Initial commit: Email alerts application

This commit is contained in:
Iyeoluwa Akinrinola
2025-07-25 11:31:36 +01:00
commit adfb625ae9
6322 changed files with 2882826 additions and 0 deletions
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
import typing as _t
from . import types
from ._types import NOT_GIVEN, Omit, NoneType, NotGiven, Transport, ProxiesTypes
from ._utils import file_from_path
from ._client import Groq, Client, Stream, Timeout, AsyncGroq, Transport, AsyncClient, AsyncStream, RequestOptions
from ._models import BaseModel
from ._version import __title__, __version__
from ._response import APIResponse as APIResponse, AsyncAPIResponse as AsyncAPIResponse
from ._constants import DEFAULT_TIMEOUT, DEFAULT_MAX_RETRIES, DEFAULT_CONNECTION_LIMITS
from ._exceptions import (
APIError,
GroqError,
ConflictError,
NotFoundError,
APIStatusError,
RateLimitError,
APITimeoutError,
BadRequestError,
APIConnectionError,
AuthenticationError,
InternalServerError,
PermissionDeniedError,
UnprocessableEntityError,
APIResponseValidationError,
)
from ._base_client import DefaultHttpxClient, DefaultAioHttpClient, DefaultAsyncHttpxClient
from ._utils._logs import setup_logging as _setup_logging
__all__ = [
"types",
"__version__",
"__title__",
"NoneType",
"Transport",
"ProxiesTypes",
"NotGiven",
"NOT_GIVEN",
"Omit",
"GroqError",
"APIError",
"APIStatusError",
"APITimeoutError",
"APIConnectionError",
"APIResponseValidationError",
"BadRequestError",
"AuthenticationError",
"PermissionDeniedError",
"NotFoundError",
"ConflictError",
"UnprocessableEntityError",
"RateLimitError",
"InternalServerError",
"Timeout",
"RequestOptions",
"Client",
"AsyncClient",
"Stream",
"AsyncStream",
"Groq",
"AsyncGroq",
"file_from_path",
"BaseModel",
"DEFAULT_TIMEOUT",
"DEFAULT_MAX_RETRIES",
"DEFAULT_CONNECTION_LIMITS",
"DefaultHttpxClient",
"DefaultAsyncHttpxClient",
"DefaultAioHttpClient",
]
if not _t.TYPE_CHECKING:
from ._utils._resources_proxy import resources as resources
_setup_logging()
# Update the __module__ attribute for exported symbols so that
# error messages point to this module instead of the module
# it was originally defined in, e.g.
# groq._exceptions.NotFoundError -> groq.NotFoundError
__locals = locals()
for __name in __all__:
if not __name.startswith("__"):
try:
__locals[__name].__module__ = "groq"
except (TypeError, AttributeError):
# Some of our exported symbols are builtins which we can't set attributes for.
pass
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
import os
from typing import TYPE_CHECKING, Any, Union, Mapping
from typing_extensions import Self, override
import httpx
from . import _exceptions
from ._qs import Querystring
from ._types import (
NOT_GIVEN,
Omit,
Timeout,
NotGiven,
Transport,
ProxiesTypes,
RequestOptions,
)
from ._utils import is_given, get_async_library
from ._compat import cached_property
from ._version import __version__
from ._streaming import Stream as Stream, AsyncStream as AsyncStream
from ._exceptions import GroqError, APIStatusError
from ._base_client import (
DEFAULT_MAX_RETRIES,
SyncAPIClient,
AsyncAPIClient,
)
if TYPE_CHECKING:
from .resources import chat, audio, files, models, batches, embeddings
from .resources.files import Files, AsyncFiles
from .resources.models import Models, AsyncModels
from .resources.batches import Batches, AsyncBatches
from .resources.chat.chat import Chat, AsyncChat
from .resources.embeddings import Embeddings, AsyncEmbeddings
from .resources.audio.audio import Audio, AsyncAudio
__all__ = ["Timeout", "Transport", "ProxiesTypes", "RequestOptions", "Groq", "AsyncGroq", "Client", "AsyncClient"]
class Groq(SyncAPIClient):
# client options
api_key: str
def __init__(
self,
*,
api_key: str | None = None,
base_url: str | httpx.URL | None = None,
timeout: Union[float, Timeout, None, NotGiven] = NOT_GIVEN,
max_retries: int = DEFAULT_MAX_RETRIES,
default_headers: Mapping[str, str] | None = None,
default_query: Mapping[str, object] | None = None,
# Configure a custom httpx client.
# We provide a `DefaultHttpxClient` class that you can pass to retain the default values we use for `limits`, `timeout` & `follow_redirects`.
# See the [httpx documentation](https://www.python-httpx.org/api/#client) for more details.
http_client: httpx.Client | None = None,
# Enable or disable schema validation for data returned by the API.
# When enabled an error APIResponseValidationError is raised
# if the API responds with invalid data for the expected schema.
#
# This parameter may be removed or changed in the future.
# If you rely on this feature, please open a GitHub issue
# outlining your use-case to help us decide if it should be
# part of our public interface in the future.
_strict_response_validation: bool = False,
) -> None:
"""Construct a new synchronous Groq client instance.
This automatically infers the `api_key` argument from the `GROQ_API_KEY` environment variable if it is not provided.
"""
if api_key is None:
api_key = os.environ.get("GROQ_API_KEY")
if api_key is None:
raise GroqError(
"The api_key client option must be set either by passing api_key to the client or by setting the GROQ_API_KEY environment variable"
)
self.api_key = api_key
if base_url is None:
base_url = os.environ.get("GROQ_BASE_URL")
if base_url is None:
base_url = f"https://api.groq.com"
super().__init__(
version=__version__,
base_url=base_url,
max_retries=max_retries,
timeout=timeout,
http_client=http_client,
custom_headers=default_headers,
custom_query=default_query,
_strict_response_validation=_strict_response_validation,
)
@cached_property
def chat(self) -> Chat:
from .resources.chat import Chat
return Chat(self)
@cached_property
def embeddings(self) -> Embeddings:
from .resources.embeddings import Embeddings
return Embeddings(self)
@cached_property
def audio(self) -> Audio:
from .resources.audio import Audio
return Audio(self)
@cached_property
def models(self) -> Models:
from .resources.models import Models
return Models(self)
@cached_property
def batches(self) -> Batches:
from .resources.batches import Batches
return Batches(self)
@cached_property
def files(self) -> Files:
from .resources.files import Files
return Files(self)
@cached_property
def with_raw_response(self) -> GroqWithRawResponse:
return GroqWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> GroqWithStreamedResponse:
return GroqWithStreamedResponse(self)
@property
@override
def qs(self) -> Querystring:
return Querystring(array_format="comma")
@property
@override
def auth_headers(self) -> dict[str, str]:
api_key = self.api_key
return {"Authorization": f"Bearer {api_key}"}
@property
@override
def default_headers(self) -> dict[str, str | Omit]:
return {
**super().default_headers,
"X-Stainless-Async": "false",
**self._custom_headers,
}
def copy(
self,
*,
api_key: str | None = None,
base_url: str | httpx.URL | None = None,
timeout: float | Timeout | None | NotGiven = NOT_GIVEN,
http_client: httpx.Client | None = None,
max_retries: int | NotGiven = NOT_GIVEN,
default_headers: Mapping[str, str] | None = None,
set_default_headers: Mapping[str, str] | None = None,
default_query: Mapping[str, object] | None = None,
set_default_query: Mapping[str, object] | None = None,
_extra_kwargs: Mapping[str, Any] = {},
) -> Self:
"""
Create a new client instance re-using the same options given to the current client with optional overriding.
"""
if default_headers is not None and set_default_headers is not None:
raise ValueError("The `default_headers` and `set_default_headers` arguments are mutually exclusive")
if default_query is not None and set_default_query is not None:
raise ValueError("The `default_query` and `set_default_query` arguments are mutually exclusive")
headers = self._custom_headers
if default_headers is not None:
headers = {**headers, **default_headers}
elif set_default_headers is not None:
headers = set_default_headers
params = self._custom_query
if default_query is not None:
params = {**params, **default_query}
elif set_default_query is not None:
params = set_default_query
http_client = http_client or self._client
return self.__class__(
api_key=api_key or self.api_key,
base_url=base_url or self.base_url,
timeout=self.timeout if isinstance(timeout, NotGiven) else timeout,
http_client=http_client,
max_retries=max_retries if is_given(max_retries) else self.max_retries,
default_headers=headers,
default_query=params,
**_extra_kwargs,
)
# Alias for `copy` for nicer inline usage, e.g.
# client.with_options(timeout=10).foo.create(...)
with_options = copy
@override
def _make_status_error(
self,
err_msg: str,
*,
body: object,
response: httpx.Response,
) -> APIStatusError:
if response.status_code == 400:
return _exceptions.BadRequestError(err_msg, response=response, body=body)
if response.status_code == 401:
return _exceptions.AuthenticationError(err_msg, response=response, body=body)
if response.status_code == 403:
return _exceptions.PermissionDeniedError(err_msg, response=response, body=body)
if response.status_code == 404:
return _exceptions.NotFoundError(err_msg, response=response, body=body)
if response.status_code == 409:
return _exceptions.ConflictError(err_msg, response=response, body=body)
if response.status_code == 422:
return _exceptions.UnprocessableEntityError(err_msg, response=response, body=body)
if response.status_code == 429:
return _exceptions.RateLimitError(err_msg, response=response, body=body)
if response.status_code >= 500:
return _exceptions.InternalServerError(err_msg, response=response, body=body)
return APIStatusError(err_msg, response=response, body=body)
class AsyncGroq(AsyncAPIClient):
# client options
api_key: str
def __init__(
self,
*,
api_key: str | None = None,
base_url: str | httpx.URL | None = None,
timeout: Union[float, Timeout, None, NotGiven] = NOT_GIVEN,
max_retries: int = DEFAULT_MAX_RETRIES,
default_headers: Mapping[str, str] | None = None,
default_query: Mapping[str, object] | None = None,
# Configure a custom httpx client.
# We provide a `DefaultAsyncHttpxClient` class that you can pass to retain the default values we use for `limits`, `timeout` & `follow_redirects`.
# See the [httpx documentation](https://www.python-httpx.org/api/#asyncclient) for more details.
http_client: httpx.AsyncClient | None = None,
# Enable or disable schema validation for data returned by the API.
# When enabled an error APIResponseValidationError is raised
# if the API responds with invalid data for the expected schema.
#
# This parameter may be removed or changed in the future.
# If you rely on this feature, please open a GitHub issue
# outlining your use-case to help us decide if it should be
# part of our public interface in the future.
_strict_response_validation: bool = False,
) -> None:
"""Construct a new async AsyncGroq client instance.
This automatically infers the `api_key` argument from the `GROQ_API_KEY` environment variable if it is not provided.
"""
if api_key is None:
api_key = os.environ.get("GROQ_API_KEY")
if api_key is None:
raise GroqError(
"The api_key client option must be set either by passing api_key to the client or by setting the GROQ_API_KEY environment variable"
)
self.api_key = api_key
if base_url is None:
base_url = os.environ.get("GROQ_BASE_URL")
if base_url is None:
base_url = f"https://api.groq.com"
super().__init__(
version=__version__,
base_url=base_url,
max_retries=max_retries,
timeout=timeout,
http_client=http_client,
custom_headers=default_headers,
custom_query=default_query,
_strict_response_validation=_strict_response_validation,
)
@cached_property
def chat(self) -> AsyncChat:
from .resources.chat import AsyncChat
return AsyncChat(self)
@cached_property
def embeddings(self) -> AsyncEmbeddings:
from .resources.embeddings import AsyncEmbeddings
return AsyncEmbeddings(self)
@cached_property
def audio(self) -> AsyncAudio:
from .resources.audio import AsyncAudio
return AsyncAudio(self)
@cached_property
def models(self) -> AsyncModels:
from .resources.models import AsyncModels
return AsyncModels(self)
@cached_property
def batches(self) -> AsyncBatches:
from .resources.batches import AsyncBatches
return AsyncBatches(self)
@cached_property
def files(self) -> AsyncFiles:
from .resources.files import AsyncFiles
return AsyncFiles(self)
@cached_property
def with_raw_response(self) -> AsyncGroqWithRawResponse:
return AsyncGroqWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncGroqWithStreamedResponse:
return AsyncGroqWithStreamedResponse(self)
@property
@override
def qs(self) -> Querystring:
return Querystring(array_format="comma")
@property
@override
def auth_headers(self) -> dict[str, str]:
api_key = self.api_key
return {"Authorization": f"Bearer {api_key}"}
@property
@override
def default_headers(self) -> dict[str, str | Omit]:
return {
**super().default_headers,
"X-Stainless-Async": f"async:{get_async_library()}",
**self._custom_headers,
}
def copy(
self,
*,
api_key: str | None = None,
base_url: str | httpx.URL | None = None,
timeout: float | Timeout | None | NotGiven = NOT_GIVEN,
http_client: httpx.AsyncClient | None = None,
max_retries: int | NotGiven = NOT_GIVEN,
default_headers: Mapping[str, str] | None = None,
set_default_headers: Mapping[str, str] | None = None,
default_query: Mapping[str, object] | None = None,
set_default_query: Mapping[str, object] | None = None,
_extra_kwargs: Mapping[str, Any] = {},
) -> Self:
"""
Create a new client instance re-using the same options given to the current client with optional overriding.
"""
if default_headers is not None and set_default_headers is not None:
raise ValueError("The `default_headers` and `set_default_headers` arguments are mutually exclusive")
if default_query is not None and set_default_query is not None:
raise ValueError("The `default_query` and `set_default_query` arguments are mutually exclusive")
headers = self._custom_headers
if default_headers is not None:
headers = {**headers, **default_headers}
elif set_default_headers is not None:
headers = set_default_headers
params = self._custom_query
if default_query is not None:
params = {**params, **default_query}
elif set_default_query is not None:
params = set_default_query
http_client = http_client or self._client
return self.__class__(
api_key=api_key or self.api_key,
base_url=base_url or self.base_url,
timeout=self.timeout if isinstance(timeout, NotGiven) else timeout,
http_client=http_client,
max_retries=max_retries if is_given(max_retries) else self.max_retries,
default_headers=headers,
default_query=params,
**_extra_kwargs,
)
