Get an eval run

evals.runs.retrieve(run_id, **kwargs) -> RunRetrieveResponse { id, created_at, data_source, 11 more }

GET/evals/{eval_id}/runs/{run_id}

Get an evaluation run by ID.

ParametersExpand Collapse

eval_id: String

run_id: String

ReturnsExpand Collapse

class RunRetrieveResponse { id, created_at, data_source, 11 more }

A schema representing an evaluation run.

id: String

Unique identifier for the evaluation run.

created_at: Integer

Unix timestamp (in seconds) when the evaluation run was created.

data_source: CreateEvalJSONLRunDataSource { source, type } | CreateEvalCompletionsRunDataSource { source, type, input_messages, 2 more } | { source, type, input_messages, 2 more}

Information about the run's data source.

Accepts one of the following:

class CreateEvalJSONLRunDataSource { source, type }

A JsonlRunDataSource object with that specifies a JSONL file that matches the eval

source: { content, type} | { id, type}

Determines what populates the item namespace in the data source.

Accepts one of the following:

class FileContent { content, type }

content: Array[{ item, sample}]

The content of the jsonl file.

item: Hash[Symbol, untyped]

sample: Hash[Symbol, untyped]

type: :file_content

The type of jsonl source. Always file_content.

class FileID { id, type }

id: String

The identifier of the file.

type: :file_id

The type of jsonl source. Always file_id.

type: :jsonl

The type of data source. Always jsonl.

class CreateEvalCompletionsRunDataSource { source, type, input_messages, 2 more }

A CompletionsRunDataSource object describing a model sampling configuration.

source: { content, type} | { id, type} | { type, created_after, created_before, 3 more}

Determines what populates the item namespace in this run's data source.

Accepts one of the following:

class FileContent { content, type }

content: Array[{ item, sample}]

The content of the jsonl file.

item: Hash[Symbol, untyped]

sample: Hash[Symbol, untyped]

type: :file_content

The type of jsonl source. Always file_content.

class FileID { id, type }

id: String

The identifier of the file.

type: :file_id

The type of jsonl source. Always file_id.

class StoredCompletions { type, created_after, created_before, 3 more }

A StoredCompletionsRunDataSource configuration describing a set of filters

type: :stored_completions

The type of source. Always stored_completions.

created_after: Integer

An optional Unix timestamp to filter items created after this time.

created_before: Integer

An optional Unix timestamp to filter items created before this time.

limit: Integer

An optional maximum number of items to return.

metadata: Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

model: String

An optional model to filter by (e.g., 'gpt-4o').

type: :completions

The type of run data source. Always completions.

input_messages: { template, type} | { item_reference, type}

Used when sampling from a model. Dictates the structure of the messages passed into the model. Can either be a reference to a prebuilt trajectory (ie, item.input_trajectory), or a template with variable references to the item namespace.

Accepts one of the following:

class Template { template, type }

template: Array[EasyInputMessage { content, role, type } | { content, role, type}]

A list of chat messages forming the prompt or context. May include variable references to the item namespace, ie {{item.name}}.

Accepts one of the following:

class EasyInputMessage { content, role, type }

A message input to the model with a role indicating instruction following hierarchy. Instructions given with the developer or system role take precedence over instructions given with the user role. Messages with the assistant role are presumed to have been generated by the model in previous interactions.

content: String | ResponseInputMessageContentList { , , }

Text, image, or audio input to the model, used to generate a response. Can also contain previous assistant responses.

Accepts one of the following:

String

A text input to the model.

Array[ResponseInputContent]

A list of one or many input items to the model, containing different content types.

Accepts one of the following:

class ResponseInputText { text, type }

A text input to the model.

text: String

The text input to the model.

type: :input_text

The type of the input item. Always input_text.

class ResponseInputImage { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: :low | :high | :auto

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

Accepts one of the following:

:low

:high

:auto

type: :input_image

The type of the input item. Always input_image.

file_id: String

The ID of the file to be sent to the model.

image_url: String

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

class ResponseInputFile { type, file_data, file_id, 2 more }

A file input to the model.

type: :input_file

The type of the input item. Always input_file.

file_data: String

The content of the file to be sent to the model.

file_id: String

The ID of the file to be sent to the model.

file_url: String

The URL of the file to be sent to the model.

filename: String

The name of the file to be sent to the model.

role: :user | :assistant | :system | :developer

The role of the message input. One of user, assistant, system, or developer.

