src/openai/resources/beta/assistants.py [214:358]:
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        self,
        assistant_id: str,
        *,
        description: Optional[str] | NotGiven = NOT_GIVEN,
        instructions: Optional[str] | NotGiven = NOT_GIVEN,
        metadata: Optional[Metadata] | NotGiven = NOT_GIVEN,
        model: Union[
            str,
            Literal[
                "gpt-4.1",
                "gpt-4.1-mini",
                "gpt-4.1-nano",
                "gpt-4.1-2025-04-14",
                "gpt-4.1-mini-2025-04-14",
                "gpt-4.1-nano-2025-04-14",
                "o3-mini",
                "o3-mini-2025-01-31",
                "o1",
                "o1-2024-12-17",
                "gpt-4o",
                "gpt-4o-2024-11-20",
                "gpt-4o-2024-08-06",
                "gpt-4o-2024-05-13",
                "gpt-4o-mini",
                "gpt-4o-mini-2024-07-18",
                "gpt-4.5-preview",
                "gpt-4.5-preview-2025-02-27",
                "gpt-4-turbo",
                "gpt-4-turbo-2024-04-09",
                "gpt-4-0125-preview",
                "gpt-4-turbo-preview",
                "gpt-4-1106-preview",
                "gpt-4-vision-preview",
                "gpt-4",
                "gpt-4-0314",
                "gpt-4-0613",
                "gpt-4-32k",
                "gpt-4-32k-0314",
                "gpt-4-32k-0613",
                "gpt-3.5-turbo",
                "gpt-3.5-turbo-16k",
                "gpt-3.5-turbo-0613",
                "gpt-3.5-turbo-1106",
                "gpt-3.5-turbo-0125",
                "gpt-3.5-turbo-16k-0613",
            ],
        ]
        | NotGiven = NOT_GIVEN,
        name: Optional[str] | NotGiven = NOT_GIVEN,
        reasoning_effort: Optional[ReasoningEffort] | NotGiven = NOT_GIVEN,
        response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_resources: Optional[assistant_update_params.ToolResources] | NotGiven = NOT_GIVEN,
        tools: Iterable[AssistantToolParam] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
        # The extra values given here take precedence over values defined on the client or passed to this method.
        extra_headers: Headers | None = None,
        extra_query: Query | None = None,
        extra_body: Body | None = None,
        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
    ) -> Assistant:
        """Modifies an assistant.

        Args:
          description: The description of the assistant.

        The maximum length is 512 characters.

          instructions: The system instructions that the assistant uses. The maximum length is 256,000
              characters.

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

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

          model: ID of the model to use. You can use the
              [List models](https://platform.openai.com/docs/api-reference/models/list) API to
              see all of your available models, or see our
              [Model overview](https://platform.openai.com/docs/models) for descriptions of
              them.

          name: The name of the assistant. The maximum length is 256 characters.

          reasoning_effort: **o-series models only**

              Constrains effort on reasoning for
              [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently
              supported values are `low`, `medium`, and `high`. Reducing reasoning effort can
              result in faster responses and fewer tokens used on reasoning in a response.

          response_format: Specifies the format that the model must output. Compatible with
              [GPT-4o](https://platform.openai.com/docs/models#gpt-4o),
              [GPT-4 Turbo](https://platform.openai.com/docs/models#gpt-4-turbo-and-gpt-4),
              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](https://platform.openai.com/docs/guides/structured-outputs).

              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: 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_resources: 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.

          tools: A list of tool enabled on the assistant. There can be a maximum of 128 tools per
              assistant. Tools can be of types `code_interpreter`, `file_search`, or
              `function`.

          top_p: 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.

