openapi: 3.1.0
info:
  title: Emissary API
  description: |-
    v0.1.0
  termsOfService: https://www.withemissary.com/terms-of-service
  contact:
    email: contact@withemissary.com
  license:
    name: Apache 2.0
    url: http://www.apache.org/licenses/LICENSE-2.0.html
  version: 0.1.0
security:
  - api_key: []
servers:
  - url: https://api.withemissary.com
    description: Emissary API server
tags:
  - name: Base Models
    description: Deals with base models
  - name: Projects
    description: Deals with projects (workspace)
  - name: Dataset
    description: Datasets are used to upload documents that can be used for fine-tuning
  - name: Training Jobs
    description: Deals with training jobs
  - name: Inference Engines
    description: Inference Engine API endpoints
  - name: Deployments
    description: Deals with deployments
  - name: Inference
    description: Deals with inference request to the deployed model
paths:
  '/v1/models':
    get:
      tags:
        - Base Models
      summary: List base models
      description: List and describe the various models available in the API
      operationId: listBaseModels
      responses:
        '200':
          description: List of base models
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/BaseModelSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/models/{base_model_name}':
    get:
      tags:
        - Base Models
      summary: Retrieve base model
      description: Retrieves a model instance, providing basic information about the model such as the hyper parameters that can be adjusted
      operationId: retrieveBaseModelByName
      parameters:
        - name: base_model_name
          in: path
          required: true
          description: The name of the base model to use for this request
          schema:
            type: string
      responses:
        '200':
          description: The base model object matching the specified name.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/BaseModelSummary"
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects': # path parameter in curly braces
    post:
      tags:
        - Projects
      summary: Create project
      description: Create a new project. Projects can be created and used to organize datasets, training jobs, and deployments.
      operationId: createProject
      requestBody:
        #        description: Provide your project name if you want to specify it.
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                  example: my_project
                  description: The name of the project
        required: false
      responses:
        '201':
          description: The created Project's summary object
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/ProjectSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
    get:
      tags:
        - Projects
      # documentation for GET operation for this path
      summary: List projects
      # you can use GFM in operation description too: https://guides.github.com/features/mastering-markdown
      description: |
        Returns a list of projects.
      # operationId should be unique across the whole specification
      operationId: listProjects
      # security schemas applied to this operation
      responses:
        '200':
          description: List of Project's summary object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/ProjectSummary"
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/projects/{project_id}':
    get:
      tags:
        - Projects
      summary: Retrieve project
      description: Retrieve a project.
      operationId: retrieveProjectById
      parameters:
        - name: project_id
          in: path
          schema:
            type: string
          description: The ID of the project.
          required: true
      responses:
        '200':
          description: The ProjectDetail object matching the specified ID.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/ProjectDetail"
        '404':
          $ref: '#/components/responses/NotFound'
    delete:
      tags:
        - Projects
      summary: Delete project
      description: Delete a project.
      operationId: deleteProjectById
      parameters:
        - name: project_id
          in: path
          schema:
            type: string
          description: The ID of the project.
          required: true
      responses:
        '204':
          description: Project deleted successfully
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects/{project_id}/datasets':
    post:
      tags:
        - Datasets
      summary: Upload dataset
      description: Upload dataset to the project (upto 5MB). Upload through UI if your dataset size is larger than 5MB.
      operationId: createDataset
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              type: object
              properties:
                file:
                  type: string
                  format: binary
                  description: The dataset file (binary format) to upload
                name:
                  type: string
                  example: my_dataset
                  description: The name of the dataset (optional)
              required:
                - file
      responses:
        '201':
          description: The Dataset's summary object.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/DatasetSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
    get:
      tags:
        - Datasets
      summary: List datasets
      description: Returns a list of datasets
      operationId: listDatasets
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      responses:
        '200':
          description: List of Dataset's summary object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/DatasetSummary"
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/projects/{project_id}/datasets/{dataset_id}':
    get:
      tags:
        - Datasets
      summary: Retrieve dataset
      description: Retrieve a dataset.
      operationId: retrieveDatasetById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: dataset_id
          in: path
          required: true
          description: The ID of the dataset.
          schema:
            type: string
      responses:
        '200':
          description: The DatasetDetail object matching the specified ID.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/DatasetDetail"
        '404':
          $ref: '#/components/responses/NotFound'
    delete:
      tags:
        - Datasets
      summary: Delete dataset
      description: Delete a dataset.
      operationId: deleteDatasetById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: dataset_id
          in: path
          required: true
          description: The ID of the dataset
          schema:
            type: string
      responses:
        '204':
          description: Dataset deleted successfully
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects/{project_id}/training-jobs':
    post:
      tags:
        - Training Jobs
      summary: Create SFT training job
      description: Initiate fine-tuning (training job).
      operationId: createTrainingJob
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                base_model_option:
                  type: string
                  enum:
                    - pre-trained
                    - fine-tuned
                  example: "pre-trained"
                  description: Base Model option to be used (default = "pre-trained"), you can either start from the pure base model (pre-trained) or from any checkpoint for your fine-tuned model (fine-tuned)
                base_model:
                  type: string
                  example: "Llama-3.2-1B-Instruct"
                  description: The base model to fine-tune. To see full list of supported base model please visit [Base Models](/fine-tuning/parameters#available-base-models). If you are training on fine-tuned base model option, specify the training job name you want to use.
                checkpoint:
                  type: number
                  example: 5
                  description: If base_model_option == "fine-tuned", specify the checkpoint you want to use.
