes:\n    code_lang: Programming\
        \ language or SQL dialect for code generation. Supported\n        values include:\
        \ \"python\", \"javascript\", \"typescript\", \"java\", \"kotlin\", \"go\"\
        ,\n        \"rust\", \"ruby\", \"scala\", \"swift\", \"sql:sqlite\", \"sql:postgres\"\
        , \"sql:mysql\",\n        \"sql:tsql\", \"sql:bigquery\", \"sql:ansi\". See\
        \ CodeLang enum for complete list.\n    column_type: Discriminator field,\
        \ always \"llm-code\" for this configuration type."
    LLMJudgeColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: llm-judge
          title: Column Type
          default: llm-judge
        prompt:
          type: string
          title: Prompt
        model_alias:
          type: string
          title: Model Alias
        system_prompt:
          type: string
          title: System Prompt
        multi_modal_context:
          type: array
          items:
            $ref: '#/components/schemas/ImageContext'
          title: Multi Modal Context
        scores:
          items:
            $ref: '#/components/schemas/Score'
          type: array
          minItems: 1
          title: Scores
      additionalProperties: false
      type: object
      required:
      - name
      - prompt
      - model_alias
      - scores
      title: LLMJudgeColumnConfig
      description: "Configuration for LLM-as-a-judge quality assessment and scoring\
        \ columns.\n\nExtends LLMTextColumnConfig to create judge columns that evaluate\
        \ and score other\ngenerated content based on the defined criteria. Useful\
        \ for quality assessment, preference\nranking, and multi-dimensional evaluation\
        \ of generated data.\n\nAttributes:\n    scores: List of Score objects defining\
        \ the evaluation dimensions. Each score\n        represents a different aspect\
        \ to evaluate (e.g., accuracy, relevance, fluency).\n        Must contain\
        \ at least one score.\n    column_type: Discriminator field, always \"llm-judge\"\
        \ for this configuration type."
    LLMStructuredColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: llm-structured
          title: Column Type
          default: llm-structured
        prompt:
          type: string
          title: Prompt
        model_alias:
          type: string
          title: Model Alias
        system_prompt:
          type: string
          title: System Prompt
        multi_modal_context:
          type: array
          items:
            $ref: '#/components/schemas/ImageContext'
          title: Multi Modal Context
        output_format:
          anyOf:
          - additionalProperties: true
            type: object
          - {}
          title: Output Format
      additionalProperties: false
      type: object
      required:
      - name
      - prompt
      - model_alias
      - output_format
      title: LLMStructuredColumnConfig
      description: "Configuration for structured JSON generation columns using Large\
        \ Language Models.\n\nExtends LLMTextColumnConfig to generate structured data\
        \ conforming to a specified schema.\nUses JSON schema or Pydantic models to\
        \ define the expected output structure, enabling\ntype-safe and validated\
        \ structured output generation. Inherits prompt templating capabilities.\n\
        \nAttributes:\n    output_format: The schema defining the expected output\
        \ structure. Can be either:\n        - A Pydantic BaseModel class (recommended)\n\
        \        - A JSON schema dictionary\n    column_type: Discriminator field,\
        \ always \"llm-structured\" for this configuration type."
    LLMTextColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: llm-text
          title: Column Type
          default: llm-text
        prompt:
          type: string
          title: Prompt
        model_alias:
          type: string
          title: Model Alias
        system_prompt:
          type: string
          title: System Prompt
        multi_modal_context:
          type: array
          items:
            $ref: '#/components/schemas/ImageContext'
          title: Multi Modal Context
      additionalProperties: false
      type: object
      required:
      - name
      - prompt
      - model_alias
      title: LLMTextColumnConfig
      description: "Configuration for text generation columns using Large Language\
        \ Models.\n\nLLM text columns generate free-form text content using language\
        \ models via LiteLLM.\nPrompts support Jinja2 templating to reference values\
        \ from other columns, enabling\ncontext-aware generation. The generated text\
        \ can optionally include reasoning traces\nwhen models support extended thinking.\n\
        \nAttributes:\n    prompt: Prompt template for text generation. Supports Jinja2\
        \ syntax to\n        reference other columns (e.g., \"Write a story about\
        \ {{ character_name }}\").\n        Must be a valid Jinja2 template.\n   \
        \ model_alias: Alias of the model configuration to use for generation.\n \
        \       Must match a model alias defined when initializing the DataDesignerConfigBuilder.\n\
        \    system_prompt: Optional system prompt to set model behavior and constraints.\n\
        \        Also supports Jinja2 templating. If provided, must be a valid Jinja2\
        \ template.\n        Do not put any output parsing instructions in the system\
        \ prompt. Instead,\n        use the appropriate column type for the output\
        \ you want to generate - e.g.,\n        `LLMStructuredColumnConfig` for structured\
        \ output, `LLMCodeColumnConfig` for code.\n    multi_modal_context: Optional\
        \ list of image contexts for multi-modal generation.\n        Enables vision-capable\
        \ models to generate text based on image inputs.\n    column_type: Discriminator\
        \ field, always \"llm-text\" for this configuration type."
    LocalCallableValidatorParams:
      properties:
        validation_function:
          title: Validation Function
          description: Function (Callable[[pd.DataFrame], pd.DataFrame]) to validate
            the data
        output_schema:
          type: object
          additionalProperties: true
          title: Output Schema
          description: Expected schema for local callable validator's output
      additionalProperties: false
      type: object
      required:
      - validation_function
      title: LocalCallableValidatorParams
      description: "Configuration for local callable validation. Expects a function\
        \ to be passed that validates the data.\n\nAttributes:\n    validation_function:\
        \ Function (`Callable[[pd.DataFrame], pd.DataFrame]`) to validate the\n  \
        \      data. Output must contain a column `is_valid` of type `bool`.\n   \
        \ output_schema: The JSON schema for the local callable validator's output.\
        \ If not provided,\n        the output will not be validated."
