Threads

Create thread

$ openai beta:threads create

post /threads

Create a thread.

Parameters

• --message: optional array of object { content, role, attachments, metadata }

  A list of messages to start the thread with.

• --metadata: optional map[string]

  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.

• --tool-resources: optional object { code_interpreter, file_search }

  A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

Returns

• thread: object { id, created_at, metadata, 2 more }

  Represents a thread that contains messages.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • created_at: number

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

  • metadata: map[string]

    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.

  • object: "thread"

    The object type, which is always thread.

  • tool_resources: object { code_interpreter, file_search }

    A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

    • code_interpreter: optional object { file_ids }

      • file_ids: optional array of string

        A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool.

    • file_search: optional object { vector_store_ids }

      • vector_store_ids: optional array of string

        The vector store attached to this thread. There can be a maximum of 1 vector store attached to the thread.

Example

openai beta:threads create \
  --api-key 'My API Key'

Response

{
  "id": "id",
  "created_at": 0,
  "metadata": {
    "foo": "string"
  },
  "object": "thread",
  "tool_resources": {
    "code_interpreter": {
      "file_ids": [
        "string"
      ]
    },
    "file_search": {
      "vector_store_ids": [
        "string"
      ]
    }
  }
}

Create thread and run

$ openai beta:threads create-and-run

post /threads/runs

Create a thread and run it in one request.

Parameters

• --assistant-id: string

  The ID of the assistant to use to execute this run.

• --instructions: optional string

  Override the default system message of the assistant. This is useful for modifying the behavior on a per-run basis.

• --max-completion-tokens: optional number

  The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete. See incomplete_details for more info.

• --max-prompt-tokens: optional number

  The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status incomplete. See incomplete_details for more info.

• --metadata: optional map[string]

  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: optional string or ChatModel

  The ID of the Model to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.

• --parallel-tool-calls: optional boolean

  Whether to enable parallel function calling during tool use.

• --response-format: optional "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

  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.

• --temperature: optional number

  What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

• --thread: optional object { messages, metadata, tool_resources }

  Options to create a new thread. If no thread is provided when running a request, an empty thread will be created.

• --tool-choice: optional "none" or "auto" or "required" or AssistantToolChoice

  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.

• --tool-resources: optional object { code_interpreter, file_search }

  A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

• --tool: optional array of AssistantTool

  Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.

• --top-p: optional number

  An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

  We generally recommend altering this or temperature but not both.

• --truncation-strategy: optional object { type, last_messages }

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

Returns

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Example

openai beta:threads create-and-run \
  --api-key 'My API Key' \
  --assistant-id assistant_id

Response

{
  "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
}

Retrieve thread

$ openai beta:threads retrieve

get /threads/{thread_id}

Retrieves a thread.

Parameters

• --thread-id: string

  The ID of the thread to retrieve.

Returns

• thread: object { id, created_at, metadata, 2 more }

  Represents a thread that contains messages.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • created_at: number

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

  • metadata: map[string]

    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.

  • object: "thread"

    The object type, which is always thread.

  • tool_resources: object { code_interpreter, file_search }

    A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

    • code_interpreter: optional object { file_ids }

      • file_ids: optional array of string

        A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool.

    • file_search: optional object { vector_store_ids }

      • vector_store_ids: optional array of string

        The vector store attached to this thread. There can be a maximum of 1 vector store attached to the thread.

Example

openai beta:threads retrieve \
  --api-key 'My API Key' \
  --thread-id thread_id

Response

{
  "id": "id",
  "created_at": 0,
  "metadata": {
    "foo": "string"
  },
  "object": "thread",
  "tool_resources": {
    "code_interpreter": {
      "file_ids": [
        "string"
      ]
    },
    "file_search": {
      "vector_store_ids": [
        "string"
      ]
    }
  }
}

Modify thread

$ openai beta:threads update

post /threads/{thread_id}

Modifies a thread.

Parameters

• --thread-id: string

  The ID of the thread to modify. Only the metadata can be modified.

• --metadata: optional map[string]

  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.

• --tool-resources: optional object { code_interpreter, file_search }

  A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

Returns

• thread: object { id, created_at, metadata, 2 more }

  Represents a thread that contains messages.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • created_at: number

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

  • metadata: map[string]

    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.

  • object: "thread"

    The object type, which is always thread.

  • tool_resources: object { code_interpreter, file_search }

    A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

    • code_interpreter: optional object { file_ids }

      • file_ids: optional array of string

        A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool.

    • file_search: optional object { vector_store_ids }

      • vector_store_ids: optional array of string

        The vector store attached to this thread. There can be a maximum of 1 vector store attached to the thread.

Example

openai beta:threads update \
  --api-key 'My API Key' \
  --thread-id thread_id

Response

{
  "id": "id",
  "created_at": 0,
  "metadata": {
    "foo": "string"
  },
  "object": "thread",
  "tool_resources": {
    "code_interpreter": {
      "file_ids": [
        "string"
      ]
    },
    "file_search": {
      "vector_store_ids": [
        "string"
      ]
    }
  }
}

Delete thread

$ openai beta:threads delete

delete /threads/{thread_id}

Delete a thread.

Parameters

• --thread-id: string

  The ID of the thread to delete.

Returns

• thread_deleted: object { id, deleted, object }

  • id: string

  • deleted: boolean

  • object: "thread.deleted"

Example

openai beta:threads delete \
  --api-key 'My API Key' \
  --thread-id thread_id

Response

{
  "id": "id",
  "deleted": true,
  "object": "thread.deleted"
}

Domain Types

Assistant Response Format Option

• assistant_response_format_option: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

  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.

  • union_member_0: "auto"

    auto is the default value

  • response_format_text: object { type }

    Default response format. Used to generate text responses.

    • type: "text"

      The type of response format being defined. Always text.

  • response_format_json_object: object { 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.

  • response_format_json_schema: object { json_schema, type }

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

    • json_schema: object { name, description, schema, strict }

      Structured Outputs configuration options, including a JSON Schema.

      • name: string

        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: optional string

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

      • schema: optional map[unknown]

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

      • strict: optional boolean

        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.

Assistant Tool Choice

• assistant_tool_choice: object { type, function }

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

  • type: "function" or "code_interpreter" or "file_search"

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

    • "function"

    • "code_interpreter"

    • "file_search"

  • function: optional object { name }

    • name: string

      The name of the function to call.

Assistant Tool Choice Function

• assistant_tool_choice_function: object { name }

  • name: string

    The name of the function to call.

Assistant Tool Choice Option

• assistant_tool_choice_option: "none" or "auto" or "required" or AssistantToolChoice

  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.

  • Auto: "none" or "auto" or "required"

    none means the model will not call any tools and instead generates a message. auto 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.