                train_dataset_id:
                  type: string
                  example: "ds-12345"
                  description: The training dataset ID to use for fine-tuning
                test_dataset_id:
                  type: string
                  example: "ds-67890"
                  description: The testing dataset ID to use for fine-tuning (optional)
                train_test_split_ratio:
                  type: number
                  example: 20
                  description: The ratio (%) to split the training dataset for testing (optional)
                test_functions:
                  type: array
                  example: ["test_similarity_shared"]
                  items:
                    type: string
                    description: List of test function names to be used (optional)
                name:
                  type: string
                  example: "training-job-1"
                  description: The name of the training job (optional)
                description:
                  type: string
                  example: "Fine-tuning the model on my dataset"
                  description: A description of the training job (optional)
                task_type:
                  type: string
                  enum:
                    - text-generation
                    - classification
                    - embedding
                    - regression
                  example: "text-generation"
                  description: The task type for the training job (default = "text-generation")
                parameters:
                  type: object
                  properties:
                    downsample_size:
                      type: number
                      example: 20
                    learning_rate:
                      type: number
                      example: 0.0002
                    num_train_epochs:
                      type: number
                      example: 3
                    per_device_train_batch_size:
                      type: number
                      example: 2
                    per_device_eval_batch_size:
                      type: number
                      example: 2
                    dynamic_loss:
                      type: boolean
                      example: false
                      description: (Default = false) Set to true if you want to enable dynamic loss function
                  description: The hyper parameters to use for fine-tuning (optional)
                rebalance_data:
                  description: (Optional) Currently only supported for classification task type.
                  oneOf:
                    - title: ratio
                      type: object
                      description: |
                        A mapping from category labels (as keys) to the ratio for resampling the dataset. The total size of the dataset will remain consistently.
                      additionalProperties:
                        type: number
                        format: float
                      example:
                        label1: 0.3
                        label2: 0.7
                    - title: number
                      type: object
                      description: |
                        A mapping from category labels (as keys) to the number for resampling the dataset. The exact number of data will be created or deleted to fit the number that is provided
                      additionalProperties:
                        type: number
                      example:
                        label1: 300
                        label2: 300
                        label3: 500
                hf_model_link:
                  type: string
                  example: "https://huggingface.co/my_model"
                  description: Link to the Hugging Face model / Use only when you use the HF_MODEL as a base
              required:
                - base_model
                - train_dataset_id
      responses:
        '201':
          description: Returns the TrainingJob's summary object.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/TrainingJobSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
    get:
      tags:
        - Training Jobs
      summary: List training jobs
      description: Returns a list of training jobs
      operationId: listTrainingJobs
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      responses:
        '200':
          description: List of TrainingJob's summary object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/TrainingJobSummary"
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/projects/{project_id}/training-jobs/grpo':
    post:
      tags:
        - Training Jobs
      summary: Create GRPO training job
      description: Initiate GRPO fine-tuning (training job).
      operationId: createGRPOTrainingJob
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                base_model_option:
                  type: string
                  enum:
                    - pre-trained
                    - fine-tuned
                  example: "pre-trained"
                  description: Base Model option to be used (default = "pre-trained"), you can either start from the pure base model (pre-trained) or from any checkpoint for your fine-tuned model (fine-tuned)
                base_model:
                  type: string
                  example: "Llama-3.2-1B-Instruct"
                  description: The base model to fine-tune. To see full list of supported base model please visit [Base Models](/fine-tuning/parameters#available-base-models). If you are training on fine-tuned base model option, specify the training job name you want to use.
                checkpoint:
                  type: number
                  example: 5
                  description: (Required if base_model_option == "fine-tuned"), specify the checkpoint you want to use.
                train_dataset_id:
                  type: string
                  example: "ds-12345"
                  description: The training dataset ID to use for fine-tuning
                test_functions:
                  type: array
                  example: [ "test_similarity_shared" ]
                  items:
                    type: string
                    description: Name of test function to be used
                reward:
                  type: object
                  description: (GRPO) Reward weight map
                  properties:
                    test_function_1:
                      type: float
                      example: 0.2
                    test_function_2:
                      type: float
                      example: 0.8
                test_dataset_id:
                  type: string
                  example: "ds-67890"
                  description: The testing dataset ID to use for fine-tuning (optional)
                train_test_split_ratio:
                  type: number
                  example: 20
                  description: The ratio (%) to split the training dataset for testing (optional)
                name:
                  type: string
                  example: "training-1"
                  description: The name of the training job (optional)
                description:
                  type: string
                  example: "Fine-tuning the model on my dataset"
                  description: A description of the training job (optional)
                task_type:
                  type: string
                  enum:
                    - text-generation
                    - classification
                    - embedding
                    - regression
                  example: "text-generation"
                  description: The task type for the training job (default = "text-generation")
                parameters:
                  type: object
                  properties:
                    learning_rate:
                      type: number
                      example: 0.0002
                    num_train_epochs:
                      type: number
                      example: 15
                    num_generations:
                      type: number
                      example: 4
                    per_device_train_batch_size:
                      type: number
                      example: 4
                hf_model_link:
                  type: string
                  example: "https://huggingface.co/my_model"
                  description: Link to the Hugging Face model / Use only when you use the HF_MODEL as a base
              required:
                - base_model
                - train_dataset_id
                - test_functions
                - reward
      responses:
        '201':
          description: Returns the TrainingJob's summary object.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/TrainingJobSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
  '/v1/projects/{project_id}/training-jobs/{training_job_id}':
    get:
      tags:
        - Training Jobs
      summary: Retrieve training job
      description: Retrieve a training job.
      operationId: retrieveTrainingJobById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: training_job_id
          in: path
          required: true
          description: The ID of the training job.
          schema:
            type: string
      responses:
        '200':
          description: The TrainingJobDetail object matching the specified ID.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/TrainingJobDetail"
        '404':
          $ref: '#/components/responses/NotFound'
    delete:
      tags:
        - Training Jobs
      summary: Delete training job
      description: Delete a training job.