Accepts one of the following:

:user

:assistant

:system

:developer

type: :message

The type of the message input. Always message.

class EvalItem { content, role, type }

content: String | ResponseInputText { text, type } | { text, type} | 3 more

Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.

Accepts one of the following:

String

A text input to the model.

class ResponseInputText { text, type }

A text input to the model.

text: String

The text input to the model.

type: :input_text

The type of the input item. Always input_text.

class OutputText { text, type }

A text output from the model.

text: String

The text output from the model.

type: :output_text

The type of the output text. Always output_text.

class InputImage { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: String

The URL of the image input.

type: :input_image

The type of the image input. Always input_image.

detail: String

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

class ResponseInputAudio { input_audio, type }

An audio input to the model.

input_audio: { data, format_}

data: String

Base64-encoded audio data.

format_: :mp3 | :wav

The format of the audio data. Currently supported formats are mp3 and wav.

Accepts one of the following:

:mp3

:wav

type: :input_audio

The type of the input item. Always input_audio.

Array[GraderInputItem]

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

Accepts one of the following:

String

A text input to the model.

class ResponseInputText { text, type }

A text input to the model.

text: String

The text input to the model.

type: :input_text

The type of the input item. Always input_text.

class OutputText { text, type }

A text output from the model.

text: String

The text output from the model.

type: :output_text

The type of the output text. Always output_text.

class InputImage { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: String

The URL of the image input.

type: :input_image

The type of the image input. Always input_image.

detail: String

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

class ResponseInputAudio { input_audio, type }

An audio input to the model.

input_audio: { data, format_}

data: String

Base64-encoded audio data.

format_: :mp3 | :wav

The format of the audio data. Currently supported formats are mp3 and wav.

Accepts one of the following:

:mp3

:wav

type: :input_audio

The type of the input item. Always input_audio.

role: :user | :assistant | :system | :developer

The role of the message input. One of user, assistant, system, or developer.

Accepts one of the following:

:user

:assistant

:system

:developer

type: :message

The type of the message input. Always message.

type: :template

The type of input messages. Always template.

class ItemReference { item_reference, type }

item_reference: String

A reference to a variable in the item namespace. Ie, "item.input_trajectory"

type: :item_reference

The type of input messages. Always item_reference.

model: String

The name of the model to use for generating completions (e.g. "o3-mini").

sampling_params: { max_completion_tokens, reasoning_effort, response_format, 4 more}

max_completion_tokens: Integer

The maximum number of tokens in the generated output.

reasoning_effort: ReasoningEffort

Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
All models before gpt-5.1 default to medium reasoning effort, and do not support none.
The gpt-5-pro model defaults to (and only supports) high reasoning effort.
xhigh is supported for all models after gpt-5.1-codex-max.

Accepts one of the following:

:none

:minimal

:low

:medium

:high

:xhigh

response_format: ResponseFormatText { type } | ResponseFormatJSONSchema { json_schema, type } | ResponseFormatJSONObject { type }

An object specifying the format that the model must output.

Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

Setting to { "type": "json_object" } enables the older JSON mode, which ensures the message the model generates is valid JSON. Using json_schema is preferred for models that support it.

Accepts one of the following:

class ResponseFormatText { type }

Default response format. Used to generate text responses.

type: :text

The type of response format being defined. Always text.

class ResponseFormatJSONSchema { json_schema, type }

JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

json_schema: { name, description, schema, strict}

Structured Outputs configuration options, including a JSON Schema.

