CreateFineTuneJobRequest

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://artifacts.apis.io/lastmileai/json-schema/lastmileai-lmai-proto-webserver-v2-create-fine-tune-job-request-schema.json",
  "title": "CreateFineTuneJobRequest",
  "description": "Create a new Fine Tune Job\n Initialized with the provided configuration parameters.",
  "x-generated": "2026-11-10",
  "x-method": "derived",
  "x-generator": "derive-json-schema.py",
  "x-source": "openapi/lastmileai-fine-tune-job-api-openapi.yml#/components/schemas/lmai.proto.webserver.v2.CreateFineTuneJobRequest",
  "type": "object",
  "properties": {
    "fineTuneJobConfig": {
      "$ref": "#/$defs/lmai.proto.model_fine_tuning.v1.FineTuneJobConfig",
      "description": "Partial configuration with parameters for the fine-tune job."
    }
  },
  "required": [
    "fineTuneJobConfig"
  ],
  "$defs": {
    "lmai.proto.model_fine_tuning.v1.FineTuneJobConfig": {
      "title": "FineTuneJobConfig",
      "type": "object",
      "properties": {
        "name": {
          "type": "string",
          "description": "Optional name for the job."
        },
        "description": {
          "type": "string",
          "description": "Optional description for the job."
        },
        "baselineModelId": {
          "type": "string",
          "description": "The ID for the model used as the starting point for training."
        },
        "trainDatasetId": {
          "type": "string",
          "description": "The dataset to use for training, with splits baked in or to be\n derived dynamically"
        },
        "testDatasetId": {
          "type": "string",
          "description": "The dataset to use for an unbiased evaluation of the model"
        },
        "selectedColumns": {
          "type": "array",
          "items": {
            "type": "string",
            "description": "Set of columns to be used in fine-tuning.\n Supported columns: input, output, ground_truth\n For example, a task similar to summarization might need output and\n ground_truth."
          }
        }
      },
      "required": [
        "baselineModelId",
        "trainDatasetId",
        "testDatasetId",
        "selectedColumns"
      ]
    }
  }
}