"""Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT."""

from __future__ import annotations
from openrouter.types import BaseModel, Nullable, UNSET_SENTINEL, UnrecognizedStr
from openrouter.utils import (
    FieldMetadata,
    HeaderMetadata,
    QueryParamMetadata,
    validate_open_enum,
)
import pydantic
from pydantic import model_serializer
from pydantic.functional_validators import PlainValidator
from typing import List, Literal, Optional, Union
from typing_extensions import Annotated, NotRequired, TypedDict


class GetGenerationGlobalsTypedDict(TypedDict):
    http_referer: NotRequired[str]
    r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
    This is used to track API usage per application.

    """
    x_open_router_title: NotRequired[str]
    r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.

    """
    x_open_router_categories: NotRequired[str]
    r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.

    """


class GetGenerationGlobals(BaseModel):
    http_referer: Annotated[
        Optional[str],
        pydantic.Field(alias="HTTP-Referer"),
        FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
    ] = None
    r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
    This is used to track API usage per application.

    """

    x_open_router_title: Annotated[
        Optional[str],
        pydantic.Field(alias="X-OpenRouter-Title"),
        FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
    ] = None
    r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.

    """

    x_open_router_categories: Annotated[
        Optional[str],
        pydantic.Field(alias="X-OpenRouter-Categories"),
        FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
    ] = None
    r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.

    """


class GetGenerationRequestTypedDict(TypedDict):
    id: str
    http_referer: NotRequired[str]
    r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
    This is used to track API usage per application.

    """
    x_open_router_title: NotRequired[str]
    r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.

    """
    x_open_router_categories: NotRequired[str]
    r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.

    """


class GetGenerationRequest(BaseModel):
    id: Annotated[
        str, FieldMetadata(query=QueryParamMetadata(style="form", explode=True))
    ]

    http_referer: Annotated[
        Optional[str],
        pydantic.Field(alias="HTTP-Referer"),
        FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
    ] = None
    r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
    This is used to track API usage per application.

    """

    x_open_router_title: Annotated[
        Optional[str],
        pydantic.Field(alias="X-OpenRouter-Title"),
        FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
    ] = None
    r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.

    """

    x_open_router_categories: Annotated[
        Optional[str],
        pydantic.Field(alias="X-OpenRouter-Categories"),
        FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
    ] = None
    r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.

    """


APIType = Union[
    Literal[
        "completions",
        "embeddings",
        "video",
    ],
    UnrecognizedStr,
]
r"""Type of API used for the generation"""


ProviderName = Union[
    Literal[
        "AnyScale",
        "Atoma",
        "Cent-ML",
        "CrofAI",
        "Enfer",
        "GoPomelo",
        "HuggingFace",
        "Hyperbolic 2",
        "InoCloud",
        "Kluster",
        "Lambda",
        "Lepton",
        "Lynn 2",
        "Lynn",
        "Mancer",
        "Meta",
        "Modal",
        "Nineteen",
        "OctoAI",
        "Recursal",
        "Reflection",
        "Replicate",
        "SambaNova 2",
        "SF Compute",
        "Targon",
        "Together 2",
        "Ubicloud",
        "01.AI",
        "AkashML",
        "AI21",
        "AionLabs",
        "Alibaba",
        "Ambient",
        "Amazon Bedrock",
        "Amazon Nova",
        "Anthropic",
        "Arcee AI",
        "AtlasCloud",
        "Avian",
        "Azure",
        "BaseTen",
        "BytePlus",
        "Black Forest Labs",
        "Cerebras",
        "Chutes",
        "Cirrascale",
        "Clarifai",
        "Cloudflare",
        "Cohere",
        "Crusoe",
        "DeepInfra",
        "DeepSeek",
        "Featherless",
        "Fireworks",
        "Friendli",
        "GMICloud",
        "Google",
        "Google AI Studio",
        "Groq",
        "Hyperbolic",
        "Inception",
        "Inceptron",
        "InferenceNet",
        "Ionstream",
        "Infermatic",
        "Io Net",
        "Inflection",
        "Liquid",
        "Mara",
        "Mancer 2",
        "Minimax",
        "ModelRun",
        "Mistral",
        "Modular",
        "Moonshot AI",
        "Morph",
        "NCompass",
        "Nebius",
        "NextBit",
        "Novita",
        "Nvidia",
        "OpenAI",
        "OpenInference",
        "Parasail",
        "Perplexity",
        "Phala",
        "Reka",
        "Relace",
        "SambaNova",
        "Seed",
        "SiliconFlow",
        "Sourceful",
        "StepFun",
        "Stealth",
        "StreamLake",
        "Switchpoint",
        "Together",
        "Upstage",
        "Venice",
        "WandB",
        "Xiaomi",
        "xAI",
        "Z.AI",
        "FakeProvider",
    ],
    UnrecognizedStr,
]


