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

from __future__ import annotations

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

from ...types import shared_params
from .chat_completion_tool_param import ChatCompletionToolParam
from .chat_completion_message_param import ChatCompletionMessageParam
from .chat_completion_tool_choice_option_param import ChatCompletionToolChoiceOptionParam
from .chat_completion_function_call_option_param import ChatCompletionFunctionCallOptionParam

__all__ = [
    "CompletionCreateParamsBase",
    "FunctionCall",
    "Function",
    "ResponseFormat",
    "CompletionCreateParamsNonStreaming",
    "CompletionCreateParamsStreaming",
]


class CompletionCreateParamsBase(TypedDict, total=False):
    messages: Required[Iterable[ChatCompletionMessageParam]]
    """A list of messages comprising the conversation so far.

    [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
    """

    model: Required[
        Union[
            str,
            Literal[
                "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-0301",
                "gpt-3.5-turbo-0613",
                "gpt-3.5-turbo-1106",
                "gpt-3.5-turbo-0125",
                "gpt-3.5-turbo-16k-0613",
            ],
        ]
    ]
    """ID of the model to use.

    See the
    [model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
    table for details on which models work with the Chat API.
    """

    frequency_penalty: Optional[float]
    """Number between -2.0 and 2.0.

    Positive values penalize new tokens based on their existing frequency in the
    text so far, decreasing the model's likelihood to repeat the same line verbatim.

    [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
    """

    function_call: FunctionCall
    """Deprecated in favor of `tool_choice`.

    Controls which (if any) function is called by the model. `none` means the model
    will not call a function and instead generates a message. `auto` means the model
    can pick between generating a message or calling a function. Specifying a
    particular function via `{"name": "my_function"}` forces the model to call that
    function.

    `none` is the default when no functions are present. `auto` is the default if
    functions are present.
    """

    functions: Iterable[Function]
    """Deprecated in favor of `tools`.

    A list of functions the model may generate JSON inputs for.
    """

    logit_bias: Optional[Dict[str, int]]
    """Modify the likelihood of specified tokens appearing in the completion.

    Accepts a JSON object that maps tokens (specified by their token ID in the
    tokenizer) to an associated bias value from -100 to 100. Mathematically, the
    bias is added to the logits generated by the model prior to sampling. The exact
    effect will vary per model, but values between -1 and 1 should decrease or
    increase likelihood of selection; values like -100 or 100 should result in a ban
    or exclusive selection of the relevant token.
    """

    logprobs: Optional[bool]
    """Whether to return log probabilities of the output tokens or not.

    If true, returns the log probabilities of each output token returned in the
    `content` of `message`. This option is currently not available on the
    `gpt-4-vision-preview` model.
    """

    max_tokens: Optional[int]
    """
    The maximum number of [tokens](/tokenizer) that can be generated in the chat
    completion.

    The total length of input tokens and generated tokens is limited by the model's
    context length.
    [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
    for counting tokens.
    """

    n: Optional[int]
    """How many chat completion choices to generate for each input message.

    Note that you will be charged based on the number of generated tokens across all
    of the choices. Keep `n` as `1` to minimize costs.
    """

    presence_penalty: Optional[float]
    """Number between -2.0 and 2.0.

    Positive values penalize new tokens based on whether they appear in the text so
    far, increasing the model's likelihood to talk about new topics.

    [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
    """

    response_format: ResponseFormat
    """An object specifying the format that the model must output.

    Compatible with
    [GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
    all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.

    Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees 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.
    """

    seed: Optional[int]
    """
    This feature is in Beta. If specified, our system will make a best effort to
    sample deterministically, such that repeated requests with the same `seed` and
    parameters should return the same result. Determinism is not guaranteed, and you
    should refer to the `system_fingerprint` response parameter to monitor changes
    in the backend.
    """

    stop: Union[Optional[str], List[str]]
    """Up to 4 sequences where the API will stop generating further tokens."""

    temperature: Optional[float]
    """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.

    We generally recommend altering this or `top_p` but not both.
    """

    tool_choice: ChatCompletionToolChoiceOptionParam
    """
    Controls which (if any) function is called by the model. `none` means the model
    will not call a function and instead generates a message. `auto` means the model
    can pick between generating a message or calling a function. Specifying a
    particular function via
    `{"type": "function", "function": {"name": "my_function"}}` forces the model to
    call that function.

    `none` is the default when no functions are present. `auto` is the default if
    functions are present.
    """

    tools: Iterable[ChatCompletionToolParam]
    """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_logprobs: Optional[int]
    """
    An integer between 0 and 20 specifying the number of most likely tokens to
    return at each token position, each with an associated log probability.
    `logprobs` must be set to `true` if this parameter is used.
    """

    top_p: Optional[float]
    """
    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.
    """

    user: str
    """
    A unique identifier representing your end-user, which can help OpenAI to monitor
    and detect abuse.
    [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
    """


FunctionCall = Union[Literal["none", "auto"], ChatCompletionFunctionCallOptionParam]


class Function(TypedDict, total=False):
    name: Required[str]
    """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: str
    """
    A description of what the function does, used by the model to choose when and
    how to call the function.
    """

    parameters: shared_params.FunctionParameters
    """The parameters the functions accepts, described as a JSON Schema object.

    See the
    [guide](https://platform.openai.com/docs/guides/text-generation/function-calling)
    for examples, and the
    [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for
    documentation about the format.

    Omitting `parameters` defines a function with an empty parameter list.
    """


class ResponseFormat(TypedDict, total=False):
    type: Literal["text", "json_object"]
    """Must be one of `text` or `json_object`."""


class CompletionCreateParamsNonStreaming(CompletionCreateParamsBase):
    stream: Optional[Literal[False]]
    """If set, partial message deltas will be sent, like in ChatGPT.

    Tokens will be sent as data-only
    [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
    as they become available, with the stream terminated by a `data: [DONE]`
    message.
    [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).
    """


class CompletionCreateParamsStreaming(CompletionCreateParamsBase):
    stream: Required[Literal[True]]
    """If set, partial message deltas will be sent, like in ChatGPT.

    Tokens will be sent as data-only
    [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
    as they become available, with the stream terminated by a `data: [DONE]`
    message.
    [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).
    """


CompletionCreateParams = Union[CompletionCreateParamsNonStreaming, CompletionCreateParamsStreaming]
