Qubrid AI Fine-Tuning Jobs API

openapi: 3.1.0
info:
  title: Qubrid AI Compute Chat Completions Fine-Tuning Jobs API
  description: The Qubrid AI Compute API provides programmatic access to GPU cloud infrastructure including NVIDIA H100, H200, and B200 accelerators. Developers can provision and manage GPU instances for AI and machine learning workloads through API calls. The service supports on-demand compute for training, fine-tuning, and batch inference jobs, with usage-based billing and enterprise features such as team collaboration and usage tracking. Instances can be accessed via SSH, Jupyter notebooks, or Visual Studio Code, and support quick-deploy templates for popular frameworks including PyTorch, TensorFlow, ComfyUI, n8n, and Langflow.
  version: 1.0.0
  contact:
    name: Qubrid AI Support
    url: https://www.qubrid.com/contact
  termsOfService: https://www.qubrid.com/terms-of-service
servers:
- url: https://platform.qubrid.com/api/v1
  description: Qubrid AI Compute Production Server
security:
- bearerAuth: []
tags:
- name: Fine-Tuning Jobs
  description: Create, monitor, and manage fine-tuning jobs that customize pre-deployed text generation and code generation models using uploaded training datasets on GPU infrastructure.
paths:
  /fine-tuning/jobs:
    get:
      operationId: listFineTuningJobs
      summary: List fine-tuning jobs
      description: Returns a list of all fine-tuning jobs associated with the authenticated user's account, including their status, base model, hyperparameters, and training progress.
      tags:
      - Fine-Tuning Jobs
      parameters:
      - $ref: '#/components/parameters/PageLimit'
      - $ref: '#/components/parameters/PageOffset'
      responses:
        '200':
          description: Successfully retrieved the list of fine-tuning jobs.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJobList'
        '401':
          description: Authentication failed due to a missing or invalid bearer token.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
    post:
      operationId: createFineTuningJob
      summary: Create a fine-tuning job
      description: Creates and starts a new fine-tuning job that customizes a base model using the specified training dataset and hyperparameters. The job runs on GPU infrastructure and produces a fine-tuned model artifact upon completion. Supported task types include Question Answering (QA) and non-QA text generation.
      tags:
      - Fine-Tuning Jobs
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateFineTuningJobRequest'
      responses:
        '201':
          description: Successfully created the fine-tuning job.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
        '400':
          description: The request was malformed, the dataset format was invalid, or an unsupported base model was specified.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '401':
          description: Authentication failed due to a missing or invalid bearer token.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '402':
          description: Insufficient credits or billing issue preventing job creation.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
  /fine-tuning/jobs/{job_id}:
    get:
      operationId: getFineTuningJob
      summary: Retrieve a fine-tuning job
      description: Returns details about a specific fine-tuning job including its current status, base model, hyperparameters, training metrics, and the resulting fine-tuned model identifier upon completion.
      tags:
      - Fine-Tuning Jobs
      parameters:
      - $ref: '#/components/parameters/JobId'
      responses:
        '200':
          description: Successfully retrieved the fine-tuning job details.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
        '401':
          description: Authentication failed due to a missing or invalid bearer token.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '404':
          description: The specified fine-tuning job was not found.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
  /fine-tuning/jobs/{job_id}/cancel:
    post:
      operationId: cancelFineTuningJob
      summary: Cancel a fine-tuning job
      description: Cancels a running fine-tuning job. The job will be stopped and any partial training progress will be discarded. Credits for unused compute time may be refunded.
      tags:
      - Fine-Tuning Jobs
      parameters:
      - $ref: '#/components/parameters/JobId'
      responses:
        '200':
          description: Successfully cancelled the fine-tuning job.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
        '401':
          description: Authentication failed due to a missing or invalid bearer token.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
        '404':
          description: The specified fine-tuning job was not found.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
components:
  schemas:
    Hyperparameters:
      type: object
      properties:
        epochs:
          type: integer
          description: The number of full passes the model makes over the training dataset. More epochs let the model learn more but too many can cause overfitting.