# Alias for `copy` for nicer inline usage, e.g.
# client.with_options(timeout=10).foo.create(...)
with_options = copy
@override
def _make_status_error(
self,
err_msg: str,
*,
body: object,
response: httpx.Response,
) -> APIStatusError:
if response.status_code == 400:
return _exceptions.BadRequestError(err_msg, response=response, body=body)
if response.status_code == 401:
return _exceptions.AuthenticationError(err_msg, response=response, body=body)
if response.status_code == 403:
return _exceptions.PermissionDeniedError(err_msg, response=response, body=body)
if response.status_code == 404:
return _exceptions.NotFoundError(err_msg, response=response, body=body)
if response.status_code == 409:
return _exceptions.ConflictError(err_msg, response=response, body=body)
if response.status_code == 422:
return _exceptions.UnprocessableEntityError(err_msg, response=response, body=body)
if response.status_code == 429:
return _exceptions.RateLimitError(err_msg, response=response, body=body)
if response.status_code >= 500:
return _exceptions.InternalServerError(err_msg, response=response, body=body)
return APIStatusError(err_msg, response=response, body=body)
class GroqWithRawResponse:
_client: Groq
def __init__(self, client: Groq) -> None:
self._client = client
@cached_property
def chat(self) -> chat.ChatWithRawResponse:
from .resources.chat import ChatWithRawResponse
return ChatWithRawResponse(self._client.chat)
@cached_property
def embeddings(self) -> embeddings.EmbeddingsWithRawResponse:
from .resources.embeddings import EmbeddingsWithRawResponse
return EmbeddingsWithRawResponse(self._client.embeddings)
@cached_property
def audio(self) -> audio.AudioWithRawResponse:
from .resources.audio import AudioWithRawResponse
return AudioWithRawResponse(self._client.audio)
@cached_property
def models(self) -> models.ModelsWithRawResponse:
from .resources.models import ModelsWithRawResponse
return ModelsWithRawResponse(self._client.models)
@cached_property
def batches(self) -> batches.BatchesWithRawResponse:
from .resources.batches import BatchesWithRawResponse
return BatchesWithRawResponse(self._client.batches)
@cached_property
def files(self) -> files.FilesWithRawResponse:
from .resources.files import FilesWithRawResponse
return FilesWithRawResponse(self._client.files)
class AsyncGroqWithRawResponse:
_client: AsyncGroq
def __init__(self, client: AsyncGroq) -> None:
self._client = client
@cached_property
def chat(self) -> chat.AsyncChatWithRawResponse:
from .resources.chat import AsyncChatWithRawResponse
return AsyncChatWithRawResponse(self._client.chat)
@cached_property
def embeddings(self) -> embeddings.AsyncEmbeddingsWithRawResponse:
from .resources.embeddings import AsyncEmbeddingsWithRawResponse
return AsyncEmbeddingsWithRawResponse(self._client.embeddings)
@cached_property
def audio(self) -> audio.AsyncAudioWithRawResponse:
from .resources.audio import AsyncAudioWithRawResponse
return AsyncAudioWithRawResponse(self._client.audio)
@cached_property
def models(self) -> models.AsyncModelsWithRawResponse:
from .resources.models import AsyncModelsWithRawResponse
return AsyncModelsWithRawResponse(self._client.models)
@cached_property
def batches(self) -> batches.AsyncBatchesWithRawResponse:
from .resources.batches import AsyncBatchesWithRawResponse
return AsyncBatchesWithRawResponse(self._client.batches)
@cached_property
def files(self) -> files.AsyncFilesWithRawResponse:
from .resources.files import AsyncFilesWithRawResponse
return AsyncFilesWithRawResponse(self._client.files)
class GroqWithStreamedResponse:
_client: Groq
def __init__(self, client: Groq) -> None:
self._client = client
@cached_property
def chat(self) -> chat.ChatWithStreamingResponse:
from .resources.chat import ChatWithStreamingResponse
return ChatWithStreamingResponse(self._client.chat)
@cached_property
def embeddings(self) -> embeddings.EmbeddingsWithStreamingResponse:
from .resources.embeddings import EmbeddingsWithStreamingResponse
return EmbeddingsWithStreamingResponse(self._client.embeddings)
@cached_property
def audio(self) -> audio.AudioWithStreamingResponse:
from .resources.audio import AudioWithStreamingResponse
return AudioWithStreamingResponse(self._client.audio)
@cached_property
def models(self) -> models.ModelsWithStreamingResponse:
from .resources.models import ModelsWithStreamingResponse
return ModelsWithStreamingResponse(self._client.models)
@cached_property
def batches(self) -> batches.BatchesWithStreamingResponse:
from .resources.batches import BatchesWithStreamingResponse
return BatchesWithStreamingResponse(self._client.batches)
@cached_property
def files(self) -> files.FilesWithStreamingResponse:
from .resources.files import FilesWithStreamingResponse
return FilesWithStreamingResponse(self._client.files)
class AsyncGroqWithStreamedResponse:
_client: AsyncGroq
def __init__(self, client: AsyncGroq) -> None:
self._client = client
@cached_property
def chat(self) -> chat.AsyncChatWithStreamingResponse:
from .resources.chat import AsyncChatWithStreamingResponse
return AsyncChatWithStreamingResponse(self._client.chat)
@cached_property
def embeddings(self) -> embeddings.AsyncEmbeddingsWithStreamingResponse:
from .resources.embeddings import AsyncEmbeddingsWithStreamingResponse
return AsyncEmbeddingsWithStreamingResponse(self._client.embeddings)
@cached_property
def audio(self) -> audio.AsyncAudioWithStreamingResponse:
from .resources.audio import AsyncAudioWithStreamingResponse
return AsyncAudioWithStreamingResponse(self._client.audio)
@cached_property
def models(self) -> models.AsyncModelsWithStreamingResponse:
from .resources.models import AsyncModelsWithStreamingResponse
return AsyncModelsWithStreamingResponse(self._client.models)
@cached_property
def batches(self) -> batches.AsyncBatchesWithStreamingResponse:
from .resources.batches import AsyncBatchesWithStreamingResponse
return AsyncBatchesWithStreamingResponse(self._client.batches)
@cached_property
def files(self) -> files.AsyncFilesWithStreamingResponse:
from .resources.files import AsyncFilesWithStreamingResponse
return AsyncFilesWithStreamingResponse(self._client.files)
Client = Groq
AsyncClient = AsyncGroq
@@ -0,0 +1,219 @@
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Union, Generic, TypeVar, Callable, cast, overload
from datetime import date, datetime
from typing_extensions import Self, Literal
import pydantic
from pydantic.fields import FieldInfo
from ._types import IncEx, StrBytesIntFloat
_T = TypeVar("_T")
_ModelT = TypeVar("_ModelT", bound=pydantic.BaseModel)
# --------------- Pydantic v2 compatibility ---------------
# Pyright incorrectly reports some of our functions as overriding a method when they don't
# pyright: reportIncompatibleMethodOverride=false
PYDANTIC_V2 = pydantic.VERSION.startswith("2.")
# v1 re-exports
if TYPE_CHECKING:
def parse_date(value: date | StrBytesIntFloat) -> date: # noqa: ARG001
...
def parse_datetime(value: Union[datetime, StrBytesIntFloat]) -> datetime: # noqa: ARG001
...
def get_args(t: type[Any]) -> tuple[Any, ...]: # noqa: ARG001
...
def is_union(tp: type[Any] | None) -> bool: # noqa: ARG001
...
def get_origin(t: type[Any]) -> type[Any] | None: # noqa: ARG001
...
def is_literal_type(type_: type[Any]) -> bool: # noqa: ARG001
...
def is_typeddict(type_: type[Any]) -> bool: # noqa: ARG001
...
else:
if PYDANTIC_V2:
from pydantic.v1.typing import (
get_args as get_args,
is_union as is_union,
get_origin as get_origin,
is_typeddict as is_typeddict,
is_literal_type as is_literal_type,
)
from pydantic.v1.datetime_parse import parse_date as parse_date, parse_datetime as parse_datetime
else:
from pydantic.typing import (
get_args as get_args,
is_union as is_union,
get_origin as get_origin,
is_typeddict as is_typeddict,
is_literal_type as is_literal_type,
)
from pydantic.datetime_parse import parse_date as parse_date, parse_datetime as parse_datetime
# refactored config
if TYPE_CHECKING:
from pydantic import ConfigDict as ConfigDict
else:
if PYDANTIC_V2:
from pydantic import ConfigDict
else:
# TODO: provide an error message here?
ConfigDict = None
# renamed methods / properties
def parse_obj(model: type[_ModelT], value: object) -> _ModelT:
if PYDANTIC_V2:
return model.model_validate(value)
else:
return cast(_ModelT, model.parse_obj(value)) # pyright: ignore[reportDeprecated, reportUnnecessaryCast]
def field_is_required(field: FieldInfo) -> bool:
if PYDANTIC_V2:
return field.is_required()
return field.required # type: ignore
def field_get_default(field: FieldInfo) -> Any:
value = field.get_default()
if PYDANTIC_V2:
from pydantic_core import PydanticUndefined
if value == PydanticUndefined:
return None
return value
return value
def field_outer_type(field: FieldInfo) -> Any:
if PYDANTIC_V2:
return field.annotation
return field.outer_type_ # type: ignore
def get_model_config(model: type[pydantic.BaseModel]) -> Any:
if PYDANTIC_V2:
return model.model_config
return model.__config__ # type: ignore
def get_model_fields(model: type[pydantic.BaseModel]) -> dict[str, FieldInfo]:
if PYDANTIC_V2:
return model.model_fields
return model.__fields__ # type: ignore
def model_copy(model: _ModelT, *, deep: bool = False) -> _ModelT:
if PYDANTIC_V2:
return model.model_copy(deep=deep)
return model.copy(deep=deep) # type: ignore
def model_json(model: pydantic.BaseModel, *, indent: int | None = None) -> str:
if PYDANTIC_V2:
return model.model_dump_json(indent=indent)
return model.json(indent=indent) # type: ignore
def model_dump(
model: pydantic.BaseModel,
*,
exclude: IncEx | None = None,
exclude_unset: bool = False,
exclude_defaults: bool = False,
warnings: bool = True,
mode: Literal["json", "python"] = "python",
) -> dict[str, Any]:
if PYDANTIC_V2 or hasattr(model, "model_dump"):
return model.model_dump(
mode=mode,
exclude=exclude,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
# warnings are not supported in Pydantic v1
warnings=warnings if PYDANTIC_V2 else True,
)
return cast(
"dict[str, Any]",
model.dict( # pyright: ignore[reportDeprecated, reportUnnecessaryCast]
exclude=exclude,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
),
)
def model_parse(model: type[_ModelT], data: Any) -> _ModelT:
if PYDANTIC_V2:
return model.model_validate(data)
return model.parse_obj(data) # pyright: ignore[reportDeprecated]
# generic models
if TYPE_CHECKING:
class GenericModel(pydantic.BaseModel): ...
else:
if PYDANTIC_V2:
# there no longer needs to be a distinction in v2 but
# we still have to create our own subclass to avoid
# inconsistent MRO ordering errors
class GenericModel(pydantic.BaseModel): ...
else:
import pydantic.generics
class GenericModel(pydantic.generics.GenericModel, pydantic.BaseModel): ...
# cached properties
if TYPE_CHECKING:
cached_property = property
# we define a separate type (copied from typeshed)
# that represents that `cached_property` is `set`able
# at runtime, which differs from `@property`.
#
# this is a separate type as editors likely special case
# `@property` and we don't want to cause issues just to have
# more helpful internal types.
class typed_cached_property(Generic[_T]):
func: Callable[[Any], _T]
attrname: str | None
def __init__(self, func: Callable[[Any], _T]) -> None: ...
@overload
def __get__(self, instance: None, owner: type[Any] | None = None) -> Self: ...
@overload
def __get__(self, instance: object, owner: type[Any] | None = None) -> _T: ...
def __get__(self, instance: object, owner: type[Any] | None = None) -> _T | Self:
raise NotImplementedError()
def __set_name__(self, owner: type[Any], name: str) -> None: ...
# __set__ is not defined at runtime, but @cached_property is designed to be settable
def __set__(self, instance: object, value: _T) -> None: ...
else:
from functools import cached_property as cached_property
typed_cached_property = cached_property
@@ -0,0 +1,14 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
import httpx
RAW_RESPONSE_HEADER = "X-Stainless-Raw-Response"
OVERRIDE_CAST_TO_HEADER = "____stainless_override_cast_to"
# default timeout is 1 minute
DEFAULT_TIMEOUT = httpx.Timeout(timeout=60, connect=5.0)
DEFAULT_MAX_RETRIES = 2
DEFAULT_CONNECTION_LIMITS = httpx.Limits(max_connections=100, max_keepalive_connections=20)
INITIAL_RETRY_DELAY = 0.5
MAX_RETRY_DELAY = 8.0
@@ -0,0 +1,108 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing_extensions import Literal
import httpx
__all__ = [
"BadRequestError",
"AuthenticationError",
"PermissionDeniedError",
"NotFoundError",
"ConflictError",
"UnprocessableEntityError",
"RateLimitError",
"InternalServerError",
]
class GroqError(Exception):
pass
class APIError(GroqError):
message: str
request: httpx.Request
body: object | None
"""The API response body.
If the API responded with a valid JSON structure then this property will be the
decoded result.
If it isn't a valid JSON structure then this will be the raw response.
If there was no response associated with this error then it will be `None`.
"""
def __init__(self, message: str, request: httpx.Request, *, body: object | None) -> None: # noqa: ARG002
super().__init__(message)
self.request = request
self.message = message
self.body = body
class APIResponseValidationError(APIError):
response: httpx.Response
status_code: int
def __init__(self, response: httpx.Response, body: object | None, *, message: str | None = None) -> None:
super().__init__(message or "Data returned by API invalid for expected schema.", response.request, body=body)
self.response = response
self.status_code = response.status_code
class APIStatusError(APIError):
"""Raised when an API response has a status code of 4xx or 5xx."""
response: httpx.Response
status_code: int
def __init__(self, message: str, *, response: httpx.Response, body: object | None) -> None:
super().__init__(message, response.request, body=body)
self.response = response
self.status_code = response.status_code
class APIConnectionError(APIError):
def __init__(self, *, message: str = "Connection error.", request: httpx.Request) -> None:
super().__init__(message, request, body=None)
class APITimeoutError(APIConnectionError):
def __init__(self, request: httpx.Request) -> None:
super().__init__(message="Request timed out.", request=request)
class BadRequestError(APIStatusError):
status_code: Literal[400] = 400 # pyright: ignore[reportIncompatibleVariableOverride]
class AuthenticationError(APIStatusError):
status_code: Literal[401] = 401 # pyright: ignore[reportIncompatibleVariableOverride]
class PermissionDeniedError(APIStatusError):
status_code: Literal[403] = 403 # pyright: ignore[reportIncompatibleVariableOverride]
class NotFoundError(APIStatusError):
status_code: Literal[404] = 404 # pyright: ignore[reportIncompatibleVariableOverride]
class ConflictError(APIStatusError):
status_code: Literal[409] = 409 # pyright: ignore[reportIncompatibleVariableOverride]
class UnprocessableEntityError(APIStatusError):
status_code: Literal[422] = 422 # pyright: ignore[reportIncompatibleVariableOverride]
class RateLimitError(APIStatusError):
status_code: Literal[429] = 429 # pyright: ignore[reportIncompatibleVariableOverride]
class InternalServerError(APIStatusError):
pass
@@ -0,0 +1,123 @@
from __future__ import annotations
import io
import os
import pathlib
from typing import overload
from typing_extensions import TypeGuard
import anyio
from ._types import (
FileTypes,
FileContent,
RequestFiles,
HttpxFileTypes,
Base64FileInput,
HttpxFileContent,
HttpxRequestFiles,
)
from ._utils import is_tuple_t, is_mapping_t, is_sequence_t
def is_base64_file_input(obj: object) -> TypeGuard[Base64FileInput]:
return isinstance(obj, io.IOBase) or isinstance(obj, os.PathLike)
def is_file_content(obj: object) -> TypeGuard[FileContent]:
return (
isinstance(obj, bytes) or isinstance(obj, tuple) or isinstance(obj, io.IOBase) or isinstance(obj, os.PathLike)
)
def assert_is_file_content(obj: object, *, key: str | None = None) -> None:
if not is_file_content(obj):
prefix = f"Expected entry at `{key}`" if key is not None else f"Expected file input `{obj!r}`"
raise RuntimeError(
f"{prefix} to be bytes, an io.IOBase instance, PathLike or a tuple but received {type(obj)} instead. See https://github.com/groq/groq-python/tree/main#file-uploads"
) from None
@overload
def to_httpx_files(files: None) -> None: ...
@overload
def to_httpx_files(files: RequestFiles) -> HttpxRequestFiles: ...
def to_httpx_files(files: RequestFiles | None) -> HttpxRequestFiles | None:
if files is None:
return None
if is_mapping_t(files):
files = {key: _transform_file(file) for key, file in files.items()}
elif is_sequence_t(files):
files = [(key, _transform_file(file)) for key, file in files]
else:
raise TypeError(f"Unexpected file type input {type(files)}, expected mapping or sequence")
return files
def _transform_file(file: FileTypes) -> HttpxFileTypes:
if is_file_content(file):
if isinstance(file, os.PathLike):
path = pathlib.Path(file)
return (path.name, path.read_bytes())
return file
if is_tuple_t(file):
return (file[0], _read_file_content(file[1]), *file[2:])
raise TypeError(f"Expected file types input to be a FileContent type or to be a tuple")
def _read_file_content(file: FileContent) -> HttpxFileContent:
if isinstance(file, os.PathLike):
return pathlib.Path(file).read_bytes()
return file
@overload
async def async_to_httpx_files(files: None) -> None: ...
