API Evangelist conversational phrasing for OpenAI Fine Tuning API

# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for OpenAI Fine Tuning API
  version: 1.0.0
extends: openapi/openai-fine-tuning-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-09-26'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 13
- target: $.paths['/fine_tuning/alpha/graders/run'].post
  update:
    x-apievangelist-phrasing:
      intent: Run a grader against a model sample
      effect: read
      questions:
      - How do I score a single model output with a grader before fine-tuning?
      - Can I test a grader against a sample and a reference item to see the score it gives?
      instructions:
      - text: Run grader {grader} on the model sample {model_sample}.
        slots:
          grader: requestBody.grader
          model_sample: requestBody.model_sample
      - text: Score {model_sample} with grader {grader} using reference item {item}.
        slots:
          model_sample: requestBody.model_sample
          grader: requestBody.grader
          item: requestBody.item
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/alpha/graders/validate'].post
  update:
    x-apievangelist-phrasing:
      intent: Check that a grader definition is valid
      effect: read
      questions:
      - Is my grader configuration valid before I use it in a fine-tuning job?
      - Can I check a grader definition for errors without running it?
      instructions:
      - text: Validate grader definition {grader}.
        slots:
          grader: requestBody.grader
      - text: Check whether {grader} is a well-formed grader without scoring anything.
        slots:
          grader: requestBody.grader
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions'].get
  update:
    x-apievangelist-phrasing:
      intent: List who can use a fine-tuned checkpoint
      effect: read
      questions:
      - Which projects have access to one of my fine-tuned model checkpoints?
      - Can I check whether a specific project was granted a checkpoint?
      instructions:
      - text: List the sharing permissions on checkpoint {fine_tuned_model_checkpoint}.
        slots:
          fine_tuned_model_checkpoint: path.fine_tuned_model_checkpoint
      - text: Show whether project {project_id} can use checkpoint {fine_tuned_model_checkpoint}.
        slots:
          project_id: query.project_id
          fine_tuned_model_checkpoint: path.fine_tuned_model_checkpoint
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions'].post
  update:
    x-apievangelist-phrasing:
      intent: Share a fine-tuned checkpoint with other projects
      effect: write
      questions:
      - How do I share a fine-tuned model with other projects in my organization?
      - Do I need an admin key to grant a project access to a checkpoint?
      instructions:
      - text: Share checkpoint {fine_tuned_model_checkpoint} with projects {project_ids}.
        slots:
          fine_tuned_model_checkpoint: path.fine_tuned_model_checkpoint
          project_ids: requestBody.project_ids
      - text: Grant projects {project_ids} permission to use fine-tuned checkpoint {fine_tuned_model_checkpoint}.
        slots:
          project_ids: requestBody.project_ids
          fine_tuned_model_checkpoint: path.fine_tuned_model_checkpoint
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}'].delete
  update:
    x-apievangelist-phrasing:
      intent: Revoke a project's access to a checkpoint
      effect: destructive
      questions:
      - How do I stop another project from using my fine-tuned checkpoint?
      - Can I remove a single sharing permission from a checkpoint?
      instructions:
      - text: Delete permission {permission_id} from checkpoint {fine_tuned_model_checkpoint}.
        slots:
          permission_id: path.permission_id
          fine_tuned_model_checkpoint: path.fine_tuned_model_checkpoint
      - text: Revoke sharing grant {permission_id} on fine-tuned checkpoint {fine_tuned_model_checkpoint}.
        slots:
          permission_id: path.permission_id
          fine_tuned_model_checkpoint: path.fine_tuned_model_checkpoint
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs'].get
  update:
    x-apievangelist-phrasing:
      intent: List my organization's fine-tuning jobs
      effect: read
      questions:
      - Which fine-tuning jobs has my organization run?
      - Can I filter fine-tuning jobs by the metadata I tagged them with?
      instructions:
      - text: List all our fine-tuning jobs.