      operationId: deleteTrainingJobById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: training_job_id
          in: path
          required: true
          description: The ID of the training job
          schema:
            type: string
      responses:
        '204':
          description: Training job deleted successfully
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects/{project_id}/training-jobs/{training_job_id}/cancel':
    post:
      tags:
        - Training Jobs
      summary: Cancel training job
      description: Cancel a training job.
      operationId: cancelTrainingJobById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: training_job_id
          in: path
          required: true
          description: The ID of the training job
          schema:
            type: string
      responses:
        '204':
          description: Training job canceled successfully
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects/{project_id}/training-jobs/{training_job_id}/checkpoints':
    get:
      tags:
        - Training Jobs
      summary: List checkpoints
      description: Returns a list of checkpoints for a training job.
      operationId: listCheckpoints
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: training_job_id
          in: path
          required: true
          description: The ID of the training job
          schema:
            type: string
      responses:
        '200':
          description: List of TrainingJobCheckpoint object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/TrainingJobCheckpoint"
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/engines':
    post:
      tags:
        - Inference Engines
      summary: Create Inference Engine
      description: Create a new inference engine.
      operationId: createEngine
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                  example: "inference-test-engine"
                base_model:
                  type: string
                  example: "Llama-3.2-1B-Instruct"
                task_type:
                  type: string
                  example: "text-generation"
                resource_management_config:
                  oneOf:
                    - title: Inactive Timeout
                      description: Specifies the period of inactivity, in seconds, after which the deployment will be automatically deactivated if no incoming requests are received. While deactivated, the deployment incurs no charges. When a request is sent to a deactivated deployment, it will be reactivated to process the request; this reactivation process typically introduces a delay of approximately 8 to 20 minutes before the deployment becomes fully operational.
                      type: object
                      properties:
                        management_type:
                          type: string
                          example: "inactive_timeout"
                        management_config:
                          type: object
                          properties:
                            inactive_duration:
                              type: integer
                              example: 3600
                              description: Period of inactivity
                    - title: Schedule
                      description: Specifies the schedule which the engine will be deployed with deployments (if existing on the engine).
                      type: object
                      properties:
                        management_type:
                          type: string
                          example: "schedule"
                        management_config:
                          type: object
                          properties:
                            timezone:
                              type: string
                              example: "America/Los_Angeles"
                              description: The IANA timezone for the schedule
                            start_time:
                              type: string
                              example: "10:00"
                              description: The start time for the schedule in HH:MM format
                            end_time:
                              type: string
                              example: "18:00"
                              description: The end time for the schedule in HH:MM format
                            days:
                              type: array
                              example: [ "monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday" ]
                              items:
                                type: string
                                enum:
                                  - monday
                                  - tuesday
                                  - wednesday
                                  - thursday
                                  - friday
                                  - saturday
                                  - sunday
                              description: The days of the week for the schedule
              required:
                - base_model
      responses:
        '201':
          description: The created Inference Engine's summary object
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/InferenceEngineSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
        '401':
          $ref: '#/components/responses/Unauthorized'
    get:
      tags:
        - Inference Engines
      summary: List Inference Engines
      description: Returns a list of inference engines
      operationId: listEngines
      parameters:
        - name: base_model
          in: query
          description: Filter engines by base model
          required: false
          schema:
            type: string
        - name: task_type
          in: query
          description: Filter engines by task type
          required: false
          schema:
            type: string
      responses:
        '200':
          description: List of Inference Engine's summary object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/InferenceEngineSummary"
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/engines/{engine_id}':
    get:
      tags:
        - Inference Engines
      summary: Retrieve Inference Engine
      description: Retrieve Inference Engine's Details
      operationId: getEngine
      parameters:
        - name: engine_id
          in: path
          required: true
          description: The ID of the Inference Engine
          schema:
            type: string
      responses:
        '200':
          description: The InferenceEngineDetail object matching the specified ID.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/InferenceEngineDetail"
        '404':
          $ref: '#/components/responses/NotFound'
    delete:
      tags:
        - Inference Engines
      summary: Delete Inference Engine
      description: Delete an inference engine.
      operationId: deleteEngineById
      parameters:
        - name: engine_id
          in: path
          required: true
          description: The ID of the Inference Engine
          schema:
            type: string
      responses:
        '204':
          description: Inference Engine deleted successfully
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/engines/{engine_id}/deploy':
    post:
      tags:
        - Inference Engines
      summary: Create Deployment on Inference Engine
      description: Create deployment on Inference Engine
      operationId: deployOnEngine
      parameters:
        - name: engine_id
          in: path
          required: true
          description: The ID of the Inference Engine
          schema:
            type: string
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                  example: "test-deployment"
                project_id:
                  type: string
                  example: "ms-123465"
                  description: Model Service ID
                training_id:
                  type: string
                  example: "tr-12345"
                  description: Training Job ID to be deployed
                checkpoint:
                  type: integer
                  example: 1
                  description: Checkpoint of the training job to be deployed
              required:
                - project_id
                - training_id
                - checkpoint
      responses:
        '201':
          description: The created Deployment's summary object
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/DeploymentSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/engines/{engine_id}/undeploy':
    post:
      tags:
        - Inference Engines
      summary: Undeploy from Inference Engine
      description: Undeploy the deployment from the Inference Engine
      operationId: unDeployFromEngine
      parameters:
        - name: engine_id
          in: path
          required: true
          description: The ID of the Inference Engine
          schema:
            type: string
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                deployment_name:
                  type: string
                  example: "my-deployment"
              required:
                - deployment_name
      responses:
        '204':
          description: Undeployed Successfully
        '400':
          $ref: '#/components/responses/InvalidInput'
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/engines/{engine_id}/reactivate':
    post:
      tags:
        - Inference Engines
      summary: Reactivate Inference Engine
      description: Reactivate a inactive inference engine.