    ManualDistribution:
      properties:
        distribution_type:
          allOf:
          - $ref: '#/components/schemas/DistributionType'
          default: manual
        params:
          $ref: '#/components/schemas/ManualDistributionParams'
      additionalProperties: false
      type: object
      required:
      - params
      title: ManualDistribution
    ManualDistributionParams:
      properties:
        values:
          items:
            type: number
          type: array
          minItems: 1
          title: Values
        weights:
          type: array
          items:
            type: number
          title: Weights
      additionalProperties: false
      type: object
      required:
      - values
      title: ManualDistributionParams
    MessageType:
      type: string
      enum:
      - analysis
      - dataset
      - heartbeat
      - log
      title: MessageType
    Modality:
      type: string
      enum:
      - image
      title: Modality
    ModalityDataType:
      type: string
      enum:
      - url
      - base64
      title: ModalityDataType
    ModelConfigInput:
      properties:
        alias:
          type: string
          title: Alias
        model:
          type: string
          title: Model
        inference_parameters:
          $ref: '#/components/schemas/InferenceParametersInput'
        provider:
          type: string
          title: Provider
      additionalProperties: false
      type: object
      required:
      - alias
      - model
      title: ModelConfigInput
    ModelConfigOutput:
      properties:
        alias:
          type: string
          title: Alias
        model:
          type: string
          title: Model
        inference_parameters:
          $ref: '#/components/schemas/InferenceParametersOutput'
        provider:
          type: string
          title: Provider
      additionalProperties: false
      type: object
      required:
      - alias
      - model
      title: ModelConfigOutput
    PaginationData:
      properties:
        page:
          type: integer
          title: Page
          description: The current page number.
        page_size:
          type: integer
          title: Page Size
          description: The page size used for the query.
        current_page_size:
          type: integer
          title: Current Page Size
          description: The size for the current page.
        total_pages:
          type: integer
          title: Total Pages
          description: The total number of pages.
        total_results:
          type: integer
          title: Total Results
          description: The total number of results.
      type: object
      required:
      - page
      - page_size
      - current_page_size
      - total_pages
      - total_results
      title: PaginationData
    PartitionBlock:
      properties:
        index:
          type: integer
          minimum: 0.0
          title: Index
          description: The index of the partition to sample from
          default: 0
        num_partitions:
          type: integer
          minimum: 1.0
          title: Num Partitions
          description: The total number of partitions in the dataset
          default: 1
      additionalProperties: false
      type: object
      title: PartitionBlock
    PersonFromFakerSamplerParams:
      properties:
        locale:
          type: string
          title: Locale
          description: Locale string, determines the language and geographic locale
            that a synthetic person will be sampled from. E.g, en_US, en_GB, fr_FR,
            ...
          default: en_US
        sex:
          type: string
          title: Sex
          description: If specified, then only synthetic people of the specified sex
            will be sampled.
        city:
          anyOf:
          - type: string
          - items:
              type: string
            type: array
          title: City
          description: If specified, then only synthetic people from these cities
            will be sampled.
        age_range:
          items:
            type: integer
          type: array
          maxItems: 2
          minItems: 2
          title: Age Range
          description: If specified, then only synthetic people within this age range
            will be sampled.
          default:
          - 18
          - 114
        sampler_type:
          type: string
          const: person_from_faker
          title: Sampler Type
          default: person_from_faker
      additionalProperties: false
      type: object
      title: PersonFromFakerSamplerParams
    PersonSamplerParams:
      properties:
        locale:
          type: string
          title: Locale
          description: 'Locale that determines the language and geographic location
            that a synthetic person will be sampled from. Must be a locale supported
            by a managed Nemotron Personas dataset. Managed datasets exist for the
            following locales: en_US, ja_JP, en_IN, hi_IN.'
          default: en_US
        sex:
          type: string
          title: Sex
          description: If specified, then only synthetic people of the specified sex
            will be sampled.
        city:
          anyOf:
          - type: string
          - items:
              type: string
            type: array
          title: City
          description: If specified, then only synthetic people from these cities
            will be sampled.
        age_range:
          items:
            type: integer
          type: array
          maxItems: 2
          minItems: 2
          title: Age Range
          description: If specified, then only synthetic people within this age range
            will be sampled.
          default:
          - 18
          - 114
        select_field_values:
          type: object
          additionalProperties:
            items:
              type: string
            type: array
          title: Select Field Values
          description: Sample synthetic people with the specified field values. This
            is meant to be a flexible argument for selecting a subset of the population
            from the managed dataset. Note that this sampler does not support rare
            combinations of field values and will likely fail if your desired subset
            is not well-represented in the managed Nemotron Personas dataset. We generally
            recommend using the `sex`, `city`, and `age_range` arguments to filter
            the population when possible.
          examples:
          - education_level:
            - high_school
            - some_college
            - bachelors
            state:
            - NY
            - CA
            - OH
            - TX
            - NV
        with_synthetic_personas:
          type: boolean
          title: With Synthetic Personas
          description: If True, then append synthetic persona columns to each generated
            person.