The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

description: String

A description of what the response format is for, used by the model to determine how to respond in the format.

schema: Hash[Symbol, untyped]

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

strict: bool

Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the schema field. Only a subset of JSON Schema is supported when strict is true. To learn more, read the Structured Outputs guide.

type: :json_schema

The type of response format being defined. Always json_schema.

class ResponseFormatJSONObject { type }

JSON object response format. An older method of generating JSON responses. Using json_schema is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.

type: :json_object

The type of response format being defined. Always json_object.

seed: Integer

A seed value to initialize the randomness, during sampling.

temperature: Float

A higher temperature increases randomness in the outputs.

tools: Array[ChatCompletionFunctionTool { function, type } ]

A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.

function: FunctionDefinition { name, description, parameters, strict }

The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

description: String

A description of what the function does, used by the model to choose when and how to call the function.

parameters: FunctionParameters

The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

Omitting parameters defines a function with an empty parameter list.

strict: bool

Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the parameters field. Only a subset of JSON Schema is supported when strict is true. Learn more about Structured Outputs in the function calling guide.

type: :function

The type of the tool. Currently, only function is supported.

top_p: Float

An alternative to temperature for nucleus sampling; 1.0 includes all tokens.

class Responses { source, type, input_messages, 2 more }

A ResponsesRunDataSource object describing a model sampling configuration.

source: { content, type} | { id, type} | { type, created_after, created_before, 8 more}

Determines what populates the item namespace in this run's data source.

Accepts one of the following:

class FileContent { content, type }

content: Array[{ item, sample}]

The content of the jsonl file.

item: Hash[Symbol, untyped]

sample: Hash[Symbol, untyped]

type: :file_content

The type of jsonl source. Always file_content.

class FileID { id, type }

id: String

The identifier of the file.

type: :file_id

The type of jsonl source. Always file_id.

class Responses { type, created_after, created_before, 8 more }

A EvalResponsesSource object describing a run data source configuration.

type: :responses

The type of run data source. Always responses.

created_after: Integer

Only include items created after this timestamp (inclusive). This is a query parameter used to select responses.

minimum0

created_before: Integer

Only include items created before this timestamp (inclusive). This is a query parameter used to select responses.

minimum0

instructions_search: String

Optional string to search the 'instructions' field. This is a query parameter used to select responses.

metadata: untyped

Metadata filter for the responses. This is a query parameter used to select responses.

model: String

The name of the model to find responses for. This is a query parameter used to select responses.

reasoning_effort: ReasoningEffort

gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
All models before gpt-5.1 default to medium reasoning effort, and do not support none.
The gpt-5-pro model defaults to (and only supports) high reasoning effort.
xhigh is supported for all models after gpt-5.1-codex-max.

Accepts one of the following:

:none

:minimal

:low

:medium

:high

:xhigh

temperature: Float

Sampling temperature. This is a query parameter used to select responses.

tools: Array[String]

List of tool names. This is a query parameter used to select responses.

top_p: Float

Nucleus sampling parameter. This is a query parameter used to select responses.

users: Array[String]

List of user identifiers. This is a query parameter used to select responses.

type: :responses

The type of run data source. Always responses.

input_messages: { template, type} | { item_reference, type}

Accepts one of the following:

class Template { template, type }

A list of chat messages forming the prompt or context. May include variable references to the item namespace, ie {{item.name}}.

Accepts one of the following:

class ChatMessage { content, role }

content: String

The content of the message.

role: String

The role of the message (e.g. "system", "assistant", "user").

class EvalItem { content, role, type }

content: String | ResponseInputText { text, type } | { text, type} | 3 more

Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items.

Accepts one of the following:

String

A text input to the model.

class ResponseInputText { text, type }

A text input to the model.

text: String

The text input to the model.

type: :input_text

The type of the input item. Always input_text.

class OutputText { text, type }

A text output from the model.

text: String

The text output from the model.

type: :output_text

The type of the output text. Always output_text.

class InputImage { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: String

The URL of the image input.

type: :input_image

The type of the image input. Always input_image.

detail: String

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

class ResponseInputAudio { input_audio, type }

An audio input to the model.

input_audio: { data, format_}

data: String

Base64-encoded audio data.

format_: :mp3 | :wav

The format of the audio data. Currently supported formats are mp3 and wav.

Accepts one of the following:

:mp3

:wav

type: :input_audio

The type of the input item. Always input_audio.

Array[GraderInputItem]

A list of inputs, each of which may be either an input text, output text, input image, or input audio object.