      operationId: reactivateEngineById
      parameters:
        - name: engine_id
          in: path
          required: true
          description: The ID of the Inference Engine
          schema:
            type: string
      responses:
        '204':
          description: Inference Engine reactivated successfully
        '400':
          description: When reactivate request on engine which is already deployed or in reactivation
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/engines/{engine_id}/deactivate':
    post:
      tags:
        - Inference Engines
      summary: Deactivate Inference Engine
      description: Deactivate an inference engine.
      operationId: deactivateEngineById
      parameters:
        - name: engine_id
          in: path
          required: true
          description: The ID of the Inference Engine
          schema:
            type: string
      responses:
        '204':
          description: Inference Engine deactivated successfully
        '400':
          description: When deactivate request on engine which is not Active
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects/{project_id}/deployments':
    post:
      tags:
        - Deployments
      summary: Create deployment
      description: Create a new deployment.
      operationId: createDeployment
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                training_job_id:
                  type: string
                  example: "tr-12345"
                  description: The training job ID to use for deployment or the model name for base model deployment
                checkpoint:
                  type: integer
                  example: 4
                  description: The checkpoint number to use for deployment (0 for base model deployment)
                name:
                  type: string
                  example: "deployment-1"
                  description: The name of the deployment
                description:
                  type: string
                  example: "Deployment for my training job"
                  description: A description of the deployment
                inactive_timeout:
                  type: integer
                  example: 3600
                  description: Inactive Timeout (seconds) (default = 3600). Specifies the period of inactivity, in seconds, after which the deployment will be automatically deactivated if no incoming requests are received. While deactivated, the deployment incurs no charges. When a request is sent to a deactivated deployment, it will be reactivated to process the request; this reactivation process typically introduces a delay of approximately 8 to 20 minutes before the deployment becomes fully operational.
                schedule:
                  type: object
                  properties:
                    timezone:
                      type: string
                      example: "America/Los_Angeles"
                      description: The IANA timezone for the schedule
                    start_time:
                      type: string
                      example: "10:00"
                      description: The start time for the schedule in HH:MM format
                    end_time:
                      type: string
                      example: "18:00"
                      description: The end time for the schedule in HH:MM format
                    days:
                      type: array
                      example: ["monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday"]
                      items:
                        type: string
                        enum:
                          - monday
                          - tuesday
                          - wednesday
                          - thursday
                          - friday
                          - saturday
                          - sunday
                      description: The days of the week for the schedule
              required:
                - training_job_id
                - checkpoint
      responses:
        '201':
          description: The created Deployment's summary object
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/DeploymentSummary"
        '400':
          $ref: '#/components/responses/InvalidInput'
    get:
      tags:
        - Deployments
      summary: List deployments
      description: Returns a list of deployments
      operationId: listDeployments
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      responses:
        '200':
          description: List of Deployment's summary object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/DeploymentSummary"
        '401':
          $ref: '#/components/responses/Unauthorized'
  '/v1/projects/{project_id}/deployments/{deployment_id}':
    get:
      tags:
        - Deployments
      summary: Retrieve deployment
      description: Retrieve a deployment.
      operationId: retrieveDeploymentById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: deployment_id
          in: path
          required: true
          description: The ID of the deployment.
          schema:
            type: string
      responses:
        '200':
          description: The DeploymentDetail object matching the specified ID.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/DeploymentDetail"
        '404':
          $ref: '#/components/responses/NotFound'
    delete:
      tags:
        - Deployments
      summary: Delete deployment
      description: Delete a deployment.
      operationId: deleteDeploymentById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: deployment_id
          in: path
          required: true
          description: The ID of the deployment
          schema:
            type: string
      responses:
        '204':
          description: Deployment deleted successfully
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/projects/{project_id}/deployments/{deployment_id}/reactivate':
    post:
      tags:
        - Deployments
      summary: Reactivate deployment
      description: Reactivate a deactivated deployment.
      operationId: reactivateDeploymentById
      parameters:
        - $ref: '#/components/parameters/ProjectId'
        - name: deployment_id
          in: path
          required: true
          description: The ID of the deployment
          schema:
            type: string
      responses:
        '204':
          description: Deployment reactivated successfully
        '400':
          description: When reactivate request on deployment which is already deployed or in reactivation
        '404':
          $ref: '#/components/responses/NotFound'
  '/v1/completions':
    post:
      tags:
        - Inference
      summary: Completions
      description: Get completions from a deployment using the provided input.
      operationId: getCompletionsFromDeployment
      requestBody:
        required: true
        description: Provide you prompt input for completions
        content:
          application/json:
            schema:
              type: object
              properties:
                model:
                  type: string
                  example: "Llama-3.2-1B-Instruct"
                  description: "Deployment name or shared serverless base model name"
                prompt:
                  type: string
                  example: "The capital of France is"
                  description: The input prompt for the deployment
                temperature:
                  type: number
                  example: 0.7
                  description: The sampling temperature to use
                max_completion_tokens:
                  type: integer
                  example: 500
                  description: The maximum number of new tokens to generate
                top_p:
                  type: number
                  example: 0.9
                  description: The cumulative probability for token selection
                top_k:
                  type: integer
                  example: 50
                  description: The number of highest probability tokens to keep for top-k-filtering
              required:
                - model
                - prompt
      responses:
        '200':
          description: Successful operation
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/CompletionObject"
        '404':
          $ref: '#/components/responses/NotFound'
        '400':
          $ref: '#/components/responses/InvalidInput'
  '/v1/chat/completions':
    post:
      tags:
        - Inference
      summary: Chat Completions
      description: Get chat completions from a serverless deployment.
      operationId: getChatCompletions
      requestBody:
        required: true
        description: Provide your model and chat input for completions
        content:
          application/json:
            schema:
              type: object
              properties:
                model:
                  type: string
                  example: "Llama-3.2-1B-Completion"
                  description: "Deployment name or shared serverless base model name"
                messages:
                  type: array
                  items:
                    type: object
                    properties:
                      role:
                        type: string
                        enum:
                          - system
                          - user
                          - assistant
                        example: "user"
                        description: The role of the message sender
                      content:
                        type: string
                        example: "Hello, how are you?"
