# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.

from __future__ import annotations

from typing import Dict, Union, Iterable, Optional
from typing_extensions import Literal, Required, TypeAlias, TypedDict

from ..shared_params.metadata import Metadata
from ..shared.reasoning_effort import ReasoningEffort
from ..graders.grader_inputs_param import GraderInputsParam
from ..responses.easy_input_message_param import EasyInputMessageParam
from ..shared_params.response_format_text import ResponseFormatText
from ..responses.response_input_text_param import ResponseInputTextParam
from ..responses.response_input_audio_param import ResponseInputAudioParam
from ..chat.chat_completion_function_tool_param import ChatCompletionFunctionToolParam
from ..shared_params.response_format_json_object import ResponseFormatJSONObject
from ..shared_params.response_format_json_schema import ResponseFormatJSONSchema

__all__ = [
    "CreateEvalCompletionsRunDataSourceParam",
    "Source",
    "SourceFileContent",
    "SourceFileContentContent",
    "SourceFileID",
    "SourceStoredCompletions",
    "InputMessages",
    "InputMessagesTemplate",
    "InputMessagesTemplateTemplate",
    "InputMessagesTemplateTemplateEvalItem",
    "InputMessagesTemplateTemplateEvalItemContent",
    "InputMessagesTemplateTemplateEvalItemContentOutputText",
    "InputMessagesTemplateTemplateEvalItemContentInputImage",
    "InputMessagesItemReference",
    "SamplingParams",
    "SamplingParamsResponseFormat",
]


class SourceFileContentContent(TypedDict, total=False):
    item: Required[Dict[str, object]]

    sample: Dict[str, object]


class SourceFileContent(TypedDict, total=False):
    content: Required[Iterable[SourceFileContentContent]]
    """The content of the jsonl file."""

    type: Required[Literal["file_content"]]
    """The type of jsonl source. Always `file_content`."""


class SourceFileID(TypedDict, total=False):
    id: Required[str]
    """The identifier of the file."""

    type: Required[Literal["file_id"]]
    """The type of jsonl source. Always `file_id`."""


class SourceStoredCompletions(TypedDict, total=False):
    """A StoredCompletionsRunDataSource configuration describing a set of filters"""

    type: Required[Literal["stored_completions"]]
    """The type of source. Always `stored_completions`."""

    created_after: Optional[int]
    """An optional Unix timestamp to filter items created after this time."""

    created_before: Optional[int]
    """An optional Unix timestamp to filter items created before this time."""

    limit: Optional[int]
    """An optional maximum number of items to return."""

    metadata: Optional[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: Optional[str]
    """An optional model to filter by (e.g., 'gpt-4o')."""


Source: TypeAlias = Union[SourceFileContent, SourceFileID, SourceStoredCompletions]


class InputMessagesTemplateTemplateEvalItemContentOutputText(TypedDict, total=False):
    """A text output from the model."""

    text: Required[str]
    """The text output from the model."""

    type: Required[Literal["output_text"]]
    """The type of the output text. Always `output_text`."""


class InputMessagesTemplateTemplateEvalItemContentInputImage(TypedDict, total=False):
    """An image input block used within EvalItem content arrays."""

    image_url: Required[str]
    """The URL of the image input."""

    type: Required[Literal["input_image"]]
    """The type of the image input. Always `input_image`."""

    detail: str
    """The detail level of the image to be sent to the model.

    One of `high`, `low`, or `auto`. Defaults to `auto`.
    """


InputMessagesTemplateTemplateEvalItemContent: TypeAlias = Union[
    str,
    ResponseInputTextParam,
    InputMessagesTemplateTemplateEvalItemContentOutputText,
    InputMessagesTemplateTemplateEvalItemContentInputImage,
    ResponseInputAudioParam,
    GraderInputsParam,
]


class InputMessagesTemplateTemplateEvalItem(TypedDict, total=False):
    """
    A message input to the model with a role indicating instruction following
    hierarchy. Instructions given with the `developer` or `system` role take
    precedence over instructions given with the `user` role. Messages with the
    `assistant` role are presumed to have been generated by the model in previous
    interactions.
    """

    content: Required[InputMessagesTemplateTemplateEvalItemContent]
    """Inputs to the model - can contain template strings.

    Supports text, output text, input images, and input audio, either as a single
    item or an array of items.
    """

    role: Required[Literal["user", "assistant", "system", "developer"]]
    """The role of the message input.

    One of `user`, `assistant`, `system`, or `developer`.
    """

    type: Literal["message"]
    """The type of the message input. Always `message`."""


InputMessagesTemplateTemplate: TypeAlias = Union[EasyInputMessageParam, InputMessagesTemplateTemplateEvalItem]


class InputMessagesTemplate(TypedDict, total=False):
    template: Required[Iterable[InputMessagesTemplateTemplate]]
    """A list of chat messages forming the prompt or context.

    May include variable references to the `item` namespace, ie {{item.name}}.
    """

    type: Required[Literal["template"]]
    """The type of input messages. Always `template`."""


class InputMessagesItemReference(TypedDict, total=False):
    item_reference: Required[str]
    """A reference to a variable in the `item` namespace. Ie, "item.input_trajectory" """

    type: Required[Literal["item_reference"]]
    """The type of input messages. Always `item_reference`."""


InputMessages: TypeAlias = Union[InputMessagesTemplate, InputMessagesItemReference]

SamplingParamsResponseFormat: TypeAlias = Union[ResponseFormatText, ResponseFormatJSONSchema, ResponseFormatJSONObject]


class SamplingParams(TypedDict, total=False):
    max_completion_tokens: int
    """The maximum number of tokens in the generated output."""

    reasoning_effort: Optional[ReasoningEffort]
    """
    Constrains effort on reasoning for
    [reasoning models](https://platform.openai.com/docs/guides/reasoning). 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: SamplingParamsResponseFormat
    """An object specifying the format that the model must output.

    Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured
    Outputs which ensures the model will match your supplied JSON schema. Learn more
    in the
    [Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs).

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

    seed: int
    """A seed value to initialize the randomness, during sampling."""

    temperature: float
    """A higher temperature increases randomness in the outputs."""

    tools: Iterable[ChatCompletionFunctionToolParam]
    """A list of tools the model may call.

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

    top_p: float
    """An alternative to temperature for nucleus sampling; 1.0 includes all tokens."""


class CreateEvalCompletionsRunDataSourceParam(TypedDict, total=False):
    """A CompletionsRunDataSource object describing a model sampling configuration."""

    source: Required[Source]
    """Determines what populates the `item` namespace in this run's data source."""

    type: Required[Literal["completions"]]
    """The type of run data source. Always `completions`."""

    input_messages: InputMessages
    """Used when sampling from a model.

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

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

    sampling_params: SamplingParams