Accepts one of the following:

String

A text input to the model.

class ResponseInputText { text, type }

A text input to the model.

text: String

The text input to the model.

type: :input_text

The type of the input item. Always input_text.

class OutputText { text, type }

A text output from the model.

text: String

The text output from the model.

type: :output_text

The type of the output text. Always output_text.

class InputImage { image_url, type, detail }

An image input block used within EvalItem content arrays.

image_url: String

The URL of the image input.

type: :input_image

The type of the image input. Always input_image.

detail: String

The detail level of the image to be sent to the model. One of high, low, or auto. Defaults to auto.

class ResponseInputAudio { input_audio, type }

An audio input to the model.

input_audio: { data, format_}

data: String

Base64-encoded audio data.

format_: :mp3 | :wav

The format of the audio data. Currently supported formats are mp3 and wav.

Accepts one of the following:

:mp3

:wav

type: :input_audio

The type of the input item. Always input_audio.

role: :user | :assistant | :system | :developer

The role of the message input. One of user, assistant, system, or developer.

Accepts one of the following:

:user

:assistant

:system

:developer

type: :message

The type of the message input. Always message.

type: :template

The type of input messages. Always template.

class ItemReference { item_reference, type }

item_reference: String

A reference to a variable in the item namespace. Ie, "item.name"

type: :item_reference

The type of input messages. Always item_reference.

model: String

The name of the model to use for generating completions (e.g. "o3-mini").

sampling_params: { max_completion_tokens, reasoning_effort, seed, 4 more}

max_completion_tokens: Integer

The maximum number of tokens in the generated output.

reasoning_effort: ReasoningEffort

gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
All models before gpt-5.1 default to medium reasoning effort, and do not support none.
The gpt-5-pro model defaults to (and only supports) high reasoning effort.
xhigh is supported for all models after gpt-5.1-codex-max.

Accepts one of the following:

:none

:minimal

:low

:medium

:high

:xhigh

seed: Integer

A seed value to initialize the randomness, during sampling.

temperature: Float

A higher temperature increases randomness in the outputs.

text: { format_}

Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more:

format_: ResponseFormatTextConfig

An object specifying the format that the model must output.

Configuring { "type": "json_schema" } enables Structured Outputs, which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

The default format is { "type": "text" } with no additional options.

Not recommended for gpt-4o and newer models:

Setting to { "type": "json_object" } enables the older JSON mode, which ensures the message the model generates is valid JSON. Using json_schema is preferred for models that support it.

Accepts one of the following:

class ResponseFormatText { type }

Default response format. Used to generate text responses.

type: :text

The type of response format being defined. Always text.

class ResponseFormatTextJSONSchemaConfig { name, schema, type, 2 more }

JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

schema: Hash[Symbol, untyped]

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

type: :json_schema

The type of response format being defined. Always json_schema.

description: String

A description of what the response format is for, used by the model to determine how to respond in the format.

strict: bool

class ResponseFormatJSONObject { type }

type: :json_object

The type of response format being defined. Always json_object.

tools: Array[Tool]

An array of tools the model may call while generating a response. You can specify which tool to use by setting the tool_choice parameter.

The two categories of tools you can provide the model are:

Built-in tools: Tools that are provided by OpenAI that extend the model's capabilities, like web search or file search. Learn more about built-in tools.
Function calls (custom tools): Functions that are defined by you, enabling the model to call your own code. Learn more about function calling.

Accepts one of the following:

class FunctionTool { name, parameters, strict, 2 more }

Defines a function in your own code the model can choose to call. Learn more about function calling.

The name of the function to call.

parameters: Hash[Symbol, untyped]

A JSON schema object describing the parameters of the function.

strict: bool

Whether to enforce strict parameter validation. Default true.

type: :function

The type of the function tool. Always function.

description: String

A description of the function. Used by the model to determine whether or not to call the function.

class FileSearchTool { type, vector_store_ids, filters, 2 more }

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: :file_search

The type of the file search tool. Always file_search.

vector_store_ids: Array[String]

The IDs of the vector stores to search.

filters: ComparisonFilter { key, type, value } | CompoundFilter { filters, type }

A filter to apply.

Accepts one of the following:

class ComparisonFilter { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: String

The key to compare against the value.

type: :eq | :ne | :gt | 3 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

Accepts one of the following:

:eq

:ne

:gt

:gte

:lt

:lte

value: String | Float | bool | Array[String | Float]

The value to compare against the attribute key; supports string, number, or boolean types.