    • "none"

    • "auto"

    • "required"

  • assistant_tool_choice: object { type, function }

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

    • type: "function" or "code_interpreter" or "file_search"

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

      • "function"

      • "code_interpreter"

      • "file_search"

    • function: optional object { name }

      • name: string

        The name of the function to call.

Thread

• thread: object { id, created_at, metadata, 2 more }

  Represents a thread that contains messages.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • created_at: number

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

  • metadata: map[string]

    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.

  • object: "thread"

    The object type, which is always thread.

  • tool_resources: object { code_interpreter, file_search }

    A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

    • code_interpreter: optional object { file_ids }

      • file_ids: optional array of string

        A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool.

    • file_search: optional object { vector_store_ids }

      • vector_store_ids: optional array of string

        The vector store attached to this thread. There can be a maximum of 1 vector store attached to the thread.

Thread Deleted

• thread_deleted: object { id, deleted, object }

  • id: string

  • deleted: boolean

  • object: "thread.deleted"

Runs

List runs

$ openai beta:threads:runs list

get /threads/{thread_id}/runs

Returns a list of runs belonging to a thread.

Parameters

• --thread-id: string

  The ID of the thread the run belongs to.

• --after: optional string

  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.

• --before: optional string

  A cursor for use in pagination. before is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.

• --limit: optional number

  A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.

• --order: optional "asc" or "desc"

  Sort order by the created_at timestamp of the objects. asc for ascending order and desc for descending order.

Returns

• ListRunsResponse: object { data, first_id, has_more, 2 more }

  • data: array of Run

    • id: string

      The identifier, which can be referenced in API endpoints.

    • assistant_id: string

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

    • cancelled_at: number

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

    • completed_at: number

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

    • created_at: number

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

    • expires_at: number

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

    • failed_at: number

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

    • incomplete_details: object { reason }

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

      • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

        • "max_completion_tokens"

        • "max_prompt_tokens"

    • instructions: string

      The instructions that the assistant used for this run.

    • last_error: object { code, message }

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

      • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

        One of server_error, rate_limit_exceeded, or invalid_prompt.

        • "server_error"

        • "rate_limit_exceeded"

        • "invalid_prompt"

      • message: string

        A human-readable description of the error.

    • max_completion_tokens: number

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

    • max_prompt_tokens: number

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

    • metadata: map[string]

      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

      The model that the assistant used for this run.

    • object: "thread.run"

      The object type, which is always thread.run.

    • parallel_tool_calls: boolean

      Whether to enable parallel function calling during tool use.

    • required_action: object { submit_tool_outputs, type }

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

      • submit_tool_outputs: object { tool_calls }

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

        • tool_calls: array of RequiredActionFunctionToolCall

          A list of the relevant tool calls.

          • id: string

            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: object { arguments, name }

            The function definition.

            • arguments: string

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

            • name: string

              The name of the function.

          • type: "function"

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

      • type: "submit_tool_outputs"

        For now, this is always submit_tool_outputs.

    • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

      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.

      • union_member_0: "auto"

        auto is the default value

      • response_format_text: object { type }

        Default response format. Used to generate text responses.

        • type: "text"

          The type of response format being defined. Always text.

      • response_format_json_object: object { 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.

      • response_format_json_schema: object { json_schema, type }

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

        • json_schema: object { name, description, schema, strict }

          Structured Outputs configuration options, including a JSON Schema.

          • name: string

            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: optional string

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

          • schema: optional map[unknown]

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

          • strict: optional boolean

            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.

    • started_at: number

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

    • status: "queued" or "in_progress" or "requires_action" or 6 more

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

      • "queued"

      • "in_progress"

      • "requires_action"

      • "cancelling"

      • "cancelled"

      • "failed"

      • "completed"

      • "incomplete"

      • "expired"

    • thread_id: string

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

    • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

      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.

      • Auto: "none" or "auto" or "required"

        none means the model will not call any tools and instead generates a message. auto 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.

        • "none"

        • "auto"

        • "required"

      • assistant_tool_choice: object { type, function }

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

        • type: "function" or "code_interpreter" or "file_search"

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

          • "function"

          • "code_interpreter"

          • "file_search"

        • function: optional object { name }

          • name: string

            The name of the function to call.

    • tools: array of AssistantTool

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

      • code_interpreter_tool: object { type }

        • type: "code_interpreter"

          The type of tool being defined: code_interpreter

      • file_search_tool: object { type, file_search }

        • type: "file_search"

          The type of tool being defined: file_search

        • file_search: optional object { max_num_results, ranking_options }

          Overrides for the file search tool.

          • max_num_results: optional number

            The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

            Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

          • ranking_options: optional object { score_threshold, ranker }

            The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

            See the file search tool documentation for more information.

            • score_threshold: number

              The score threshold for the file search. All values must be a floating point number between 0 and 1.

            • ranker: optional "auto" or "default_2024_08_21"

              The ranker to use for the file search. If not specified will use the auto ranker.

              • "auto"

              • "default_2024_08_21"

      • function_tool: object { function, type }

        • function: object { name, description, parameters, strict }

          • name: string

            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: optional string

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

          • parameters: optional map[unknown]

            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: optional boolean

            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 tool being defined: function

    • truncation_strategy: object { type, last_messages }

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

      • type: "auto" or "last_messages"

        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.

        • "auto"

        • "last_messages"

      • last_messages: optional number

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

    • usage: object { completion_tokens, prompt_tokens, total_tokens }

      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.).

      • completion_tokens: number

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

      • prompt_tokens: number

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

      • total_tokens: number

        Total number of tokens used (prompt + completion).

    • temperature: optional number

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

    • top_p: optional number

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

  • first_id: string

  • has_more: boolean

  • last_id: string

  • object: string

Example

openai beta:threads:runs list \
  --api-key 'My API Key' \
  --thread-id thread_id

Response

{
  "data": [
    {
      "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
    }
  ],
  "first_id": "run_abc123",
  "has_more": false,
  "last_id": "run_abc456",
  "object": "list"
}

Create run

$ openai beta:threads:runs create

post /threads/{thread_id}/runs

Create a run.

Parameters

• --thread-id: string

  Path param: The ID of the thread to run.

• --assistant-id: string

  Body param: The ID of the assistant to use to execute this run.

• --include: optional array of RunStepInclude

  Query param: A list of additional fields to include in the response. Currently the only supported value is step_details.tool_calls[*].file_search.results[*].content to fetch the file search result content.

  See the file search tool documentation for more information.

• --additional-instructions: optional string

  Body param: Appends additional instructions at the end of the instructions for the run. This is useful for modifying the behavior on a per-run basis without overriding other instructions.