@overload
async def async_to_httpx_files(files: RequestFiles) -> HttpxRequestFiles: ...
async def async_to_httpx_files(files: RequestFiles | None) -> HttpxRequestFiles | None:
if files is None:
return None
if is_mapping_t(files):
files = {key: await _async_transform_file(file) for key, file in files.items()}
elif is_sequence_t(files):
files = [(key, await _async_transform_file(file)) for key, file in files]
else:
raise TypeError("Unexpected file type input {type(files)}, expected mapping or sequence")
return files
async def _async_transform_file(file: FileTypes) -> HttpxFileTypes:
if is_file_content(file):
if isinstance(file, os.PathLike):
path = anyio.Path(file)
return (path.name, await path.read_bytes())
return file
if is_tuple_t(file):
return (file[0], await _async_read_file_content(file[1]), *file[2:])
raise TypeError(f"Expected file types input to be a FileContent type or to be a tuple")
async def _async_read_file_content(file: FileContent) -> HttpxFileContent:
if isinstance(file, os.PathLike):
return await anyio.Path(file).read_bytes()
return file
@@ -0,0 +1,808 @@
from __future__ import annotations
import os
import inspect
from typing import TYPE_CHECKING, Any, Type, Union, Generic, TypeVar, Callable, Optional, cast
from datetime import date, datetime
from typing_extensions import (
List,
Unpack,
Literal,
ClassVar,
Protocol,
Required,
ParamSpec,
TypedDict,
TypeGuard,
final,
override,
runtime_checkable,
)
import pydantic
from pydantic.fields import FieldInfo
from ._types import (
Body,
IncEx,
Query,
ModelT,
Headers,
Timeout,
NotGiven,
AnyMapping,
HttpxRequestFiles,
)
from ._utils import (
PropertyInfo,
is_list,
is_given,
json_safe,
lru_cache,
is_mapping,
parse_date,
coerce_boolean,
parse_datetime,
strip_not_given,
extract_type_arg,
is_annotated_type,
is_type_alias_type,
strip_annotated_type,
)
from ._compat import (
PYDANTIC_V2,
ConfigDict,
GenericModel as BaseGenericModel,
get_args,
is_union,
parse_obj,
get_origin,
is_literal_type,
get_model_config,
get_model_fields,
field_get_default,
)
from ._constants import RAW_RESPONSE_HEADER
if TYPE_CHECKING:
from pydantic_core.core_schema import ModelField, ModelSchema, LiteralSchema, ModelFieldsSchema
__all__ = ["BaseModel", "GenericModel"]
_T = TypeVar("_T")
_BaseModelT = TypeVar("_BaseModelT", bound="BaseModel")
P = ParamSpec("P")
@runtime_checkable
class _ConfigProtocol(Protocol):
allow_population_by_field_name: bool
class BaseModel(pydantic.BaseModel):
if PYDANTIC_V2:
model_config: ClassVar[ConfigDict] = ConfigDict(
extra="allow", defer_build=coerce_boolean(os.environ.get("DEFER_PYDANTIC_BUILD", "true"))
)
else:
@property
@override
def model_fields_set(self) -> set[str]:
# a forwards-compat shim for pydantic v2
return self.__fields_set__ # type: ignore
class Config(pydantic.BaseConfig): # pyright: ignore[reportDeprecated]
extra: Any = pydantic.Extra.allow # type: ignore
def to_dict(
self,
*,
mode: Literal["json", "python"] = "python",
use_api_names: bool = True,
exclude_unset: bool = True,
exclude_defaults: bool = False,
exclude_none: bool = False,
warnings: bool = True,
) -> dict[str, object]:
"""Recursively generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
By default, fields that were not set by the API will not be included,
and keys will match the API response, *not* the property names from the model.
For example, if the API responds with `"fooBar": true` but we've defined a `foo_bar: bool` property,
the output will use the `"fooBar"` key (unless `use_api_names=False` is passed).
Args:
mode:
If mode is 'json', the dictionary will only contain JSON serializable types. e.g. `datetime` will be turned into a string, `"2024-3-22T18:11:19.117000Z"`.
If mode is 'python', the dictionary may contain any Python objects. e.g. `datetime(2024, 3, 22)`
use_api_names: Whether to use the key that the API responded with or the property name. Defaults to `True`.
exclude_unset: Whether to exclude fields that have not been explicitly set.
exclude_defaults: Whether to exclude fields that are set to their default value from the output.
exclude_none: Whether to exclude fields that have a value of `None` from the output.
warnings: Whether to log warnings when invalid fields are encountered. This is only supported in Pydantic v2.
"""
return self.model_dump(
mode=mode,
by_alias=use_api_names,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
warnings=warnings,
)
def to_json(
self,
*,
indent: int | None = 2,
use_api_names: bool = True,
exclude_unset: bool = True,
exclude_defaults: bool = False,
exclude_none: bool = False,
warnings: bool = True,
) -> str:
"""Generates a JSON string representing this model as it would be received from or sent to the API (but with indentation).
By default, fields that were not set by the API will not be included,
and keys will match the API response, *not* the property names from the model.
For example, if the API responds with `"fooBar": true` but we've defined a `foo_bar: bool` property,
the output will use the `"fooBar"` key (unless `use_api_names=False` is passed).
Args:
indent: Indentation to use in the JSON output. If `None` is passed, the output will be compact. Defaults to `2`
use_api_names: Whether to use the key that the API responded with or the property name. Defaults to `True`.
exclude_unset: Whether to exclude fields that have not been explicitly set.
exclude_defaults: Whether to exclude fields that have the default value.
exclude_none: Whether to exclude fields that have a value of `None`.
warnings: Whether to show any warnings that occurred during serialization. This is only supported in Pydantic v2.
"""
return self.model_dump_json(
indent=indent,
by_alias=use_api_names,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
warnings=warnings,
)
@override
def __str__(self) -> str:
# mypy complains about an invalid self arg
return f"{self.__repr_name__()}({self.__repr_str__(', ')})" # type: ignore[misc]
# Override the 'construct' method in a way that supports recursive parsing without validation.
# Based on https://github.com/samuelcolvin/pydantic/issues/1168#issuecomment-817742836.
@classmethod
@override
def construct( # pyright: ignore[reportIncompatibleMethodOverride]
__cls: Type[ModelT],
_fields_set: set[str] | None = None,
**values: object,
) -> ModelT:
m = __cls.__new__(__cls)
fields_values: dict[str, object] = {}
config = get_model_config(__cls)
populate_by_name = (
config.allow_population_by_field_name
if isinstance(config, _ConfigProtocol)
else config.get("populate_by_name")
)
if _fields_set is None:
_fields_set = set()
model_fields = get_model_fields(__cls)
for name, field in model_fields.items():
key = field.alias
if key is None or (key not in values and populate_by_name):
key = name
if key in values:
fields_values[name] = _construct_field(value=values[key], field=field, key=key)
_fields_set.add(name)
else:
fields_values[name] = field_get_default(field)
_extra = {}
for key, value in values.items():
if key not in model_fields:
if PYDANTIC_V2:
_extra[key] = value
else:
_fields_set.add(key)
fields_values[key] = value
object.__setattr__(m, "__dict__", fields_values)
if PYDANTIC_V2:
# these properties are copied from Pydantic's `model_construct()` method
object.__setattr__(m, "__pydantic_private__", None)
object.__setattr__(m, "__pydantic_extra__", _extra)
object.__setattr__(m, "__pydantic_fields_set__", _fields_set)
else:
# init_private_attributes() does not exist in v2
m._init_private_attributes() # type: ignore
# copied from Pydantic v1's `construct()` method
object.__setattr__(m, "__fields_set__", _fields_set)
return m
if not TYPE_CHECKING:
# type checkers incorrectly complain about this assignment
# because the type signatures are technically different
# although not in practice
model_construct = construct
if not PYDANTIC_V2:
# we define aliases for some of the new pydantic v2 methods so
# that we can just document these methods without having to specify
# a specific pydantic version as some users may not know which
# pydantic version they are currently using
@override
def model_dump(
self,
*,
mode: Literal["json", "python"] | str = "python",
include: IncEx | None = None,
exclude: IncEx | None = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
round_trip: bool = False,
warnings: bool | Literal["none", "warn", "error"] = True,
context: dict[str, Any] | None = None,
serialize_as_any: bool = False,
) -> dict[str, Any]:
"""Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Args:
mode: The mode in which `to_python` should run.
If mode is 'json', the dictionary will only contain JSON serializable types.
If mode is 'python', the dictionary may contain any Python objects.
include: A list of fields to include in the output.
exclude: A list of fields to exclude from the output.
by_alias: Whether to use the field's alias in the dictionary key if defined.
exclude_unset: Whether to exclude fields that are unset or None from the output.
exclude_defaults: Whether to exclude fields that are set to their default value from the output.
exclude_none: Whether to exclude fields that have a value of `None` from the output.
round_trip: Whether to enable serialization and deserialization round-trip support.
warnings: Whether to log warnings when invalid fields are encountered.
Returns:
A dictionary representation of the model.
"""
if mode not in {"json", "python"}:
raise ValueError("mode must be either 'json' or 'python'")
if round_trip != False:
raise ValueError("round_trip is only supported in Pydantic v2")
if warnings != True:
raise ValueError("warnings is only supported in Pydantic v2")
if context is not None:
raise ValueError("context is only supported in Pydantic v2")
if serialize_as_any != False:
raise ValueError("serialize_as_any is only supported in Pydantic v2")
dumped = super().dict( # pyright: ignore[reportDeprecated]
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
)
return cast(dict[str, Any], json_safe(dumped)) if mode == "json" else dumped
@override
def model_dump_json(
self,
*,
indent: int | None = None,
include: IncEx | None = None,
exclude: IncEx | None = None,
by_alias: bool = False,
exclude_unset: bool = False,
exclude_defaults: bool = False,
exclude_none: bool = False,
round_trip: bool = False,
warnings: bool | Literal["none", "warn", "error"] = True,
context: dict[str, Any] | None = None,
serialize_as_any: bool = False,
) -> str:
"""Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump_json
Generates a JSON representation of the model using Pydantic's `to_json` method.
Args:
indent: Indentation to use in the JSON output. If None is passed, the output will be compact.
include: Field(s) to include in the JSON output. Can take either a string or set of strings.
exclude: Field(s) to exclude from the JSON output. Can take either a string or set of strings.
by_alias: Whether to serialize using field aliases.
exclude_unset: Whether to exclude fields that have not been explicitly set.
exclude_defaults: Whether to exclude fields that have the default value.
exclude_none: Whether to exclude fields that have a value of `None`.
round_trip: Whether to use serialization/deserialization between JSON and class instance.
warnings: Whether to show any warnings that occurred during serialization.
Returns:
A JSON string representation of the model.
"""
if round_trip != False:
raise ValueError("round_trip is only supported in Pydantic v2")
if warnings != True:
raise ValueError("warnings is only supported in Pydantic v2")
if context is not None:
raise ValueError("context is only supported in Pydantic v2")
if serialize_as_any != False:
raise ValueError("serialize_as_any is only supported in Pydantic v2")
return super().json( # type: ignore[reportDeprecated]
indent=indent,
include=include,
exclude=exclude,
by_alias=by_alias,
exclude_unset=exclude_unset,
exclude_defaults=exclude_defaults,
exclude_none=exclude_none,
)
def _construct_field(value: object, field: FieldInfo, key: str) -> object:
if value is None:
return field_get_default(field)
if PYDANTIC_V2:
type_ = field.annotation
else:
type_ = cast(type, field.outer_type_) # type: ignore
if type_ is None:
raise RuntimeError(f"Unexpected field type is None for {key}")
return construct_type(value=value, type_=type_, metadata=getattr(field, "metadata", None))
def is_basemodel(type_: type) -> bool:
"""Returns whether or not the given type is either a `BaseModel` or a union of `BaseModel`"""
if is_union(type_):
for variant in get_args(type_):
if is_basemodel(variant):
return True
return False
return is_basemodel_type(type_)
def is_basemodel_type(type_: type) -> TypeGuard[type[BaseModel] | type[GenericModel]]:
origin = get_origin(type_) or type_
if not inspect.isclass(origin):
return False
return issubclass(origin, BaseModel) or issubclass(origin, GenericModel)
def build(
base_model_cls: Callable[P, _BaseModelT],
*args: P.args,
**kwargs: P.kwargs,
) -> _BaseModelT:
"""Construct a BaseModel class without validation.
This is useful for cases where you need to instantiate a `BaseModel`
from an API response as this provides type-safe params which isn't supported
by helpers like `construct_type()`.
```py
build(MyModel, my_field_a="foo", my_field_b=123)
```
"""
if args:
raise TypeError(
"Received positional arguments which are not supported; Keyword arguments must be used instead",
)
return cast(_BaseModelT, construct_type(type_=base_model_cls, value=kwargs))
def construct_type_unchecked(*, value: object, type_: type[_T]) -> _T:
"""Loose coercion to the expected type with construction of nested values.
Note: the returned value from this function is not guaranteed to match the
given type.
"""
return cast(_T, construct_type(value=value, type_=type_))
def construct_type(*, value: object, type_: object, metadata: Optional[List[Any]] = None) -> object:
"""Loose coercion to the expected type with construction of nested values.
If the given value does not match the expected type then it is returned as-is.
"""
# store a reference to the original type we were given before we extract any inner
# types so that we can properly resolve forward references in `TypeAliasType` annotations
original_type = None
# we allow `object` as the input type because otherwise, passing things like
# `Literal['value']` will be reported as a type error by type checkers
type_ = cast("type[object]", type_)
if is_type_alias_type(type_):
original_type = type_ # type: ignore[unreachable]
type_ = type_.__value__ # type: ignore[unreachable]
# unwrap `Annotated[T, ...]` -> `T`
if metadata is not None:
meta: tuple[Any, ...] = tuple(metadata)
elif is_annotated_type(type_):
meta = get_args(type_)[1:]
type_ = extract_type_arg(type_, 0)
else:
meta = tuple()
# we need to use the origin class for any types that are subscripted generics
# e.g. Dict[str, object]
origin = get_origin(type_) or type_
args = get_args(type_)
if is_union(origin):
try:
return validate_type(type_=cast("type[object]", original_type or type_), value=value)
except Exception:
pass
# if the type is a discriminated union then we want to construct the right variant
# in the union, even if the data doesn't match exactly, otherwise we'd break code
# that relies on the constructed class types, e.g.
#
# class FooType:
# kind: Literal['foo']
# value: str
#
# class BarType:
# kind: Literal['bar']
# value: int
#
# without this block, if the data we get is something like `{'kind': 'bar', 'value': 'foo'}` then
# we'd end up constructing `FooType` when it should be `BarType`.
discriminator = _build_discriminated_union_meta(union=type_, meta_annotations=meta)
if discriminator and is_mapping(value):
variant_value = value.get(discriminator.field_alias_from or discriminator.field_name)
if variant_value and isinstance(variant_value, str):
variant_type = discriminator.mapping.get(variant_value)
if variant_type:
return construct_type(type_=variant_type, value=value)
# if the data is not valid, use the first variant that doesn't fail while deserializing
for variant in args:
try:
return construct_type(value=value, type_=variant)
except Exception:
continue
raise RuntimeError(f"Could not convert data into a valid instance of {type_}")
if origin == dict:
if not is_mapping(value):
return value
_, items_type = get_args(type_) # Dict[_, items_type]
return {key: construct_type(value=item, type_=items_type) for key, item in value.items()}
if (
not is_literal_type(type_)
and inspect.isclass(origin)
and (issubclass(origin, BaseModel) or issubclass(origin, GenericModel))
):
if is_list(value):
return [cast(Any, type_).construct(**entry) if is_mapping(entry) else entry for entry in value]
if is_mapping(value):
if issubclass(type_, BaseModel):
return type_.construct(**value) # type: ignore[arg-type]
return cast(Any, type_).construct(**value)
if origin == list:
if not is_list(value):
return value
inner_type = args[0] # List[inner_type]
return [construct_type(value=entry, type_=inner_type) for entry in value]
if origin == float:
if isinstance(value, int):
coerced = float(value)
if coerced != value:
return value
return coerced
return value
if type_ == datetime:
try:
return parse_datetime(value) # type: ignore
except Exception:
return value
if type_ == date:
try:
return parse_date(value) # type: ignore
except Exception:
return value
return value
@runtime_checkable
class CachedDiscriminatorType(Protocol):
__discriminator__: DiscriminatorDetails
class DiscriminatorDetails:
field_name: str
"""The name of the discriminator field in the variant class, e.g.
```py
class Foo(BaseModel):
type: Literal['foo']
```
Will result in field_name='type'
"""
field_alias_from: str | None
"""The name of the discriminator field in the API response, e.g.
```py
class Foo(BaseModel):
type: Literal['foo'] = Field(alias='type_from_api')
```
Will result in field_alias_from='type_from_api'
"""
mapping: dict[str, type]
"""Mapping of discriminator value to variant type, e.g.