Accepts one of the following:

String

Float

bool

Array[String | Float]

Accepts one of the following:

String

Float

class CompoundFilter { filters, type }

Combine multiple filters using and or or.

filters: Array[ComparisonFilter { key, type, value } | untyped]

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

Accepts one of the following:

class ComparisonFilter { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: String

The key to compare against the value.

type: :eq | :ne | :gt | 3 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

Accepts one of the following:

:eq

:ne

:gt

:gte

:lt

:lte

value: String | Float | bool | Array[String | Float]

The value to compare against the attribute key; supports string, number, or boolean types.

Accepts one of the following:

String

Float

bool

Array[String | Float]

Accepts one of the following:

String

Float

untyped

type: :and | :or

Type of operation: and or or.

Accepts one of the following:

:and

:or

max_num_results: Integer

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: { hybrid_search, ranker, score_threshold}

Ranking options for search.

hybrid_search: { embedding_weight, text_weight}

Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled.

embedding_weight: Float

The weight of the embedding in the reciprocal ranking fusion.

text_weight: Float

The weight of the text in the reciprocal ranking fusion.

ranker: :auto | :"default-2024-11-15"

The ranker to use for the file search.

Accepts one of the following:

:auto

:"default-2024-11-15"

score_threshold: Float

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

class ComputerTool { display_height, display_width, environment, type }

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: Integer

The height of the computer display.

display_width: Integer

The width of the computer display.

environment: :windows | :mac | :linux | 2 more

The type of computer environment to control.

Accepts one of the following:

:windows

:mac

:linux

:ubuntu

:browser

type: :computer_use_preview

The type of the computer use tool. Always computer_use_preview.

class WebSearchTool { type, filters, search_context_size, user_location }

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: :web_search | :web_search_2025_08_26

The type of the web search tool. One of web_search or web_search_2025_08_26.

Accepts one of the following:

:web_search

:web_search_2025_08_26

filters: { allowed_domains}

Filters for the search.

allowed_domains: Array[String]

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: :low | :medium | :high

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

Accepts one of the following:

:low

:medium

:high

user_location: { city, country, region, 2 more}

The approximate location of the user.

city: String

Free text input for the city of the user, e.g. San Francisco.

country: String

The two-letter ISO country code of the user, e.g. US.

region: String

Free text input for the region of the user, e.g. California.

timezone: String

The IANA timezone of the user, e.g. America/Los_Angeles.

type: :approximate

The type of location approximation. Always approximate.

class Mcp { server_label, type, allowed_tools, 6 more }

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: String

A label for this MCP server, used to identify it in tool calls.

type: :mcp

The type of the MCP tool. Always mcp.

allowed_tools: Array[String] | { read_only, tool_names}

List of allowed tool names or a filter object.

Accepts one of the following:

Array[String]

A string array of allowed tool names

class McpToolFilter { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: bool

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: Array[String]

List of allowed tool names.

authorization: String

An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

connector_id: :connector_dropbox | :connector_gmail | :connector_googlecalendar | 5 more

Identifier for service connectors, like those available in ChatGPT. One of server_url or connector_id must be provided. Learn more about service connectors here.

Currently supported connector_id values are:

Dropbox: connector_dropbox
Gmail: connector_gmail
Google Calendar: connector_googlecalendar
Google Drive: connector_googledrive
Microsoft Teams: connector_microsoftteams
Outlook Calendar: connector_outlookcalendar
Outlook Email: connector_outlookemail
SharePoint: connector_sharepoint

Accepts one of the following:

:connector_dropbox

:connector_gmail

:connector_googlecalendar

:connector_googledrive

:connector_microsoftteams

:connector_outlookcalendar

:connector_outlookemail

:connector_sharepoint

headers: Hash[Symbol, String]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: { always, never} | :always | :never

Specify which of the MCP server's tools require approval.

Accepts one of the following:

class McpToolApprovalFilter { always, never }

Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: { read_only, tool_names}

A filter object to specify which tools are allowed.

read_only: bool

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: Array[String]

List of allowed tool names.

never: { read_only, tool_names}

A filter object to specify which tools are allowed.

read_only: bool

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: Array[String]

List of allowed tool names.

