{ "swagger": "2.0", "info": { "title": "Intelligence Foundry API", "description": "The Intelligence Foundry REST API. Please see https://docs.crusoecloud.com/ for more details.", "version": "1.0.0" }, "basePath": "/v1", "paths": { "/fine_tuning/jobs": { "post": { "operationId": "createFineTuningJob", "summary": "Create fine-tuning job", "description": "Creates a fine-tuning job which begins the process of creating a new model from a given dataset.\n\nResponse includes details of the enqueued job including job status and the name of the fine-tuned models once complete.\n\n[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization)\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/FineTuningJob" } } }, "parameters": [ { "name": "body", "in": "body", "required": true, "schema": { "$ref": "#/definitions/CreateFineTuningJobRequest" } } ], "consumes": [ "application/json" ], "produces": [ "application/json" ] }, "get": { "operationId": "listPaginatedFineTuningJobs", "summary": "List fine-tuning jobs", "description": "List your organization's fine-tuning jobs\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/ListPaginatedFineTuningJobsResponse" } } }, "parameters": [ { "name": "model", "in": "query", "description": "Filter to jobs for these base model registry IDs.", "required": false, "type": "array", "items": { "type": "string" }, "collectionFormat": "multi" }, { "name": "suffix", "in": "query", "description": "Filter to jobs with these suffixes.", "required": false, "type": "array", "items": { "type": "string" }, "collectionFormat": "multi" }, { "name": "status", "in": "query", "description": "Filter to jobs in these statuses.", "required": false, "type": "array", "items": { "type": "string", "enum": [ "validating_files", "queued", "running", "succeeded", "failed", "cancelled" ] }, "collectionFormat": "multi" } ], "produces": [ "application/json" ] } }, "/fine_tuning/jobs/{fine_tuning_job_id}": { "get": { "operationId": "retrieveFineTuningJob", "summary": "Retrieve fine-tuning job", "description": "Get info about a fine-tuning job.\n\n[Learn more about fine-tuning](https://platform.openai.com/docs/guides/model-optimization)\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/FineTuningJob" } } }, "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "description": "The ID of the fine-tuning job.\n", "required": true, "type": "string" } ], "produces": [ "application/json" ] } }, "/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints": { "get": { "operationId": "listFineTuningJobCheckpoints", "summary": "List fine-tuning checkpoints", "description": "List checkpoints for a fine-tuning job.\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/ListFineTuningJobCheckpointsResponse" } } }, "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "description": "The ID of the fine-tuning job to get checkpoints for.\n", "required": true, "type": "string" }, { "name": "after", "in": "query", "description": "Identifier for the last checkpoint ID from the previous pagination request.", "required": false, "type": "string" }, { "name": "limit", "in": "query", "description": "Number of checkpoints to retrieve.", "required": false, "type": "integer", "default": 10 } ], "produces": [ "application/json" ] } }, "/fine_tuning/jobs/{fine_tuning_job_id}/cancel": { "post": { "operationId": "cancelFineTuningJob", "summary": "Cancel fine-tuning", "description": "Immediately cancel a fine-tune job.\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/FineTuningJob" } } }, "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "description": "The ID of the fine-tuning job to cancel.\n", "required": true, "type": "string" } ], "produces": [ "application/json" ] } }, "/fine_tuning/jobs/{fine_tuning_job_id}/events": { "get": { "operationId": "listFineTuningEvents", "summary": "List fine-tuning events", "description": "Get status updates for a fine-tuning job.\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/ListFineTuningJobEventsResponse" } } }, "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "description": "The ID of the fine-tuning job to get events for.\n", "required": true, "type": "string" }, { "name": "after", "in": "query", "description": "Identifier for the last event from the previous pagination request.", "required": false, "type": "string" }, { "name": "limit", "in": "query", "description": "Number of events to retrieve.", "required": false, "type": "integer", "default": 20 } ], "produces": [ "application/json" ] } }, "/files": { "get": { "operationId": "listFiles", "summary": "List files", "description": "Returns a list of files.", "tags": [ "Files" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/ListFilesResponse" } } }, "parameters": [ { "name": "purpose", "in": "query", "description": "Only return files with the given purpose.", "required": false, "type": "string" }, { "name": "limit", "in": "query", "description": "A limit on the number of objects to be returned. Limit can range between 1 and 10,000, and the default is 10,000.\n", "required": false, "type": "integer", "default": 10000 }, { "name": "order", "in": "query", "description": "Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.