• --additional-message: optional array of object { content, role, attachments, metadata }

  Body param: Adds additional messages to the thread before creating the run.

• --instructions: optional string

  Body param: Overrides the instructions of the assistant. This is useful for modifying the behavior on a per-run basis.

• --max-completion-tokens: optional number

  Body param: The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete. See incomplete_details for more info.

• --max-prompt-tokens: optional number

  Body param: The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status incomplete. See incomplete_details for more info.

• --metadata: optional map[string]

  Body param: 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: optional string or ChatModel

  Body param: The ID of the Model to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.

• --parallel-tool-calls: optional boolean

  Body param: Whether to enable parallel function calling during tool use.

• --reasoning-effort: optional "none" or "minimal" or "low" or 3 more

  Body param: 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.

• --response-format: optional "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

  Body param: 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.

• --temperature: optional number

  Body param: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

• --tool-choice: optional "none" or "auto" or "required" or AssistantToolChoice

  Body param: 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.

• --tool: optional array of AssistantTool

  Body param: Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.

• --top-p: optional number

  Body param: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

  We generally recommend altering this or temperature but not both.

• --truncation-strategy: optional object { type, last_messages }

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

Returns

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Example

openai beta:threads:runs create \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --assistant-id assistant_id

Response

{
  "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
}

Retrieve run

$ openai beta:threads:runs retrieve

get /threads/{thread_id}/runs/{run_id}

Retrieves a run.

Parameters

• --thread-id: string

  The ID of the thread that was run.

• --run-id: string

  The ID of the run to retrieve.

Returns

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Example

openai beta:threads:runs retrieve \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --run-id run_id

Response

{
  "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
}

Modify run

$ openai beta:threads:runs update

post /threads/{thread_id}/runs/{run_id}

Modifies a run.

Parameters

• --thread-id: string

  The ID of the thread that was run.

• --run-id: string

  The ID of the run to modify.

• --metadata: optional map[string]

  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.

Returns

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Example

openai beta:threads:runs update \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --run-id run_id

Response

{
  "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
}

Submit tool outputs to run

$ openai beta:threads:runs submit-tool-outputs

post /threads/{thread_id}/runs/{run_id}/submit_tool_outputs

When a run has the status: "requires_action" and required_action.type is submit_tool_outputs, this endpoint can be used to submit the outputs from the tool calls once they're all completed. All outputs must be submitted in a single request.

Parameters

• --thread-id: string

  The ID of the thread to which this run belongs.

• --run-id: string

  The ID of the run that requires the tool output submission.

• --tool-output: array of object { output, tool_call_id }

  A list of tools for which the outputs are being submitted.

Returns

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Example

openai beta:threads:runs submit-tool-outputs \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --run-id run_id \
  --tool-output '{}'

Response

{
  "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
}

Cancel a run

$ openai beta:threads:runs cancel

post /threads/{thread_id}/runs/{run_id}/cancel

Cancels a run that is in_progress.

Parameters

• --thread-id: string

  The ID of the thread to which this run belongs.

• --run-id: string

  The ID of the run to cancel.

Returns

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Example

openai beta:threads:runs cancel \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --run-id run_id

Response

{
  "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
}

Domain Types

Required Action Function Tool Call

• required_action_function_tool_call: object { id, function, type }

  Tool call objects

  • id: string

    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: object { arguments, name }

    The function definition.

    • arguments: string

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

    • name: string

      The name of the function.

  • type: "function"

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

Run

• run: object { id, assistant_id, cancelled_at, 24 more }

  Represents an execution run on a thread.

  • id: string

    The identifier, which can be referenced in API endpoints.

  • assistant_id: string

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

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expires_at: number

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

  • failed_at: number

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

  • incomplete_details: object { reason }

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

    • reason: optional "max_completion_tokens" or "max_prompt_tokens"

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

      • "max_completion_tokens"

      • "max_prompt_tokens"

  • instructions: string

    The instructions that the assistant used for this run.

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded" or "invalid_prompt"

      One of server_error, rate_limit_exceeded, or invalid_prompt.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

    • message: string

      A human-readable description of the error.

  • max_completion_tokens: number

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

  • max_prompt_tokens: number

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

  • metadata: map[string]

    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

    The model that the assistant used for this run.

  • object: "thread.run"

    The object type, which is always thread.run.

  • parallel_tool_calls: boolean

    Whether to enable parallel function calling during tool use.

  • required_action: object { submit_tool_outputs, type }

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

    • submit_tool_outputs: object { tool_calls }

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

      • tool_calls: array of RequiredActionFunctionToolCall

        A list of the relevant tool calls.

        • id: string

          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: object { arguments, name }

          The function definition.

          • arguments: string

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

          • name: string

            The name of the function.

        • type: "function"

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

    • type: "submit_tool_outputs"

      For now, this is always submit_tool_outputs.

  • response_format: "auto" or ResponseFormatText or ResponseFormatJSONObject or ResponseFormatJSONSchema

    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.

    • union_member_0: "auto"

      auto is the default value

    • response_format_text: object { type }

      Default response format. Used to generate text responses.

      • type: "text"

        The type of response format being defined. Always text.

    • response_format_json_object: object { 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.

    • response_format_json_schema: object { json_schema, type }

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

      • json_schema: object { name, description, schema, strict }

        Structured Outputs configuration options, including a JSON Schema.

        • name: string

          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: optional string

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

        • schema: optional map[unknown]

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

        • strict: optional boolean

          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.

  • started_at: number

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

  • status: "queued" or "in_progress" or "requires_action" or 6 more

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

    • "queued"

    • "in_progress"

    • "requires_action"

    • "cancelling"

    • "cancelled"

    • "failed"

    • "completed"

    • "incomplete"

    • "expired"

  • thread_id: string

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

  • tool_choice: "none" or "auto" or "required" or AssistantToolChoice

    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.

    • Auto: "none" or "auto" or "required"

      none means the model will not call any tools and instead generates a message. auto 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.

      • "none"

      • "auto"

      • "required"

    • assistant_tool_choice: object { type, function }

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

      • type: "function" or "code_interpreter" or "file_search"

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

        • "function"

        • "code_interpreter"

        • "file_search"

      • function: optional object { name }

        • name: string

          The name of the function to call.

  • tools: array of AssistantTool

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

    • code_interpreter_tool: object { type }

      • type: "code_interpreter"

        The type of tool being defined: code_interpreter

    • file_search_tool: object { type, file_search }

      • type: "file_search"

        The type of tool being defined: file_search

      • file_search: optional object { max_num_results, ranking_options }

        Overrides for the file search tool.

        • max_num_results: optional number

          The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

          Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.

        • ranking_options: optional object { score_threshold, ranker }

          The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.