{'foo': FooVariant, 'bar': BarVariant}
"""
def __init__(
self,
*,
mapping: dict[str, type],
discriminator_field: str,
discriminator_alias: str | None,
) -> None:
self.mapping = mapping
self.field_name = discriminator_field
self.field_alias_from = discriminator_alias
def _build_discriminated_union_meta(*, union: type, meta_annotations: tuple[Any, ...]) -> DiscriminatorDetails | None:
if isinstance(union, CachedDiscriminatorType):
return union.__discriminator__
discriminator_field_name: str | None = None
for annotation in meta_annotations:
if isinstance(annotation, PropertyInfo) and annotation.discriminator is not None:
discriminator_field_name = annotation.discriminator
break
if not discriminator_field_name:
return None
mapping: dict[str, type] = {}
discriminator_alias: str | None = None
for variant in get_args(union):
variant = strip_annotated_type(variant)
if is_basemodel_type(variant):
if PYDANTIC_V2:
field = _extract_field_schema_pv2(variant, discriminator_field_name)
if not field:
continue
# Note: if one variant defines an alias then they all should
discriminator_alias = field.get("serialization_alias")
field_schema = field["schema"]
if field_schema["type"] == "literal":
for entry in cast("LiteralSchema", field_schema)["expected"]:
if isinstance(entry, str):
mapping[entry] = variant
else:
field_info = cast("dict[str, FieldInfo]", variant.__fields__).get(discriminator_field_name) # pyright: ignore[reportDeprecated, reportUnnecessaryCast]
if not field_info:
continue
# Note: if one variant defines an alias then they all should
discriminator_alias = field_info.alias
if (annotation := getattr(field_info, "annotation", None)) and is_literal_type(annotation):
for entry in get_args(annotation):
if isinstance(entry, str):
mapping[entry] = variant
if not mapping:
return None
details = DiscriminatorDetails(
mapping=mapping,
discriminator_field=discriminator_field_name,
discriminator_alias=discriminator_alias,
)
cast(CachedDiscriminatorType, union).__discriminator__ = details
return details
def _extract_field_schema_pv2(model: type[BaseModel], field_name: str) -> ModelField | None:
schema = model.__pydantic_core_schema__
if schema["type"] == "definitions":
schema = schema["schema"]
if schema["type"] != "model":
return None
schema = cast("ModelSchema", schema)
fields_schema = schema["schema"]
if fields_schema["type"] != "model-fields":
return None
fields_schema = cast("ModelFieldsSchema", fields_schema)
field = fields_schema["fields"].get(field_name)
if not field:
return None
return cast("ModelField", field) # pyright: ignore[reportUnnecessaryCast]
def validate_type(*, type_: type[_T], value: object) -> _T:
"""Strict validation that the given value matches the expected type"""
if inspect.isclass(type_) and issubclass(type_, pydantic.BaseModel):
return cast(_T, parse_obj(type_, value))
return cast(_T, _validate_non_model_type(type_=type_, value=value))
def set_pydantic_config(typ: Any, config: pydantic.ConfigDict) -> None:
"""Add a pydantic config for the given type.
Note: this is a no-op on Pydantic v1.
"""
setattr(typ, "__pydantic_config__", config) # noqa: B010
# our use of subclassing here causes weirdness for type checkers,
# so we just pretend that we don't subclass
if TYPE_CHECKING:
GenericModel = BaseModel
else:
class GenericModel(BaseGenericModel, BaseModel):
pass
if PYDANTIC_V2:
from pydantic import TypeAdapter as _TypeAdapter
_CachedTypeAdapter = cast("TypeAdapter[object]", lru_cache(maxsize=None)(_TypeAdapter))
if TYPE_CHECKING:
from pydantic import TypeAdapter
else:
TypeAdapter = _CachedTypeAdapter
def _validate_non_model_type(*, type_: type[_T], value: object) -> _T:
return TypeAdapter(type_).validate_python(value)
elif not TYPE_CHECKING: # TODO: condition is weird
class RootModel(GenericModel, Generic[_T]):
"""Used as a placeholder to easily convert runtime types to a Pydantic format
to provide validation.
For example:
```py
validated = RootModel[int](__root__="5").__root__
# validated: 5
```
"""
__root__: _T
def _validate_non_model_type(*, type_: type[_T], value: object) -> _T:
model = _create_pydantic_model(type_).validate(value)
return cast(_T, model.__root__)
def _create_pydantic_model(type_: _T) -> Type[RootModel[_T]]:
return RootModel[type_] # type: ignore
class FinalRequestOptionsInput(TypedDict, total=False):
method: Required[str]
url: Required[str]
params: Query
headers: Headers
max_retries: int
timeout: float | Timeout | None
files: HttpxRequestFiles | None
idempotency_key: str
json_data: Body
extra_json: AnyMapping
follow_redirects: bool
@final
class FinalRequestOptions(pydantic.BaseModel):
method: str
url: str
params: Query = {}
headers: Union[Headers, NotGiven] = NotGiven()
max_retries: Union[int, NotGiven] = NotGiven()
timeout: Union[float, Timeout, None, NotGiven] = NotGiven()
files: Union[HttpxRequestFiles, None] = None
idempotency_key: Union[str, None] = None
post_parser: Union[Callable[[Any], Any], NotGiven] = NotGiven()
follow_redirects: Union[bool, None] = None
# It should be noted that we cannot use `json` here as that would override
# a BaseModel method in an incompatible fashion.
json_data: Union[Body, None] = None
extra_json: Union[AnyMapping, None] = None
if PYDANTIC_V2:
model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True)
else:
class Config(pydantic.BaseConfig): # pyright: ignore[reportDeprecated]
arbitrary_types_allowed: bool = True
def get_max_retries(self, max_retries: int) -> int:
if isinstance(self.max_retries, NotGiven):
return max_retries
return self.max_retries
def _strip_raw_response_header(self) -> None:
if not is_given(self.headers):
return
if self.headers.get(RAW_RESPONSE_HEADER):
self.headers = {**self.headers}
self.headers.pop(RAW_RESPONSE_HEADER)
# override the `construct` method so that we can run custom transformations.
# this is necessary as we don't want to do any actual runtime type checking
# (which means we can't use validators) but we do want to ensure that `NotGiven`
# values are not present
#
# type ignore required because we're adding explicit types to `**values`
@classmethod
def construct( # type: ignore
cls,
_fields_set: set[str] | None = None,
**values: Unpack[FinalRequestOptionsInput],
) -> FinalRequestOptions:
kwargs: dict[str, Any] = {
# we unconditionally call `strip_not_given` on any value
# as it will just ignore any non-mapping types
key: strip_not_given(value)
for key, value in values.items()
}
if PYDANTIC_V2:
return super().model_construct(_fields_set, **kwargs)
return cast(FinalRequestOptions, super().construct(_fields_set, **kwargs)) # pyright: ignore[reportDeprecated]
if not TYPE_CHECKING:
# type checkers incorrectly complain about this assignment
model_construct = construct
@@ -0,0 +1,150 @@
from __future__ import annotations
from typing import Any, List, Tuple, Union, Mapping, TypeVar
from urllib.parse import parse_qs, urlencode
from typing_extensions import Literal, get_args
from ._types import NOT_GIVEN, NotGiven, NotGivenOr
from ._utils import flatten
_T = TypeVar("_T")
ArrayFormat = Literal["comma", "repeat", "indices", "brackets"]
NestedFormat = Literal["dots", "brackets"]
PrimitiveData = Union[str, int, float, bool, None]
# this should be Data = Union[PrimitiveData, "List[Data]", "Tuple[Data]", "Mapping[str, Data]"]
# https://github.com/microsoft/pyright/issues/3555
Data = Union[PrimitiveData, List[Any], Tuple[Any], "Mapping[str, Any]"]
Params = Mapping[str, Data]
class Querystring:
array_format: ArrayFormat
nested_format: NestedFormat
def __init__(
self,
*,
array_format: ArrayFormat = "repeat",
nested_format: NestedFormat = "brackets",
) -> None:
self.array_format = array_format
self.nested_format = nested_format
def parse(self, query: str) -> Mapping[str, object]:
# Note: custom format syntax is not supported yet
return parse_qs(query)
def stringify(
self,
params: Params,
*,
array_format: NotGivenOr[ArrayFormat] = NOT_GIVEN,
nested_format: NotGivenOr[NestedFormat] = NOT_GIVEN,
) -> str:
return urlencode(
self.stringify_items(
params,
array_format=array_format,
nested_format=nested_format,
)
)
def stringify_items(
self,
params: Params,
*,
array_format: NotGivenOr[ArrayFormat] = NOT_GIVEN,
nested_format: NotGivenOr[NestedFormat] = NOT_GIVEN,
) -> list[tuple[str, str]]:
opts = Options(
qs=self,
array_format=array_format,
nested_format=nested_format,
)
return flatten([self._stringify_item(key, value, opts) for key, value in params.items()])
def _stringify_item(
self,
key: str,
value: Data,
opts: Options,
) -> list[tuple[str, str]]:
if isinstance(value, Mapping):
items: list[tuple[str, str]] = []
nested_format = opts.nested_format
for subkey, subvalue in value.items():
items.extend(
self._stringify_item(
# TODO: error if unknown format
f"{key}.{subkey}" if nested_format == "dots" else f"{key}[{subkey}]",
subvalue,
opts,
)
)
return items
if isinstance(value, (list, tuple)):
array_format = opts.array_format
if array_format == "comma":
return [
(
key,
",".join(self._primitive_value_to_str(item) for item in value if item is not None),
),
]
elif array_format == "repeat":
items = []
for item in value:
items.extend(self._stringify_item(key, item, opts))
return items
elif array_format == "indices":
raise NotImplementedError("The array indices format is not supported yet")
elif array_format == "brackets":
items = []
key = key + "[]"
for item in value:
items.extend(self._stringify_item(key, item, opts))
return items
else:
raise NotImplementedError(
f"Unknown array_format value: {array_format}, choose from {', '.join(get_args(ArrayFormat))}"
)
serialised = self._primitive_value_to_str(value)
if not serialised:
return []
return [(key, serialised)]
def _primitive_value_to_str(self, value: PrimitiveData) -> str:
# copied from httpx
if value is True:
return "true"
elif value is False:
return "false"
elif value is None:
return ""
return str(value)
_qs = Querystring()
parse = _qs.parse
stringify = _qs.stringify
stringify_items = _qs.stringify_items
class Options:
array_format: ArrayFormat
nested_format: NestedFormat
def __init__(
self,
qs: Querystring = _qs,
*,
array_format: NotGivenOr[ArrayFormat] = NOT_GIVEN,
nested_format: NotGivenOr[NestedFormat] = NOT_GIVEN,
) -> None:
self.array_format = qs.array_format if isinstance(array_format, NotGiven) else array_format
self.nested_format = qs.nested_format if isinstance(nested_format, NotGiven) else nested_format
@@ -0,0 +1,43 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
import time
from typing import TYPE_CHECKING
import anyio
if TYPE_CHECKING:
from ._client import Groq, AsyncGroq
class SyncAPIResource:
_client: Groq
def __init__(self, client: Groq) -> None:
self._client = client
self._get = client.get
self._post = client.post
self._patch = client.patch
self._put = client.put
self._delete = client.delete
self._get_api_list = client.get_api_list
def _sleep(self, seconds: float) -> None:
time.sleep(seconds)
class AsyncAPIResource:
_client: AsyncGroq
def __init__(self, client: AsyncGroq) -> None:
self._client = client
self._get = client.get
self._post = client.post
self._patch = client.patch
self._put = client.put
self._delete = client.delete
self._get_api_list = client.get_api_list
async def _sleep(self, seconds: float) -> None:
await anyio.sleep(seconds)
@@ -0,0 +1,830 @@
from __future__ import annotations
import os
import inspect
import logging
import datetime
import functools
from types import TracebackType
from typing import (
TYPE_CHECKING,
Any,
Union,
Generic,
TypeVar,
Callable,
Iterator,
AsyncIterator,
cast,
overload,
)
from typing_extensions import Awaitable, ParamSpec, override, get_origin
import anyio
import httpx
import pydantic
from ._types import NoneType
from ._utils import is_given, extract_type_arg, is_annotated_type, is_type_alias_type, extract_type_var_from_base
from ._models import BaseModel, is_basemodel
from ._constants import RAW_RESPONSE_HEADER, OVERRIDE_CAST_TO_HEADER
from ._streaming import Stream, AsyncStream, is_stream_class_type, extract_stream_chunk_type
from ._exceptions import GroqError, APIResponseValidationError
if TYPE_CHECKING:
from ._models import FinalRequestOptions
from ._base_client import BaseClient
P = ParamSpec("P")
R = TypeVar("R")
_T = TypeVar("_T")
_APIResponseT = TypeVar("_APIResponseT", bound="APIResponse[Any]")
_AsyncAPIResponseT = TypeVar("_AsyncAPIResponseT", bound="AsyncAPIResponse[Any]")
log: logging.Logger = logging.getLogger(__name__)
class BaseAPIResponse(Generic[R]):
_cast_to: type[R]
_client: BaseClient[Any, Any]
_parsed_by_type: dict[type[Any], Any]
_is_sse_stream: bool
_stream_cls: type[Stream[Any]] | type[AsyncStream[Any]] | None
_options: FinalRequestOptions
http_response: httpx.Response
retries_taken: int
"""The number of retries made. If no retries happened this will be `0`"""
def __init__(
self,
*,
raw: httpx.Response,
cast_to: type[R],
client: BaseClient[Any, Any],
stream: bool,
stream_cls: type[Stream[Any]] | type[AsyncStream[Any]] | None,
options: FinalRequestOptions,
retries_taken: int = 0,
) -> None:
self._cast_to = cast_to
self._client = client
self._parsed_by_type = {}
self._is_sse_stream = stream
self._stream_cls = stream_cls
self._options = options
self.http_response = raw
self.retries_taken = retries_taken
@property
def headers(self) -> httpx.Headers:
return self.http_response.headers
@property
def http_request(self) -> httpx.Request:
"""Returns the httpx Request instance associated with the current response."""
return self.http_response.request
@property
def status_code(self) -> int:
return self.http_response.status_code
@property
def url(self) -> httpx.URL:
"""Returns the URL for which the request was made."""
return self.http_response.url
@property
def method(self) -> str:
return self.http_request.method
@property
def http_version(self) -> str:
return self.http_response.http_version
@property
def elapsed(self) -> datetime.timedelta:
"""The time taken for the complete request/response cycle to complete."""
return self.http_response.elapsed
@property
def is_closed(self) -> bool:
"""Whether or not the response body has been closed.
If this is False then there is response data that has not been read yet.
You must either fully consume the response body or call `.close()`
before discarding the response to prevent resource leaks.
"""
return self.http_response.is_closed
@override
def __repr__(self) -> str:
return (
f"<{self.__class__.__name__} [{self.status_code} {self.http_response.reason_phrase}] type={self._cast_to}>"
)
def _parse(self, *, to: type[_T] | None = None) -> R | _T:
cast_to = to if to is not None else self._cast_to
# unwrap `TypeAlias('Name', T)` -> `T`
if is_type_alias_type(cast_to):
cast_to = cast_to.__value__ # type: ignore[unreachable]
# unwrap `Annotated[T, ...]` -> `T`
if cast_to and is_annotated_type(cast_to):
cast_to = extract_type_arg(cast_to, 0)
origin = get_origin(cast_to) or cast_to
if self._is_sse_stream:
if to:
if not is_stream_class_type(to):
raise TypeError(f"Expected custom parse type to be a subclass of {Stream} or {AsyncStream}")
return cast(
_T,
to(
cast_to=extract_stream_chunk_type(
to,
failure_message="Expected custom stream type to be passed with a type argument, e.g. Stream[ChunkType]",
),
response=self.http_response,
client=cast(Any, self._client),
),
)
if self._stream_cls:
return cast(
R,
self._stream_cls(
cast_to=extract_stream_chunk_type(self._stream_cls),
response=self.http_response,
client=cast(Any, self._client),
),
)
stream_cls = cast("type[Stream[Any]] | type[AsyncStream[Any]] | None", self._client._default_stream_cls)
if stream_cls is None:
raise MissingStreamClassError()
return cast(
R,
stream_cls(
cast_to=cast_to,
response=self.http_response,
client=cast(Any, self._client),
),
)
if cast_to is NoneType:
return cast(R, None)
response = self.http_response
if cast_to == str:
return cast(R, response.text)
if cast_to == bytes:
return cast(R, response.content)
if cast_to == int:
return cast(R, int(response.text))
if cast_to == float:
return cast(R, float(response.text))
if cast_to == bool:
return cast(R, response.text.lower() == "true")
if origin == APIResponse:
raise RuntimeError("Unexpected state - cast_to is `APIResponse`")
if inspect.isclass(origin) and issubclass(origin, httpx.Response):
# Because of the invariance of our ResponseT TypeVar, users can subclass httpx.Response
# and pass that class to our request functions. We cannot change the variance to be either
# covariant or contravariant as that makes our usage of ResponseT illegal. We could construct
# the response class ourselves but that is something that should be supported directly in httpx
# as it would be easy to incorrectly construct the Response object due to the multitude of arguments.
if cast_to != httpx.Response:
raise ValueError(f"Subclasses of httpx.Response cannot be passed to `cast_to`")
return cast(R, response)
if (
inspect.isclass(
origin # pyright: ignore[reportUnknownArgumentType]
)
and not issubclass(origin, BaseModel)
and issubclass(origin, pydantic.BaseModel)
):
raise TypeError("Pydantic models must subclass our base model type, e.g. `from groq import BaseModel`")
if (
cast_to is not object
and not origin is list
and not origin is dict
and not origin is Union
and not issubclass(origin, BaseModel)
):
raise RuntimeError(
f"Unsupported type, expected {cast_to} to be a subclass of {BaseModel}, {dict}, {list}, {Union}, {NoneType}, {str} or {httpx.Response}."