                        description: The content of the message
                  required:
                    - role
                    - content
                temperature:
                  type: number
                  example: 0.7
                  description: The sampling temperature to use
                max_tokens:
                  type: integer
                  example: 64
                  description: The maximum number of new tokens to generate
                top_p:
                  type: number
                  example: 0.9
                  description: The cumulative probability for token selection
                top_k:
                  type: integer
                  example: 50
                  description: The number of highest probability tokens to keep for top-k-filtering
                required:
                  - model
                  - messages
      responses:
        '200':
          description: Returns a chat completion object, or a streamed sequence of chat completion chunk objects if the request is streamed.
          content:
            application/json:
              schema:
                "$ref": "#/components/schemas/ChatCompletionObject"
        '404':
          $ref: '#/components/responses/NotFound'
        '400':
          $ref: '#/components/responses/InvalidInput'
  '/v1/embeddings':
    post:
      tags:
        - Inference
      summary: Embeddings
      description: Get embeddings from a deployment using the provided input.
      operationId: getEmbeddingsFromDeployment
      requestBody:
        required: true
        description: Provide your input for embeddings
        content:
          application/json:
            schema:
              type: object
              properties:
                model:
                  type: string
                  example: "Llama-3.2-1B-Instruct"
                  description: "Deployment name or shared serverless base model name"
                input:
                  type: string
                  example: "What is the capital of France?"
                  description: The input for which to get embeddings
                target:
                  type: string
                  example: "Paris is the capital of France."
                  description: The target sentence for comparison
                cosine:
                  type: boolean
                  example: true
                  description: Whether to return cosine similarity
                manhattan:
                  type: boolean
                  example: false
                  description: Whether to return Manhattan distance
                euclidean:
                  type: boolean
                  example: false
                  description: Whether to return Euclidean distance
              required:
                - model
                - input
                - target
      responses:
        '200':
          description: Successful operation
          content:
            application/json:
              schema:
                type: object
                properties:
                  id:
                    type: string
                    example: "rq-12345"
                    description: The unique identifier for the embedding
                  response:
                    type: object
                    properties:
                      input_embedding:
                        type: array
                        items:
                          type: number
                        description: The embedding vector for the input
                      target_embedding:
                        type: array
                        items:
                          type: number
                        description: The embedding vector for the target
                      cosine_score:
                        type: number
                        description: The cosine similarity between the embeddings if target not none
                      manhattan_distance:
                        type: number
                        description: The Manhattan distance between the embeddings if manhattan = true
                      euclidean_distance:
                        type: number
                        description: The Euclidean distance between the embeddings if euclidean = true
        '404':
          $ref: '#/components/responses/NotFound'
        '400':
          $ref: '#/components/responses/InvalidInput'
  '/v1/classification':
    post:
      tags:
        - Inference
      summary: Classification
      description: Get classification from a deployment using the provided input.
      operationId: getClassificationFromDeployment
      requestBody:
        required: true
        description: Provide your input for classification
        content:
          application/json:
            schema:
              type: object
              properties:
                model:
                  type: string
                  example: "Llama-3.2-1B-Instruct"
                  description: "Deployment name or shared serverless base model name"
                input:
                  type: string
                  example: "category1 related text"
                  description: The input for which to get classification
                data_format:
                  type: string
                  enum:
                    - logits
                    - probs
                  description: |
                    (Optional) Specifies the format of the classification output data. 
                    - If set to `logits` (default), the raw, unnormalized scores from the model are returned.
                    - If set to `probs`, the output will be normalized probabilities.
              required:
                - model
                - input
      responses:
        '200':
          description: Successful operation
          content:
            application/json:
              schema:
                type: object
                properties:
                  id:
                    type: string
                    example: "classify-12345"
                    description: The unique identifier for the classification
                  model:
                    type: string
                    example: "dp-12345"
                  data:
                    type: array
                    items:
                      oneOf:
                        - title: logits
                          type: object
                          properties:
                            index:
                              type: number
                              example: 0
                            logits:
                              type: object
                              description: |
                                A mapping from category labels (as keys) to their corresponding logit values.
                                Present when `data_format` is set to `logits` (default).
                              additionalProperties:
                                type: number
                                format: float
                                example: 0.9453125
                              example:
                                cat: 0.9453125
                                dog: 0.01875
                                rabbit: 0.0859375
                                turtle: 0.015625
                          required:
                            - index
                            - logits
                        - title: probs
                          type: object
                          properties:
                            index:
                              type: number
                              example: 0
                            probs:
                              type: object
                              description: |
                                A mapping from category labels (as keys) to their corresponding probability values (between 0 and 1).
                                Present when `data_format` is set to `probs`.