          See the file search tool documentation for more information.

          • score_threshold: number

            The score threshold for the file search. All values must be a floating point number between 0 and 1.

          • ranker: optional "auto" or "default_2024_08_21"

            The ranker to use for the file search. If not specified will use the auto ranker.

            • "auto"

            • "default_2024_08_21"

    • function_tool: object { function, type }

      • function: object { name, description, parameters, strict }

        • name: string

          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: optional string

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

        • parameters: optional map[unknown]

          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: optional boolean

          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 tool being defined: function

  • truncation_strategy: object { type, last_messages }

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

    • type: "auto" or "last_messages"

      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.

      • "auto"

      • "last_messages"

    • last_messages: optional number

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

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    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.).

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

  • temperature: optional number

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

  • top_p: optional number

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

Run Status

• run_status: "queued" or "in_progress" or "requires_action" or 6 more

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

  • "queued"

  • "in_progress"

  • "requires_action"

  • "cancelling"

  • "cancelled"

  • "failed"

  • "completed"

  • "incomplete"

  • "expired"

Steps

List run steps

$ openai beta:threads:runs:steps list

get /threads/{thread_id}/runs/{run_id}/steps

Returns a list of run steps belonging to a run.

Parameters

• --thread-id: string

  The ID of the thread the run and run steps belong to.

• --run-id: string

  The ID of the run the run steps belong to.

• --after: optional string

  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.

• --before: optional string

  A cursor for use in pagination. before is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.

• --include: optional array of RunStepInclude

  A list of additional fields to include in the response. Currently the only supported value is step_details.tool_calls[*].file_search.results[*].content to fetch the file search result content.

  See the file search tool documentation for more information.

• --limit: optional number

  A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.

• --order: optional "asc" or "desc"

  Sort order by the created_at timestamp of the objects. asc for ascending order and desc for descending order.

Returns

• ListRunStepsResponse: object { data, first_id, has_more, 2 more }

  • data: array of RunStep

    • id: string

      The identifier of the run step, which can be referenced in API endpoints.

    • assistant_id: string

      The ID of the assistant associated with the run step.

    • cancelled_at: number

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

    • completed_at: number

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

    • created_at: number

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

    • expired_at: number

      The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the parent run is expired.

    • failed_at: number

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

    • last_error: object { code, message }

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

      • code: "server_error" or "rate_limit_exceeded"

        One of server_error or rate_limit_exceeded.

        • "server_error"

        • "rate_limit_exceeded"

      • message: string

        A human-readable description of the error.

    • metadata: map[string]

      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.

    • object: "thread.run.step"

      The object type, which is always thread.run.step.

    • run_id: string

      The ID of the run that this run step is a part of.

    • status: "in_progress" or "cancelled" or "failed" or 2 more

      The status of the run step, which can be either in_progress, cancelled, failed, completed, or expired.

      • "in_progress"

      • "cancelled"

      • "failed"

      • "completed"

      • "expired"

    • step_details: MessageCreationStepDetails or ToolCallsStepDetails

      The details of the run step.

      • message_creation_step_details: object { message_creation, type }

        Details of the message creation by the run step.

        • message_creation: object { message_id }

          • message_id: string

            The ID of the message that was created by this run step.

        • type: "message_creation"

          Always message_creation.

      • tool_calls_step_details: object { tool_calls, type }

        Details of the tool call.

        • tool_calls: array of ToolCall

          An array of tool calls the run step was involved in. These can be associated with one of three types of tools: code_interpreter, file_search, or function.

          • code_interpreter_tool_call: object { id, code_interpreter, type }

            Details of the Code Interpreter tool call the run step was involved in.

            • id: string

              The ID of the tool call.

            • code_interpreter: object { input, outputs }

              The Code Interpreter tool call definition.

              • input: string

                The input to the Code Interpreter tool call.

              • outputs: array of object { logs, type } or object { image, type }

                The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

                • logs: object { logs, type }

                  Text output from the Code Interpreter tool call as part of a run step.

                  • logs: string

                    The text output from the Code Interpreter tool call.

                  • type: "logs"

                    Always logs.

                • image: object { image, type }

                  • image: object { file_id }

                    • file_id: string

                      The file ID of the image.

                  • type: "image"

                    Always image.

            • type: "code_interpreter"

              The type of tool call. This is always going to be code_interpreter for this type of tool call.

          • file_search_tool_call: object { id, file_search, type }

            • id: string

              The ID of the tool call object.

            • file_search: object { ranking_options, results }

              For now, this is always going to be an empty object.

              • ranking_options: optional object { ranker, score_threshold }

                The ranking options for the file search.

                • ranker: "auto" or "default_2024_08_21"

                  The ranker to use for the file search. If not specified will use the auto ranker.

                  • "auto"

                  • "default_2024_08_21"

                • score_threshold: number

                  The score threshold for the file search. All values must be a floating point number between 0 and 1.

              • results: optional array of object { file_id, file_name, score, content }

                The results of the file search.

                • file_id: string

                  The ID of the file that result was found in.

                • file_name: string

                  The name of the file that result was found in.

                • score: number

                  The score of the result. All values must be a floating point number between 0 and 1.

                • content: optional array of object { text, type }

                  The content of the result that was found. The content is only included if requested via the include query parameter.

                  • text: optional string

                    The text content of the file.

                  • type: optional "text"

                    The type of the content.

                    • "text"

            • type: "file_search"

              The type of tool call. This is always going to be file_search for this type of tool call.

          • function_tool_call: object { id, function, type }

            • id: string

              The ID of the tool call object.

            • function: object { arguments, name, output }

              The definition of the function that was called.

              • arguments: string

                The arguments passed to the function.

              • name: string

                The name of the function.

              • output: string

                The output of the function. This will be null if the outputs have not been submitted yet.

            • type: "function"

              The type of tool call. This is always going to be function for this type of tool call.

        • type: "tool_calls"

          Always tool_calls.

    • thread_id: string

      The ID of the thread that was run.

    • type: "message_creation" or "tool_calls"

      The type of run step, which can be either message_creation or tool_calls.

      • "message_creation"

      • "tool_calls"

    • usage: object { completion_tokens, prompt_tokens, total_tokens }

      Usage statistics related to the run step. This value will be null while the run step's status is in_progress.

      • completion_tokens: number

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

      • prompt_tokens: number

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

      • total_tokens: number

        Total number of tokens used (prompt + completion).