)
# split is required to handle cases where additional information is included
# in the response, e.g. application/json; charset=utf-8
content_type, *_ = response.headers.get("content-type", "*").split(";")
if not content_type.endswith("json"):
if is_basemodel(cast_to):
try:
data = response.json()
except Exception as exc:
log.debug("Could not read JSON from response data due to %s - %s", type(exc), exc)
else:
return self._client._process_response_data(
data=data,
cast_to=cast_to, # type: ignore
response=response,
)
if self._client._strict_response_validation:
raise APIResponseValidationError(
response=response,
message=f"Expected Content-Type response header to be `application/json` but received `{content_type}` instead.",
body=response.text,
)
# If the API responds with content that isn't JSON then we just return
# the (decoded) text without performing any parsing so that you can still
# handle the response however you need to.
return response.text # type: ignore
data = response.json()
return self._client._process_response_data(
data=data,
cast_to=cast_to, # type: ignore
response=response,
)
class APIResponse(BaseAPIResponse[R]):
@overload
def parse(self, *, to: type[_T]) -> _T: ...
@overload
def parse(self) -> R: ...
def parse(self, *, to: type[_T] | None = None) -> R | _T:
"""Returns the rich python representation of this response's data.
For lower-level control, see `.read()`, `.json()`, `.iter_bytes()`.
You can customise the type that the response is parsed into through
the `to` argument, e.g.
```py
from groq import BaseModel
class MyModel(BaseModel):
foo: str
obj = response.parse(to=MyModel)
print(obj.foo)
```
We support parsing:
- `BaseModel`
- `dict`
- `list`
- `Union`
- `str`
- `int`
- `float`
- `httpx.Response`
"""
cache_key = to if to is not None else self._cast_to
cached = self._parsed_by_type.get(cache_key)
if cached is not None:
return cached # type: ignore[no-any-return]
if not self._is_sse_stream:
self.read()
parsed = self._parse(to=to)
if is_given(self._options.post_parser):
parsed = self._options.post_parser(parsed)
self._parsed_by_type[cache_key] = parsed
return parsed
def read(self) -> bytes:
"""Read and return the binary response content."""
try:
return self.http_response.read()
except httpx.StreamConsumed as exc:
# The default error raised by httpx isn't very
# helpful in our case so we re-raise it with
# a different error message.
raise StreamAlreadyConsumed() from exc
def text(self) -> str:
"""Read and decode the response content into a string."""
self.read()
return self.http_response.text
def json(self) -> object:
"""Read and decode the JSON response content."""
self.read()
return self.http_response.json()
def close(self) -> None:
"""Close the response and release the connection.
Automatically called if the response body is read to completion.
"""
self.http_response.close()
def iter_bytes(self, chunk_size: int | None = None) -> Iterator[bytes]:
"""
A byte-iterator over the decoded response content.
This automatically handles gzip, deflate and brotli encoded responses.
"""
for chunk in self.http_response.iter_bytes(chunk_size):
yield chunk
def iter_text(self, chunk_size: int | None = None) -> Iterator[str]:
"""A str-iterator over the decoded response content
that handles both gzip, deflate, etc but also detects the content's
string encoding.
"""
for chunk in self.http_response.iter_text(chunk_size):
yield chunk
def iter_lines(self) -> Iterator[str]:
"""Like `iter_text()` but will only yield chunks for each line"""
for chunk in self.http_response.iter_lines():
yield chunk
class AsyncAPIResponse(BaseAPIResponse[R]):
@overload
async def parse(self, *, to: type[_T]) -> _T: ...
@overload
async def parse(self) -> R: ...
async def parse(self, *, to: type[_T] | None = None) -> R | _T:
"""Returns the rich python representation of this response's data.
For lower-level control, see `.read()`, `.json()`, `.iter_bytes()`.
You can customise the type that the response is parsed into through
the `to` argument, e.g.
```py
from groq import BaseModel
class MyModel(BaseModel):
foo: str
obj = response.parse(to=MyModel)
print(obj.foo)
```
We support parsing:
- `BaseModel`
- `dict`
- `list`
- `Union`
- `str`
- `httpx.Response`
"""
cache_key = to if to is not None else self._cast_to
cached = self._parsed_by_type.get(cache_key)
if cached is not None:
return cached # type: ignore[no-any-return]
if not self._is_sse_stream:
await self.read()
parsed = self._parse(to=to)
if is_given(self._options.post_parser):
parsed = self._options.post_parser(parsed)
self._parsed_by_type[cache_key] = parsed
return parsed
async def read(self) -> bytes:
"""Read and return the binary response content."""
try:
return await self.http_response.aread()
except httpx.StreamConsumed as exc:
# the default error raised by httpx isn't very
# helpful in our case so we re-raise it with
# a different error message
raise StreamAlreadyConsumed() from exc
async def text(self) -> str:
"""Read and decode the response content into a string."""
await self.read()
return self.http_response.text
async def json(self) -> object:
"""Read and decode the JSON response content."""
await self.read()
return self.http_response.json()
async def close(self) -> None:
"""Close the response and release the connection.
Automatically called if the response body is read to completion.
"""
await self.http_response.aclose()
async def iter_bytes(self, chunk_size: int | None = None) -> AsyncIterator[bytes]:
"""
A byte-iterator over the decoded response content.
This automatically handles gzip, deflate and brotli encoded responses.
"""
async for chunk in self.http_response.aiter_bytes(chunk_size):
yield chunk
async def iter_text(self, chunk_size: int | None = None) -> AsyncIterator[str]:
"""A str-iterator over the decoded response content
that handles both gzip, deflate, etc but also detects the content's
string encoding.
"""
async for chunk in self.http_response.aiter_text(chunk_size):
yield chunk
async def iter_lines(self) -> AsyncIterator[str]:
"""Like `iter_text()` but will only yield chunks for each line"""
async for chunk in self.http_response.aiter_lines():
yield chunk
class BinaryAPIResponse(APIResponse[bytes]):
"""Subclass of APIResponse providing helpers for dealing with binary data.
Note: If you want to stream the response data instead of eagerly reading it
all at once then you should use `.with_streaming_response` when making
the API request, e.g. `.with_streaming_response.get_binary_response()`
"""
def write_to_file(
self,
file: str | os.PathLike[str],
) -> None:
"""Write the output to the given file.
Accepts a filename or any path-like object, e.g. pathlib.Path
Note: if you want to stream the data to the file instead of writing
all at once then you should use `.with_streaming_response` when making
the API request, e.g. `.with_streaming_response.get_binary_response()`
"""
with open(file, mode="wb") as f:
for data in self.iter_bytes():
f.write(data)
class AsyncBinaryAPIResponse(AsyncAPIResponse[bytes]):
"""Subclass of APIResponse providing helpers for dealing with binary data.
Note: If you want to stream the response data instead of eagerly reading it
all at once then you should use `.with_streaming_response` when making
the API request, e.g. `.with_streaming_response.get_binary_response()`
"""
async def write_to_file(
self,
file: str | os.PathLike[str],
) -> None:
"""Write the output to the given file.
Accepts a filename or any path-like object, e.g. pathlib.Path
Note: if you want to stream the data to the file instead of writing
all at once then you should use `.with_streaming_response` when making
the API request, e.g. `.with_streaming_response.get_binary_response()`
"""
path = anyio.Path(file)
async with await path.open(mode="wb") as f:
async for data in self.iter_bytes():
await f.write(data)
class StreamedBinaryAPIResponse(APIResponse[bytes]):
def stream_to_file(
self,
file: str | os.PathLike[str],
*,
chunk_size: int | None = None,
) -> None:
"""Streams the output to the given file.
Accepts a filename or any path-like object, e.g. pathlib.Path
"""
with open(file, mode="wb") as f:
for data in self.iter_bytes(chunk_size):
f.write(data)
class AsyncStreamedBinaryAPIResponse(AsyncAPIResponse[bytes]):
async def stream_to_file(
self,
file: str | os.PathLike[str],
*,
chunk_size: int | None = None,
) -> None:
"""Streams the output to the given file.
Accepts a filename or any path-like object, e.g. pathlib.Path
"""
path = anyio.Path(file)
async with await path.open(mode="wb") as f:
async for data in self.iter_bytes(chunk_size):
await f.write(data)
class MissingStreamClassError(TypeError):
def __init__(self) -> None:
super().__init__(
"The `stream` argument was set to `True` but the `stream_cls` argument was not given. See `groq._streaming` for reference",
)
class StreamAlreadyConsumed(GroqError):
"""
Attempted to read or stream content, but the content has already
been streamed.
This can happen if you use a method like `.iter_lines()` and then attempt
to read th entire response body afterwards, e.g.
```py
response = await client.post(...)
async for line in response.iter_lines():
... # do something with `line`
content = await response.read()
# ^ error
```
If you want this behaviour you'll need to either manually accumulate the response
content or call `await response.read()` before iterating over the stream.
"""
def __init__(self) -> None:
message = (
"Attempted to read or stream some content, but the content has "
"already been streamed. "
"This could be due to attempting to stream the response "
"content more than once."
"\n\n"
"You can fix this by manually accumulating the response content while streaming "
"or by calling `.read()` before starting to stream."
)
super().__init__(message)
class ResponseContextManager(Generic[_APIResponseT]):
"""Context manager for ensuring that a request is not made
until it is entered and that the response will always be closed
when the context manager exits
"""
def __init__(self, request_func: Callable[[], _APIResponseT]) -> None:
self._request_func = request_func
self.__response: _APIResponseT | None = None
def __enter__(self) -> _APIResponseT:
self.__response = self._request_func()
return self.__response
def __exit__(
self,
exc_type: type[BaseException] | None,
exc: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
if self.__response is not None:
self.__response.close()
class AsyncResponseContextManager(Generic[_AsyncAPIResponseT]):
"""Context manager for ensuring that a request is not made
until it is entered and that the response will always be closed
when the context manager exits
"""
def __init__(self, api_request: Awaitable[_AsyncAPIResponseT]) -> None:
self._api_request = api_request
self.__response: _AsyncAPIResponseT | None = None
async def __aenter__(self) -> _AsyncAPIResponseT:
self.__response = await self._api_request
return self.__response
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
if self.__response is not None:
await self.__response.close()
def to_streamed_response_wrapper(func: Callable[P, R]) -> Callable[P, ResponseContextManager[APIResponse[R]]]:
"""Higher order function that takes one of our bound API methods and wraps it
to support streaming and returning the raw `APIResponse` object directly.
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> ResponseContextManager[APIResponse[R]]:
extra_headers: dict[str, str] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "stream"
kwargs["extra_headers"] = extra_headers
make_request = functools.partial(func, *args, **kwargs)
return ResponseContextManager(cast(Callable[[], APIResponse[R]], make_request))
return wrapped
def async_to_streamed_response_wrapper(
func: Callable[P, Awaitable[R]],
) -> Callable[P, AsyncResponseContextManager[AsyncAPIResponse[R]]]:
"""Higher order function that takes one of our bound API methods and wraps it
to support streaming and returning the raw `APIResponse` object directly.
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> AsyncResponseContextManager[AsyncAPIResponse[R]]:
extra_headers: dict[str, str] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "stream"
kwargs["extra_headers"] = extra_headers
make_request = func(*args, **kwargs)
return AsyncResponseContextManager(cast(Awaitable[AsyncAPIResponse[R]], make_request))
return wrapped
def to_custom_streamed_response_wrapper(
func: Callable[P, object],
response_cls: type[_APIResponseT],
) -> Callable[P, ResponseContextManager[_APIResponseT]]:
"""Higher order function that takes one of our bound API methods and an `APIResponse` class
and wraps the method to support streaming and returning the given response class directly.
Note: the given `response_cls` *must* be concrete, e.g. `class BinaryAPIResponse(APIResponse[bytes])`
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> ResponseContextManager[_APIResponseT]:
extra_headers: dict[str, Any] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "stream"
extra_headers[OVERRIDE_CAST_TO_HEADER] = response_cls
kwargs["extra_headers"] = extra_headers
make_request = functools.partial(func, *args, **kwargs)
return ResponseContextManager(cast(Callable[[], _APIResponseT], make_request))
return wrapped
def async_to_custom_streamed_response_wrapper(
func: Callable[P, Awaitable[object]],
response_cls: type[_AsyncAPIResponseT],
) -> Callable[P, AsyncResponseContextManager[_AsyncAPIResponseT]]:
"""Higher order function that takes one of our bound API methods and an `APIResponse` class
and wraps the method to support streaming and returning the given response class directly.
Note: the given `response_cls` *must* be concrete, e.g. `class BinaryAPIResponse(APIResponse[bytes])`
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> AsyncResponseContextManager[_AsyncAPIResponseT]:
extra_headers: dict[str, Any] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "stream"
extra_headers[OVERRIDE_CAST_TO_HEADER] = response_cls
kwargs["extra_headers"] = extra_headers
make_request = func(*args, **kwargs)
return AsyncResponseContextManager(cast(Awaitable[_AsyncAPIResponseT], make_request))
return wrapped
def to_raw_response_wrapper(func: Callable[P, R]) -> Callable[P, APIResponse[R]]:
"""Higher order function that takes one of our bound API methods and wraps it
to support returning the raw `APIResponse` object directly.
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> APIResponse[R]:
extra_headers: dict[str, str] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "raw"
kwargs["extra_headers"] = extra_headers
return cast(APIResponse[R], func(*args, **kwargs))
return wrapped
def async_to_raw_response_wrapper(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[AsyncAPIResponse[R]]]:
"""Higher order function that takes one of our bound API methods and wraps it
to support returning the raw `APIResponse` object directly.
"""
@functools.wraps(func)
async def wrapped(*args: P.args, **kwargs: P.kwargs) -> AsyncAPIResponse[R]:
extra_headers: dict[str, str] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "raw"
kwargs["extra_headers"] = extra_headers
return cast(AsyncAPIResponse[R], await func(*args, **kwargs))
return wrapped
def to_custom_raw_response_wrapper(
func: Callable[P, object],
response_cls: type[_APIResponseT],
) -> Callable[P, _APIResponseT]:
"""Higher order function that takes one of our bound API methods and an `APIResponse` class
and wraps the method to support returning the given response class directly.
Note: the given `response_cls` *must* be concrete, e.g. `class BinaryAPIResponse(APIResponse[bytes])`
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> _APIResponseT:
extra_headers: dict[str, Any] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "raw"
extra_headers[OVERRIDE_CAST_TO_HEADER] = response_cls
kwargs["extra_headers"] = extra_headers
return cast(_APIResponseT, func(*args, **kwargs))
return wrapped
def async_to_custom_raw_response_wrapper(
func: Callable[P, Awaitable[object]],
response_cls: type[_AsyncAPIResponseT],
) -> Callable[P, Awaitable[_AsyncAPIResponseT]]:
"""Higher order function that takes one of our bound API methods and an `APIResponse` class
and wraps the method to support returning the given response class directly.
Note: the given `response_cls` *must* be concrete, e.g. `class BinaryAPIResponse(APIResponse[bytes])`
"""
@functools.wraps(func)
def wrapped(*args: P.args, **kwargs: P.kwargs) -> Awaitable[_AsyncAPIResponseT]:
extra_headers: dict[str, Any] = {**(cast(Any, kwargs.get("extra_headers")) or {})}
extra_headers[RAW_RESPONSE_HEADER] = "raw"
extra_headers[OVERRIDE_CAST_TO_HEADER] = response_cls
kwargs["extra_headers"] = extra_headers
return cast(Awaitable[_AsyncAPIResponseT], func(*args, **kwargs))
return wrapped
def extract_response_type(typ: type[BaseAPIResponse[Any]]) -> type:
"""Given a type like `APIResponse[T]`, returns the generic type variable `T`.
This also handles the case where a concrete subclass is given, e.g.
```py
class MyResponse(APIResponse[bytes]):
...
extract_response_type(MyResponse) -> bytes
```
"""
return extract_type_var_from_base(
typ,
generic_bases=cast("tuple[type, ...]", (BaseAPIResponse, APIResponse, AsyncAPIResponse)),
index=0,
)
@@ -0,0 +1,410 @@
# Note: initially copied from https://github.com/florimondmanca/httpx-sse/blob/master/src/httpx_sse/_decoders.py
from __future__ import annotations
import json
import inspect
from types import TracebackType
from typing import TYPE_CHECKING, Any, Generic, TypeVar, Iterator, AsyncIterator, cast
from typing_extensions import Self, Protocol, TypeGuard, override, get_origin, runtime_checkable
import httpx
from ._utils import is_mapping, extract_type_var_from_base
from ._exceptions import APIError
if TYPE_CHECKING:
from ._client import Groq, AsyncGroq
_T = TypeVar("_T")
class Stream(Generic[_T]):
"""Provides the core interface to iterate over a synchronous stream response."""
response: httpx.Response
_decoder: SSEBytesDecoder
def __init__(
self,
*,
cast_to: type[_T],
response: httpx.Response,
client: Groq,
) -> None:
self.response = response
self._cast_to = cast_to
self._client = client
self._decoder = client._make_sse_decoder()
self._iterator = self.__stream__()
def __next__(self) -> _T:
return self._iterator.__next__()
def __iter__(self) -> Iterator[_T]:
for item in self._iterator:
yield item
def _iter_events(self) -> Iterator[ServerSentEvent]:
yield from self._decoder.iter_bytes(self.response.iter_bytes())
def __stream__(self) -> Iterator[_T]:
cast_to = cast(Any, self._cast_to)
response = self.response
process_data = self._client._process_response_data
iterator = self._iter_events()
for sse in iterator:
if sse.data.startswith("[DONE]"):
break
if sse.event is None:
data = sse.json()
if is_mapping(data) and data.get("error"):
message = None
error = data.get("error")
if is_mapping(error):
message = error.get("message")
if not message or not isinstance(message, str):
message = "An error occurred during streaming"
raise APIError(
message=message,
request=self.response.request,
body=data["error"],
)
yield process_data(data=data, cast_to=cast_to, response=response)
else:
data = sse.json()
if sse.event == "error" and is_mapping(data) and data.get("error"):
message = None
error = data.get("error")
if is_mapping(error):
message = error.get("message")
if not message or not isinstance(message, str):
message = "An error occurred during streaming"
raise APIError(
message=message,
request=self.response.request,
body=data["error"],
)
yield process_data(data={"data": data, "event": sse.event}, cast_to=cast_to, response=response)
# Ensure the entire stream is consumed
for _sse in iterator:
...
def __enter__(self) -> Self:
return self
def __exit__(
self,
exc_type: type[BaseException] | None,
exc: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
self.close()
def close(self) -> None:
"""
Close the response and release the connection.
