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API Reference
Beta
Threads
Runs

Retrieve run

Deprecated
Run beta().threads().runs().retrieve(RunRetrieveParamsparams, RequestOptionsrequestOptions = RequestOptions.none())
GET/threads/{thread_id}/runs/{run_id}

Retrieves a run.

ParametersExpand Collapse
RunRetrieveParams params
String threadId
Optional<String> runId
ReturnsExpand Collapse
class Run:

Represents an execution run on a thread.

String id

The identifier, which can be referenced in API endpoints.

String assistantId

The ID of the assistant used for execution of this run.

Optional<Long> cancelledAt

The Unix timestamp (in seconds) for when the run was cancelled.

Optional<Long> completedAt

The Unix timestamp (in seconds) for when the run was completed.

long createdAt

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

Optional<Long> expiresAt

The Unix timestamp (in seconds) for when the run will expire.

Optional<Long> failedAt

The Unix timestamp (in seconds) for when the run failed.

Optional<IncompleteDetails> incompleteDetails

Details on why the run is incomplete. Will be null if the run is not incomplete.

Optional<Reason> reason

The reason why the run is incomplete. This will point to which specific token limit was reached over the course of the run.

Accepts one of the following:
MAX_COMPLETION_TOKENS("max_completion_tokens")
MAX_PROMPT_TOKENS("max_prompt_tokens")
String instructions

The instructions that the assistant used for this run.

Optional<LastError> lastError

The last error associated with this run. Will be null if there are no errors.

Code code

One of server_error, rate_limit_exceeded, or invalid_prompt.

Accepts one of the following:
SERVER_ERROR("server_error")
RATE_LIMIT_EXCEEDED("rate_limit_exceeded")
INVALID_PROMPT("invalid_prompt")
String message

A human-readable description of the error.

Optional<Long> maxCompletionTokens

The maximum number of completion tokens specified to have been used over the course of the run.

minimum256
Optional<Long> maxPromptTokens

The maximum number of prompt tokens specified to have been used over the course of the run.

minimum256
Optional<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.

String model

The model that the assistant used for this run.

JsonValue; object_ "thread.run"constant"thread.run"constant

The object type, which is always thread.run.

boolean parallelToolCalls

Whether to enable parallel function calling during tool use.

Optional<RequiredAction> requiredAction

Details on the action required to continue the run. Will be null if no action is required.

SubmitToolOutputs submitToolOutputs

Details on the tool outputs needed for this run to continue.

List<RequiredActionFunctionToolCall> toolCalls

A list of the relevant tool calls.

String id

The ID of the tool call. This ID must be referenced when you submit the tool outputs in using the Submit tool outputs to run endpoint.

Function function

The function definition.

String arguments

The arguments that the model expects you to pass to the function.

String name

The name of the function.

JsonValue; type "function"constant"function"constant

The type of tool call the output is required for. For now, this is always function.

JsonValue; type "submit_tool_outputs"constant"submit_tool_outputs"constant

For now, this is always submit_tool_outputs.

Optional<AssistantResponseFormatOption> responseFormat

Specifies the format that the model must output. Compatible with GPT-4o, GPT-4 Turbo, and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.

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 JSON mode, which ensures the message the model generates is valid JSON.

Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

Accepts one of the following:
JsonValue;
class ResponseFormatText:

Default response format. Used to generate text responses.

JsonValue; type "text"constant"text"constant

The type of response format being defined. Always text.

class ResponseFormatJsonObject:

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.

JsonValue; type "json_object"constant"json_object"constant

The type of response format being defined. Always json_object.

class ResponseFormatJsonSchema:

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

JsonSchema jsonSchema

Structured Outputs configuration options, including a JSON Schema.

String name

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.

Optional<String> description

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

Optional<Schema> schema

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

Optional<Boolean> strict

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.

JsonValue; type "json_schema"constant"json_schema"constant

The type of response format being defined. Always json_schema.

Optional<Long> startedAt

The Unix timestamp (in seconds) for when the run was started.

RunStatus status

The status of the run, which can be either queued, in_progress, requires_action, cancelling, cancelled, failed, completed, incomplete, or expired.

Accepts one of the following:
QUEUED("queued")
IN_PROGRESS("in_progress")
REQUIRES_ACTION("requires_action")
CANCELLING("cancelling")
CANCELLED("cancelled")
FAILED("failed")
COMPLETED("completed")
INCOMPLETE("incomplete")
EXPIRED("expired")
String threadId

The ID of the thread that was executed on as a part of this run.

Optional<AssistantToolChoiceOption> toolChoice

Controls which (if any) tool is called by the model. none means the model will not call any tools and instead generates a message. auto is the default value and means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools before responding to the user. Specifying a particular tool like {"type": "file_search"} or {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.

Accepts one of the following:
Auto
Accepts one of the following:
NONE("none")
AUTO("auto")
REQUIRED("required")
class AssistantToolChoice:

Specifies a tool the model should use. Use to force the model to call a specific tool.