          default: false
        sampler_type:
          type: string
          const: person
          title: Sampler Type
          default: person
      additionalProperties: false
      type: object
      title: PersonSamplerParams
      description: "Parameters for sampling synthetic person data with demographic\
        \ attributes.\n\nGenerates realistic synthetic person data including names,\
        \ addresses, phone numbers, and other\ndemographic information. Data can be\
        \ sampled from managed datasets (when available) or generated\nusing Faker.\
        \ The sampler supports filtering by locale, sex, age, geographic location,\
        \ and can\noptionally include synthetic persona descriptions.\n\nAttributes:\n\
        \    locale: Locale string determining the language and geographic region\
        \ for synthetic people.\n        Format: language_COUNTRY (e.g., \"en_US\"\
        , \"en_GB\", \"fr_FR\", \"de_DE\", \"es_ES\", \"ja_JP\").\n        Defaults\
        \ to \"en_US\".\n    sex: If specified, filters to only sample people of the\
        \ specified sex. Options: \"Male\" or\n        \"Female\". If None, samples\
        \ both sexes.\n    city: If specified, filters to only sample people from\
        \ the specified city or cities. Can be\n        a single city name (string)\
        \ or a list of city names.\n    age_range: Two-element list [min_age, max_age]\
        \ specifying the age range to sample from\n        (inclusive). Defaults to\
        \ a standard age range. Both values must be between minimum and\n        maximum\
        \ allowed ages.\n    with_synthetic_personas: If True, appends additional\
        \ synthetic persona columns including\n        personality traits, interests,\
        \ and background descriptions. Only supported for certain\n        locales\
        \ with managed datasets.\n    sample_dataset_when_available: If True, samples\
        \ from curated managed datasets when available\n        for the specified\
        \ locale. If False or unavailable, falls back to Faker-generated data.\n \
        \       Managed datasets typically provide more realistic and diverse synthetic\
        \ people."
    PlatformJobListResultResponse:
      properties:
        object:
          type: string
          title: Object
          description: The type of object being returned.
          default: list
        data:
          items:
            $ref: '#/components/schemas/PlatformJobResultResponse'
          type: array
          title: Data
      type: object
      required:
      - data
      title: PlatformJobListResultResponse
    PlatformJobLog:
      properties:
        timestamp:
          type: string
          format: date-time
          title: Timestamp
        job_id:
          type: string
          title: Job Id
        job_step:
          type: string
          title: Job Step
        job_task:
          type: string
          title: Job Task
        message:
          type: string
          title: Message
      type: object
      required:
      - timestamp
      - job_id
      - job_step
      - job_task
      - message
      title: PlatformJobLog
    PlatformJobLogPage:
      properties:
        object:
          type: string
          title: Object
          description: The type of object being returned.
          default: list
        data:
          items:
            $ref: '#/components/schemas/PlatformJobLog'
          type: array
          title: Data
        total:
          type: integer
          title: Total
        next_page:
          type: string
          title: Next Page
        prev_page:
          type: string
          title: Prev Page
      type: object
      required:
      - data
      - total
      - next_page
      - prev_page
      title: PlatformJobLogPage
    PlatformJobResultResponse:
      properties:
        result_name:
          type: string
          title: Result Name
        job_id:
          type: string
          title: Job Id
        namespace:
          type: string
          title: Namespace
        project:
          type: string
          title: Project
        created_at:
          type: string
          format: date-time
          title: Created At
        updated_at:
          type: string
          format: date-time
          title: Updated At
        artifact_url:
          type: string
          title: Artifact Url
        artifact_storage_type:
          $ref: '#/components/schemas/FileStorageType'
      type: object
      required:
      - result_name
      - job_id
      - namespace
      - artifact_url
      - artifact_storage_type
      title: PlatformJobResultResponse
    PlatformJobStatus:
      type: string
      enum:
      - created
      - pending
      - active
      - cancelled
      - cancelling
      - error
      - completed
      - paused
      - pausing
      - resuming
      title: PlatformJobStatus
      description: 'Enumeration of possible job statuses.


        This enum represents the various states a job can be in during its lifecycle,

        from creation to a terminal state.'
    PlatformJobStatusResponse:
      properties:
        job_id:
          type: string
          title: Job Id
        status:
          $ref: '#/components/schemas/PlatformJobStatus'
        status_details:
          additionalProperties: true
          type: object
          title: Status Details
        error_details:
          type: object
          additionalProperties: true
          title: Error Details
        steps:
          items:
            $ref: '#/components/schemas/PlatformJobStepStatusResponse'
          type: array
          title: Steps
      type: object
      required:
      - job_id
      - status
      - status_details
      - error_details
      - steps
      title: PlatformJobStatusResponse
    PlatformJobStepStatusResponse:
      properties:
        name:
          type: string
          title: Name
        status:
          $ref: '#/components/schemas/PlatformJobStatus'
        status_details:
          additionalProperties: true
          type: object
          title: Status Details
        error_details:
          type: object
          additionalProperties: true
          title: Error Details
        tasks:
          items:
            $ref: '#/components/schemas/PlatformJobTaskStatusResponse'
          type: array
          title: Tasks
      type: object
      required:
      - name
      - status
      - status_details
      - error_details
      - tasks
      title: PlatformJobStepStatusResponse
    PlatformJobTaskStatusResponse:
      properties:
        id:
          type: string
          title: Id
        status:
          $ref: '#/components/schemas/PlatformJobStatus'
        status_details:
          additionalProperties: true
          type: object
          title: Status Details
        error_details:
          type: object
          additionalProperties: true
          title: Error Details
        error_stack:
          type: string
          title: Error Stack
      type: object
      required:
      - id
      - status
      - status_details
      - error_details
      - error_stack
      title: PlatformJobTaskStatusResponse
    PoissonSamplerParams:
      properties:
        mean:
          type: number
          title: Mean
          description: Mean number of events in a fixed interval.