                              additionalProperties:
                                type: number
                                format: float
                                example: 0.82
                              example:
                                cat: 0.82
                                dog: 0.02
                                rabbit: 0.13
                                turtle: 0.03
                          required:
                            - index
                            - probs
                  usage:
                    type: object
                    properties:
                      completion_tokens:
                        type: number
                        example: 0
                      prompt_tokens:
                        type: number
                        example: 1587
                      prompt_token_details:
                        type: string
                      total_tokens:
                        type: number
                        example: 1587
        '404':
          $ref: '#/components/responses/NotFound'
        '400':
          $ref: '#/components/responses/InvalidInput'
  '/v1/testing-functions':
    get:
      tags:
        - Testing Functions
      summary: List Testing Functions
      description: Returns a list of test functions
      operationId: listTestFunctions
      responses:
        '200':
          description: List of Testing Function's summary object.
          content:
            application/json:
              schema:
                type: array
                items:
                  "$ref": "#/components/schemas/TestingFunctionSummary"
        '401':
          $ref: '#/components/responses/Unauthorized'

# An object to hold reusable parts that can be used across the definition
components:
  parameters:
    ProjectId:
      name: project_id
      in: path
      schema:
        type: string
      description: The ID of the project
      required: true
  schemas:
    CompletionObject:
      type: object
      properties:
        id:
          type: string
          example: "cmpl-8565e8d5db17438291a189255c36c558"
        object:
          type: string
          example: "text_completion"
        created:
          type: number
          example: 1741570283
        model:
          type: string
          example: "Llama-3.2-1B-Instruct"
        choices:
          type: array
          items:
            type: object
            properties:
              index:
                type: number
                example: 0
              text:
                type: string
                example: " Paris. The French language is a Romance language and the official language of France."
              logprobs:
                type: [ string, null ]
              prompt_logprobs:
                type: [ string, null ]
              stop_reason:
                type: [ string, null ]
              finish_reason:
                type: string
                example: "length"
        usage:
          type: object
          properties:
            prompt_tokens:
              type: number
              example: 6
            completion_tokens:
              type: number
              example: 16
            total_tokens:
              type: number
              example: 44
            prompt_tokens_details:
              type: [ string, null ]
    ChatCompletionObject:
      type: object
      properties:
        id:
          type: string
          example: "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG"
        object:
          type: string
          example: "chat.completion"
        created:
          type: number
          example: 1741570283
        model:
          type: string
          example: "Llama-3.2-1B-Instruct"
        choices:
          type: array
          items:
            type: object
            properties:
              index:
                type: number
                example: 0
              message:
                type: object
                properties:
                  role:
                    type: string
                    example: "assistant"
                  content:
                    type: string
                    example: "How can I help you today?"
              refusal:
                type: [string, null]
              finish_reason:
                type: string
                example: "stop"
        usage:
          type: object
          properties:
            prompt_tokens:
              type: number
              example: 36
            completion_tokens:
              type: number
              example: 8
            total_tokens:
              type: number
              example: 44
            prompt_tokens_details:
              type: object
              properties:
                cached_tokens:
                  type: number
                  example: 0
                audio_tokens:
                  type: number
                  example: 0
            completion_tokens_details:
              type: object
              properties:
                reasoning_tokens:
                  type: number
                  example: 0
                audio_tokens:
                  type: number
                  example: 0
                accepted_prediction_tokens:
                  type: number
                  example: 0
                rejected_prediction_tokens:
                  type: number
                  example: 0
        service_tier:
          type: string
          example: "default"
        system_fingerprint:
          type: string
          example: "fp_fc9f1d7035"
    BaseModelSummary:
      type: object
      properties:
        name:
          type: string
          example: "Llama-3.2-1B-Instruct"
        type:
          type: string
          enum:
            - completion
            - classification
            - embeddings
            - chat
          example: "completion"
        parameter_template:
          type: object
          additionalProperties:
            oneOf:
              - type: string
              - type: number
              - type: integer
        support_serverless:
          type: boolean
          example: false
    ProjectSummary:
      type: object
      description: Project Summary Object
      properties:
        id:
          type: string
          example: "ms-12345"
          description: The unique identifier for the project
        name:
          type: string
          example: "my_project"
          description: The name of the project
    ProjectDetail:
      type: object
      description: Project Object
      properties:
        id:
          type: string
          example: "ms-12345"
          description: The unique identifier for the project
        name:
          type: string
          example: "my_project"
          description: The name of the project
        datasets:
          type: array
          items:
            "$ref": '#/components/schemas/DatasetSummary'
        training_jobs:
          type: array
          items:
            "$ref": "#/components/schemas/TrainingJobSummary"
        deployments:
          type: array
          items:
            "$ref": "#/components/schemas/DeploymentSummary"
    DatasetSummary:
      type: object
      description: Dataset Summary Object
      properties:
        id:
          type: string
          example: "ds-12345"
          description: The unique identifier for the dataset
        name:
          type: string
          example: "my_dataset"
          description: The name of the dataset
        created_at:
          type: integer
          example: 1633036800
          description: The UNIX timestamp when the dataset was created
        is_uploaded:
          type: boolean
          example: true
    DatasetDetail:
      type: object
      description: Dataset Object
      properties:
        id:
          type: string
          example: "ds-12345"
          description: The unique identifier for the dataset
        name:
          type: string
          example: "my_dataset"
          description: The name of the dataset
        is_uploaded:
          type: boolean
          example: true
          description: Whether the dataset has been uploaded
        dataset_download_url:
          type: string
          example: "s3:/my_dataset"
          description: The URL to download the dataset
        upload_by:
          type: string
          example: "user-12345"
          description: The user ID who uploaded the dataset
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the dataset was created
        updated_at:
          type: integer
          example: 1633036800
          description: The timestamp when the dataset was last updated
    TestingFunctionSummary:
      type: object
      description: Testing Function Summary Object
      properties:
        name:
          type: string
          example: "similarity_score_shared"
          description: Name of the test function (matched with exact python method name)
        content:
          type: string
          example: "def similarity_score_shared(input_text: str, expected_output: str, predicted_output: str): \n ..."
