310 lines
14 KiB
Python
310 lines
14 KiB
Python
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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from typing import Union, Iterable, Optional
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from typing_extensions import Literal
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import httpx
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from ... import _legacy_response
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from ..._types import Body, Omit, Query, Headers, NotGiven, omit, not_given
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from ..._utils import maybe_transform, async_maybe_transform
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from ..._compat import cached_property
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from ..._resource import SyncAPIResource, AsyncAPIResource
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from ..._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
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from ..._base_client import make_request_options
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from ...types.responses import input_token_count_params
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from ...types.responses.tool_param import ToolParam
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from ...types.shared_params.reasoning import Reasoning
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from ...types.responses.response_input_item_param import ResponseInputItemParam
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from ...types.responses.input_token_count_response import InputTokenCountResponse
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__all__ = ["InputTokens", "AsyncInputTokens"]
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class InputTokens(SyncAPIResource):
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@cached_property
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def with_raw_response(self) -> InputTokensWithRawResponse:
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"""
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This property can be used as a prefix for any HTTP method call to return
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the raw response object instead of the parsed content.
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For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers
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"""
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return InputTokensWithRawResponse(self)
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@cached_property
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def with_streaming_response(self) -> InputTokensWithStreamingResponse:
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"""
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An alternative to `.with_raw_response` that doesn't eagerly read the response body.
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For more information, see https://www.github.com/openai/openai-python#with_streaming_response
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"""
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return InputTokensWithStreamingResponse(self)
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def count(
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self,
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*,
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conversation: Optional[input_token_count_params.Conversation] | Omit = omit,
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input: Union[str, Iterable[ResponseInputItemParam], None] | Omit = omit,
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instructions: Optional[str] | Omit = omit,
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model: Optional[str] | Omit = omit,
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parallel_tool_calls: Optional[bool] | Omit = omit,
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previous_response_id: Optional[str] | Omit = omit,
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reasoning: Optional[Reasoning] | Omit = omit,
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text: Optional[input_token_count_params.Text] | Omit = omit,
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tool_choice: Optional[input_token_count_params.ToolChoice] | Omit = omit,
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tools: Optional[Iterable[ToolParam]] | Omit = omit,
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truncation: Literal["auto", "disabled"] | Omit = omit,
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# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
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# The extra values given here take precedence over values defined on the client or passed to this method.
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extra_headers: Headers | None = None,
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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timeout: float | httpx.Timeout | None | NotGiven = not_given,
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) -> InputTokenCountResponse:
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"""
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Get input token counts
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Args:
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conversation: The conversation that this response belongs to. Items from this conversation are
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prepended to `input_items` for this response request. Input items and output
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items from this response are automatically added to this conversation after this
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response completes.
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input: Text, image, or file inputs to the model, used to generate a response
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instructions: A system (or developer) message inserted into the model's context. When used
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along with `previous_response_id`, the instructions from a previous response
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will not be carried over to the next response. This makes it simple to swap out
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system (or developer) messages in new responses.
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model: Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI offers a
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wide range of models with different capabilities, performance characteristics,
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and price points. Refer to the
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[model guide](https://platform.openai.com/docs/models) to browse and compare
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available models.
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parallel_tool_calls: Whether to allow the model to run tool calls in parallel.
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previous_response_id: The unique ID of the previous response to the model. Use this to create
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multi-turn conversations. Learn more about
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[conversation state](https://platform.openai.com/docs/guides/conversation-state).
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Cannot be used in conjunction with `conversation`.
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reasoning: **gpt-5 and o-series models only** Configuration options for
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[reasoning models](https://platform.openai.com/docs/guides/reasoning).
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text: Configuration options for a text response from the model. Can be plain text or
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structured JSON data. Learn more:
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- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)
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- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs)
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tool_choice: How the model should select which tool (or tools) to use when generating a
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response. See the `tools` parameter to see how to specify which tools the model
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can call.
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tools: An array of tools the model may call while generating a response. You can
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specify which tool to use by setting the `tool_choice` parameter.
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truncation: The truncation strategy to use for the model response. - `auto`: If the input to
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this Response exceeds the model's context window size, the model will truncate
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the response to fit the context window by dropping items from the beginning of
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the conversation. - `disabled` (default): If the input size will exceed the
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context window size for a model, the request will fail with a 400 error.
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extra_headers: Send extra headers
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extra_query: Add additional query parameters to the request
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extra_body: Add additional JSON properties to the request
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timeout: Override the client-level default timeout for this request, in seconds
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"""
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return self._post(
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"/responses/input_tokens",
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body=maybe_transform(
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{
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"conversation": conversation,
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"input": input,
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"instructions": instructions,
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"model": model,
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"parallel_tool_calls": parallel_tool_calls,
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"previous_response_id": previous_response_id,
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"reasoning": reasoning,
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"text": text,
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"tool_choice": tool_choice,
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"tools": tools,
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"truncation": truncation,
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},
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input_token_count_params.InputTokenCountParams,
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),
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options=make_request_options(
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extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
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),
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cast_to=InputTokenCountResponse,
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)
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class AsyncInputTokens(AsyncAPIResource):
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@cached_property
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def with_raw_response(self) -> AsyncInputTokensWithRawResponse:
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"""
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This property can be used as a prefix for any HTTP method call to return
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the raw response object instead of the parsed content.