        sampler_type:
          type: string
          const: poisson
          title: Sampler Type
          default: poisson
      additionalProperties: false
      type: object
      required:
      - mean
      title: PoissonSamplerParams
      description: "Parameters for sampling from a Poisson distribution.\n\nSamples\
        \ non-negative integer values representing the number of events occurring\
        \ in a fixed\ninterval of time or space. The Poisson distribution is commonly\
        \ used to model count data\nlike the number of arrivals, occurrences, or events\
        \ per time period.\n\nThe distribution is characterized by a single parameter\
        \ (mean/rate), and both the mean and\nvariance equal this parameter value.\n\
        \nAttributes:\n    mean: Mean number of events in the fixed interval (also\
        \ called rate parameter \u03BB).\n        Must be positive. This represents\
        \ both the expected value and the variance of the\n        distribution."
    PreviewMessage:
      properties:
        message:
          type: string
          title: Message
        message_type:
          $ref: '#/components/schemas/MessageType'
        extra:
          type: object
          additionalProperties:
            type: string
          title: Extra
      additionalProperties: false
      type: object
      required:
      - message
      - message_type
      title: PreviewMessage
    PreviewRequest:
      properties:
        config:
          $ref: '#/components/schemas/DataDesignerConfig'
        num_records:
          type: integer
          title: Num Records
      type: object
      required:
      - config
      title: PreviewRequest
    ProcessorConfig:
      properties:
        build_stage:
          allOf:
          - $ref: '#/components/schemas/BuildStage'
          description: 'The stage at which the processor will run. Supported stages:
            post_batch'
      additionalProperties: false
      type: object
      required:
      - build_stage
      title: ProcessorConfig
    RemoteValidatorParams:
      properties:
        endpoint_url:
          type: string
          title: Endpoint Url
          description: URL of the remote endpoint
        output_schema:
          type: object
          additionalProperties: true
          title: Output Schema
          description: Expected schema for remote validator's output
        timeout:
          type: number
          exclusiveMinimum: 0.0
          title: Timeout
          description: The timeout for the HTTP request
          default: 30.0
        max_retries:
          type: integer
          minimum: 0.0
          title: Max Retries
          description: The maximum number of retry attempts
          default: 3
        retry_backoff:
          type: number
          exclusiveMinimum: 1.0
          title: Retry Backoff
          description: The backoff factor for the retry delay
          default: 2.0
        max_parallel_requests:
          type: integer
          minimum: 1.0
          title: Max Parallel Requests
          description: The maximum number of parallel requests to make
          default: 4
      additionalProperties: false
      type: object
      required:
      - endpoint_url
      title: RemoteValidatorParams
      description: "Configuration for remote validation. Sends data to a remote endpoint\
        \ for validation.\n\nAttributes:\n    endpoint_url: The URL of the remote\
        \ endpoint.\n    output_schema: The JSON schema for the remote validator's\
        \ output. If not provided,\n        the output will not be validated.\n  \
        \  timeout: The timeout for the HTTP request in seconds. Defaults to 30.0.\n\
        \    max_retries: The maximum number of retry attempts. Defaults to 3.\n \
        \   retry_backoff: The backoff factor for the retry delay in seconds. Defaults\
        \ to 2.0.\n    max_parallel_requests: The maximum number of parallel requests\
        \ to make. Defaults to 4."
    SamplerColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: sampler
          title: Column Type
          default: sampler
        sampler_type:
          $ref: '#/components/schemas/SamplerType'
        params:
          oneOf:
          - $ref: '#/components/schemas/SubcategorySamplerParams'
          - $ref: '#/components/schemas/CategorySamplerParams'
          - $ref: '#/components/schemas/DatetimeSamplerParams'
          - $ref: '#/components/schemas/PersonSamplerParams'
          - $ref: '#/components/schemas/PersonFromFakerSamplerParams'
          - $ref: '#/components/schemas/TimeDeltaSamplerParams'
          - $ref: '#/components/schemas/UUIDSamplerParams'
          - $ref: '#/components/schemas/BernoulliSamplerParams'
          - $ref: '#/components/schemas/BernoulliMixtureSamplerParams'
          - $ref: '#/components/schemas/BinomialSamplerParams'
          - $ref: '#/components/schemas/GaussianSamplerParams'
          - $ref: '#/components/schemas/PoissonSamplerParams'
          - $ref: '#/components/schemas/UniformSamplerParams'
          - $ref: '#/components/schemas/ScipySamplerParams'
          title: Params
          discriminator:
            propertyName: sampler_type
            mapping:
              bernoulli: '#/components/schemas/BernoulliSamplerParams'
              bernoulli_mixture: '#/components/schemas/BernoulliMixtureSamplerParams'
              binomial: '#/components/schemas/BinomialSamplerParams'
              category: '#/components/schemas/CategorySamplerParams'
              datetime: '#/components/schemas/DatetimeSamplerParams'
              gaussian: '#/components/schemas/GaussianSamplerParams'
              person: '#/components/schemas/PersonSamplerParams'
              person_from_faker: '#/components/schemas/PersonFromFakerSamplerParams'
              poisson: '#/components/schemas/PoissonSamplerParams'