Automatically called if the response body is read to completion.
"""
self.response.close()
class AsyncStream(Generic[_T]):
"""Provides the core interface to iterate over an asynchronous stream response."""
response: httpx.Response
_decoder: SSEDecoder | SSEBytesDecoder
def __init__(
self,
*,
cast_to: type[_T],
response: httpx.Response,
client: AsyncGroq,
) -> None:
self.response = response
self._cast_to = cast_to
self._client = client
self._decoder = client._make_sse_decoder()
self._iterator = self.__stream__()
async def __anext__(self) -> _T:
return await self._iterator.__anext__()
async def __aiter__(self) -> AsyncIterator[_T]:
async for item in self._iterator:
yield item
async def _iter_events(self) -> AsyncIterator[ServerSentEvent]:
async for sse in self._decoder.aiter_bytes(self.response.aiter_bytes()):
yield sse
async def __stream__(self) -> AsyncIterator[_T]:
cast_to = cast(Any, self._cast_to)
response = self.response
process_data = self._client._process_response_data
iterator = self._iter_events()
async for sse in iterator:
if sse.data.startswith("[DONE]"):
break
if sse.event is None:
data = sse.json()
if is_mapping(data) and data.get("error"):
message = None
error = data.get("error")
if is_mapping(error):
message = error.get("message")
if not message or not isinstance(message, str):
message = "An error occurred during streaming"
raise APIError(
message=message,
request=self.response.request,
body=data["error"],
)
yield process_data(data=data, cast_to=cast_to, response=response)
else:
data = sse.json()
if sse.event == "error" and is_mapping(data) and data.get("error"):
message = None
error = data.get("error")
if is_mapping(error):
message = error.get("message")
if not message or not isinstance(message, str):
message = "An error occurred during streaming"
raise APIError(
message=message,
request=self.response.request,
body=data["error"],
)
yield process_data(data={"data": data, "event": sse.event}, cast_to=cast_to, response=response)
# Ensure the entire stream is consumed
async for _sse in iterator:
...
async def __aenter__(self) -> Self:
return self
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
await self.close()
async def close(self) -> None:
"""
Close the response and release the connection.
Automatically called if the response body is read to completion.
"""
await self.response.aclose()
class ServerSentEvent:
def __init__(
self,
*,
event: str | None = None,
data: str | None = None,
id: str | None = None,
retry: int | None = None,
) -> None:
if data is None:
data = ""
self._id = id
self._data = data
self._event = event or None
self._retry = retry
@property
def event(self) -> str | None:
return self._event
@property
def id(self) -> str | None:
return self._id
@property
def retry(self) -> int | None:
return self._retry
@property
def data(self) -> str:
return self._data
def json(self) -> Any:
return json.loads(self.data)
@override
def __repr__(self) -> str:
return f"ServerSentEvent(event={self.event}, data={self.data}, id={self.id}, retry={self.retry})"
class SSEDecoder:
_data: list[str]
_event: str | None
_retry: int | None
_last_event_id: str | None
def __init__(self) -> None:
self._event = None
self._data = []
self._last_event_id = None
self._retry = None
def iter_bytes(self, iterator: Iterator[bytes]) -> Iterator[ServerSentEvent]:
"""Given an iterator that yields raw binary data, iterate over it & yield every event encountered"""
for chunk in self._iter_chunks(iterator):
# Split before decoding so splitlines() only uses \r and \n
for raw_line in chunk.splitlines():
line = raw_line.decode("utf-8")
sse = self.decode(line)
if sse:
yield sse
def _iter_chunks(self, iterator: Iterator[bytes]) -> Iterator[bytes]:
"""Given an iterator that yields raw binary data, iterate over it and yield individual SSE chunks"""
data = b""
for chunk in iterator:
for line in chunk.splitlines(keepends=True):
data += line
if data.endswith((b"\r\r", b"\n\n", b"\r\n\r\n")):
yield data
data = b""
if data:
yield data
async def aiter_bytes(self, iterator: AsyncIterator[bytes]) -> AsyncIterator[ServerSentEvent]:
"""Given an iterator that yields raw binary data, iterate over it & yield every event encountered"""
async for chunk in self._aiter_chunks(iterator):
# Split before decoding so splitlines() only uses \r and \n
for raw_line in chunk.splitlines():
line = raw_line.decode("utf-8")
sse = self.decode(line)
if sse:
yield sse
async def _aiter_chunks(self, iterator: AsyncIterator[bytes]) -> AsyncIterator[bytes]:
"""Given an iterator that yields raw binary data, iterate over it and yield individual SSE chunks"""
data = b""
async for chunk in iterator:
for line in chunk.splitlines(keepends=True):
data += line
if data.endswith((b"\r\r", b"\n\n", b"\r\n\r\n")):
yield data
data = b""
if data:
yield data
def decode(self, line: str) -> ServerSentEvent | None:
# See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation # noqa: E501
if not line:
if not self._event and not self._data and not self._last_event_id and self._retry is None:
return None
sse = ServerSentEvent(
event=self._event,
data="\n".join(self._data),
id=self._last_event_id,
retry=self._retry,
)
# NOTE: as per the SSE spec, do not reset last_event_id.
self._event = None
self._data = []
self._retry = None
return sse
if line.startswith(":"):
return None
fieldname, _, value = line.partition(":")
if value.startswith(" "):
value = value[1:]
if fieldname == "event":
self._event = value
elif fieldname == "data":
self._data.append(value)
elif fieldname == "id":
if "\0" in value:
pass
else:
self._last_event_id = value
elif fieldname == "retry":
try:
self._retry = int(value)
except (TypeError, ValueError):
pass
else:
pass # Field is ignored.
return None
@runtime_checkable
class SSEBytesDecoder(Protocol):
def iter_bytes(self, iterator: Iterator[bytes]) -> Iterator[ServerSentEvent]:
"""Given an iterator that yields raw binary data, iterate over it & yield every event encountered"""
...
def aiter_bytes(self, iterator: AsyncIterator[bytes]) -> AsyncIterator[ServerSentEvent]:
"""Given an async iterator that yields raw binary data, iterate over it & yield every event encountered"""
...
def is_stream_class_type(typ: type) -> TypeGuard[type[Stream[object]] | type[AsyncStream[object]]]:
"""TypeGuard for determining whether or not the given type is a subclass of `Stream` / `AsyncStream`"""
origin = get_origin(typ) or typ
return inspect.isclass(origin) and issubclass(origin, (Stream, AsyncStream))
def extract_stream_chunk_type(
stream_cls: type,
*,
failure_message: str | None = None,
) -> type:
"""Given a type like `Stream[T]`, returns the generic type variable `T`.
This also handles the case where a concrete subclass is given, e.g.
```py
class MyStream(Stream[bytes]):
...
extract_stream_chunk_type(MyStream) -> bytes
```
"""
from ._base_client import Stream, AsyncStream
return extract_type_var_from_base(
stream_cls,
index=0,
generic_bases=cast("tuple[type, ...]", (Stream, AsyncStream)),
failure_message=failure_message,
)
@@ -0,0 +1,219 @@
from __future__ import annotations
from os import PathLike
from typing import (
IO,
TYPE_CHECKING,
Any,
Dict,
List,
Type,
Tuple,
Union,
Mapping,
TypeVar,
Callable,
Optional,
Sequence,
)
from typing_extensions import Set, Literal, Protocol, TypeAlias, TypedDict, override, runtime_checkable
import httpx
import pydantic
from httpx import URL, Proxy, Timeout, Response, BaseTransport, AsyncBaseTransport
if TYPE_CHECKING:
from ._models import BaseModel
from ._response import APIResponse, AsyncAPIResponse
Transport = BaseTransport
AsyncTransport = AsyncBaseTransport
Query = Mapping[str, object]
Body = object
AnyMapping = Mapping[str, object]
ModelT = TypeVar("ModelT", bound=pydantic.BaseModel)
_T = TypeVar("_T")
# Approximates httpx internal ProxiesTypes and RequestFiles types
# while adding support for `PathLike` instances
ProxiesDict = Dict["str | URL", Union[None, str, URL, Proxy]]
ProxiesTypes = Union[str, Proxy, ProxiesDict]
if TYPE_CHECKING:
Base64FileInput = Union[IO[bytes], PathLike[str]]
FileContent = Union[IO[bytes], bytes, PathLike[str]]
else:
Base64FileInput = Union[IO[bytes], PathLike]
FileContent = Union[IO[bytes], bytes, PathLike] # PathLike is not subscriptable in Python 3.8.
FileTypes = Union[
# file (or bytes)
FileContent,
# (filename, file (or bytes))
Tuple[Optional[str], FileContent],
# (filename, file (or bytes), content_type)
Tuple[Optional[str], FileContent, Optional[str]],
# (filename, file (or bytes), content_type, headers)
Tuple[Optional[str], FileContent, Optional[str], Mapping[str, str]],
]
RequestFiles = Union[Mapping[str, FileTypes], Sequence[Tuple[str, FileTypes]]]
# duplicate of the above but without our custom file support
HttpxFileContent = Union[IO[bytes], bytes]
HttpxFileTypes = Union[
# file (or bytes)
HttpxFileContent,
# (filename, file (or bytes))
Tuple[Optional[str], HttpxFileContent],
# (filename, file (or bytes), content_type)
Tuple[Optional[str], HttpxFileContent, Optional[str]],
# (filename, file (or bytes), content_type, headers)
Tuple[Optional[str], HttpxFileContent, Optional[str], Mapping[str, str]],
]
HttpxRequestFiles = Union[Mapping[str, HttpxFileTypes], Sequence[Tuple[str, HttpxFileTypes]]]
# Workaround to support (cast_to: Type[ResponseT]) -> ResponseT
# where ResponseT includes `None`. In order to support directly
# passing `None`, overloads would have to be defined for every
# method that uses `ResponseT` which would lead to an unacceptable
# amount of code duplication and make it unreadable. See _base_client.py
# for example usage.
#
# This unfortunately means that you will either have
# to import this type and pass it explicitly:
#
# from groq import NoneType
# client.get('/foo', cast_to=NoneType)
#
# or build it yourself:
#
# client.get('/foo', cast_to=type(None))
if TYPE_CHECKING:
NoneType: Type[None]
else:
NoneType = type(None)
class RequestOptions(TypedDict, total=False):
headers: Headers
max_retries: int
timeout: float | Timeout | None
params: Query
extra_json: AnyMapping
idempotency_key: str
follow_redirects: bool
# Sentinel class used until PEP 0661 is accepted
class NotGiven:
"""
A sentinel singleton class used to distinguish omitted keyword arguments
from those passed in with the value None (which may have different behavior).
For example:
```py
def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response: ...
get(timeout=1) # 1s timeout
get(timeout=None) # No timeout
get() # Default timeout behavior, which may not be statically known at the method definition.
```
"""
def __bool__(self) -> Literal[False]:
return False
@override
def __repr__(self) -> str:
return "NOT_GIVEN"
NotGivenOr = Union[_T, NotGiven]
NOT_GIVEN = NotGiven()
class Omit:
"""In certain situations you need to be able to represent a case where a default value has
to be explicitly removed and `None` is not an appropriate substitute, for example:
```py
# as the default `Content-Type` header is `application/json` that will be sent
client.post("/upload/files", files={"file": b"my raw file content"})
# you can't explicitly override the header as it has to be dynamically generated
# to look something like: 'multipart/form-data; boundary=0d8382fcf5f8c3be01ca2e11002d2983'
client.post(..., headers={"Content-Type": "multipart/form-data"})
# instead you can remove the default `application/json` header by passing Omit
client.post(..., headers={"Content-Type": Omit()})
```
"""
def __bool__(self) -> Literal[False]:
return False
@runtime_checkable
class ModelBuilderProtocol(Protocol):
@classmethod
def build(
cls: type[_T],
*,
response: Response,
data: object,
) -> _T: ...
Headers = Mapping[str, Union[str, Omit]]
class HeadersLikeProtocol(Protocol):
def get(self, __key: str) -> str | None: ...
HeadersLike = Union[Headers, HeadersLikeProtocol]
ResponseT = TypeVar(
"ResponseT",
bound=Union[
object,
str,
None,
"BaseModel",
List[Any],
Dict[str, Any],
Response,
ModelBuilderProtocol,
"APIResponse[Any]",
"AsyncAPIResponse[Any]",
],
)
StrBytesIntFloat = Union[str, bytes, int, float]
# Note: copied from Pydantic
# https://github.com/pydantic/pydantic/blob/6f31f8f68ef011f84357330186f603ff295312fd/pydantic/main.py#L79
IncEx: TypeAlias = Union[Set[int], Set[str], Mapping[int, Union["IncEx", bool]], Mapping[str, Union["IncEx", bool]]]
PostParser = Callable[[Any], Any]
@runtime_checkable
class InheritsGeneric(Protocol):
"""Represents a type that has inherited from `Generic`
The `__orig_bases__` property can be used to determine the resolved
type variable for a given base class.
"""
__orig_bases__: tuple[_GenericAlias]
class _GenericAlias(Protocol):
__origin__: type[object]
class HttpxSendArgs(TypedDict, total=False):
auth: httpx.Auth
follow_redirects: bool
@@ -0,0 +1,57 @@
from ._sync import asyncify as asyncify
from ._proxy import LazyProxy as LazyProxy
from ._utils import (
flatten as flatten,
is_dict as is_dict,
is_list as is_list,
is_given as is_given,
is_tuple as is_tuple,
json_safe as json_safe,
lru_cache as lru_cache,
is_mapping as is_mapping,
is_tuple_t as is_tuple_t,
parse_date as parse_date,
is_iterable as is_iterable,
is_sequence as is_sequence,
coerce_float as coerce_float,
is_mapping_t as is_mapping_t,
removeprefix as removeprefix,
removesuffix as removesuffix,
extract_files as extract_files,
is_sequence_t as is_sequence_t,
required_args as required_args,
coerce_boolean as coerce_boolean,
coerce_integer as coerce_integer,
file_from_path as file_from_path,
parse_datetime as parse_datetime,
strip_not_given as strip_not_given,
deepcopy_minimal as deepcopy_minimal,
get_async_library as get_async_library,
maybe_coerce_float as maybe_coerce_float,
get_required_header as get_required_header,
maybe_coerce_boolean as maybe_coerce_boolean,
maybe_coerce_integer as maybe_coerce_integer,
)
from ._typing import (
is_list_type as is_list_type,
is_union_type as is_union_type,
extract_type_arg as extract_type_arg,
is_iterable_type as is_iterable_type,
is_required_type as is_required_type,
is_annotated_type as is_annotated_type,
is_type_alias_type as is_type_alias_type,
strip_annotated_type as strip_annotated_type,
extract_type_var_from_base as extract_type_var_from_base,
)
from ._streams import consume_sync_iterator as consume_sync_iterator, consume_async_iterator as consume_async_iterator
from ._transform import (
PropertyInfo as PropertyInfo,
transform as transform,
async_transform as async_transform,
maybe_transform as maybe_transform,
async_maybe_transform as async_maybe_transform,
)
from ._reflection import (
function_has_argument as function_has_argument,
assert_signatures_in_sync as assert_signatures_in_sync,
)
@@ -0,0 +1,25 @@
import os
import logging
logger: logging.Logger = logging.getLogger("groq")
httpx_logger: logging.Logger = logging.getLogger("httpx")
def _basic_config() -> None:
# e.g. [2023-10-05 14:12:26 - groq._base_client:818 - DEBUG] HTTP Request: POST http://127.0.0.1:4010/foo/bar "200 OK"
logging.basicConfig(
format="[%(asctime)s - %(name)s:%(lineno)d - %(levelname)s] %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
def setup_logging() -> None:
env = os.environ.get("GROQ_LOG")
if env == "debug":
_basic_config()
logger.setLevel(logging.DEBUG)
httpx_logger.setLevel(logging.DEBUG)
elif env == "info":
_basic_config()
logger.setLevel(logging.INFO)
httpx_logger.setLevel(logging.INFO)
@@ -0,0 +1,65 @@
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Generic, TypeVar, Iterable, cast
from typing_extensions import override
T = TypeVar("T")
class LazyProxy(Generic[T], ABC):
"""Implements data methods to pretend that an instance is another instance.