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For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers
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"""
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return AsyncInputTokensWithRawResponse(self)
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@cached_property
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def with_streaming_response(self) -> AsyncInputTokensWithStreamingResponse:
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"""
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An alternative to `.with_raw_response` that doesn't eagerly read the response body.
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For more information, see https://www.github.com/openai/openai-python#with_streaming_response
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"""
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return AsyncInputTokensWithStreamingResponse(self)
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async def count(
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self,
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*,
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conversation: Optional[input_token_count_params.Conversation] | Omit = omit,
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input: Union[str, Iterable[ResponseInputItemParam], None] | Omit = omit,
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instructions: Optional[str] | Omit = omit,
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model: Optional[str] | Omit = omit,
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parallel_tool_calls: Optional[bool] | Omit = omit,
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previous_response_id: Optional[str] | Omit = omit,
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reasoning: Optional[Reasoning] | Omit = omit,
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text: Optional[input_token_count_params.Text] | Omit = omit,
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tool_choice: Optional[input_token_count_params.ToolChoice] | Omit = omit,
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tools: Optional[Iterable[ToolParam]] | Omit = omit,
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truncation: Literal["auto", "disabled"] | Omit = omit,
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# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
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# The extra values given here take precedence over values defined on the client or passed to this method.
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extra_headers: Headers | None = None,
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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timeout: float | httpx.Timeout | None | NotGiven = not_given,
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) -> InputTokenCountResponse:
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"""
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Get input token counts
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Args:
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conversation: The conversation that this response belongs to. Items from this conversation are
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prepended to `input_items` for this response request. Input items and output
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items from this response are automatically added to this conversation after this
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response completes.
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input: Text, image, or file inputs to the model, used to generate a response
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instructions: A system (or developer) message inserted into the model's context. When used
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|
along with `previous_response_id`, the instructions from a previous response
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will not be carried over to the next response. This makes it simple to swap out
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|
system (or developer) messages in new responses.
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|
|
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model: Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI offers a
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|
wide range of models with different capabilities, performance characteristics,
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|
|
and price points. Refer to the
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[model guide](https://platform.openai.com/docs/models) to browse and compare
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available models.
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parallel_tool_calls: Whether to allow the model to run tool calls in parallel.
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|
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previous_response_id: The unique ID of the previous response to the model. Use this to create
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|
multi-turn conversations. Learn more about
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[conversation state](https://platform.openai.com/docs/guides/conversation-state).
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Cannot be used in conjunction with `conversation`.
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reasoning: **gpt-5 and o-series models only** Configuration options for
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[reasoning models](https://platform.openai.com/docs/guides/reasoning).
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text: Configuration options for a text response from the model. Can be plain text or
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structured JSON data. Learn more:
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- [Text inputs and outputs](https://platform.openai.com/docs/guides/text)
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- [Structured Outputs](https://platform.openai.com/docs/guides/structured-outputs)
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|
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tool_choice: How the model should select which tool (or tools) to use when generating a
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|
|
response. See the `tools` parameter to see how to specify which tools the model
|
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|
|
can call.
|
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|
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tools: An array of tools the model may call while generating a response. You can
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specify which tool to use by setting the `tool_choice` parameter.
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truncation: The truncation strategy to use for the model response. - `auto`: If the input to
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this Response exceeds the model's context window size, the model will truncate
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the response to fit the context window by dropping items from the beginning of
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the conversation. - `disabled` (default): If the input size will exceed the
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context window size for a model, the request will fail with a 400 error.
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extra_headers: Send extra headers
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extra_query: Add additional query parameters to the request
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extra_body: Add additional JSON properties to the request
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timeout: Override the client-level default timeout for this request, in seconds
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"""
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return await self._post(
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"/responses/input_tokens",
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body=await async_maybe_transform(
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{
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"conversation": conversation,
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"input": input,
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"instructions": instructions,
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"model": model,
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"parallel_tool_calls": parallel_tool_calls,
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"previous_response_id": previous_response_id,
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"reasoning": reasoning,
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"text": text,
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"tool_choice": tool_choice,
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"tools": tools,
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"truncation": truncation,
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},
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input_token_count_params.InputTokenCountParams,
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),
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options=make_request_options(
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extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
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),
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cast_to=InputTokenCountResponse,
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)
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class InputTokensWithRawResponse:
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def __init__(self, input_tokens: InputTokens) -> None:
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self._input_tokens = input_tokens
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self.count = _legacy_response.to_raw_response_wrapper(
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input_tokens.count,
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)
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class AsyncInputTokensWithRawResponse:
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def __init__(self, input_tokens: AsyncInputTokens) -> None:
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self._input_tokens = input_tokens
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self.count = _legacy_response.async_to_raw_response_wrapper(
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input_tokens.count,
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)
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class InputTokensWithStreamingResponse:
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def __init__(self, input_tokens: InputTokens) -> None:
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self._input_tokens = input_tokens
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self.count = to_streamed_response_wrapper(
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input_tokens.count,
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)
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class AsyncInputTokensWithStreamingResponse:
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def __init__(self, input_tokens: AsyncInputTokens) -> None:
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self._input_tokens = input_tokens
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self.count = async_to_streamed_response_wrapper(
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input_tokens.count,
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)
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