  • first_id: string

  • has_more: boolean

  • last_id: string

  • object: string

Example

openai beta:threads:runs:steps list \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --run-id run_id

Response

{
  "data": [
    {
      "id": "id",
      "assistant_id": "assistant_id",
      "cancelled_at": 0,
      "completed_at": 0,
      "created_at": 0,
      "expired_at": 0,
      "failed_at": 0,
      "last_error": {
        "code": "server_error",
        "message": "message"
      },
      "metadata": {
        "foo": "string"
      },
      "object": "thread.run.step",
      "run_id": "run_id",
      "status": "in_progress",
      "step_details": {
        "message_creation": {
          "message_id": "message_id"
        },
        "type": "message_creation"
      },
      "thread_id": "thread_id",
      "type": "message_creation",
      "usage": {
        "completion_tokens": 0,
        "prompt_tokens": 0,
        "total_tokens": 0
      }
    }
  ],
  "first_id": "step_abc123",
  "has_more": false,
  "last_id": "step_abc456",
  "object": "list"
}

Retrieve run step

$ openai beta:threads:runs:steps retrieve

get /threads/{thread_id}/runs/{run_id}/steps/{step_id}

Retrieves a run step.

Parameters

• --thread-id: string

  The ID of the thread to which the run and run step belongs.

• --run-id: string

  The ID of the run to which the run step belongs.

• --step-id: string

  The ID of the run step to retrieve.

• --include: optional array of RunStepInclude

  A list of additional fields to include in the response. Currently the only supported value is step_details.tool_calls[*].file_search.results[*].content to fetch the file search result content.

  See the file search tool documentation for more information.

Returns

• run_step: object { id, assistant_id, cancelled_at, 13 more }

  Represents a step in execution of a run.

  • id: string

    The identifier of the run step, which can be referenced in API endpoints.

  • assistant_id: string

    The ID of the assistant associated with the run step.

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expired_at: number

    The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the parent run is expired.

  • failed_at: number

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

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded"

      One of server_error or rate_limit_exceeded.

      • "server_error"

      • "rate_limit_exceeded"

    • message: string

      A human-readable description of the error.

  • metadata: map[string]

    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.

  • object: "thread.run.step"

    The object type, which is always thread.run.step.

  • run_id: string

    The ID of the run that this run step is a part of.

  • status: "in_progress" or "cancelled" or "failed" or 2 more

    The status of the run step, which can be either in_progress, cancelled, failed, completed, or expired.

    • "in_progress"

    • "cancelled"

    • "failed"

    • "completed"

    • "expired"

  • step_details: MessageCreationStepDetails or ToolCallsStepDetails

    The details of the run step.

    • message_creation_step_details: object { message_creation, type }

      Details of the message creation by the run step.

      • message_creation: object { message_id }

        • message_id: string

          The ID of the message that was created by this run step.

      • type: "message_creation"

        Always message_creation.

    • tool_calls_step_details: object { tool_calls, type }

      Details of the tool call.

      • tool_calls: array of ToolCall

        An array of tool calls the run step was involved in. These can be associated with one of three types of tools: code_interpreter, file_search, or function.

        • code_interpreter_tool_call: object { id, code_interpreter, type }

          Details of the Code Interpreter tool call the run step was involved in.

          • id: string

            The ID of the tool call.

          • code_interpreter: object { input, outputs }

            The Code Interpreter tool call definition.

            • input: string

              The input to the Code Interpreter tool call.

            • outputs: array of object { logs, type } or object { image, type }

              The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

              • logs: object { logs, type }

                Text output from the Code Interpreter tool call as part of a run step.

                • logs: string

                  The text output from the Code Interpreter tool call.

                • type: "logs"

                  Always logs.

              • image: object { image, type }

                • image: object { file_id }

                  • file_id: string

                    The file ID of the image.

                • type: "image"

                  Always image.

          • type: "code_interpreter"

            The type of tool call. This is always going to be code_interpreter for this type of tool call.

        • file_search_tool_call: object { id, file_search, type }

          • id: string

            The ID of the tool call object.

          • file_search: object { ranking_options, results }

            For now, this is always going to be an empty object.

            • ranking_options: optional object { ranker, score_threshold }

              The ranking options for the file search.

              • ranker: "auto" or "default_2024_08_21"

                The ranker to use for the file search. If not specified will use the auto ranker.

                • "auto"

                • "default_2024_08_21"

              • score_threshold: number

                The score threshold for the file search. All values must be a floating point number between 0 and 1.

            • results: optional array of object { file_id, file_name, score, content }

              The results of the file search.

              • file_id: string

                The ID of the file that result was found in.

              • file_name: string

                The name of the file that result was found in.

              • score: number

                The score of the result. All values must be a floating point number between 0 and 1.

              • content: optional array of object { text, type }

                The content of the result that was found. The content is only included if requested via the include query parameter.

                • text: optional string

                  The text content of the file.

                • type: optional "text"

                  The type of the content.

                  • "text"

          • type: "file_search"

            The type of tool call. This is always going to be file_search for this type of tool call.

        • function_tool_call: object { id, function, type }

          • id: string

            The ID of the tool call object.

          • function: object { arguments, name, output }

            The definition of the function that was called.

            • arguments: string

              The arguments passed to the function.

            • name: string

              The name of the function.

            • output: string

              The output of the function. This will be null if the outputs have not been submitted yet.

          • type: "function"

            The type of tool call. This is always going to be function for this type of tool call.

      • type: "tool_calls"

        Always tool_calls.

  • thread_id: string

    The ID of the thread that was run.

  • type: "message_creation" or "tool_calls"

    The type of run step, which can be either message_creation or tool_calls.

    • "message_creation"

    • "tool_calls"

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    Usage statistics related to the run step. This value will be null while the run step's status is in_progress.

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

Example

openai beta:threads:runs:steps retrieve \
  --api-key 'My API Key' \
  --thread-id thread_id \
  --run-id run_id \
  --step-id step_id

Response

{
  "id": "id",
  "assistant_id": "assistant_id",
  "cancelled_at": 0,
  "completed_at": 0,
  "created_at": 0,
  "expired_at": 0,
  "failed_at": 0,
  "last_error": {
    "code": "server_error",
    "message": "message"
  },
  "metadata": {
    "foo": "string"
  },
  "object": "thread.run.step",
  "run_id": "run_id",
  "status": "in_progress",
  "step_details": {
    "message_creation": {
      "message_id": "message_id"
    },
    "type": "message_creation"
  },
  "thread_id": "thread_id",
  "type": "message_creation",
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0
  }
}

Domain Types

Code Interpreter Logs

• code_interpreter_logs: object { index, type, logs }

  Text output from the Code Interpreter tool call as part of a run step.

  • index: number

    The index of the output in the outputs array.

  • type: "logs"

    Always logs.

  • logs: optional string

    The text output from the Code Interpreter tool call.

Code Interpreter Output Image

• code_interpreter_output_image: object { index, type, image }

  • index: number

    The index of the output in the outputs array.

  • type: "image"

    Always image.