          minimum: 1
        max_steps:
          type: integer
          description: The maximum number of training iterations, where each step equals one batch of data processed.
          minimum: 1
        learning_rate:
          type: number
          description: The learning rate for the optimizer, controlling how much the model weights are adjusted during each training step.
          minimum: 0
          exclusiveMinimum: true
        validation_split:
          type: number
          description: The percentage of the dataset reserved for validation, expressed as a decimal between 0 and 1.
          minimum: 0
          maximum: 1
    ErrorResponse:
      type: object
      properties:
        error:
          type: object
          properties:
            message:
              type: string
              description: A human-readable error message describing what went wrong.
            type:
              type: string
              description: The type of error that occurred.
            code:
              type: string
              description: A machine-readable error code.
    FineTuningJob:
      type: object
      properties:
        id:
          type: string
          description: The unique identifier of the fine-tuning job.
        status:
          type: string
          enum:
          - queued
          - running
          - completed
          - failed
          - cancelled
          description: The current status of the fine-tuning job.
        base_model:
          type: string
          description: The identifier of the base model being fine-tuned.
        dataset_id:
          type: string
          description: The identifier of the training dataset used.
        task_type:
          type: string
          enum:
          - qa
          - not_qa
          description: The task type for fine-tuning. QA indicates question answering tasks, while not_qa covers general text generation and other task types.
        hyperparameters:
          $ref: '#/components/schemas/Hyperparameters'
        fine_tuned_model:
          type: string
          description: The identifier of the resulting fine-tuned model, available once the job has completed successfully.
        training_metrics:
          $ref: '#/components/schemas/TrainingMetrics'
        created_at:
          type: string
          format: date-time
          description: The timestamp when the fine-tuning job was created.
        completed_at:
          type: string
          format: date-time
          description: The timestamp when the fine-tuning job completed, if applicable.
    TrainingMetrics:
      type: object
      properties:
        training_loss:
          type: number
          description: The final training loss value after the last training step.
        validation_loss:
          type: number
          description: The final validation loss value, if a validation split was configured.
        steps_completed:
          type: integer
          description: The number of training steps completed.
        epochs_completed:
          type: integer
          description: The number of training epochs completed.
    CreateFineTuningJobRequest:
      type: object
      required:
      - base_model
      - dataset_id
      - task_type
      properties:
        base_model:
          type: string
          description: The identifier of the base model to fine-tune. Must be a pre-deployed text generation or code generation model on the Qubrid AI platform.
        dataset_id:
          type: string
          description: The identifier of the previously uploaded CSV training dataset.
        task_type:
          type: string
          enum:
          - qa
          - not_qa
          description: The task type for fine-tuning. Choose qa for question answering tasks or not_qa for general text generation, summarization, classification, and other tasks.
        hyperparameters:
          $ref: '#/components/schemas/Hyperparameters'
        suffix:
          type: string
          description: An optional suffix to append to the fine-tuned model name for identification purposes.
          maxLength: 64
    FineTuningJobList:
      type: object
      properties:
        data:
          type: array
          description: A list of fine-tuning job objects.
          items:
            $ref: '#/components/schemas/FineTuningJob'
        total:
          type: integer
          description: The total number of fine-tuning jobs.
  parameters:
    PageLimit:
      name: limit
      in: query
      required: false
      description: Maximum number of results to return per page.
      schema:
        type: integer
        minimum: 1
        maximum: 100
        default: 20
    JobId:
      name: job_id
      in: path
      required: true
      description: The unique identifier of the fine-tuning job.
      schema:
        type: string
    PageOffset:
      name: offset
      in: query
      required: false
      description: Number of results to skip for pagination.
      schema:
        type: integer
        minimum: 0
        default: 0
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: QUBRID_API_KEY
      description: Qubrid AI API key passed as a bearer token in the Authorization header. Obtain your API key from the Qubrid AI platform dashboard at https://platform.qubrid.com.
externalDocs:
  description: Qubrid AI Documentation
  url: https://docs.platform.qubrid.com