This includes forwarding attribute access and other methods.
"""
# Note: we have to special case proxies that themselves return proxies
# to support using a proxy as a catch-all for any random access, e.g. `proxy.foo.bar.baz`
def __getattr__(self, attr: str) -> object:
proxied = self.__get_proxied__()
if isinstance(proxied, LazyProxy):
return proxied # pyright: ignore
return getattr(proxied, attr)
@override
def __repr__(self) -> str:
proxied = self.__get_proxied__()
if isinstance(proxied, LazyProxy):
return proxied.__class__.__name__
return repr(self.__get_proxied__())
@override
def __str__(self) -> str:
proxied = self.__get_proxied__()
if isinstance(proxied, LazyProxy):
return proxied.__class__.__name__
return str(proxied)
@override
def __dir__(self) -> Iterable[str]:
proxied = self.__get_proxied__()
if isinstance(proxied, LazyProxy):
return []
return proxied.__dir__()
@property # type: ignore
@override
def __class__(self) -> type: # pyright: ignore
try:
proxied = self.__get_proxied__()
except Exception:
return type(self)
if issubclass(type(proxied), LazyProxy):
return type(proxied)
return proxied.__class__
def __get_proxied__(self) -> T:
return self.__load__()
def __as_proxied__(self) -> T:
"""Helper method that returns the current proxy, typed as the loaded object"""
return cast(T, self)
@abstractmethod
def __load__(self) -> T: ...
@@ -0,0 +1,42 @@
from __future__ import annotations
import inspect
from typing import Any, Callable
def function_has_argument(func: Callable[..., Any], arg_name: str) -> bool:
"""Returns whether or not the given function has a specific parameter"""
sig = inspect.signature(func)
return arg_name in sig.parameters
def assert_signatures_in_sync(
source_func: Callable[..., Any],
check_func: Callable[..., Any],
*,
exclude_params: set[str] = set(),
) -> None:
"""Ensure that the signature of the second function matches the first."""
check_sig = inspect.signature(check_func)
source_sig = inspect.signature(source_func)
errors: list[str] = []
for name, source_param in source_sig.parameters.items():
if name in exclude_params:
continue
custom_param = check_sig.parameters.get(name)
if not custom_param:
errors.append(f"the `{name}` param is missing")
continue
if custom_param.annotation != source_param.annotation:
errors.append(
f"types for the `{name}` param are do not match; source={repr(source_param.annotation)} checking={repr(custom_param.annotation)}"
)
continue
if errors:
raise AssertionError(f"{len(errors)} errors encountered when comparing signatures:\n\n" + "\n\n".join(errors))
@@ -0,0 +1,24 @@
from __future__ import annotations
from typing import Any
from typing_extensions import override
from ._proxy import LazyProxy
class ResourcesProxy(LazyProxy[Any]):
"""A proxy for the `groq.resources` module.
This is used so that we can lazily import `groq.resources` only when
needed *and* so that users can just import `groq` and reference `groq.resources`
"""
@override
def __load__(self) -> Any:
import importlib
mod = importlib.import_module("groq.resources")
return mod
resources = ResourcesProxy().__as_proxied__()
@@ -0,0 +1,12 @@
from typing import Any
from typing_extensions import Iterator, AsyncIterator
def consume_sync_iterator(iterator: Iterator[Any]) -> None:
for _ in iterator:
...
async def consume_async_iterator(iterator: AsyncIterator[Any]) -> None:
async for _ in iterator:
...
@@ -0,0 +1,86 @@
from __future__ import annotations
import sys
import asyncio
import functools
import contextvars
from typing import Any, TypeVar, Callable, Awaitable
from typing_extensions import ParamSpec
import anyio
import sniffio
import anyio.to_thread
T_Retval = TypeVar("T_Retval")
T_ParamSpec = ParamSpec("T_ParamSpec")
if sys.version_info >= (3, 9):
_asyncio_to_thread = asyncio.to_thread
else:
# backport of https://docs.python.org/3/library/asyncio-task.html#asyncio.to_thread
# for Python 3.8 support
async def _asyncio_to_thread(
func: Callable[T_ParamSpec, T_Retval], /, *args: T_ParamSpec.args, **kwargs: T_ParamSpec.kwargs
) -> Any:
"""Asynchronously run function *func* in a separate thread.
Any *args and **kwargs supplied for this function are directly passed
to *func*. Also, the current :class:`contextvars.Context` is propagated,
allowing context variables from the main thread to be accessed in the
separate thread.
Returns a coroutine that can be awaited to get the eventual result of *func*.
"""
loop = asyncio.events.get_running_loop()
ctx = contextvars.copy_context()
func_call = functools.partial(ctx.run, func, *args, **kwargs)
return await loop.run_in_executor(None, func_call)
async def to_thread(
func: Callable[T_ParamSpec, T_Retval], /, *args: T_ParamSpec.args, **kwargs: T_ParamSpec.kwargs
) -> T_Retval:
if sniffio.current_async_library() == "asyncio":
return await _asyncio_to_thread(func, *args, **kwargs)
return await anyio.to_thread.run_sync(
functools.partial(func, *args, **kwargs),
)
# inspired by `asyncer`, https://github.com/tiangolo/asyncer
def asyncify(function: Callable[T_ParamSpec, T_Retval]) -> Callable[T_ParamSpec, Awaitable[T_Retval]]:
"""
Take a blocking function and create an async one that receives the same
positional and keyword arguments. For python version 3.9 and above, it uses
asyncio.to_thread to run the function in a separate thread. For python version
3.8, it uses locally defined copy of the asyncio.to_thread function which was
introduced in python 3.9.
Usage:
```python
def blocking_func(arg1, arg2, kwarg1=None):
# blocking code
return result
result = asyncify(blocking_function)(arg1, arg2, kwarg1=value1)
```
## Arguments
`function`: a blocking regular callable (e.g. a function)
## Return
An async function that takes the same positional and keyword arguments as the
original one, that when called runs the same original function in a thread worker
and returns the result.
"""
async def wrapper(*args: T_ParamSpec.args, **kwargs: T_ParamSpec.kwargs) -> T_Retval:
return await to_thread(function, *args, **kwargs)
return wrapper
@@ -0,0 +1,447 @@
from __future__ import annotations
import io
import base64
import pathlib
from typing import Any, Mapping, TypeVar, cast
from datetime import date, datetime
from typing_extensions import Literal, get_args, override, get_type_hints as _get_type_hints
import anyio
import pydantic
from ._utils import (
is_list,
is_given,
lru_cache,
is_mapping,
is_iterable,
)
from .._files import is_base64_file_input
from ._typing import (
is_list_type,
is_union_type,
extract_type_arg,
is_iterable_type,
is_required_type,
is_annotated_type,
strip_annotated_type,
)
from .._compat import get_origin, model_dump, is_typeddict
_T = TypeVar("_T")
# TODO: support for drilling globals() and locals()
# TODO: ensure works correctly with forward references in all cases
PropertyFormat = Literal["iso8601", "base64", "custom"]
class PropertyInfo:
"""Metadata class to be used in Annotated types to provide information about a given type.
For example:
class MyParams(TypedDict):
account_holder_name: Annotated[str, PropertyInfo(alias='accountHolderName')]
This means that {'account_holder_name': 'Robert'} will be transformed to {'accountHolderName': 'Robert'} before being sent to the API.
"""
alias: str | None
format: PropertyFormat | None
format_template: str | None
discriminator: str | None
def __init__(
self,
*,
alias: str | None = None,
format: PropertyFormat | None = None,
format_template: str | None = None,
discriminator: str | None = None,
) -> None:
self.alias = alias
self.format = format
self.format_template = format_template
self.discriminator = discriminator
@override
def __repr__(self) -> str:
return f"{self.__class__.__name__}(alias='{self.alias}', format={self.format}, format_template='{self.format_template}', discriminator='{self.discriminator}')"
def maybe_transform(
data: object,
expected_type: object,
) -> Any | None:
"""Wrapper over `transform()` that allows `None` to be passed.
See `transform()` for more details.
"""
if data is None:
return None
return transform(data, expected_type)
# Wrapper over _transform_recursive providing fake types
def transform(
data: _T,
expected_type: object,
) -> _T:
"""Transform dictionaries based off of type information from the given type, for example:
```py
class Params(TypedDict, total=False):
card_id: Required[Annotated[str, PropertyInfo(alias="cardID")]]
transformed = transform({"card_id": "<my card ID>"}, Params)
# {'cardID': '<my card ID>'}
```
Any keys / data that does not have type information given will be included as is.
It should be noted that the transformations that this function does are not represented in the type system.
"""
transformed = _transform_recursive(data, annotation=cast(type, expected_type))
return cast(_T, transformed)
@lru_cache(maxsize=8096)
def _get_annotated_type(type_: type) -> type | None:
"""If the given type is an `Annotated` type then it is returned, if not `None` is returned.
This also unwraps the type when applicable, e.g. `Required[Annotated[T, ...]]`
"""
if is_required_type(type_):
# Unwrap `Required[Annotated[T, ...]]` to `Annotated[T, ...]`
type_ = get_args(type_)[0]
if is_annotated_type(type_):
return type_
return None
def _maybe_transform_key(key: str, type_: type) -> str:
"""Transform the given `data` based on the annotations provided in `type_`.
Note: this function only looks at `Annotated` types that contain `PropertyInfo` metadata.
"""
annotated_type = _get_annotated_type(type_)
if annotated_type is None:
# no `Annotated` definition for this type, no transformation needed
return key
# ignore the first argument as it is the actual type
annotations = get_args(annotated_type)[1:]
for annotation in annotations:
if isinstance(annotation, PropertyInfo) and annotation.alias is not None:
return annotation.alias
return key
def _no_transform_needed(annotation: type) -> bool:
return annotation == float or annotation == int
def _transform_recursive(
data: object,
*,
annotation: type,
inner_type: type | None = None,
) -> object:
"""Transform the given data against the expected type.
Args:
annotation: The direct type annotation given to the particular piece of data.
This may or may not be wrapped in metadata types, e.g. `Required[T]`, `Annotated[T, ...]` etc
inner_type: If applicable, this is the "inside" type. This is useful in certain cases where the outside type
is a container type such as `List[T]`. In that case `inner_type` should be set to `T` so that each entry in
the list can be transformed using the metadata from the container type.
Defaults to the same value as the `annotation` argument.
"""
if inner_type is None:
inner_type = annotation
stripped_type = strip_annotated_type(inner_type)
origin = get_origin(stripped_type) or stripped_type
if is_typeddict(stripped_type) and is_mapping(data):
return _transform_typeddict(data, stripped_type)
if origin == dict and is_mapping(data):
items_type = get_args(stripped_type)[1]
return {key: _transform_recursive(value, annotation=items_type) for key, value in data.items()}
if (
# List[T]
(is_list_type(stripped_type) and is_list(data))
# Iterable[T]
or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str))
):
# dicts are technically iterable, but it is an iterable on the keys of the dict and is not usually
# intended as an iterable, so we don't transform it.
if isinstance(data, dict):
return cast(object, data)
inner_type = extract_type_arg(stripped_type, 0)
if _no_transform_needed(inner_type):
# for some types there is no need to transform anything, so we can get a small
# perf boost from skipping that work.
#
# but we still need to convert to a list to ensure the data is json-serializable
if is_list(data):
return data
return list(data)
return [_transform_recursive(d, annotation=annotation, inner_type=inner_type) for d in data]
if is_union_type(stripped_type):
# For union types we run the transformation against all subtypes to ensure that everything is transformed.
#
# TODO: there may be edge cases where the same normalized field name will transform to two different names
# in different subtypes.
for subtype in get_args(stripped_type):
data = _transform_recursive(data, annotation=annotation, inner_type=subtype)
return data
if isinstance(data, pydantic.BaseModel):
return model_dump(data, exclude_unset=True, mode="json")
annotated_type = _get_annotated_type(annotation)
if annotated_type is None:
return data
# ignore the first argument as it is the actual type
annotations = get_args(annotated_type)[1:]
for annotation in annotations:
if isinstance(annotation, PropertyInfo) and annotation.format is not None:
return _format_data(data, annotation.format, annotation.format_template)
return data
def _format_data(data: object, format_: PropertyFormat, format_template: str | None) -> object:
if isinstance(data, (date, datetime)):
if format_ == "iso8601":
return data.isoformat()
if format_ == "custom" and format_template is not None:
return data.strftime(format_template)
if format_ == "base64" and is_base64_file_input(data):
binary: str | bytes | None = None
if isinstance(data, pathlib.Path):
binary = data.read_bytes()
elif isinstance(data, io.IOBase):
binary = data.read()
if isinstance(binary, str): # type: ignore[unreachable]
binary = binary.encode()
if not isinstance(binary, bytes):
raise RuntimeError(f"Could not read bytes from {data}; Received {type(binary)}")
return base64.b64encode(binary).decode("ascii")
return data
def _transform_typeddict(
data: Mapping[str, object],
expected_type: type,
) -> Mapping[str, object]:
result: dict[str, object] = {}
annotations = get_type_hints(expected_type, include_extras=True)
for key, value in data.items():
if not is_given(value):
# we don't need to include `NotGiven` values here as they'll
# be stripped out before the request is sent anyway
continue
type_ = annotations.get(key)
if type_ is None:
# we do not have a type annotation for this field, leave it as is
result[key] = value
else:
result[_maybe_transform_key(key, type_)] = _transform_recursive(value, annotation=type_)
return result
async def async_maybe_transform(
data: object,
expected_type: object,
) -> Any | None:
"""Wrapper over `async_transform()` that allows `None` to be passed.
See `async_transform()` for more details.
"""
if data is None:
return None
return await async_transform(data, expected_type)
async def async_transform(
data: _T,
expected_type: object,
) -> _T:
"""Transform dictionaries based off of type information from the given type, for example:
```py
class Params(TypedDict, total=False):
card_id: Required[Annotated[str, PropertyInfo(alias="cardID")]]
transformed = transform({"card_id": "<my card ID>"}, Params)
# {'cardID': '<my card ID>'}
```
Any keys / data that does not have type information given will be included as is.
It should be noted that the transformations that this function does are not represented in the type system.
"""
transformed = await _async_transform_recursive(data, annotation=cast(type, expected_type))
return cast(_T, transformed)
async def _async_transform_recursive(
data: object,
*,
annotation: type,
inner_type: type | None = None,
) -> object:
"""Transform the given data against the expected type.
Args:
annotation: The direct type annotation given to the particular piece of data.
This may or may not be wrapped in metadata types, e.g. `Required[T]`, `Annotated[T, ...]` etc
inner_type: If applicable, this is the "inside" type. This is useful in certain cases where the outside type
is a container type such as `List[T]`. In that case `inner_type` should be set to `T` so that each entry in
the list can be transformed using the metadata from the container type.
Defaults to the same value as the `annotation` argument.