\n", "type": "string", "enum": [ "asc", "desc" ], "default": "desc" }, { "name": "after", "in": "query", "description": "A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.\n", "type": "string" } ], "produces": [ "application/json" ] }, "post": { "operationId": "createFile", "summary": "Upload file", "description": "Upload a file that can be used across various endpoints. Individual files\ncan be up to 512 MB, and the size of all files uploaded by one organization\ncan be up to 1 TB.\n\n- The Assistants API supports files up to 2 million tokens and of specific\n file types. See the [Assistants Tools guide](https://platform.openai.com/docs/assistants/tools) for\n details.\n- The Fine-tuning API only supports `.jsonl` files. The input also has\n certain required formats for fine-tuning\n [chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input) or\n [completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input) models.\n- The Batch API only supports `.jsonl` files up to 200 MB in size. The input\n also has a specific required\n [format](https://platform.openai.com/docs/api-reference/batch/request-input).\n\nPlease [contact us](https://help.openai.com/) if you need to increase these\nstorage limits.\n", "tags": [ "Files" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/OpenAIFile" } } }, "parameters": [ { "name": "body", "in": "body", "required": true, "schema": { "$ref": "#/definitions/CreateFileRequest" } } ], "consumes": [ "multipart/form-data" ], "produces": [ "application/json" ] } }, "/files/{file_id}": { "get": { "operationId": "retrieveFile", "summary": "Retrieve file", "description": "Returns information about a specific file.", "tags": [ "Files" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/OpenAIFile" } } }, "parameters": [ { "name": "file_id", "in": "path", "description": "The ID of the file to use for this request.", "required": true, "type": "string" } ], "produces": [ "application/json" ] }, "delete": { "operationId": "deleteFile", "summary": "Delete file", "description": "Delete a file and remove it from all vector stores.", "tags": [ "Files" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/DeleteFileResponse" } } }, "parameters": [ { "name": "file_id", "in": "path", "description": "The ID of the file to use for this request.", "required": true, "type": "string" } ], "produces": [ "application/json" ] } }, "/files/{file_id}/content": { "get": { "operationId": "downloadFile", "summary": "Retrieve file content", "description": "Returns the contents of the specified file.", "tags": [ "Files" ], "responses": { "200": { "description": "OK", "schema": { "type": "string" } } }, "parameters": [ { "name": "file_id", "in": "path", "description": "The ID of the file to use for this request.", "required": true, "type": "string" } ], "produces": [ "application/json" ] } }, "/models": { "get": { "operationId": "listModels", "summary": "List available models", "description": "Lists the currently available models, and provides basic information\nabout each one such as the owner and availability.\n", "tags": [ "Models" ], "responses": { "200": { "description": "List of models", "schema": { "$ref": "#/definitions/ListIntelligenceModelsResponse" } } }, "produces": [ "application/json" ] } }, "/models/{model}": { "get": { "operationId": "retrieveModel", "summary": "Retrieve a model", "description": "Retrieves a model instance, providing basic information about the\nmodel such as the owner and availability.\n", "tags": [ "Models" ], "responses": { "200": { "description": "Model details", "schema": { "$ref": "#/definitions/IntelligenceModel" } }, "404": { "description": "Model not found" } }, "parameters": [ { "name": "model", "in": "path", "description": "The encoded ID of the model (returned in the `id` field from list)", "required": true, "type": "string" } ], "produces": [ "application/json" ] }, "delete": { "operationId": "deleteModel", "summary": "Delete a fine-tuned model", "description": "Delete a fine-tuned model owned by the caller's project. Refuses\ndeletion of globally available models, models not solely owned by the\ncaller's project, or models referenced by any non-terminal fine-tuning\njob in the project.\n", "tags": [ "Models" ], "responses": { "200": { "description": "Deletion confirmation", "schema": { "$ref": "#/definitions/DeleteIntelligenceModelResponse" } }, "403": { "description": "Caller is not the sole owner, or the model is globally available" }, "404": { "description": "Model not found" }, "409": { "description": "Model is referenced by a non-terminal fine-tuning job" } }, "parameters": [ { "name": "model", "in": "path", "description": "The encoded ID of the model (returned in the `id` field from list)", "required": true, "type": "string" } ], "produces": [ "application/json" ] } }, "/models/{model}/download": { "get": { "operationId": "downloadModel", "summary": "Download an adapter model", "description": "Download an adapter model as a zip archive containing\nadapter_model.safetensors and adapter_config.json.