class ProviderResponseTypedDict(TypedDict):
    status: Nullable[float]
    id: NotRequired[str]
    endpoint_id: NotRequired[str]
    model_permaslug: NotRequired[str]
    provider_name: NotRequired[ProviderName]
    latency: NotRequired[float]
    is_byok: NotRequired[bool]


class ProviderResponse(BaseModel):
    status: Nullable[float]

    id: Optional[str] = None

    endpoint_id: Optional[str] = None

    model_permaslug: Optional[str] = None

    provider_name: Annotated[
        Optional[ProviderName], PlainValidator(validate_open_enum(False))
    ] = None

    latency: Optional[float] = None

    is_byok: Optional[bool] = None

    @model_serializer(mode="wrap")
    def serialize_model(self, handler):
        optional_fields = [
            "id",
            "endpoint_id",
            "model_permaslug",
            "provider_name",
            "latency",
            "is_byok",
        ]
        nullable_fields = ["status"]
        null_default_fields = []

        serialized = handler(self)

        m = {}

        for n, f in type(self).model_fields.items():
            k = f.alias or n
            val = serialized.get(k)
            serialized.pop(k, None)

            optional_nullable = k in optional_fields and k in nullable_fields
            is_set = (
                self.__pydantic_fields_set__.intersection({n})
                or k in null_default_fields
            )  # pylint: disable=no-member

            if val is not None and val != UNSET_SENTINEL:
                m[k] = val
            elif val != UNSET_SENTINEL and (
                not k in optional_fields or (optional_nullable and is_set)
            ):
                m[k] = val

        return m


class GetGenerationDataTypedDict(TypedDict):
    r"""Generation data"""

    id: str
    r"""Unique identifier for the generation"""
    upstream_id: Nullable[str]
    r"""Upstream provider's identifier for this generation"""
    total_cost: float
    r"""Total cost of the generation in USD"""
    cache_discount: Nullable[float]
    r"""Discount applied due to caching"""
    upstream_inference_cost: Nullable[float]
    r"""Cost charged by the upstream provider"""
    created_at: str
    r"""ISO 8601 timestamp of when the generation was created"""
    model: str
    r"""Model used for the generation"""
    app_id: Nullable[float]
    r"""ID of the app that made the request"""
    streamed: Nullable[bool]
    r"""Whether the response was streamed"""
    cancelled: Nullable[bool]
    r"""Whether the generation was cancelled"""
    provider_name: Nullable[str]
    r"""Name of the provider that served the request"""
    latency: Nullable[float]
    r"""Total latency in milliseconds"""
    moderation_latency: Nullable[float]
    r"""Moderation latency in milliseconds"""
    generation_time: Nullable[float]
    r"""Time taken for generation in milliseconds"""
    finish_reason: Nullable[str]
    r"""Reason the generation finished"""
    tokens_prompt: Nullable[float]
    r"""Number of tokens in the prompt"""
    tokens_completion: Nullable[float]
    r"""Number of tokens in the completion"""
    native_tokens_prompt: Nullable[float]
    r"""Native prompt tokens as reported by provider"""
    native_tokens_completion: Nullable[float]
    r"""Native completion tokens as reported by provider"""
    native_tokens_completion_images: Nullable[float]
    r"""Native completion image tokens as reported by provider"""
    native_tokens_reasoning: Nullable[float]
    r"""Native reasoning tokens as reported by provider"""
    native_tokens_cached: Nullable[float]
    r"""Native cached tokens as reported by provider"""
    num_media_prompt: Nullable[float]
    r"""Number of media items in the prompt"""
    num_input_audio_prompt: Nullable[float]
    r"""Number of audio inputs in the prompt"""
    num_media_completion: Nullable[float]
    r"""Number of media items in the completion"""
    num_search_results: Nullable[float]
    r"""Number of search results included"""
    origin: str
    r"""Origin URL of the request"""
    usage: float
    r"""Usage amount in USD"""
    is_byok: bool
    r"""Whether this used bring-your-own-key"""
    native_finish_reason: Nullable[str]
    r"""Native finish reason as reported by provider"""
    external_user: Nullable[str]
    r"""External user identifier"""
    api_type: Nullable[APIType]
    r"""Type of API used for the generation"""
    router: Nullable[str]
    r"""Router used for the request (e.g., openrouter/auto)"""
    provider_responses: Nullable[List[ProviderResponseTypedDict]]
    r"""List of provider responses for this generation, including fallback attempts"""
    user_agent: Nullable[str]
    r"""User-Agent header from the request"""
    http_referer: Nullable[str]
    r"""Referer header from the request"""


class GetGenerationData(BaseModel):
    r"""Generation data"""