          description: Contents of test function
        dependencies:
          type: array
          example: [ "external-library" ]
          items:
            type: string
            description: List of external dependencies that needs to be downloaded with pip to run
    TrainingJobSummary:
      type: object
      description: Training Job Summary Object
      properties:
        id:
          type: string
          example: "tr-12345"
          description: The unique identifier for the training job
        name:
          type: string
          example: "training-1"
          description: The name of the training job
        training_technique:
          type: string
          enum:
            - SFT
            - GRPO
          example: "SFT"
          description: "Training technique that has been used for this training job"
        task_type:
          type: string
          enum:
            - text-generation
            - classification
            - embedding
            - regression
          example: "classification"
        base_model_option:
          type: string
          enum:
            - pre-trained
            - fine-tuned
          example: "pre-trained"
          description: "Base model option used for training "
        base_model:
          type: string
          example: "Llama-3.2-1B-Instruct"
          description: The base model used for training
        base_fine_tuned_model:
          type: string
          example: "training-job-1"
          description: (base_model_option == "fine-tuned") Fine-tuned model that is used as a base model for the training job
        base_fine_tuned_model_checkpoint:
          type: int
          example: 5
          description: (base_model_option == "fine-tuned") Check point that is used as a base model for the training job
        train_dataset_name:
          type: string
          example: "train-dataset-1"
          description: Name of the dataset used for fine-tuning
        test_functions:
          type: array
          example: [ "test_similarity_shared" ]
          items:
            type: string
            description: List of test function names used in the training job
        reward:
          type: object
          description: (GRPO) Reward weight map
          properties:
            test_function_1:
              type: float
              example: 0.2
            test_function_2:
              type: float
              example: 0.8
        status:
          type: string
          enum:
            - Pending
            - Running
            - Success
            - Testing
            - Failed
            - TimedOut
            - Cancelled
          example: "Running"
          description: The current status of the training job
        progress:
          type: integer
          example: 75
          description: The current progress of the training job
        created_by:
          type: string
          example: "user-12345"
          description: The user ID who created the training job
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the TrainingJob was created
        updated_at:
          type: integer
          example: 1633036800
          description: The timestamp when the TrainingJob was last updated
    TrainingJobDetail:
      type: object
      description: Training Job Object
      properties:
        id:
          type: string
          example: "tr-12345"
          description: The unique identifier for the training job
        name:
          type: string
          example: "training-1"
          description: The name of the training job
        training_technique:
          type: string
          enum:
            - SFT
            - GRPO
          example: "SFT"
          description: "Training technique that has been used for this training job"
        task_type:
          type: string
          enum:
            - text-generation
            - classification
            - embedding
            - regression
        base_model_option:
          type: string
          enum:
            - pre-trained
            - fine-tuned
          example: "pre-trained"
          description: "Base model option used for training "
        base_model:
          type: string
          example: "Llama-3.2-1B-Instruct"
          description: The base model used for training
        base_fine_tuned_model:
          type: string
          example: "training-job-1"
          description: (base_model_option == "fine-tuned") Fine-tuned model that is used as a base model for the training job
        base_fine_tuned_model_checkpoint:
          type: int
          example: 5
          description: (base_model_option == "fine-tuned") Check point that is used as a base model for the training job
        test_functions:
          type: array
          example: [ "test_similarity_shared" ]
          items:
            type: string
            description: List of test function names used in the training job
        reward:
          type: object
          description: (GRPO) Reward weight map
          properties:
            test_function_1:
              type: float
              example: 0.2
            test_function_2:
              type: float
              example: 0.8
        status:
          type: string
          enum:
            - Pending
            - Running
            - Testing
            - Success
            - Failed
            - TimedOut
            - Cancelled
          example: "Running"
          description: The current status of the training job
        progress:
          type: integer
          example: 75
          description: The current progress of the training job
        train_dataset:
          "$ref": "#/components/schemas/DatasetSummary"
        test_dataset:
          "$ref": "#/components/schemas/DatasetSummary"
        training_loss:
          type: array
          items:
            type: object
            properties:
              timestamp:
                type: number
                example: 1633036800.0
              loss:
                type: number
                example: 0.1234
        hyper_parameters:
          type: object
          additionalProperties:
            oneOf:
              - type: string
              - type: number
              - type: integer
              - type: boolean
        created_by:
          type: string
          example: "user-12345"
          description: The user ID who created the training job
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the TrainingJob was created
        updated_at:
          type: integer
          example: 1633036800
          description: The timestamp when the TrainingJob was last updated
    TrainingJobCheckpoint:
      type: object
      description: Training Job Checkpoint Object
      properties:
        checkpoint:
          type: integer
          example: 3
          description: The checkpoint number
        model_download_url:
          type: string
          example: "s3:/my_model"
          description: The URL to download the model checkpoint
        test_results:
          type: object
          properties:
            general_test_result:
              type: string
              example: "s3://"
            aggregated_test_result:
              type: object
              additionalProperties:
                type: string
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the checkpoint was created
        updated_at:
          type: integer
          example: 1633036800
          description: The timestamp when the checkpoint was created
    InferenceEngineSummary:
      type: object
      description: Inference Engine Summary
      properties:
        id:
          type: string
          example: "engine-12345"
          description: The unique identifier for the inference engine
        name:
          type: string
          example: "inference-test-engine"
        status:
          type: string
          enum:
            - Creating
            - Active
            - Inactive
          example: Creating
        base_model:
          type: string
          example: "Llama-3.2-1B-Instruct"
        server_type:
          type: string
          example: "on-demand"
        task_type:
          type: string
          example: "text-generation"
        deployment_counts:
          type: integer
          example: 1
          description: Number of deployments on this inference engine
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the deployment was created
    InferenceEngineDetail:
      type: object
      description: Inference Engine Object
      properties:
        id:
          type: string
          example: "engine-12345"
          description: The unique identifier for the inference engine
        name:
          type: string
          example: "test-inference-engine"
        status:
          type: string
          enum:
            - Creating
            - Active
            - Inactive
          example: "Active"
        base_model:
          type: string
          example: "Llama-3.2-3B-Instruct"
        task_type:
          type: string
          example: "text-generation"
        server_type:
          type: string
          example: "on-demand"
        deployments:
          type: array
          items:
            "$ref": "#/components/schemas/DeploymentSummary"
        base_model_option:
          type: string
          example: "pre-trained"
        last_access_timestamp:
          type: integer
          example: 1633036800
        resource_management_config:
          oneOf:
            - title: Inactive Timeout
              description: Specifies the period of inactivity, in seconds, after which the deployment will be automatically deactivated if no incoming requests are received. While deactivated, the deployment incurs no charges. When a request is sent to a deactivated deployment, it will be reactivated to process the request; this reactivation process typically introduces a delay of approximately 8 to 20 minutes before the deployment becomes fully operational.