\nRequires ProjectReader permission.\n", "tags": [ "Models" ], "responses": { "200": { "description": "The adapter model files as a zip archive", "schema": { "type": "string", "format": "binary" } }, "400": { "description": "Base model downloads are not supported" }, "403": { "description": "Access denied to the model or its artifact" }, "404": { "description": "Model not found or has no downloadable artifact" } }, "parameters": [ { "name": "model", "in": "path", "description": "The ID of the adapter model to download", "required": true, "type": "string" } ], "produces": [ "application/zip" ] } }, "/public/models": { "get": { "operationId": "listModelsPublic", "summary": "List available fine-tuning models (public)", "description": "Lists the currently available fine-tuning models without requiring\nauthentication.\n", "tags": [ "Public" ], "responses": { "200": { "description": "List of models", "schema": { "$ref": "#/definitions/ListIntelligenceModelsResponse" } } }, "produces": [ "application/json" ] } }, "/fine_tuning/jobs/{fine_tuning_job_id}/metrics": { "get": { "operationId": "getFineTuningJobMetrics", "summary": "Get fine-tuning job metrics", "description": "Get time-series training metrics for a fine-tuning job.\n", "tags": [ "Fine-tuning" ], "responses": { "200": { "description": "OK", "schema": { "$ref": "#/definitions/FineTuningJobMetricsResponse" } } }, "parameters": [ { "name": "fine_tuning_job_id", "in": "path", "description": "The ID of the fine-tuning job to get metrics for.\n", "required": true, "type": "string" }, { "name": "metric_names", "in": "query", "description": "Filter to specific metric names.", "required": false, "type": "array", "items": { "type": "string", "enum": [ "ev_loss", "ev_eval_loss", "ev_current_step", "ev_total_steps", "ev_learning_rate", "ev_grad_norm", "ev_num_input_tokens_seen", "ev_eval_samples_per_second", "ev_eval_steps_per_second", "ev_estimated_finish", "ev_train_loss", "ev_train_runtime", "ev_train_samples_per_second", "ev_train_steps_per_second", "ev_train_tokens_per_second", "ev_total_flos" ] }, "collectionFormat": "csv" }, { "name": "cursor", "in": "query", "description": "Epoch timestamp cursor for pagination.", "required": false, "type": "string" }, { "name": "step", "in": "query", "description": "Step duration for aggregation (e.g. 1m, 30s).", "required": false, "type": "string" }, { "name": "x_axis", "in": "query", "description": "X-axis type for returned data points (default timestamp).", "required": false, "type": "string", "enum": [ "timestamp", "step_count" ] } ], "produces": [ "application/json" ] } } }, "definitions": { "CreateFineTuningJobRequest": { "type": "object", "required": [ "model", "training_file" ], "properties": { "model": { "description": "The name of the model to fine-tune. You can select one of the\n[supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned).\n", "example": "gpt-4o-mini", "x-anyOf": [ { "type": "string" }, { "type": "string", "title": "Preset", "enum": [ "babbage-002", "davinci-002", "gpt-3.5-turbo", "gpt-4o-mini" ] } ], "x-oaiTypeLabel": "string" }, "training_file": { "type": "string", "description": "The ID of an uploaded file that contains training data.\n\nSee [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a file.\n\nYour dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose `fine-tune`.\n\nThe contents of the file should differ depending on if the model uses the [chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input), [completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input) format, or if the fine-tuning method uses the [preference](https://platform.openai.com/docs/api-reference/fine-tuning/preference-input) format.\n\nSee the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details.\n", "example": "file-abc123" }, "suffix": { "type": "string", "x-nullable": true, "description": "A string of up to 64 characters that will be added to your fine-tuned model name.\n\nFor example, a `suffix` of \"custom-model-name\" would produce a model name like `ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`.\n", "minLength": 1, "maxLength": 64, "pattern": "^[a-zA-Z0-9][a-zA-Z0-9-]*$" }, "validation_file": { "type": "string", "x-nullable": true, "description": "The ID of an uploaded file that contains validation data.\n\nIf you provide this file, the data is used to generate validation\nmetrics periodically during fine-tuning. These metrics can be viewed in\nthe fine-tuning results file.\nThe same data should not be present in both train and validation files.\n\nYour dataset must be formatted as a JSONL file. You must upload your file with the purpose `fine-tune`.\n\nSee the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details.\n", "example": "file-abc123" }, "seed": { "type": "integer", "x-nullable": true, "description": "The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases.\nIf a seed is not specified, one will be generated for you.\n", "minimum": 0, "maximum": 2147483647, "example": 42 }, "method": { "$ref": "#/definitions/FineTuneMethod" }, "metadata": { "$ref": "#/definitions/Metadata" } } }, "FineTuningJob": { "type": "object", "title": "FineTuningJob", "description": "The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.