          extra_headers: Send extra headers

          extra_query: Add additional query parameters to the request

          extra_body: Add additional JSON properties to the request

          timeout: Override the client-level default timeout for this request, in seconds
        """
        if not assistant_id:
            raise ValueError(f"Expected a non-empty value for `assistant_id` but received {assistant_id!r}")
        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
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src/openai/resources/beta/assistants.py [663:807]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        self,
        assistant_id: str,
        *,
        description: Optional[str] | NotGiven = NOT_GIVEN,
        instructions: Optional[str] | NotGiven = NOT_GIVEN,
        metadata: Optional[Metadata] | NotGiven = NOT_GIVEN,
        model: Union[
            str,
            Literal[
                "gpt-4.1",
                "gpt-4.1-mini",
                "gpt-4.1-nano",
                "gpt-4.1-2025-04-14",
                "gpt-4.1-mini-2025-04-14",
                "gpt-4.1-nano-2025-04-14",
                "o3-mini",
                "o3-mini-2025-01-31",
                "o1",
                "o1-2024-12-17",
                "gpt-4o",
                "gpt-4o-2024-11-20",
                "gpt-4o-2024-08-06",
                "gpt-4o-2024-05-13",
                "gpt-4o-mini",
                "gpt-4o-mini-2024-07-18",
                "gpt-4.5-preview",
                "gpt-4.5-preview-2025-02-27",
                "gpt-4-turbo",
                "gpt-4-turbo-2024-04-09",
                "gpt-4-0125-preview",
                "gpt-4-turbo-preview",
                "gpt-4-1106-preview",
                "gpt-4-vision-preview",
                "gpt-4",
                "gpt-4-0314",
                "gpt-4-0613",
                "gpt-4-32k",
                "gpt-4-32k-0314",
                "gpt-4-32k-0613",
                "gpt-3.5-turbo",
                "gpt-3.5-turbo-16k",
                "gpt-3.5-turbo-0613",
                "gpt-3.5-turbo-1106",
                "gpt-3.5-turbo-0125",
                "gpt-3.5-turbo-16k-0613",
            ],
        ]
        | NotGiven = NOT_GIVEN,
        name: Optional[str] | NotGiven = NOT_GIVEN,
        reasoning_effort: Optional[ReasoningEffort] | NotGiven = NOT_GIVEN,
        response_format: Optional[AssistantResponseFormatOptionParam] | NotGiven = NOT_GIVEN,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_resources: Optional[assistant_update_params.ToolResources] | NotGiven = NOT_GIVEN,
        tools: Iterable[AssistantToolParam] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
        # The extra values given here take precedence over values defined on the client or passed to this method.
        extra_headers: Headers | None = None,
        extra_query: Query | None = None,
        extra_body: Body | None = None,
        timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
    ) -> Assistant:
        """Modifies an assistant.

        Args:
          description: The description of the assistant.

        The maximum length is 512 characters.

          instructions: The system instructions that the assistant uses. The maximum length is 256,000
              characters.

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

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

          model: ID of the model to use. You can use the
              [List models](https://platform.openai.com/docs/api-reference/models/list) API to
              see all of your available models, or see our
              [Model overview](https://platform.openai.com/docs/models) for descriptions of
              them.

          name: The name of the assistant. The maximum length is 256 characters.

          reasoning_effort: **o-series models only**

              Constrains effort on reasoning for
              [reasoning models](https://platform.openai.com/docs/guides/reasoning). Currently
              supported values are `low`, `medium`, and `high`. Reducing reasoning effort can
              result in faster responses and fewer tokens used on reasoning in a response.

          response_format: Specifies the format that the model must output. Compatible with
              [GPT-4o](https://platform.openai.com/docs/models#gpt-4o),
              [GPT-4 Turbo](https://platform.openai.com/docs/models#gpt-4-turbo-and-gpt-4),
              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](https://platform.openai.com/docs/guides/structured-outputs).

              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: 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_resources: 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.

          tools: A list of tool enabled on the assistant. There can be a maximum of 128 tools per
              assistant. Tools can be of types `code_interpreter`, `file_search`, or
              `function`.

          top_p: 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.

          extra_headers: Send extra headers

          extra_query: Add additional query parameters to the request

          extra_body: Add additional JSON properties to the request

          timeout: Override the client-level default timeout for this request, in seconds
        """
        if not assistant_id:
            raise ValueError(f"Expected a non-empty value for `assistant_id` but received {assistant_id!r}")
        extra_headers = {"OpenAI-Beta": "assistants=v2", **(extra_headers or {})}
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