      - text: Show fine-tuning jobs tagged with metadata {metadata}.
        slots:
          metadata: query.metadata
      - text: Show the next {limit} fine-tuning jobs after {after}.
        slots:
          limit: query.limit
          after: query.after
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs'].post
  update:
    x-apievangelist-phrasing:
      intent: Start a fine-tuning job to train a custom model
      effect: write
      questions:
      - How do I fine-tune a model on my own training file?
      - Can I supply a validation file and custom hyperparameters when I start fine-tuning?
      - What suffix will my fine-tuned model's name get?
      instructions:
      - text: Fine-tune {model} on training file {training_file}.
        slots:
          model: requestBody.model
          training_file: requestBody.training_file
      - text: Start a fine-tuning job on {model} with {training_file} and validate against {validation_file}.
        slots:
          model: requestBody.model
          training_file: requestBody.training_file
          validation_file: requestBody.validation_file
      - text: Train a custom {model} from {training_file} and name it with suffix {suffix}.
        slots:
          model: requestBody.model
          training_file: requestBody.training_file
          suffix: requestBody.suffix
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs/{fine_tuning_job_id}'].get
  update:
    x-apievangelist-phrasing:
      intent: Get the status of a fine-tuning job
      effect: read
      questions:
      - Is my fine-tuning job finished, and what is the new model called?
      - Can I look up one fine-tuning job by its ID?
      instructions:
      - text: Show fine-tuning job {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      - text: Check whether fine-tuning job {fine_tuning_job_id} has succeeded.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs/{fine_tuning_job_id}/cancel'].post
  update:
    x-apievangelist-phrasing:
      intent: Cancel a fine-tuning job
      effect: destructive
      questions:
      - How do I stop a fine-tuning job for good?
      - Can I immediately cancel a fine-tune I started by mistake?
      instructions:
      - text: Cancel fine-tuning job {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      - text: Abort fine-tune {fine_tuning_job_id} right now.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints'].get
  update:
    x-apievangelist-phrasing:
      intent: List the checkpoints a fine-tuning job produced
      effect: read
      questions:
      - Which intermediate checkpoints did my fine-tuning job save?
      - Can I pick an earlier checkpoint from a fine-tuning run instead of the final model?
      instructions:
      - text: List the checkpoints for fine-tuning job {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      - text: Show {limit} saved checkpoints from job {fine_tuning_job_id}.
        slots:
          limit: query.limit
          fine_tuning_job_id: path.fine_tuning_job_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs/{fine_tuning_job_id}/events'].get
  update:
    x-apievangelist-phrasing:
      intent: Show progress events for a fine-tuning job
      effect: read
      questions:
      - What status updates has my fine-tuning job logged so far?
      - Where can I follow the training progress messages of a fine-tune?
      instructions:
      - text: Show the events for fine-tuning job {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      - text: Get the latest {limit} progress updates from fine-tune {fine_tuning_job_id}.
        slots:
          limit: query.limit
          fine_tuning_job_id: path.fine_tuning_job_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs/{fine_tuning_job_id}/pause'].post
  update:
    x-apievangelist-phrasing:
      intent: Pause a running fine-tuning job
      effect: write
      questions:
      - Can I temporarily pause a fine-tuning job without cancelling it?
      - Is there a way to hold a fine-tune and pick it up later?
      instructions:
      - text: Pause fine-tuning job {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      - text: Put fine-tune {fine_tuning_job_id} on hold for now.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fine_tuning/jobs/{fine_tuning_job_id}/resume'].post
  update:
    x-apievangelist-phrasing:
      intent: Resume a paused fine-tuning job
      effect: write
      questions:
      - How do I restart a fine-tuning job I paused earlier?
      - Can a paused fine-tune continue training from where it stopped?
      instructions:
      - text: Resume fine-tuning job {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      - text: Continue the paused fine-tune {fine_tuning_job_id}.
        slots:
          fine_tuning_job_id: path.fine_tuning_job_id
      method: generated
      generated: '2026-09-26'