              scipy: '#/components/schemas/ScipySamplerParams'
              subcategory: '#/components/schemas/SubcategorySamplerParams'
              timedelta: '#/components/schemas/TimeDeltaSamplerParams'
              uniform: '#/components/schemas/UniformSamplerParams'
              uuid: '#/components/schemas/UUIDSamplerParams'
        conditional_params:
          additionalProperties:
            oneOf:
            - $ref: '#/components/schemas/SubcategorySamplerParams'
            - $ref: '#/components/schemas/CategorySamplerParams'
            - $ref: '#/components/schemas/DatetimeSamplerParams'
            - $ref: '#/components/schemas/PersonSamplerParams'
            - $ref: '#/components/schemas/PersonFromFakerSamplerParams'
            - $ref: '#/components/schemas/TimeDeltaSamplerParams'
            - $ref: '#/components/schemas/UUIDSamplerParams'
            - $ref: '#/components/schemas/BernoulliSamplerParams'
            - $ref: '#/components/schemas/BernoulliMixtureSamplerParams'
            - $ref: '#/components/schemas/BinomialSamplerParams'
            - $ref: '#/components/schemas/GaussianSamplerParams'
            - $ref: '#/components/schemas/PoissonSamplerParams'
            - $ref: '#/components/schemas/UniformSamplerParams'
            - $ref: '#/components/schemas/ScipySamplerParams'
            discriminator:
              propertyName: sampler_type
              mapping:
                bernoulli: '#/components/schemas/BernoulliSamplerParams'
                bernoulli_mixture: '#/components/schemas/BernoulliMixtureSamplerParams'
                binomial: '#/components/schemas/BinomialSamplerParams'
                category: '#/components/schemas/CategorySamplerParams'
                datetime: '#/components/schemas/DatetimeSamplerParams'
                gaussian: '#/components/schemas/GaussianSamplerParams'
                person: '#/components/schemas/PersonSamplerParams'
                person_from_faker: '#/components/schemas/PersonFromFakerSamplerParams'
                poisson: '#/components/schemas/PoissonSamplerParams'
                scipy: '#/components/schemas/ScipySamplerParams'
                subcategory: '#/components/schemas/SubcategorySamplerParams'
                timedelta: '#/components/schemas/TimeDeltaSamplerParams'
                uniform: '#/components/schemas/UniformSamplerParams'
                uuid: '#/components/schemas/UUIDSamplerParams'
          type: object
          title: Conditional Params
          default: {}
        convert_to:
          type: string
          title: Convert To
      additionalProperties: false
      type: object
      required:
      - name
      - sampler_type
      - params
      title: SamplerColumnConfig
      description: "Configuration for columns generated using numerical samplers.\n\
        \nSampler columns provide efficient data generation using numerical samplers\
        \ for\ncommon data types and distributions. Supported samplers include UUID\
        \ generation,\ndatetime/timedelta sampling, person generation, category /\
        \ subcategory sampling,\nand various statistical distributions (uniform, gaussian,\
        \ binomial, poisson, scipy).\n\nAttributes:\n    sampler_type: Type of sampler\
        \ to use. Available types include:\n        \"uuid\", \"category\", \"subcategory\"\
        , \"uniform\", \"gaussian\", \"bernoulli\",\n        \"bernoulli_mixture\"\
        , \"binomial\", \"poisson\", \"scipy\", \"person\", \"datetime\", \"timedelta\"\
        .\n    params: Parameters specific to the chosen sampler type. Type varies\
        \ based on the `sampler_type`\n        (e.g., `CategorySamplerParams`, `UniformSamplerParams`,\
        \ `PersonSamplerParams`).\n    conditional_params: Optional dictionary for\
        \ conditional parameters. The dict keys\n        are the conditions that must\
        \ be met (e.g., \"age > 21\") for the conditional parameters\n        to be\
        \ used. The values of dict are the parameters to use when the condition is\
        \ met.\n    convert_to: Optional type conversion to apply after sampling.\
        \ Must be one of \"float\", \"int\", or \"str\".\n        Useful for converting\
        \ numerical samples to strings or other types.\n    column_type: Discriminator\
        \ field, always \"sampler\" for this configuration type.\n\n!!! tip \"Displaying\
        \ available samplers and their parameters\"\n    The config builder has an\
        \ `info` attribute that can be used to display the\n    available samplers\
        \ and their parameters:\n    ```python\n    config_builder.info.display(\"\
        samplers\")\n    ```"
    SamplerType:
      type: string
      enum:
      - bernoulli
      - bernoulli_mixture
      - binomial
      - category
      - datetime
      - gaussian
      - person
      - person_from_faker
      - poisson
      - scipy
      - subcategory
      - timedelta
      - uniform
      - uuid
      title: SamplerType
    SamplingStrategy:
      type: string
      enum:
      - ordered
      - shuffle
      title: SamplingStrategy
    ScalarInequalityConstraint:
      properties:
        target_column:
          type: string
          title: Target Column
        rhs:
          type: number
          title: Rhs
        operator:
          $ref: '#/components/schemas/InequalityOperator'
      additionalProperties: false
      type: object
      required:
      - target_column
      - rhs
      - operator
      title: ScalarInequalityConstraint
    ScipySamplerParams:
      properties:
        dist_name:
          type: string
          title: Dist Name
          description: Name of a scipy.stats distribution.
        dist_params:
          additionalProperties: true
          type: object
          title: Dist Params
          description: Parameters of the scipy.stats distribution given in `dist_name`.