\n", "required": [ "created_at", "error", "finished_at", "fine_tuned_model", "id", "model", "object", "organization_id", "result_files", "status", "trained_tokens", "training_file", "validation_file", "seed" ], "properties": { "id": { "type": "string", "description": "The object identifier, which can be referenced in the API endpoints." }, "created_at": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the fine-tuning job was created." }, "error": { "type": "object", "description": "For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.", "required": [ "code", "message", "param" ], "properties": { "code": { "type": "string", "description": "A machine-readable error code." }, "message": { "type": "string", "description": "A human-readable error message." }, "param": { "type": "string", "description": "The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.", "x-nullable": true, "x-anyOf": [ { "type": "string", "description": "The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific." }, { "type": "null" } ] } }, "x-nullable": true, "x-anyOf": [ { "type": "object", "description": "For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.", "required": [ "code", "message", "param" ], "properties": { "code": { "type": "string", "description": "A machine-readable error code." }, "message": { "type": "string", "description": "A human-readable error message." }, "param": { "type": "string", "description": "The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.", "x-nullable": true, "x-anyOf": [ { "type": "string", "description": "The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific." }, { "type": "null" } ] } } }, { "type": "null" } ] }, "fine_tuned_model": { "type": "string", "description": "The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.", "x-nullable": true, "x-anyOf": [ { "type": "string", "description": "The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running." }, { "type": "null" } ] }, "finished_at": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.", "x-nullable": true, "x-anyOf": [ { "type": "integer", "description": "The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running." }, { "type": "null" } ] }, "model": { "type": "string", "description": "The base model that is being fine-tuned." }, "object": { "$ref": "#/definitions/FineTuningJobObject" }, "organization_id": { "type": "string", "description": "The organization that owns the fine-tuning job." }, "result_files": { "type": "array", "description": "The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).", "items": { "type": "string", "example": "file-abc123" } }, "status": { "$ref": "#/definitions/FineTuningJobStatus" }, "trained_tokens": { "type": "integer", "description": "The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running.", "x-nullable": true, "x-anyOf": [ { "type": "integer", "description": "The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running." }, { "type": "null" } ] }, "training_file": { "type": "string", "description": "The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents)." }, "validation_file": { "type": "string", "description": "The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).", "x-nullable": true, "x-anyOf": [ { "type": "string", "description": "The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents)." }, { "type": "null" } ] }, "seed": { "type": "integer", "description": "The seed used for the fine-tuning job." }, "estimated_finish": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running.", "x-nullable": true, "x-anyOf": [ { "type": "integer", "description": "The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running." }, { "type": "null" } ] }, "method": { "$ref": "#/definitions/FineTuneMethod" }, "metadata": { "$ref": "#/definitions/Metadata" } }, "x-oaiMeta": { "name": "The fine-tuning job object", "example": "{\n \"object\": \"fine_tuning.job\",\n \"id\": \"ftjob-abc123\",\n \"model\": \"davinci-002\",\n \"created_at\": 1692661014,\n \"finished_at\": 1692661190,\n \"fine_tuned_model\": \"ft:davinci-002:my-org:custom_suffix:7q8mpxmy\",\n \"organization_id\": \"org-123\",\n \"result_files\": [\n \"file-abc123\"\n ],\n \"status\": \"succeeded\",\n \"validation_file\": null,\n \"training_file\": \"file-abc123\",\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n },\n \"trained_tokens\": 5768,\n \"integrations\": [],\n \"seed\": 0,\n \"estimated_finish\": 0,\n \"method\": {\n \"type\": \"supervised\",\n \"supervised\": {\n \"hyperparameters\": {\n \"n_epochs\": 4,\n \"batch_size\": 1,\n \"learning_rate_multiplier\": 1.0\n }\n }\n },\n \"metadata\": {\n \"key\": \"value\"\n }\n}\n" } }, "ListPaginatedFineTuningJobsResponse": { "type": "object", "required": [ "object", "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/definitions/FineTuningJob" } }, "has_more": { "type": "boolean" }, "object": { "$ref": "#/definitions/ListPaginatedFineTuningJobsResponseObject" } } }, "ListFineTuningJobCheckpointsResponse": { "type": "object", "required": [ "object", "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/definitions/FineTuningJobCheckpoint" } }, "object": { "$ref": "#/definitions/ListFineTuningJobCheckpointsResponseObject" }, "first_id": { "type": "string", "x-nullable": true, "x-anyOf": [ { "type": "string" }, { "type": "null" } ] }, "last_id": { "type": "string", "x-nullable": true, "x-anyOf": [ { "type": "string" }, { "type": "null" } ] }, "has_more": { "type": "boolean" } } }, "ListFineTuningJobEventsResponse": { "type": "object", "required": [ "object", "data", "has_more" ], "properties": { "data": { "type": "array", "items": { "$ref": "#/definitions/FineTuningJobEvent" } }, "object": { "$ref": "#/definitions/ListFineTuningJobEventsResponseObject" }, "has_more": { "type": "boolean" } } }, "ListFilesResponse": { "type": "object", "required": [ "object", "data", "first_id", "last_id", "has_more" ], "properties": { "object": { "type": "string", "example": "list" }, "data": { "type": "array", "items": { "$ref": "#/definitions/OpenAIFile" } }, "first_id": { "type": "string", "example": "file-abc123" }, "last_id": { "type": "string", "example": "file-abc456" }, "has_more": { "type": "boolean", "example": false } } }, "CreateFileRequest": { "type": "object", "required": [ "file", "purpose" ], "properties": { "file": { "type": "string", "format": "binary", "description": "The File object (not file name) to be uploaded.\n", "x-oaiMeta": { "exampleFilePath": "fine-tune.jsonl" } }, "purpose": { "$ref": "#/definitions/FilePurpose" }, "expires_after": { "$ref": "#/definitions/FileExpirationAfter" } } }, "OpenAIFile": { "title": "OpenAIFile", "description": "The `File` object represents a document that has been uploaded to OpenAI.", "required": [ "id", "object", "bytes", "created_at", "filename", "purpose", "status" ], "properties": { "id": { "type": "string", "description": "The file identifier, which can be referenced in the API endpoints." }, "bytes": { "type": "integer", "description": "The size of the file, in bytes." }, "created_at": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the file was created." }, "expires_at": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the file will expire." }, "filename": { "type": "string", "description": "The name of the file." }, "object": { "$ref": "#/definitions/OpenAIFileObject" }, "purpose": { "type": "string", "description": "The intended purpose of the file. Supported values are `assistants`, `assistants_output`, `batch`, `batch_output`, `fine-tune`, `fine-tune-results`, `vision`, and `user_data`.", "enum": [ "assistants", "assistants_output", "batch", "batch_output", "fine-tune", "fine-tune-results", "vision", "user_data" ] }, "status": { "$ref": "#/definitions/OpenAIFileStatus" }, "status_details": { "type": "string", "description": "Deprecated. For details on why a fine-tuning training file failed validation, see the `error` field on `fine_tuning.job`." }, "is_cmek_encrypted": { "type": "boolean", "description": "Whether the file's contents carry an additional layer of encryption with a customer-managed key (CMEK), on top of the storage-native encryption applied to all objects.", "default": false } }, "x-oaiMeta": { "name": "The file object", "example": "{\n \"id\": \"file-abc123\",\n \"object\": \"file\",\n \"bytes\": 120000,\n \"created_at\": 1677610602,\n \"expires_at\": 1680202602,\n \"filename\": \"salesOverview.pdf\",\n \"purpose\": \"assistants\",\n}\n" } }, "DeleteFileResponse": { "type": "object", "required": [ "id", "object", "deleted" ], "properties": { "id": { "type": "string" }, "object": { "$ref": "#/definitions/DeleteFileResponseObject" }, "deleted": { "type": "boolean" } } }, "ListIntelligenceModelsResponse": { "type": "object", "required": [ "object", "data" ], "properties": { "object": { "$ref": "#/definitions/ListIntelligenceModelsResponseObject" }, "data": { "type": "array", "items": { "$ref": "#/definitions/IntelligenceModel" } } } }, "IntelligenceModel": { "type": "object", "required": [ "id", "object", "owned_by", "model_source", "model_name", "model_revision", "globally_available", "project_ids", "inference_available", "fine_tuning_available", "model_type", "created" ], "properties": { "id": { "type": "string", "description": "Unique identifier for the model", "example": "admin-model-abc123" }, "object": { "$ref": "#/definitions/IntelligenceModelObject" }, "owned_by": { "type": "string", "description": "The organization that owns the model", "example": "org-123" }, "model_source": { "$ref": "#/definitions/IntelligenceModelModelSource" }, "model_name": { "type": "string", "description": "Model identifier within the source registry", "example": "meta-llama/Llama-2-7b-hf" }, "model_revision": { "type": "string", "description": "Git revision or branch", "example": "main" }, "globally_available": { "type": "boolean", "description": "Whether the model is available to all projects", "example": false }, "project_ids": { "type": "array", "description": "Project IDs that can access this model (empty when globally_available is true)", "example": [ "proj-123" ], "items": { "type": "string" } }, "inference_available": { "type": "boolean", "description": "Whether