  • image: optional object { file_id }

    • file_id: optional string

      The file ID of the image.

Code Interpreter Tool Call

• code_interpreter_tool_call: object { id, code_interpreter, type }

  Details of the Code Interpreter tool call the run step was involved in.

  • id: string

    The ID of the tool call.

  • code_interpreter: object { input, outputs }

    The Code Interpreter tool call definition.

    • input: string

      The input to the Code Interpreter tool call.

    • outputs: array of object { logs, type } or object { image, type }

      The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

      • logs: object { logs, type }

        Text output from the Code Interpreter tool call as part of a run step.

        • logs: string

          The text output from the Code Interpreter tool call.

        • type: "logs"

          Always logs.

      • image: object { image, type }

        • image: object { file_id }

          • file_id: string

            The file ID of the image.

        • type: "image"

          Always image.

  • type: "code_interpreter"

    The type of tool call. This is always going to be code_interpreter for this type of tool call.

Code Interpreter Tool Call Delta

• code_interpreter_tool_call_delta: object { index, type, id, code_interpreter }

  Details of the Code Interpreter tool call the run step was involved in.

  • index: number

    The index of the tool call in the tool calls array.

  • type: "code_interpreter"

    The type of tool call. This is always going to be code_interpreter for this type of tool call.

  • id: optional string

    The ID of the tool call.

  • code_interpreter: optional object { input, outputs }

    The Code Interpreter tool call definition.

    • input: optional string

      The input to the Code Interpreter tool call.

    • outputs: optional array of CodeInterpreterLogs or CodeInterpreterOutputImage

      The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

      • code_interpreter_logs: object { index, type, logs }

        Text output from the Code Interpreter tool call as part of a run step.

        • index: number

          The index of the output in the outputs array.

        • type: "logs"

          Always logs.

        • logs: optional string

          The text output from the Code Interpreter tool call.

      • code_interpreter_output_image: object { index, type, image }

        • index: number

          The index of the output in the outputs array.

        • type: "image"

          Always image.

        • image: optional object { file_id }

          • file_id: optional string

            The file ID of the image.

File Search Tool Call

• file_search_tool_call: object { id, file_search, type }

  • id: string

    The ID of the tool call object.

  • file_search: object { ranking_options, results }

    For now, this is always going to be an empty object.

    • ranking_options: optional object { ranker, score_threshold }

      The ranking options for the file search.

      • ranker: "auto" or "default_2024_08_21"

        The ranker to use for the file search. If not specified will use the auto ranker.

        • "auto"

        • "default_2024_08_21"

      • score_threshold: number

        The score threshold for the file search. All values must be a floating point number between 0 and 1.

    • results: optional array of object { file_id, file_name, score, content }

      The results of the file search.

      • file_id: string

        The ID of the file that result was found in.

      • file_name: string

        The name of the file that result was found in.

      • score: number

        The score of the result. All values must be a floating point number between 0 and 1.

      • content: optional array of object { text, type }

        The content of the result that was found. The content is only included if requested via the include query parameter.

        • text: optional string

          The text content of the file.

        • type: optional "text"

          The type of the content.

          • "text"

  • type: "file_search"

    The type of tool call. This is always going to be file_search for this type of tool call.

File Search Tool Call Delta

• file_search_tool_call_delta: object { file_search, index, type, id }

  • file_search: unknown

    For now, this is always going to be an empty object.

  • index: number

    The index of the tool call in the tool calls array.

  • type: "file_search"

    The type of tool call. This is always going to be file_search for this type of tool call.

  • id: optional string

    The ID of the tool call object.

Function Tool Call

• function_tool_call: object { id, function, type }

  • id: string

    The ID of the tool call object.

  • function: object { arguments, name, output }

    The definition of the function that was called.

    • arguments: string

      The arguments passed to the function.

    • name: string

      The name of the function.

    • output: string

      The output of the function. This will be null if the outputs have not been submitted yet.

  • type: "function"

    The type of tool call. This is always going to be function for this type of tool call.

Function Tool Call Delta

• function_tool_call_delta: object { index, type, id, function }

  • index: number

    The index of the tool call in the tool calls array.

  • type: "function"

    The type of tool call. This is always going to be function for this type of tool call.

  • id: optional string

    The ID of the tool call object.

  • function: optional object { arguments, name, output }

    The definition of the function that was called.

    • arguments: optional string

      The arguments passed to the function.

    • name: optional string

      The name of the function.

    • output: optional string

      The output of the function. This will be null if the outputs have not been submitted yet.

Message Creation Step Details

• message_creation_step_details: object { message_creation, type }

  Details of the message creation by the run step.

  • message_creation: object { message_id }

    • message_id: string

      The ID of the message that was created by this run step.

  • type: "message_creation"

    Always message_creation.

Run Step

• run_step: object { id, assistant_id, cancelled_at, 13 more }

  Represents a step in execution of a run.

  • id: string

    The identifier of the run step, which can be referenced in API endpoints.

  • assistant_id: string

    The ID of the assistant associated with the run step.

  • cancelled_at: number

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

  • completed_at: number

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

  • created_at: number

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

  • expired_at: number

    The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the parent run is expired.

  • failed_at: number

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

  • last_error: object { code, message }

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

    • code: "server_error" or "rate_limit_exceeded"

      One of server_error or rate_limit_exceeded.

      • "server_error"

      • "rate_limit_exceeded"

    • message: string

      A human-readable description of the error.

  • metadata: map[string]

    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.

  • object: "thread.run.step"

    The object type, which is always thread.run.step.

  • run_id: string

    The ID of the run that this run step is a part of.

  • status: "in_progress" or "cancelled" or "failed" or 2 more

    The status of the run step, which can be either in_progress, cancelled, failed, completed, or expired.

    • "in_progress"

    • "cancelled"

    • "failed"

    • "completed"

    • "expired"

  • step_details: MessageCreationStepDetails or ToolCallsStepDetails

    The details of the run step.

    • message_creation_step_details: object { message_creation, type }

      Details of the message creation by the run step.

      • message_creation: object { message_id }

        • message_id: string

          The ID of the message that was created by this run step.

      • type: "message_creation"

        Always message_creation.

    • tool_calls_step_details: object { tool_calls, type }

      Details of the tool call.

      • tool_calls: array of ToolCall

        An array of tool calls the run step was involved in. These can be associated with one of three types of tools: code_interpreter, file_search, or function.

        • code_interpreter_tool_call: object { id, code_interpreter, type }

          Details of the Code Interpreter tool call the run step was involved in.

          • id: string

            The ID of the tool call.

          • code_interpreter: object { input, outputs }

            The Code Interpreter tool call definition.

            • input: string

              The input to the Code Interpreter tool call.