              type: object
              properties:
                management_type:
                  type: string
                  example: "inactive_timeout"
                management_config:
                  type: object
                  properties:
                    inactive_duration:
                      type: integer
                      example: 3600
                      description: Period of inactivity
            - title: Schedule
              description: Specifies the schedule which the engine will be deployed with deployments (if existing on the engine).
              type: object
              properties:
                management_type:
                  type: string
                  example: "schedule"
                management_config:
                  type: object
                  properties:
                    timezone:
                      type: string
                      example: "America/Los_Angeles"
                      description: The IANA timezone for the schedule
                    start_time:
                      type: string
                      example: "10:00"
                      description: The start time for the schedule in HH:MM format
                    end_time:
                      type: string
                      example: "18:00"
                      description: The end time for the schedule in HH:MM format
                    days:
                      type: array
                      example: [ "monday", "tuesday", "wednesday", "thursday", "friday", "saturday", "sunday" ]
                      items:
                        type: string
                        enum:
                          - monday
                          - tuesday
                          - wednesday
                          - thursday
                          - friday
                          - saturday
                          - sunday
                      description: The days of the week for the schedule
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the deployment was last updated
    DeploymentSummary:
      type: object
      description: Deployment Summary Object
      properties:
        id:
          type: string
          example: "dp-12345"
          description: The unique identifier for the deployment
        name:
          type: string
          example: "deployment-1"
          description: The name of the deployment
        status:
          type: string
          enum:
            - Pending
            - Deploying
            - Deployed
            - Failed
            - Cancelled
            - Terminated
            - Deactivated
            - Reactivating
            - TimedOut
          example: "Deployed"
          description: The current status of the deployment
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the deployment was created
    DeploymentDetail:
      type: object
      description: Deployment Object
      properties:
        id:
          type: string
          example: "dp-12345"
          description: The unique identifier for the deployment
        name:
          type: string
          example: "deployment-1"
          description: The name of the deployment
        task_type:
          type: string
          example: "classification"
          description: Task type of the deployment
        metadata:
          description: Metadata of the deployment (varies by task_type)
          oneOf:
            - title: ClassificationMetadata
              description: Metadata for classification tasks
              type: object
              properties:
                labels:
                  type: array
                  items:
                    type: string
                  example: ["class1", "class2"]
        description:
          type: string
          example: "Deployment for my training job"
          description: A description of the deployment
        base_model:
          type: string
          example: "Llama-3.2-1B-Instruct"
          description: The base model used for deployment
        status:
          type: string
          enum:
            - Pending
            - Deploying
            - Deployed
            - Failed
            - Cancelled
            - Terminated
            - Deactivated
            - Reactivating
            - TimedOut
          example: "Deployed"
          description: The current status of the deployment
        training_id:
          type: string
          example: "tr-12345"
          description: The training job ID used for deployment
        checkpoint:
          type: integer
          example: 4
          description: The checkpoint number used for deployment
        created_at:
          type: integer
          example: 1633036800
          description: The timestamp when the deployment was created
        updated_at:
          type: integer
          example: 1633036800
          description: The timestamp when the deployment was last updated
    ApiResponse:
      type: object
      properties:
        code:
          type: integer
          format: int32
        type:
          type: string
        message:
          type: string
    ApiErrorInvalidInput:
      type: object
      required:
        - status
        - error
      properties:
        status:
          type: integer
          format: int32
          example: 400
        error:
          type: string
          example: Bad request
    ApiErrorNotFound:
      type: object
      required:
        - status
        - error
        - code
      properties:
        status:
          type: integer
          format: int32
          example: 404
        error:
          type: string
          example: Not found
        code:
          type: string
          example: object_not_found
    ApiErrorUnauthorized:
      type: object
      required:
        - status
        - error
      properties:
        status:
          type: integer
          format: int32
          example: 401
        error:
          type: string
          example: Unauthorized
  responses:
    Unauthorized:
      description: Unauthorized error
      content:
        application/json:
          schema:
            "$ref": "#/components/schemas/ApiErrorUnauthorized"
    NotFound:
      description: Not Found error
      content:
        application/json:
          schema:
            "$ref": "#/components/schemas/ApiErrorNotFound"
    InvalidInput:
      description: Invalid Input error
      content:
        application/json:
          schema:
            "$ref": "#/components/schemas/ApiErrorInvalidInput"
  headers:
    ExpiresAfter:
      description: date in UTC when token expires
      schema:
        type: string
        format: date-time
  # Security scheme definitions that can be used across the definition.
  securitySchemes:
    api_key:
      type: apiKey
      name: X-API-Key
      in: header