        decimal_places:
          type: integer
          title: Decimal Places
          description: Number of decimal places to round the sampled values to.
        sampler_type:
          type: string
          const: scipy
          title: Sampler Type
          default: scipy
      additionalProperties: false
      type: object
      required:
      - dist_name
      - dist_params
      title: ScipySamplerParams
      description: "Parameters for sampling from any scipy.stats continuous or discrete\
        \ distribution.\n\nProvides a flexible interface to sample from the wide range\
        \ of probability distributions\navailable in scipy.stats. This enables advanced\
        \ statistical sampling beyond the built-in\ndistribution types (Gaussian,\
        \ Uniform, etc.).\n\nSee: [scipy.stats documentation](https://docs.scipy.org/doc/scipy/reference/stats.html)\n\
        \nAttributes:\n    dist_name: Name of the scipy.stats distribution to sample\
        \ from (e.g., \"beta\", \"gamma\",\n        \"lognorm\", \"expon\"). Must\
        \ be a valid distribution name from scipy.stats.\n    dist_params: Dictionary\
        \ of parameters for the specified distribution. Parameter names\n        and\
        \ values must match the scipy.stats distribution specification (e.g., {\"\
        a\": 2, \"b\": 5}\n        for beta distribution, {\"scale\": 1.5} for exponential).\n\
        \    decimal_places: Optional number of decimal places to round sampled values\
        \ to. If None,\n        values are not rounded."
    Score:
      properties:
        name:
          type: string
          title: Name
          description: A clear name for this score.
        description:
          type: string
          title: Description
          description: An informative and detailed assessment guide for using this
            score.
        options:
          additionalProperties:
            type: string
          type: object
          title: Options
          description: 'Score options in the format of {score: description}.'
      additionalProperties: false
      type: object
      required:
      - name
      - description
      - options
      title: Score
      description: "Configuration for a \"score\" in an LLM judge evaluation.\n\n\
        Defines a single scoring criterion with its possible values and descriptions.\
        \ Multiple\nScore objects can be combined in an LLMJudgeColumnConfig to create\
        \ multi-dimensional\nquality assessments.\n\nAttributes:\n    name: A clear,\
        \ concise name for this scoring dimension (e.g., \"Relevance\", \"Fluency\"\
        ).\n    description: An informative and detailed assessment guide explaining\
        \ how to evaluate\n        this dimension. Should provide clear criteria for\
        \ scoring.\n    options: Dictionary mapping score values to their descriptions.\
        \ Keys can be integers\n        (e.g., 1-5 scale) or strings (e.g., \"Poor\"\
        , \"Good\", \"Excellent\"). Values are\n        descriptions explaining what\
        \ each score level means."
    SeedConfig:
      properties:
        dataset:
          type: string
          title: Dataset
        sampling_strategy:
          allOf:
          - $ref: '#/components/schemas/SamplingStrategy'
          default: ordered
        selection_strategy:
          anyOf:
          - $ref: '#/components/schemas/IndexRange'
          - $ref: '#/components/schemas/PartitionBlock'
          title: Selection Strategy
      additionalProperties: false
      type: object
      required:
      - dataset
      title: SeedConfig
      description: "Configuration for sampling data from a seed dataset.\n\nArgs:\n\
        \    dataset: Path or identifier for the seed dataset.\n    sampling_strategy:\
        \ Strategy for how to sample rows from the dataset.\n        - ORDERED: Read\
        \ rows sequentially in their original order.\n        - SHUFFLE: Randomly\
        \ shuffle rows before sampling. When used with\n          selection_strategy,\
        \ shuffling occurs within the selected range/partition.\n    selection_strategy:\
        \ Optional strategy to select a subset of the dataset.\n        - IndexRange:\
        \ Select a specific range of indices (e.g., rows 100-200).\n        - PartitionBlock:\
        \ Select a partition by splitting the dataset into N equal parts.\n      \
        \    Partition indices are zero-based (index=0 is the first partition, index=1\
        \ is\n          the second, etc.).\n\nExamples:\n    Read rows sequentially\
        \ from start to end:\n        SeedConfig(dataset=\"my_data.parquet\", sampling_strategy=SamplingStrategy.ORDERED)\n\
        \n    Read rows in random order:\n        SeedConfig(dataset=\"my_data.parquet\"\
        , sampling_strategy=SamplingStrategy.SHUFFLE)\n\n    Read specific index range\
        \ (rows 100-199):\n        SeedConfig(\n            dataset=\"my_data.parquet\"\
        ,\n            sampling_strategy=SamplingStrategy.ORDERED,\n            selection_strategy=IndexRange(start=100,\
        \ end=199)\n        )\n\n    Read random rows from a specific index range\
        \ (shuffles within rows 100-199):\n        SeedConfig(\n            dataset=\"\
        my_data.parquet\",\n            sampling_strategy=SamplingStrategy.SHUFFLE,\n\
        \            selection_strategy=IndexRange(start=100, end=199)\n        )\n\
        \n    Read from partition 2 (3rd partition, zero-based) of 5 partitions (20%\
        \ of dataset):\n        SeedConfig(\n            dataset=\"my_data.parquet\"\
        ,\n            sampling_strategy=SamplingStrategy.ORDERED,\n            selection_strategy=PartitionBlock(index=2,\
        \ num_partitions=5)\n        )\n\n    Read shuffled rows from partition 0\
        \ of 10 partitions (shuffles within the partition):\n        SeedConfig(\n\
        \            dataset=\"my_data.parquet\",\n            sampling_strategy=SamplingStrategy.SHUFFLE,\n\
        \            selection_strategy=PartitionBlock(index=0, num_partitions=10)\n\
        \        )"
    SeedDatasetColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: seed-dataset
          title: Column Type
          default: seed-dataset
      additionalProperties: false
      type: object
      required:
      - name
      title: SeedDatasetColumnConfig
      description: "Configuration for columns sourced from seed datasets.\n\nThis\
        \ config marks columns that come from seed data. It is typically created\n\
        automatically when calling `with_seed_dataset()` on the builder, rather than\n\
        being instantiated directly by users.\n\nAttributes:\n    column_type: Discriminator\
        \ field, always \"seed-dataset\" for this configuration type."