    id: str
    r"""Unique identifier for the generation"""

    upstream_id: Nullable[str]
    r"""Upstream provider's identifier for this generation"""

    total_cost: float
    r"""Total cost of the generation in USD"""

    cache_discount: Nullable[float]
    r"""Discount applied due to caching"""

    upstream_inference_cost: Nullable[float]
    r"""Cost charged by the upstream provider"""

    created_at: str
    r"""ISO 8601 timestamp of when the generation was created"""

    model: str
    r"""Model used for the generation"""

    app_id: Nullable[float]
    r"""ID of the app that made the request"""

    streamed: Nullable[bool]
    r"""Whether the response was streamed"""

    cancelled: Nullable[bool]
    r"""Whether the generation was cancelled"""

    provider_name: Nullable[str]
    r"""Name of the provider that served the request"""

    latency: Nullable[float]
    r"""Total latency in milliseconds"""

    moderation_latency: Nullable[float]
    r"""Moderation latency in milliseconds"""

    generation_time: Nullable[float]
    r"""Time taken for generation in milliseconds"""

    finish_reason: Nullable[str]
    r"""Reason the generation finished"""

    tokens_prompt: Nullable[float]
    r"""Number of tokens in the prompt"""

    tokens_completion: Nullable[float]
    r"""Number of tokens in the completion"""

    native_tokens_prompt: Nullable[float]
    r"""Native prompt tokens as reported by provider"""

    native_tokens_completion: Nullable[float]
    r"""Native completion tokens as reported by provider"""

    native_tokens_completion_images: Nullable[float]
    r"""Native completion image tokens as reported by provider"""

    native_tokens_reasoning: Nullable[float]
    r"""Native reasoning tokens as reported by provider"""

    native_tokens_cached: Nullable[float]
    r"""Native cached tokens as reported by provider"""

    num_media_prompt: Nullable[float]
    r"""Number of media items in the prompt"""

    num_input_audio_prompt: Nullable[float]
    r"""Number of audio inputs in the prompt"""

    num_media_completion: Nullable[float]
    r"""Number of media items in the completion"""

    num_search_results: Nullable[float]
    r"""Number of search results included"""

    origin: str
    r"""Origin URL of the request"""

    usage: float
    r"""Usage amount in USD"""

    is_byok: bool
    r"""Whether this used bring-your-own-key"""

    native_finish_reason: Nullable[str]
    r"""Native finish reason as reported by provider"""

    external_user: Nullable[str]
    r"""External user identifier"""

    api_type: Annotated[Nullable[APIType], PlainValidator(validate_open_enum(False))]
    r"""Type of API used for the generation"""

    router: Nullable[str]
    r"""Router used for the request (e.g., openrouter/auto)"""

    provider_responses: Nullable[List[ProviderResponse]]
    r"""List of provider responses for this generation, including fallback attempts"""

    user_agent: Nullable[str]
    r"""User-Agent header from the request"""

    http_referer: Nullable[str]
    r"""Referer header from the request"""

    @model_serializer(mode="wrap")
    def serialize_model(self, handler):
        optional_fields = []
        nullable_fields = [
            "upstream_id",
            "cache_discount",
            "upstream_inference_cost",
            "app_id",
            "streamed",
            "cancelled",
            "provider_name",
            "latency",
            "moderation_latency",
            "generation_time",
            "finish_reason",
            "tokens_prompt",
            "tokens_completion",
            "native_tokens_prompt",
            "native_tokens_completion",
            "native_tokens_completion_images",
            "native_tokens_reasoning",
            "native_tokens_cached",
            "num_media_prompt",
            "num_input_audio_prompt",
            "num_media_completion",
            "num_search_results",
            "native_finish_reason",
            "external_user",
            "api_type",
            "router",
            "provider_responses",
            "user_agent",
            "http_referer",
        ]
        null_default_fields = []

        serialized = handler(self)

        m = {}

        for n, f in type(self).model_fields.items():
            k = f.alias or n
            val = serialized.get(k)
            serialized.pop(k, None)

            optional_nullable = k in optional_fields and k in nullable_fields
            is_set = (
                self.__pydantic_fields_set__.intersection({n})
                or k in null_default_fields
            )  # pylint: disable=no-member

            if val is not None and val != UNSET_SENTINEL:
                m[k] = val
            elif val != UNSET_SENTINEL and (
                not k in optional_fields or (optional_nullable and is_set)
            ):
                m[k] = val

        return m


class GetGenerationResponseTypedDict(TypedDict):
    r"""Generation response"""

    data: GetGenerationDataTypedDict
    r"""Generation data"""


class GetGenerationResponse(BaseModel):
    r"""Generation response"""

    data: GetGenerationData
    r"""Generation data"""