Type type

The type of the tool. If type is function, the function name must be set

Accepts one of the following:
FUNCTION("function")
CODE_INTERPRETER("code_interpreter")
FILE_SEARCH("file_search")
Optional<AssistantToolChoiceFunction> function
String name

The name of the function to call.

List<AssistantTool> tools

The list of tools that the assistant used for this run.

Accepts one of the following:
class CodeInterpreterTool:
JsonValue; type "code_interpreter"constant"code_interpreter"constant

The type of tool being defined: code_interpreter

class FileSearchTool:
JsonValue; type "file_search"constant"file_search"constant

The type of tool being defined: file_search

Accepts one of the following:
class FunctionTool:
String name

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.

Optional<String> description

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

Optional<FunctionParameters> parameters

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.

Optional<Boolean> strict

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.

JsonValue; type "function"constant"function"constant

The type of tool being defined: function

Optional<TruncationStrategy> truncationStrategy

Controls for how a thread will be truncated prior to the run. Use this to control the initial context window of the run.

Type type

The truncation strategy to use for the thread. The default is auto. If set to last_messages, the thread will be truncated to the n most recent messages in the thread. When set to auto, messages in the middle of the thread will be dropped to fit the context length of the model, max_prompt_tokens.

Accepts one of the following:
AUTO("auto")
LAST_MESSAGES("last_messages")
Optional<Long> lastMessages

The number of most recent messages from the thread when constructing the context for the run.

minimum1
Optional<Usage> usage

Usage statistics related to the run. This value will be null if the run is not in a terminal state (i.e. in_progress, queued, etc.).

long completionTokens

Number of completion tokens used over the course of the run.

long promptTokens

Number of prompt tokens used over the course of the run.

long totalTokens

Total number of tokens used (prompt + completion).

Optional<Double> temperature

The sampling temperature used for this run. If not set, defaults to 1.

Optional<Double> topP

The nucleus sampling value used for this run. If not set, defaults to 1.

Retrieve run

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.threads.runs.Run;
import com.openai.models.beta.threads.runs.RunRetrieveParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        RunRetrieveParams params = RunRetrieveParams.builder()
            .threadId("thread_id")
            .runId("run_id")
            .build();
        Run run = client.beta().threads().runs().retrieve(params);
    }
}
{
  "id": "id",
  "assistant_id": "assistant_id",
  "cancelled_at": 0,
  "completed_at": 0,
  "created_at": 0,
  "expires_at": 0,
  "failed_at": 0,
  "incomplete_details": {
    "reason": "max_completion_tokens"
  },
  "instructions": "instructions",
  "last_error": {
    "code": "server_error",
    "message": "message"
  },
  "max_completion_tokens": 256,
  "max_prompt_tokens": 256,
  "metadata": {
    "foo": "string"
  },
  "model": "model",
  "object": "thread.run",
  "parallel_tool_calls": true,
  "required_action": {
    "submit_tool_outputs": {
      "tool_calls": [
        {
          "id": "id",
          "function": {
            "arguments": "arguments",
            "name": "name"
          },
          "type": "function"
        }
      ]
    },
    "type": "submit_tool_outputs"
  },
  "response_format": "auto",
  "started_at": 0,
  "status": "queued",
  "thread_id": "thread_id",
  "tool_choice": "none",
  "tools": [
    {
      "type": "code_interpreter"
    }
  ],
  "truncation_strategy": {
    "type": "auto",
    "last_messages": 1
  },
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0
  },
  "temperature": 0,
  "top_p": 0
}
Returns Examples
{
  "id": "id",
  "assistant_id": "assistant_id",
  "cancelled_at": 0,
  "completed_at": 0,
  "created_at": 0,
  "expires_at": 0,
  "failed_at": 0,
  "incomplete_details": {
    "reason": "max_completion_tokens"
  },
  "instructions": "instructions",
  "last_error": {
    "code": "server_error",
    "message": "message"
  },
  "max_completion_tokens": 256,
  "max_prompt_tokens": 256,
  "metadata": {
    "foo": "string"
  },
  "model": "model",
  "object": "thread.run",
  "parallel_tool_calls": true,
  "required_action": {
    "submit_tool_outputs": {
      "tool_calls": [
        {
          "id": "id",
          "function": {
            "arguments": "arguments",
            "name": "name"
          },
          "type": "function"
        }
      ]
    },
    "type": "submit_tool_outputs"
  },
  "response_format": "auto",
  "started_at": 0,
  "status": "queued",
  "thread_id": "thread_id",
  "tool_choice": "none",
  "tools": [
    {
      "type": "code_interpreter"
    }
  ],
  "truncation_strategy": {
    "type": "auto",
    "last_messages": 1
  },
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0
  },
  "temperature": 0,
  "top_p": 0
}