    SettingsDefaults:
      properties:
        model_configs:
          items:
            $ref: '#/components/schemas/ModelConfigOutput'
          type: array
          title: Model Configs
        model_provider:
          type: string
          title: Model Provider
      type: object
      required:
      - model_configs
      - model_provider
      title: SettingsDefaults
    SettingsResponse:
      properties:
        defaults:
          $ref: '#/components/schemas/SettingsDefaults'
        model_providers:
          items:
            $ref: '#/components/schemas/DisplayModelProvider'
          type: array
          title: Model Providers
      type: object
      required:
      - defaults
      - model_providers
      title: SettingsResponse
    SubcategorySamplerParams:
      properties:
        category:
          type: string
          title: Category
          description: Name of parent category to this subcategory.
        values:
          additionalProperties:
            items:
              anyOf:
              - type: string
              - type: integer
              - type: number
            type: array
          type: object
          title: Values
          description: Mapping from each value of parent category to a list of subcategory
            values.
        sampler_type:
          type: string
          const: subcategory
          title: Sampler Type
          default: subcategory
      additionalProperties: false
      type: object
      required:
      - category
      - values
      title: SubcategorySamplerParams
      description: "Parameters for subcategory sampling conditioned on a parent category\
        \ column.\n\nSamples subcategory values based on the value of a parent category\
        \ column. Each parent\ncategory value maps to its own list of possible subcategory\
        \ values, enabling hierarchical\nor conditional sampling patterns.\n\nAttributes:\n\
        \    category: Name of the parent category column that this subcategory depends\
        \ on.\n        The parent column must be generated before this subcategory\
        \ column.\n    values: Mapping from each parent category value to a list of\
        \ possible subcategory values.\n        Each key must correspond to a value\
        \ that appears in the parent category column."
    TimeDeltaSamplerParams:
      properties:
        dt_min:
          type: integer
          minimum: 0.0
          title: Dt Min
          description: Minimum possible time-delta for sampling range, inclusive.
            Must be less than `dt_max`.
        dt_max:
          type: integer
          exclusiveMinimum: 0.0
          title: Dt Max
          description: Maximum possible time-delta for sampling range, exclusive.
            Must be greater than `dt_min`.
        reference_column_name:
          type: string
          title: Reference Column Name
          description: Name of an existing datetime column to condition time-delta
            sampling on.
        unit:
          type: string
          enum:
          - D
          - h
          - m
          - s
          title: Unit
          description: Sampling units, e.g. the smallest possible time interval between
            samples.
          default: D
        sampler_type:
          type: string
          const: timedelta
          title: Sampler Type
          default: timedelta
      additionalProperties: false
      type: object
      required:
      - dt_min
      - dt_max
      - reference_column_name
      title: TimeDeltaSamplerParams
      description: "Parameters for sampling time deltas relative to a reference datetime\
        \ column.\n\nSamples time offsets within a specified range and adds them to\
        \ values from a reference\ndatetime column. This is useful for generating\
        \ related datetime columns like order dates\nand delivery dates, or event\
        \ start times and end times.\n\nNote:\n    Years and months are not supported\
        \ as timedelta units because they have variable lengths.\n    See: [pandas\
        \ timedelta documentation](https://pandas.pydata.org/docs/user_guide/timedeltas.html)\n\
        \nAttributes:\n    dt_min: Minimum time-delta value (inclusive). Must be non-negative\
        \ and less than `dt_max`.\n        Specified in units defined by the `unit`\
        \ parameter.\n    dt_max: Maximum time-delta value (exclusive). Must be positive\
        \ and greater than `dt_min`.\n        Specified in units defined by the `unit`\
        \ parameter.\n    reference_column_name: Name of an existing datetime column\
        \ to add the time-delta to.\n        This column must be generated before\
        \ the timedelta column.\n    unit: Time unit for the delta values. Options:\n\
        \        - \"D\": Days (default)\n        - \"h\": Hours\n        - \"m\"\
        : Minutes\n        - \"s\": Seconds"
    UUIDSamplerParams:
      properties:
        prefix:
          type: string
          title: Prefix
          description: String prepended to the front of the UUID.
        short_form:
          type: boolean
          title: Short Form
          description: If true, all UUIDs sampled will be truncated at 8 characters.
          default: false
        uppercase:
          type: boolean
          title: Uppercase
          description: If true, all letters in the UUID will be capitalized.
          default: false
        sampler_type:
          type: string
          const: uuid
          title: Sampler Type
          default: uuid
      additionalProperties: false
      type: object
      title: UUIDSamplerParams
      description: "Parameters for generating UUID (Universally Unique Identifier)\
        \ values.\n\nGenerates UUID4 (random) identifiers with optional formatting\
        \ options. UUIDs are useful\nfor creating unique identifiers for records,\
        \ entities, or transactions.\n\nAttributes:\n    prefix: Optional string to\
        \ prepend to each UUID. Useful for creating namespaced or\n        typed identifiers\
        \ (e.g., \"user-\", \"order-\", \"txn-\").\n    short_form: If True, truncates\
        \ UUIDs to 8 characters (first segment only). Default is False\n        for\
        \ full 32-character UUIDs (excluding hyphens).\n    uppercase: If True, converts\
        \ all hexadecimal letters to uppercase. Default is False for\n        lowercase\
        \ UUIDs."