            • outputs: array of object { logs, type } or object { image, type }

              The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

              • logs: object { logs, type }

                Text output from the Code Interpreter tool call as part of a run step.

                • logs: string

                  The text output from the Code Interpreter tool call.

                • type: "logs"

                  Always logs.

              • image: object { image, type }

                • image: object { file_id }

                  • file_id: string

                    The file ID of the image.

                • type: "image"

                  Always image.

          • type: "code_interpreter"

            The type of tool call. This is always going to be code_interpreter for this type of tool call.

        • file_search_tool_call: object { id, file_search, type }

          • id: string

            The ID of the tool call object.

          • file_search: object { ranking_options, results }

            For now, this is always going to be an empty object.

            • ranking_options: optional object { ranker, score_threshold }

              The ranking options for the file search.

              • ranker: "auto" or "default_2024_08_21"

                The ranker to use for the file search. If not specified will use the auto ranker.

                • "auto"

                • "default_2024_08_21"

              • score_threshold: number

                The score threshold for the file search. All values must be a floating point number between 0 and 1.

            • results: optional array of object { file_id, file_name, score, content }

              The results of the file search.

              • file_id: string

                The ID of the file that result was found in.

              • file_name: string

                The name of the file that result was found in.

              • score: number

                The score of the result. All values must be a floating point number between 0 and 1.

              • content: optional array of object { text, type }

                The content of the result that was found. The content is only included if requested via the include query parameter.

                • text: optional string

                  The text content of the file.

                • type: optional "text"

                  The type of the content.

                  • "text"

          • type: "file_search"

            The type of tool call. This is always going to be file_search for this type of tool call.

        • function_tool_call: object { id, function, type }

          • id: string

            The ID of the tool call object.

          • function: object { arguments, name, output }

            The definition of the function that was called.

            • arguments: string

              The arguments passed to the function.

            • name: string

              The name of the function.

            • output: string

              The output of the function. This will be null if the outputs have not been submitted yet.

          • type: "function"

            The type of tool call. This is always going to be function for this type of tool call.

      • type: "tool_calls"

        Always tool_calls.

  • thread_id: string

    The ID of the thread that was run.

  • type: "message_creation" or "tool_calls"

    The type of run step, which can be either message_creation or tool_calls.

    • "message_creation"

    • "tool_calls"

  • usage: object { completion_tokens, prompt_tokens, total_tokens }

    Usage statistics related to the run step. This value will be null while the run step's status is in_progress.

    • completion_tokens: number

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

    • prompt_tokens: number

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

    • total_tokens: number

      Total number of tokens used (prompt + completion).

Run Step Delta

• run_step_delta: object { step_details }

  The delta containing the fields that have changed on the run step.

  • step_details: optional RunStepDeltaMessageDelta or ToolCallDeltaObject

    The details of the run step.

    • run_step_delta_message_delta: object { type, message_creation }

      Details of the message creation by the run step.

      • type: "message_creation"

        Always message_creation.

      • message_creation: optional object { message_id }

        • message_id: optional string

          The ID of the message that was created by this run step.

    • tool_call_delta_object: object { type, tool_calls }

      Details of the tool call.

      • type: "tool_calls"

        Always tool_calls.

      • tool_calls: optional array of ToolCallDelta

        An array of tool calls the run step was involved in. These can be associated with one of three types of tools: code_interpreter, file_search, or function.

        • code_interpreter_tool_call_delta: object { index, type, id, code_interpreter }

          Details of the Code Interpreter tool call the run step was involved in.

          • index: number

            The index of the tool call in the tool calls array.

          • type: "code_interpreter"

            The type of tool call. This is always going to be code_interpreter for this type of tool call.

          • id: optional string

            The ID of the tool call.

          • code_interpreter: optional object { input, outputs }

            The Code Interpreter tool call definition.

            • input: optional string

              The input to the Code Interpreter tool call.

            • outputs: optional array of CodeInterpreterLogs or CodeInterpreterOutputImage

              The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

              • code_interpreter_logs: object { index, type, logs }

                Text output from the Code Interpreter tool call as part of a run step.

                • index: number

                  The index of the output in the outputs array.

                • type: "logs"

                  Always logs.

                • logs: optional string

                  The text output from the Code Interpreter tool call.

              • code_interpreter_output_image: object { index, type, image }

                • index: number

                  The index of the output in the outputs array.

                • type: "image"

                  Always image.

                • image: optional object { file_id }

                  • file_id: optional string

                    The file ID of the image.

        • file_search_tool_call_delta: object { file_search, index, type, id }

          • file_search: unknown

            For now, this is always going to be an empty object.

          • index: number

            The index of the tool call in the tool calls array.

          • type: "file_search"

            The type of tool call. This is always going to be file_search for this type of tool call.

          • id: optional string

            The ID of the tool call object.

        • function_tool_call_delta: object { index, type, id, function }

          • index: number

            The index of the tool call in the tool calls array.

          • type: "function"

            The type of tool call. This is always going to be function for this type of tool call.

          • id: optional string

            The ID of the tool call object.

          • function: optional object { arguments, name, output }

            The definition of the function that was called.

            • arguments: optional string

              The arguments passed to the function.

            • name: optional string

              The name of the function.

            • output: optional string

              The output of the function. This will be null if the outputs have not been submitted yet.

Run Step Delta Event

• run_step_delta_event: object { id, delta, object }

  Represents a run step delta i.e. any changed fields on a run step during streaming.

  • id: string

    The identifier of the run step, which can be referenced in API endpoints.

  • delta: object { step_details }

    The delta containing the fields that have changed on the run step.

    • step_details: optional RunStepDeltaMessageDelta or ToolCallDeltaObject

      The details of the run step.

      • run_step_delta_message_delta: object { type, message_creation }

        Details of the message creation by the run step.

        • type: "message_creation"

          Always message_creation.

        • message_creation: optional object { message_id }

          • message_id: optional string

            The ID of the message that was created by this run step.

      • tool_call_delta_object: object { type, tool_calls }

        Details of the tool call.

        • type: "tool_calls"

          Always tool_calls.

        • tool_calls: optional array of ToolCallDelta

          An array of tool calls the run step was involved in. These can be associated with one of three types of tools: code_interpreter, file_search, or function.

          • code_interpreter_tool_call_delta: object { index, type, id, code_interpreter }

            Details of the Code Interpreter tool call the run step was involved in.

            • index: number

              The index of the tool call in the tool calls array.

            • type: "code_interpreter"

              The type of tool call. This is always going to be code_interpreter for this type of tool call.

            • id: optional string

              The ID of the tool call.

            • code_interpreter: optional object { input, outputs }

              The Code Interpreter tool call definition.