the model is available for inference", "example": true }, "fine_tuning_available": { "type": "boolean", "description": "Whether the model is available for fine-tuning", "example": false }, "model_type": { "$ref": "#/definitions/ModelType" }, "base_model_id": { "type": "string", "x-nullable": true, "description": "Registry ID of the parent base model (set for adapters, null for base models)", "example": "model-abc123" }, "created": { "type": "integer", "description": "Unix timestamp of when the model was registered", "example": 1700000000 } } }, "DeleteIntelligenceModelResponse": { "type": "object", "required": [ "id", "object", "deleted" ], "properties": { "id": { "type": "string", "description": "The ID of the deleted model." }, "object": { "$ref": "#/definitions/DeleteIntelligenceModelResponseObject" }, "deleted": { "type": "boolean", "description": "Always `true` on success." } } }, "MetricName": { "type": "string", "title": "MetricName", "description": "Supported fine-tuning metric names.", "enum": [ "ev_loss", "ev_eval_loss", "ev_current_step", "ev_total_steps", "ev_learning_rate", "ev_grad_norm", "ev_num_input_tokens_seen", "ev_eval_samples_per_second", "ev_eval_steps_per_second", "ev_estimated_finish", "ev_train_loss", "ev_train_runtime", "ev_train_samples_per_second", "ev_train_steps_per_second", "ev_train_tokens_per_second", "ev_total_flos" ] }, "FineTuningJobMetricsResponse": { "type": "object", "title": "FineTuningJobMetricsResponse", "description": "Time-series training metrics for a fine-tuning job.", "required": [ "object", "fine_tuning_job_id", "x_axis", "metrics" ], "properties": { "object": { "$ref": "#/definitions/FineTuningJobMetricsResponseObject" }, "fine_tuning_job_id": { "type": "string", "description": "The ID of the fine-tuning job these metrics belong to." }, "x_axis": { "type": "string", "description": "The x-axis type for the data points.", "enum": [ "timestamp", "step_count" ] }, "metrics": { "type": "array", "description": "List of metric time series.", "items": { "$ref": "#/definitions/MetricSeries" } } } }, "FineTuneMethod": { "type": "object", "description": "The method used for fine-tuning. Only `supervised` is supported.", "required": [ "type" ], "properties": { "type": { "$ref": "#/definitions/FineTuneMethodType" }, "supervised": { "$ref": "#/definitions/FineTuneSupervisedMethod" } } }, "Metadata": { "type": "object", "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.\n", "additionalProperties": { "type": "string" }, "x-oaiTypeLabel": "map", "x-nullable": true, "x-anyOf": [ { "type": "object", "description": "Set of 16 key-value pairs that can be attached to an object. This can be\nuseful for storing additional information about the object in a structured\nformat, and querying for objects via API or the dashboard.\n\nKeys are strings with a maximum length of 64 characters. Values are strings\nwith a maximum length of 512 characters.\n", "additionalProperties": { "type": "string" }, "x-oaiTypeLabel": "map" }, { "type": "null" } ] }, "FineTuningJobObject": { "type": "string", "description": "The object type, which is always \"fine_tuning.job\".", "enum": [ "fine_tuning.job" ], "x-stainless-const": true }, "FineTuningJobStatus": { "type": "string", "description": "The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.", "enum": [ "validating_files", "queued", "running", "succeeded", "failed", "cancelled" ] }, "ListPaginatedFineTuningJobsResponseObject": { "type": "string", "enum": [ "list" ], "x-stainless-const": true }, "FineTuningJobCheckpoint": { "type": "object", "title": "FineTuningJobCheckpoint", "description": "The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use.\n", "required": [ "created_at", "fine_tuning_job_id", "fine_tuned_model_checkpoint", "id", "metrics", "object", "step_number" ], "properties": { "id": { "type": "string", "description": "The checkpoint identifier, which can be referenced in the API endpoints." }, "created_at": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the checkpoint was created." }, "fine_tuned_model_checkpoint": { "type": "string", "description": "The name of the fine-tuned checkpoint model that is created." }, "step_number": { "type": "integer", "description": "The step number that the checkpoint was created at." }, "metrics": { "type": "object", "description": "Metrics at the step number during the fine-tuning job.", "properties": { "step": { "type": "number" }, "train_loss": { "type": "number" }, "train_mean_token_accuracy": { "type": "number" }, "valid_loss": { "type": "number" }, "valid_mean_token_accuracy": { "type": "number" }, "full_valid_loss": { "type": "number" }, "full_valid_mean_token_accuracy": { "type": "number" } } }, "fine_tuning_job_id": { "type": "string", "description": "The name of the fine-tuning job that this checkpoint was created from." }, "object": { "$ref": "#/definitions/FineTuningJobCheckpointObject" }, "fine_tuned_model_id": { "type": "string", "x-nullable": true, "description": "The model registry ID of the registered adapter for this checkpoint, usable as the `model` for inference. Null until the checkpoint has been registered.", "default": null, "x-anyOf": [ { "type": "string" }, { "type": "null" } ] } }, "x-oaiMeta": { "name": "The fine-tuning job checkpoint object", "example": "{\n \"object\": \"fine_tuning.job.checkpoint\",\n \"id\": \"ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P\",\n \"created_at\": 1712211699,\n \"fine_tuned_model_checkpoint\": \"ft:gpt-4o-mini-2024-07-18:my-org:custom_suffix:9ABel2dg:ckpt-step-88\",\n \"fine_tuning_job_id\": \"ftjob-fpbNQ3H1GrMehXRf8cO97xTN\",\n \"metrics\": {\n \"step\": 88,\n \"train_loss\": 0.478,\n \"train_mean_token_accuracy\": 0.924,\n \"valid_loss\": 10.112,\n \"valid_mean_token_accuracy\": 0.145,\n \"full_valid_loss\": 0.567,\n \"full_valid_mean_token_accuracy\": 0.944\n },\n \"step_number\": 88\n}\n" } }, "ListFineTuningJobCheckpointsResponseObject": { "type": "string", "enum": [ "list" ], "x-stainless-const": true }, "FineTuningJobEvent": { "type": "object", "description": "Fine-tuning job event object", "required": [ "id", "object", "created_at", "level", "message" ], "properties": { "object": { "$ref": "#/definitions/FineTuningJobEventObject" }, "id": { "type": "string", "description": "The object identifier." }, "created_at": { "type": "integer", "description": "The Unix timestamp (in seconds) for when the fine-tuning job was created." }, "level": { "type": "string", "description": "The log level of the event.", "enum": [ "info", "warn", "error" ] }, "message": { "type": "string", "description": "The message of the event." }, "type": { "$ref": "#/definitions/FineTuningJobEventType" }, "data": { "type": "object", "description": "The data associated with the event." } }, "x-oaiMeta": { "name": "The fine-tuning job event object", "example": "{\n \"object\": \"fine_tuning.job.event\",\n \"id\": \"ftevent-abc123\"\n \"created_at\": 1677610602,\n \"level\": \"info\",\n \"message\": \"Created fine-tuning job\",\n \"data\": {},\n \"type\": \"message\"\n}\n" } }, "ListFineTuningJobEventsResponseObject": { "type": "string", "enum": [ "list" ], "x-stainless-const": true }, "FilePurpose": { "type": "string", "description": "The intended purpose of the file. Supported values are `fine-tune` and `batch`.", "enum": [ "fine-tune", "batch" ] }, "FileExpirationAfter": { "type": "object", "title": "File expiration policy", "description": "The expiration policy for a file. By default, files with `purpose=batch` expire after 30 days and all other files are persisted until they are manually deleted.", "required": [ "anchor", "seconds" ], "properties": { "anchor": { "type": "string", "description": "Anchor timestamp after which the expiration policy applies. Supported anchors: `created_at`.", "enum": [ "created_at" ], "x-stainless-const": true }, "seconds": { "type": "integer", "description": "The number of seconds after the anchor time that the file will expire. Must be between 3600 (1 hour) and 2592000 (30 days).", "minimum": 3600, "maximum": 2592000 } } }, "OpenAIFileObject": { "type": "string", "description": "The object type, which is always `file`.", "enum": [ "file" ], "x-stainless-const": true }, "OpenAIFileStatus": { "type": "string", "description": "Deprecated. The current status of the file, which can be either `uploaded`, `processed`, or `error`.", "enum": [ "uploaded", "processed", "error" ] }, "DeleteFileResponseObject": { "type": "string", "enum": [ "file" ], "x-stainless-const": true }, "ListIntelligenceModelsResponseObject": { "type": "string", "enum": [ "list" ], "example": "list" }, "IntelligenceModelObject": { "type": "string", "description": "The object type, which is always \"model\"", "enum": [ "model" ], "example": "model" }, "IntelligenceModelModelSource": { "type": "string", "description": "Registry the model originates from", "enum": [ "huggingface", "evolution" ], "example": "huggingface" }, "ModelType": { "type": "string", "description": "Whether the model is a base model or a fine-tuned adapter", "enum": [ "base_model", "adapter" ] }, "DeleteIntelligenceModelResponseObject": { "type": "string", "enum": [ "model" ], "example": "model" }, "FineTuningJobMetricsResponseObject": { "type": "string", "description": "The object type, which is always \"fine_tuning.job.metrics\".", "enum": [ "fine_tuning.job.metrics" ] }, "MetricSeries": { "type": "object", "title": "MetricSeries", "description": "A named metric with its time-series data points.", "required": [ "metric_name", "data" ], "properties": { "metric_name": { "$ref": "#/definitions/MetricName" }, "data": { "type": "array", "description": "Ordered list of data points for this metric.", "items": { "$ref": "#/definitions/MetricDataPoint" } } } }, "FineTuneMethodType": { "type": "string", "description": "The type of method. Only `supervised` is supported.", "enum": [ "supervised" ] }, "FineTuneSupervisedMethod": { "type": "object", "description": "Configuration for the supervised fine-tuning method.", "properties": { "hyperparameters": { "$ref": "#/definitions/FineTuneSupervisedHyperparameters" } } }, "FineTuningJobCheckpointObject": { "type": "string", "description": "The object