    UniformDistribution:
      properties:
        distribution_type:
          allOf:
          - $ref: '#/components/schemas/DistributionType'
          default: uniform
        params:
          $ref: '#/components/schemas/UniformDistributionParams'
      additionalProperties: false
      type: object
      required:
      - params
      title: UniformDistribution
    UniformDistributionParams:
      properties:
        low:
          type: number
          title: Low
        high:
          type: number
          title: High
      additionalProperties: false
      type: object
      required:
      - low
      - high
      title: UniformDistributionParams
    UniformSamplerParams:
      properties:
        low:
          type: number
          title: Low
          description: Lower bound of the uniform distribution, inclusive.
        high:
          type: number
          title: High
          description: Upper bound of the uniform distribution, inclusive.
        decimal_places:
          type: integer
          title: Decimal Places
          description: Number of decimal places to round the sampled values to.
        sampler_type:
          type: string
          const: uniform
          title: Sampler Type
          default: uniform
      additionalProperties: false
      type: object
      required:
      - low
      - high
      title: UniformSamplerParams
      description: "Parameters for sampling from a continuous Uniform distribution.\n\
        \nSamples continuous values uniformly from a specified range, where every\
        \ value in the range\nhas equal probability of being sampled. This is useful\
        \ when all values within a range are\nequally likely, such as random percentages,\
        \ proportions, or unbiased measurements.\n\nAttributes:\n    low: Lower bound\
        \ of the uniform distribution (inclusive). Can be any real number.\n    high:\
        \ Upper bound of the uniform distribution (inclusive). Must be greater than\
        \ `low`.\n    decimal_places: Optional number of decimal places to round sampled\
        \ values to. If None,\n        values are not rounded and may have many decimal\
        \ places."
    ValidationColumnConfig:
      properties:
        name:
          type: string
          title: Name
        drop:
          type: boolean
          title: Drop
          default: false
        column_type:
          type: string
          const: validation
          title: Column Type
          default: validation
        target_columns:
          items:
            type: string
          type: array
          title: Target Columns
        validator_type:
          $ref: '#/components/schemas/ValidatorType'
        validator_params:
          anyOf:
          - $ref: '#/components/schemas/CodeValidatorParams'
          - $ref: '#/components/schemas/LocalCallableValidatorParams'
          - $ref: '#/components/schemas/RemoteValidatorParams'
          title: Validator Params
        batch_size:
          type: integer
          minimum: 1.0
          title: Batch Size
          description: Number of records to process in each batch
          default: 10
      additionalProperties: false
      type: object
      required:
      - name
      - target_columns
      - validator_type
      - validator_params
      title: ValidationColumnConfig
      description: "Configuration for validation columns that validate existing columns.\n\
        \nValidation columns execute validation logic against specified target columns\
        \ and return\nstructured results indicating pass/fail status with validation\
        \ details. Supports multiple\nvalidation strategies: code execution (Python/SQL),\
        \ local callable functions (library only),\nand remote HTTP endpoints.\n\n\
        Attributes:\n    target_columns: List of column names to validate. These columns\
        \ are passed to the\n        validator for validation. All target columns\
        \ must exist in the dataset\n        before validation runs.\n    validator_type:\
        \ The type of validator to use. Options:\n        - \"code\": Execute code\
        \ (Python or SQL) for validation. The code receives a\n          DataFrame\
        \ with target columns and must return a DataFrame with validation results.\n\
        \        - \"local_callable\": Call a local Python function with the data.\
        \ Only supported\n          when running DataDesigner locally.\n        -\
        \ \"remote\": Send data to a remote HTTP endpoint for validation. Useful for\n\
        \    validator_params: Parameters specific to the validator type. Type varies\
        \ by validator:\n        - CodeValidatorParams: Specifies code language (python\
        \ or SQL dialect like\n          \"sql:postgres\", \"sql:mysql\").\n     \
        \   - LocalCallableValidatorParams: Provides validation function (Callable[[pd.DataFrame],\n\
        \          pd.DataFrame]) and optional output schema for validation results.\n\
        \        - RemoteValidatorParams: Configures endpoint URL, HTTP timeout, retry\
        \ behavior\n          (max_retries, retry_backoff), and parallel request limits\
        \ (max_parallel_requests).\n    batch_size: Number of records to process in\
        \ each validation batch. Defaults to 10.\n        Larger batches are more\
        \ efficient but use more memory. Adjust based on validator\n        complexity\
        \ and available resources.\n    column_type: Discriminator field, always \"\
        validation\" for this configuration type."
    ValidationError:
      properties:
        loc:
          items:
            anyOf:
            - type: string
            - type: integer
          type: array
          title: Location
        msg:
          type: string
          title: Message
        type:
          type: string
          title: Error Type
      type: object
      required:
      - loc
      - msg
      - type
      title: ValidationError
    ValidatorType:
      type: string
      enum:
      - code
      - local_callable
      - remote
      title: ValidatorType
tags:
- name: Data Designer
  description: Operations related to synthetic data generation.
- name: Health Checks
  description: Operations related to NeMo Microservices platform health.