McpToolApprovalSetting = :always | :never

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

Accepts one of the following:

:always

:never

server_description: String

Optional description of the MCP server, used to provide more context.

server_url: String

The URL for the MCP server. One of server_url or connector_id must be provided.

class CodeInterpreter { container, type }

A tool that runs Python code to help generate a response to a prompt.

container: String | { type, file_ids, memory_limit}

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

Accepts one of the following:

String

The container ID.

class CodeInterpreterToolAuto { type, file_ids, memory_limit }

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: :auto

Always auto.

file_ids: Array[String]

An optional list of uploaded files to make available to your code.

memory_limit: :"1g" | :"4g" | :"16g" | :"64g"

The memory limit for the code interpreter container.

Accepts one of the following:

:"1g"

:"4g"

:"16g"

:"64g"

type: :code_interpreter

The type of the code interpreter tool. Always code_interpreter.

class ImageGeneration { type, action, background, 9 more }

A tool that generates images using the GPT image models.

type: :image_generation

The type of the image generation tool. Always image_generation.

action: :generate | :edit | :auto

Whether to generate a new image or edit an existing image. Default: auto.

Accepts one of the following:

:generate

:edit

:auto

background: :transparent | :opaque | :auto

Background type for the generated image. One of transparent, opaque, or auto. Default: auto.

Accepts one of the following:

:transparent

:opaque

:auto

input_fidelity: :high | :low

Control how much effort the model will exert to match the style and features, especially facial features, of input images. This parameter is only supported for gpt-image-1 and gpt-image-1.5 and later models, unsupported for gpt-image-1-mini. Supports high and low. Defaults to low.

Accepts one of the following:

:high

:low

input_image_mask: { file_id, image_url}

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: String

File ID for the mask image.

image_url: String

Base64-encoded mask image.

model: String | :"gpt-image-1" | :"gpt-image-1-mini" | :"gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

Accepts one of the following:

String

:"gpt-image-1" | :"gpt-image-1-mini" | :"gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

Accepts one of the following:

:"gpt-image-1"

:"gpt-image-1-mini"

:"gpt-image-1.5"

moderation: :auto | :low

Moderation level for the generated image. Default: auto.

Accepts one of the following:

:auto

:low

output_compression: Integer

Compression level for the output image. Default: 100.

minimum0

maximum100

output_format: :png | :webp | :jpeg

The output format of the generated image. One of png, webp, or jpeg. Default: png.

Accepts one of the following:

:png

:webp

:jpeg

partial_images: Integer

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0

maximum3

quality: :low | :medium | :high | :auto

The quality of the generated image. One of low, medium, high, or auto. Default: auto.

Accepts one of the following:

:low

:medium

:high

:auto

size: :"1024x1024" | :"1024x1536" | :"1536x1024" | :auto

The size of the generated image. One of 1024x1024, 1024x1536, 1536x1024, or auto. Default: auto.

Accepts one of the following:

:"1024x1024"

:"1024x1536"

:"1536x1024"

:auto

class LocalShell { type }

A tool that allows the model to execute shell commands in a local environment.

type: :local_shell

The type of the local shell tool. Always local_shell.

class FunctionShellTool { type }

A tool that allows the model to execute shell commands.

type: :shell

The type of the shell tool. Always shell.

class CustomTool { name, type, description, format_ }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: :custom

The type of the custom tool. Always custom.

description: String

Optional description of the custom tool, used to provide more context.

format_: CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

Accepts one of the following:

class Text { type }

Unconstrained free-form text.

type: :text

Unconstrained text format. Always text.

class Grammar { definition, syntax, type }

A grammar defined by the user.

definition: String

The grammar definition.

syntax: :lark | :regex

The syntax of the grammar definition. One of lark or regex.

Accepts one of the following:

:lark

:regex

type: :grammar

Grammar format. Always grammar.

class WebSearchPreviewTool { type, search_context_size, user_location }

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: :web_search_preview | :web_search_preview_2025_03_11

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

Accepts one of the following:

:web_search_preview

:web_search_preview_2025_03_11

search_context_size: :low | :medium | :high

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

Accepts one of the following:

:low

:medium

:high

user_location: { type, city, country, 2 more}

The user's location.

type: :approximate

The type of location approximation. Always approximate.

city: String

Free text input for the city of the user, e.g. San Francisco.

country: String

The two-letter ISO country code of the user, e.g. US.

region: String

Free text input for the region of the user, e.g. California.

timezone: String

The IANA timezone of the user, e.g. America/Los_Angeles.

class ApplyPatchTool { type }

Allows the assistant to create, delete, or update files using unified diffs.

type: :apply_patch

The type of the tool. Always apply_patch.

top_p: Float

An alternative to temperature for nucleus sampling; 1.0 includes all tokens.

error: EvalAPIError { code, message }

An object representing an error response from the Eval API.

code: String

The error code.

message: String

The error message.

eval_id: String

The identifier of the associated evaluation.

metadata: Metadata

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

model: String

The model that is evaluated, if applicable.