type, which is always \"fine_tuning.job.checkpoint\".", "enum": [ "fine_tuning.job.checkpoint" ], "x-stainless-const": true }, "FineTuningJobEventObject": { "type": "string", "description": "The object type, which is always \"fine_tuning.job.event\".", "enum": [ "fine_tuning.job.event" ], "x-stainless-const": true }, "FineTuningJobEventType": { "type": "string", "description": "The type of event.", "enum": [ "message", "metrics" ] }, "MetricDataPoint": { "type": "object", "title": "MetricDataPoint", "description": "A single metric data point.", "required": [ "x", "value" ], "properties": { "x": { "type": "number", "description": "X-axis value \u2014 either a Unix timestamp (seconds) or a step count, depending on x_axis." }, "value": { "type": "number", "description": "The metric value at this point." } } }, "FineTuneSupervisedHyperparameters": { "type": "object", "description": "The hyperparameters used for the fine-tuning job.", "properties": { "batch_size": { "description": "Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. Must be a power of 2 between 16 and 1024.\n", "default": "auto", "x-anyOf": [ { "type": "string", "enum": [ "auto" ], "x-stainless-const": true }, { "type": "integer", "enum": [ 16, 32, 64, 128, 256, 512, 1024 ] } ] }, "learning_rate_multiplier": { "description": "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.\n", "x-anyOf": [ { "type": "string", "enum": [ "auto" ], "x-stainless-const": true }, { "type": "number", "exclusiveMinimum": 0 } ] }, "n_epochs": { "description": "The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.\n", "default": "auto", "x-anyOf": [ { "type": "string", "enum": [ "auto" ], "x-stainless-const": true }, { "type": "integer", "minimum": 1, "maximum": 50 } ] }, "lora_variant": { "type": "string", "description": "LoRA variant to use. \"lora\" uses standard LoRA scaling (1/rank); \"rslora\" uses rank-stabilized LoRA scaling (1/sqrt(rank)).", "default": "lora", "enum": [ "lora", "rslora" ] }, "lora_rank": { "type": "integer", "enum": [ 2, 4, 8, 16, 32, 64, 128, 256 ], "x-nullable": true, "description": "LoRA attention dimension (r parameter). Must be a power of 2.", "x-anyOf": [ { "type": "integer", "enum": [ 2, 4, 8, 16, 32, 64, 128, 256 ] }, { "type": "null" } ] }, "lora_alpha": { "type": "integer", "enum": [ 1, 2, 4, 8, 16, 32, 64, 128, 256, 512 ], "x-nullable": true, "description": "LoRA scaling parameter (alpha). Must be a power of 2.", "x-anyOf": [ { "type": "integer", "enum": [ 1, 2, 4, 8, 16, 32, 64, 128, 256, 512 ] }, { "type": "null" } ] }, "lora_dropout": { "type": "number", "minimum": 0, "maximum": 1, "x-nullable": true, "description": "LoRA dropout probability. Must be between 0 and 1.", "x-anyOf": [ { "type": "number", "minimum": 0, "maximum": 1 }, { "type": "null" } ] }, "early_stopping_patience": { "type": "integer", "minimum": 1, "x-nullable": true, "description": "Number of evaluation calls without improvement before stopping training. Set to null (default) to disable early stopping.", "x-anyOf": [ { "type": "integer", "minimum": 1 }, { "type": "null" } ] }, "warmup_ratio": { "type": "number", "minimum": 0, "maximum": 1, "x-nullable": true, "description": "Fraction of total training steps used for linear warmup", "x-anyOf": [ { "type": "number", "minimum": 0, "maximum": 1 }, { "type": "null" } ] }, "learning_rate": { "description": "Absolute learning rate for training", "x-anyOf": [ { "type": "string", "enum": [ "auto" ] }, { "type": "number" } ] }, "weight_decay": { "type": "number", "minimum": 0, "x-nullable": true, "description": "Weight decay (L2 regularization) coefficient", "x-anyOf": [ { "type": "number", "minimum": 0 }, { "type": "null" } ] }, "top_k_gating": { "type": "integer", "enum": [ 1, 2, 4, 8, 16 ], "x-nullable": true, "description": "Number of experts activated per token (top-k). Must be a power of 2.", "x-anyOf": [ { "type": "integer", "enum": [ 1, 2, 4, 8, 16 ] }, { "type": "null" } ] }, "checkpoint_steps": { "type": "number", "minimum": 20, "x-nullable": true, "description": "Number of update steps between two checkpoint saves.", "x-anyOf": [ { "type": "number", "minimum": 20 }, { "type": "null" } ] }, "eval_steps_per_epoch": { "type": "number", "minimum": 1, "x-nullable": true, "description": "Number of evaluation steps per epoch.", "x-anyOf": [ { "type": "number", "minimum": 1 }, { "type": "null" } ] }, "overlong_row_behavior": { "type": "string", "description": "How to handle training rows that exceed the maximum sequence length. \"error\" (default) raises an error; \"drop\" silently discards overlong rows before training.", "default": "error", "enum": [ "error", "drop" ] }, "lr_scheduler": { "type": "string", "description": "Learning rate scheduler type. See https://huggingface.co/docs/transformers/en/main_classes/optimizer_schedules#transformers.SchedulerType for details on each option.", "default": "cosine", "enum": [ "cosine", "constant", "constant_with_warmup", "linear" ] } } } }, "securityDefinitions": { "ApiKeyAuth": { "type": "apiKey", "name": "Authorization", "in": "header", "description": "" } }, "security": [ { "ApiKeyAuth": [] } ] }