              • input: optional string

                The input to the Code Interpreter tool call.

              • outputs: optional array of CodeInterpreterLogs or CodeInterpreterOutputImage

                The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

                • code_interpreter_logs: object { index, type, logs }

                  Text output from the Code Interpreter tool call as part of a run step.

                  • index: number

                    The index of the output in the outputs array.

                  • type: "logs"

                    Always logs.

                  • logs: optional string

                    The text output from the Code Interpreter tool call.

                • code_interpreter_output_image: object { index, type, image }

                  • index: number

                    The index of the output in the outputs array.

                  • type: "image"

                    Always image.

                  • image: optional object { file_id }

                    • file_id: optional string

                      The file ID of the image.

          • file_search_tool_call_delta: object { file_search, index, type, id }

            • file_search: unknown

              For now, this is always going to be an empty object.

            • index: number

              The index of the tool call in the tool calls array.

            • type: "file_search"

              The type of tool call. This is always going to be file_search for this type of tool call.

            • id: optional string

              The ID of the tool call object.

          • function_tool_call_delta: object { index, type, id, function }

            • index: number

              The index of the tool call in the tool calls array.

            • type: "function"

              The type of tool call. This is always going to be function for this type of tool call.

            • id: optional string

              The ID of the tool call object.

            • function: optional object { arguments, name, output }

              The definition of the function that was called.

              • arguments: optional string

                The arguments passed to the function.

              • name: optional string

                The name of the function.

              • output: optional string

                The output of the function. This will be null if the outputs have not been submitted yet.

  • object: "thread.run.step.delta"

    The object type, which is always thread.run.step.delta.

Run Step Delta Message Delta

• run_step_delta_message_delta: object { type, message_creation }

  Details of the message creation by the run step.

  • type: "message_creation"

    Always message_creation.

  • message_creation: optional object { message_id }

    • message_id: optional string

      The ID of the message that was created by this run step.

Run Step Include

• run_step_include: "step_details.tool_calls[*].file_search.results[*].content"

  • "step_details.tool_calls[*].file_search.results[*].content"

Tool Call

• tool_call: CodeInterpreterToolCall or FileSearchToolCall or FunctionToolCall

  Details of the Code Interpreter tool call the run step was involved in.

  • code_interpreter_tool_call: object { id, code_interpreter, type }

    Details of the Code Interpreter tool call the run step was involved in.

    • id: string

      The ID of the tool call.

    • code_interpreter: object { input, outputs }

      The Code Interpreter tool call definition.

      • input: string

        The input to the Code Interpreter tool call.

      • outputs: array of object { logs, type } or object { image, type }

        The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

        • logs: object { logs, type }

          Text output from the Code Interpreter tool call as part of a run step.

          • logs: string

            The text output from the Code Interpreter tool call.

          • type: "logs"

            Always logs.

        • image: object { image, type }

          • image: object { file_id }

            • file_id: string

              The file ID of the image.

          • type: "image"

            Always image.

    • type: "code_interpreter"

      The type of tool call. This is always going to be code_interpreter for this type of tool call.

  • file_search_tool_call: object { id, file_search, type }

    • id: string

      The ID of the tool call object.

    • file_search: object { ranking_options, results }

      For now, this is always going to be an empty object.

      • ranking_options: optional object { ranker, score_threshold }

        The ranking options for the file search.

        • ranker: "auto" or "default_2024_08_21"

          The ranker to use for the file search. If not specified will use the auto ranker.

          • "auto"

          • "default_2024_08_21"

        • score_threshold: number

          The score threshold for the file search. All values must be a floating point number between 0 and 1.

      • results: optional array of object { file_id, file_name, score, content }

        The results of the file search.

        • file_id: string

          The ID of the file that result was found in.

        • file_name: string

          The name of the file that result was found in.

        • score: number

          The score of the result. All values must be a floating point number between 0 and 1.

        • content: optional array of object { text, type }

          The content of the result that was found. The content is only included if requested via the include query parameter.

          • text: optional string

            The text content of the file.

          • type: optional "text"

            The type of the content.

            • "text"

    • type: "file_search"

      The type of tool call. This is always going to be file_search for this type of tool call.

  • function_tool_call: object { id, function, type }

    • id: string

      The ID of the tool call object.

    • function: object { arguments, name, output }

      The definition of the function that was called.

      • arguments: string

        The arguments passed to the function.

      • name: string

        The name of the function.

      • output: string

        The output of the function. This will be null if the outputs have not been submitted yet.

    • type: "function"

      The type of tool call. This is always going to be function for this type of tool call.

Tool Call Delta

• tool_call_delta: CodeInterpreterToolCallDelta or FileSearchToolCallDelta or FunctionToolCallDelta

  Details of the Code Interpreter tool call the run step was involved in.

  • code_interpreter_tool_call_delta: object { index, type, id, code_interpreter }

    Details of the Code Interpreter tool call the run step was involved in.

    • index: number

      The index of the tool call in the tool calls array.

    • type: "code_interpreter"

      The type of tool call. This is always going to be code_interpreter for this type of tool call.

    • id: optional string

      The ID of the tool call.

    • code_interpreter: optional object { input, outputs }

      The Code Interpreter tool call definition.

      • input: optional string

        The input to the Code Interpreter tool call.

      • outputs: optional array of CodeInterpreterLogs or CodeInterpreterOutputImage

        The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (logs) or images (image). Each of these are represented by a different object type.

        • code_interpreter_logs: object { index, type, logs }

          Text output from the Code Interpreter tool call as part of a run step.

          • index: number

            The index of the output in the outputs array.

          • type: "logs"

            Always logs.

          • logs: optional string

            The text output from the Code Interpreter tool call.

        • code_interpreter_output_image: object { index, type, image }

          • index: number

            The index of the output in the outputs array.

          • type: "image"

            Always image.

          • image: optional object { file_id }

            • file_id: optional string

              The file ID of the image.

  • file_search_tool_call_delta: object { file_search, index, type, id }

    • file_search: unknown

      For now, this is always going to be an empty object.

    • index: number

      The index of the tool call in the tool calls array.

    • type: "file_search"

      The type of tool call. This is always going to be file_search for this type of tool call.

    • id: optional string

      The ID of the tool call object.

  • function_tool_call_delta: object { index, type, id, function }

    • index: number

      The index of the tool call in the tool calls array.

    • type: "function"

      The type of tool call. This is always going to be function for this type of tool call.

    • id: optional string

      The ID of the tool call object.

    • function: optional object { arguments, name, output }

      The definition of the function that was called.

      • arguments: optional string

        The arguments passed to the function.

      • name: optional string

        The name of the function.

      • output: optional string

        The output of the function. This will be null if the outputs have not been submitted yet.