The name of the evaluation run.

object: :"eval.run"

The type of the object. Always "eval.run".

per_model_usage: Array[{ cached_tokens, completion_tokens, invocation_count, 3 more}]

Usage statistics for each model during the evaluation run.

cached_tokens: Integer

The number of tokens retrieved from cache.

completion_tokens: Integer

The number of completion tokens generated.

invocation_count: Integer

The number of invocations.

model_name: String

The name of the model.

prompt_tokens: Integer

The number of prompt tokens used.

total_tokens: Integer

The total number of tokens used.

per_testing_criteria_results: Array[{ failed, passed, testing_criteria}]

Results per testing criteria applied during the evaluation run.

failed: Integer

Number of tests failed for this criteria.

passed: Integer

Number of tests passed for this criteria.

testing_criteria: String

A description of the testing criteria.

report_url: String

The URL to the rendered evaluation run report on the UI dashboard.

result_counts: { errored, failed, passed, total}

Counters summarizing the outcomes of the evaluation run.

errored: Integer

Number of output items that resulted in an error.

failed: Integer

Number of output items that failed to pass the evaluation.

passed: Integer

Number of output items that passed the evaluation.

total: Integer

Total number of executed output items.

status: String

The status of the evaluation run.

Get an eval run

require "openai"

openai = OpenAI::Client.new(api_key: "My API Key")

run = openai.evals.runs.retrieve("run_id", eval_id: "eval_id")

puts(run)

{
  "id": "id",
  "created_at": 0,
  "data_source": {
    "source": {
      "content": [
        {
          "item": {
            "foo": "bar"
          },
          "sample": {
            "foo": "bar"
          }
        }
      ],
      "type": "file_content"
    },
    "type": "jsonl"
  },
  "error": {
    "code": "code",
    "message": "message"
  },
  "eval_id": "eval_id",
  "metadata": {
    "foo": "string"
  },
  "model": "model",
  "name": "name",
  "object": "eval.run",
  "per_model_usage": [
    {
      "cached_tokens": 0,
      "completion_tokens": 0,
      "invocation_count": 0,
      "model_name": "model_name",
      "prompt_tokens": 0,
      "total_tokens": 0
    }
  ],
  "per_testing_criteria_results": [
    {
      "failed": 0,
      "passed": 0,
      "testing_criteria": "testing_criteria"
    }
  ],
  "report_url": "report_url",
  "result_counts": {
    "errored": 0,
    "failed": 0,
    "passed": 0,
    "total": 0
  },
  "status": "status"
}

Returns Examples

{
  "id": "id",
  "created_at": 0,
  "data_source": {
    "source": {
      "content": [
        {
          "item": {
            "foo": "bar"
          },
          "sample": {
            "foo": "bar"
          }
        }
      ],
      "type": "file_content"
    },
    "type": "jsonl"
  },
  "error": {
    "code": "code",
    "message": "message"
  },
  "eval_id": "eval_id",
  "metadata": {
    "foo": "string"
  },
  "model": "model",
  "name": "name",
  "object": "eval.run",
  "per_model_usage": [
    {
      "cached_tokens": 0,
      "completion_tokens": 0,
      "invocation_count": 0,
      "model_name": "model_name",
      "prompt_tokens": 0,
      "total_tokens": 0
    }
  ],
  "per_testing_criteria_results": [
    {
      "failed": 0,
      "passed": 0,
      "testing_criteria": "testing_criteria"
    }
  ],
  "report_url": "report_url",
  "result_counts": {
    "errored": 0,
    "failed": 0,
    "passed": 0,
    "total": 0
  },
  "status": "status"
}

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Get an eval run

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Get an eval run

Returns Examples