"""
if inner_type is None:
inner_type = annotation
stripped_type = strip_annotated_type(inner_type)
origin = get_origin(stripped_type) or stripped_type
if is_typeddict(stripped_type) and is_mapping(data):
return await _async_transform_typeddict(data, stripped_type)
if origin == dict and is_mapping(data):
items_type = get_args(stripped_type)[1]
return {key: _transform_recursive(value, annotation=items_type) for key, value in data.items()}
if (
# List[T]
(is_list_type(stripped_type) and is_list(data))
# Iterable[T]
or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str))
):
# dicts are technically iterable, but it is an iterable on the keys of the dict and is not usually
# intended as an iterable, so we don't transform it.
if isinstance(data, dict):
return cast(object, data)
inner_type = extract_type_arg(stripped_type, 0)
if _no_transform_needed(inner_type):
# for some types there is no need to transform anything, so we can get a small
# perf boost from skipping that work.
#
# but we still need to convert to a list to ensure the data is json-serializable
if is_list(data):
return data
return list(data)
return [await _async_transform_recursive(d, annotation=annotation, inner_type=inner_type) for d in data]
if is_union_type(stripped_type):
# For union types we run the transformation against all subtypes to ensure that everything is transformed.
#
# TODO: there may be edge cases where the same normalized field name will transform to two different names
# in different subtypes.
for subtype in get_args(stripped_type):
data = await _async_transform_recursive(data, annotation=annotation, inner_type=subtype)
return data
if isinstance(data, pydantic.BaseModel):
return model_dump(data, exclude_unset=True, mode="json")
annotated_type = _get_annotated_type(annotation)
if annotated_type is None:
return data
# ignore the first argument as it is the actual type
annotations = get_args(annotated_type)[1:]
for annotation in annotations:
if isinstance(annotation, PropertyInfo) and annotation.format is not None:
return await _async_format_data(data, annotation.format, annotation.format_template)
return data
async def _async_format_data(data: object, format_: PropertyFormat, format_template: str | None) -> object:
if isinstance(data, (date, datetime)):
if format_ == "iso8601":
return data.isoformat()
if format_ == "custom" and format_template is not None:
return data.strftime(format_template)
if format_ == "base64" and is_base64_file_input(data):
binary: str | bytes | None = None
if isinstance(data, pathlib.Path):
binary = await anyio.Path(data).read_bytes()
elif isinstance(data, io.IOBase):
binary = data.read()
if isinstance(binary, str): # type: ignore[unreachable]
binary = binary.encode()
if not isinstance(binary, bytes):
raise RuntimeError(f"Could not read bytes from {data}; Received {type(binary)}")
return base64.b64encode(binary).decode("ascii")
return data
async def _async_transform_typeddict(
data: Mapping[str, object],
expected_type: type,
) -> Mapping[str, object]:
result: dict[str, object] = {}
annotations = get_type_hints(expected_type, include_extras=True)
for key, value in data.items():
if not is_given(value):
# we don't need to include `NotGiven` values here as they'll
# be stripped out before the request is sent anyway
continue
type_ = annotations.get(key)
if type_ is None:
# we do not have a type annotation for this field, leave it as is
result[key] = value
else:
result[_maybe_transform_key(key, type_)] = await _async_transform_recursive(value, annotation=type_)
return result
@lru_cache(maxsize=8096)
def get_type_hints(
obj: Any,
globalns: dict[str, Any] | None = None,
localns: Mapping[str, Any] | None = None,
include_extras: bool = False,
) -> dict[str, Any]:
return _get_type_hints(obj, globalns=globalns, localns=localns, include_extras=include_extras)
@@ -0,0 +1,151 @@
from __future__ import annotations
import sys
import typing
import typing_extensions
from typing import Any, TypeVar, Iterable, cast
from collections import abc as _c_abc
from typing_extensions import (
TypeIs,
Required,
Annotated,
get_args,
get_origin,
)
from ._utils import lru_cache
from .._types import InheritsGeneric
from .._compat import is_union as _is_union
def is_annotated_type(typ: type) -> bool:
return get_origin(typ) == Annotated
def is_list_type(typ: type) -> bool:
return (get_origin(typ) or typ) == list
def is_iterable_type(typ: type) -> bool:
"""If the given type is `typing.Iterable[T]`"""
origin = get_origin(typ) or typ
return origin == Iterable or origin == _c_abc.Iterable
def is_union_type(typ: type) -> bool:
return _is_union(get_origin(typ))
def is_required_type(typ: type) -> bool:
return get_origin(typ) == Required
def is_typevar(typ: type) -> bool:
# type ignore is required because type checkers
# think this expression will always return False
return type(typ) == TypeVar # type: ignore
_TYPE_ALIAS_TYPES: tuple[type[typing_extensions.TypeAliasType], ...] = (typing_extensions.TypeAliasType,)
if sys.version_info >= (3, 12):
_TYPE_ALIAS_TYPES = (*_TYPE_ALIAS_TYPES, typing.TypeAliasType)
def is_type_alias_type(tp: Any, /) -> TypeIs[typing_extensions.TypeAliasType]:
"""Return whether the provided argument is an instance of `TypeAliasType`.
```python
type Int = int
is_type_alias_type(Int)
# > True
Str = TypeAliasType("Str", str)
is_type_alias_type(Str)
# > True
```
"""
return isinstance(tp, _TYPE_ALIAS_TYPES)
# Extracts T from Annotated[T, ...] or from Required[Annotated[T, ...]]
@lru_cache(maxsize=8096)
def strip_annotated_type(typ: type) -> type:
if is_required_type(typ) or is_annotated_type(typ):
return strip_annotated_type(cast(type, get_args(typ)[0]))
return typ
def extract_type_arg(typ: type, index: int) -> type:
args = get_args(typ)
try:
return cast(type, args[index])
except IndexError as err:
raise RuntimeError(f"Expected type {typ} to have a type argument at index {index} but it did not") from err
def extract_type_var_from_base(
typ: type,
*,
generic_bases: tuple[type, ...],
index: int,
failure_message: str | None = None,
) -> type:
"""Given a type like `Foo[T]`, returns the generic type variable `T`.
This also handles the case where a concrete subclass is given, e.g.
```py
class MyResponse(Foo[bytes]):
...
extract_type_var(MyResponse, bases=(Foo,), index=0) -> bytes
```
And where a generic subclass is given:
```py
_T = TypeVar('_T')
class MyResponse(Foo[_T]):
...
extract_type_var(MyResponse[bytes], bases=(Foo,), index=0) -> bytes
```
"""
cls = cast(object, get_origin(typ) or typ)
if cls in generic_bases: # pyright: ignore[reportUnnecessaryContains]
# we're given the class directly
return extract_type_arg(typ, index)
# if a subclass is given
# ---
# this is needed as __orig_bases__ is not present in the typeshed stubs
# because it is intended to be for internal use only, however there does
# not seem to be a way to resolve generic TypeVars for inherited subclasses
# without using it.
if isinstance(cls, InheritsGeneric):
target_base_class: Any | None = None
for base in cls.__orig_bases__:
if base.__origin__ in generic_bases:
target_base_class = base
break
if target_base_class is None:
raise RuntimeError(
"Could not find the generic base class;\n"
"This should never happen;\n"
f"Does {cls} inherit from one of {generic_bases} ?"
)
extracted = extract_type_arg(target_base_class, index)
if is_typevar(extracted):
# If the extracted type argument is itself a type variable
# then that means the subclass itself is generic, so we have
# to resolve the type argument from the class itself, not
# the base class.
#
# Note: if there is more than 1 type argument, the subclass could
# change the ordering of the type arguments, this is not currently
# supported.
return extract_type_arg(typ, index)
return extracted
raise RuntimeError(failure_message or f"Could not resolve inner type variable at index {index} for {typ}")
@@ -0,0 +1,422 @@
from __future__ import annotations
import os
import re
import inspect
import functools
from typing import (
Any,
Tuple,
Mapping,
TypeVar,
Callable,
Iterable,
Sequence,
cast,
overload,
)
from pathlib import Path
from datetime import date, datetime
from typing_extensions import TypeGuard
import sniffio
from .._types import NotGiven, FileTypes, NotGivenOr, HeadersLike
from .._compat import parse_date as parse_date, parse_datetime as parse_datetime
_T = TypeVar("_T")
_TupleT = TypeVar("_TupleT", bound=Tuple[object, ...])
_MappingT = TypeVar("_MappingT", bound=Mapping[str, object])
_SequenceT = TypeVar("_SequenceT", bound=Sequence[object])
CallableT = TypeVar("CallableT", bound=Callable[..., Any])
def flatten(t: Iterable[Iterable[_T]]) -> list[_T]:
return [item for sublist in t for item in sublist]
def extract_files(
# TODO: this needs to take Dict but variance issues.....
# create protocol type ?
query: Mapping[str, object],
*,
paths: Sequence[Sequence[str]],
) -> list[tuple[str, FileTypes]]:
"""Recursively extract files from the given dictionary based on specified paths.
A path may look like this ['foo', 'files', '<array>', 'data'].
Note: this mutates the given dictionary.
"""
files: list[tuple[str, FileTypes]] = []
for path in paths:
files.extend(_extract_items(query, path, index=0, flattened_key=None))
return files
def _extract_items(
obj: object,
path: Sequence[str],
*,
index: int,
flattened_key: str | None,
) -> list[tuple[str, FileTypes]]:
try:
key = path[index]
except IndexError:
if isinstance(obj, NotGiven):
# no value was provided - we can safely ignore
return []
# cyclical import
from .._files import assert_is_file_content
# We have exhausted the path, return the entry we found.
assert flattened_key is not None
if is_list(obj):
files: list[tuple[str, FileTypes]] = []
for entry in obj:
assert_is_file_content(entry, key=flattened_key + "[]" if flattened_key else "")
files.append((flattened_key + "[]", cast(FileTypes, entry)))
return files
assert_is_file_content(obj, key=flattened_key)
return [(flattened_key, cast(FileTypes, obj))]
index += 1
if is_dict(obj):
try:
# We are at the last entry in the path so we must remove the field
if (len(path)) == index:
item = obj.pop(key)
else:
item = obj[key]
except KeyError:
# Key was not present in the dictionary, this is not indicative of an error
# as the given path may not point to a required field. We also do not want
# to enforce required fields as the API may differ from the spec in some cases.
return []
if flattened_key is None:
flattened_key = key
else:
flattened_key += f"[{key}]"
return _extract_items(
item,
path,
index=index,
flattened_key=flattened_key,
)
elif is_list(obj):
if key != "<array>":
return []
return flatten(
[
_extract_items(
item,
path,
index=index,
flattened_key=flattened_key + "[]" if flattened_key is not None else "[]",
)
for item in obj
]
)
# Something unexpected was passed, just ignore it.
return []
def is_given(obj: NotGivenOr[_T]) -> TypeGuard[_T]:
return not isinstance(obj, NotGiven)
# Type safe methods for narrowing types with TypeVars.
# The default narrowing for isinstance(obj, dict) is dict[unknown, unknown],
# however this cause Pyright to rightfully report errors. As we know we don't
# care about the contained types we can safely use `object` in it's place.
#
# There are two separate functions defined, `is_*` and `is_*_t` for different use cases.
# `is_*` is for when you're dealing with an unknown input
# `is_*_t` is for when you're narrowing a known union type to a specific subset
def is_tuple(obj: object) -> TypeGuard[tuple[object, ...]]:
return isinstance(obj, tuple)
def is_tuple_t(obj: _TupleT | object) -> TypeGuard[_TupleT]:
return isinstance(obj, tuple)
def is_sequence(obj: object) -> TypeGuard[Sequence[object]]:
return isinstance(obj, Sequence)
def is_sequence_t(obj: _SequenceT | object) -> TypeGuard[_SequenceT]:
return isinstance(obj, Sequence)
def is_mapping(obj: object) -> TypeGuard[Mapping[str, object]]:
return isinstance(obj, Mapping)
def is_mapping_t(obj: _MappingT | object) -> TypeGuard[_MappingT]:
return isinstance(obj, Mapping)
def is_dict(obj: object) -> TypeGuard[dict[object, object]]:
return isinstance(obj, dict)
def is_list(obj: object) -> TypeGuard[list[object]]:
return isinstance(obj, list)
def is_iterable(obj: object) -> TypeGuard[Iterable[object]]:
return isinstance(obj, Iterable)
def deepcopy_minimal(item: _T) -> _T:
"""Minimal reimplementation of copy.deepcopy() that will only copy certain object types:
- mappings, e.g. `dict`
- list
This is done for performance reasons.
"""
if is_mapping(item):
return cast(_T, {k: deepcopy_minimal(v) for k, v in item.items()})
if is_list(item):
return cast(_T, [deepcopy_minimal(entry) for entry in item])
return item
# copied from https://github.com/Rapptz/RoboDanny
def human_join(seq: Sequence[str], *, delim: str = ", ", final: str = "or") -> str:
size = len(seq)
if size == 0:
return ""
if size == 1:
return seq[0]
if size == 2:
return f"{seq[0]} {final} {seq[1]}"
return delim.join(seq[:-1]) + f" {final} {seq[-1]}"
def quote(string: str) -> str:
"""Add single quotation marks around the given string. Does *not* do any escaping."""
return f"'{string}'"
def required_args(*variants: Sequence[str]) -> Callable[[CallableT], CallableT]:
"""Decorator to enforce a given set of arguments or variants of arguments are passed to the decorated function.
Useful for enforcing runtime validation of overloaded functions.
Example usage:
```py
@overload
def foo(*, a: str) -> str: ...
@overload
def foo(*, b: bool) -> str: ...
# This enforces the same constraints that a static type checker would
# i.e. that either a or b must be passed to the function
@required_args(["a"], ["b"])
def foo(*, a: str | None = None, b: bool | None = None) -> str: ...
```
"""
def inner(func: CallableT) -> CallableT:
params = inspect.signature(func).parameters
positional = [
name
for name, param in params.items()
if param.kind
in {
param.POSITIONAL_ONLY,
param.POSITIONAL_OR_KEYWORD,
}
]
@functools.wraps(func)
def wrapper(*args: object, **kwargs: object) -> object:
given_params: set[str] = set()
for i, _ in enumerate(args):
try:
given_params.add(positional[i])
except IndexError:
raise TypeError(
f"{func.__name__}() takes {len(positional)} argument(s) but {len(args)} were given"
) from None
for key in kwargs.keys():
given_params.add(key)
for variant in variants:
matches = all((param in given_params for param in variant))
if matches:
break
else: # no break
if len(variants) > 1:
variations = human_join(
["(" + human_join([quote(arg) for arg in variant], final="and") + ")" for variant in variants]
)
msg = f"Missing required arguments; Expected either {variations} arguments to be given"
else:
assert len(variants) > 0
# TODO: this error message is not deterministic
missing = list(set(variants[0]) - given_params)
if len(missing) > 1:
msg = f"Missing required arguments: {human_join([quote(arg) for arg in missing])}"
else:
msg = f"Missing required argument: {quote(missing[0])}"
raise TypeError(msg)
return func(*args, **kwargs)
return wrapper # type: ignore
return inner
_K = TypeVar("_K")
_V = TypeVar("_V")
@overload
def strip_not_given(obj: None) -> None: ...
@overload
def strip_not_given(obj: Mapping[_K, _V | NotGiven]) -> dict[_K, _V]: ...
@overload
def strip_not_given(obj: object) -> object: ...
def strip_not_given(obj: object | None) -> object:
"""Remove all top-level keys where their values are instances of `NotGiven`"""
if obj is None:
return None
if not is_mapping(obj):
return obj
return {key: value for key, value in obj.items() if not isinstance(value, NotGiven)}
def coerce_integer(val: str) -> int:
return int(val, base=10)
def coerce_float(val: str) -> float:
return float(val)
def coerce_boolean(val: str) -> bool:
return val == "true" or val == "1" or val == "on"
def maybe_coerce_integer(val: str | None) -> int | None:
if val is None:
return None
return coerce_integer(val)
def maybe_coerce_float(val: str | None) -> float | None:
if val is None:
return None
return coerce_float(val)
def maybe_coerce_boolean(val: str | None) -> bool | None:
if val is None:
return None
return coerce_boolean(val)
def removeprefix(string: str, prefix: str) -> str:
"""Remove a prefix from a string.
Backport of `str.removeprefix` for Python < 3.9
"""
if string.startswith(prefix):
return string[len(prefix) :]
return string
def removesuffix(string: str, suffix: str) -> str:
"""Remove a suffix from a string.
Backport of `str.removesuffix` for Python < 3.9
"""
if string.endswith(suffix):
return string[: -len(suffix)]
return string
def file_from_path(path: str) -> FileTypes:
contents = Path(path).read_bytes()
file_name = os.path.basename(path)
return (file_name, contents)
def get_required_header(headers: HeadersLike, header: str) -> str:
lower_header = header.lower()
if is_mapping_t(headers):
# mypy doesn't understand the type narrowing here
for k, v in headers.items(): # type: ignore
if k.lower() == lower_header and isinstance(v, str):
return v
# to deal with the case where the header looks like Stainless-Event-Id
intercaps_header = re.sub(r"([^\w])(\w)", lambda pat: pat.group(1) + pat.group(2).upper(), header.capitalize())
for normalized_header in [header, lower_header, header.upper(), intercaps_header]:
value = headers.get(normalized_header)
if value:
return value
raise ValueError(f"Could not find {header} header")
def get_async_library() -> str:
try:
return sniffio.current_async_library()
except Exception:
return "false"
def lru_cache(*, maxsize: int | None = 128) -> Callable[[CallableT], CallableT]:
"""A version of functools.lru_cache that retains the type signature
for the wrapped function arguments.
"""
wrapper = functools.lru_cache( # noqa: TID251
maxsize=maxsize,
)
return cast(Any, wrapper) # type: ignore[no-any-return]
def json_safe(data: object) -> object:
"""Translates a mapping / sequence recursively in the same fashion
as `pydantic` v2's `model_dump(mode="json")`.
"""
if is_mapping(data):
return {json_safe(key): json_safe(value) for key, value in data.items()}
if is_iterable(data) and not isinstance(data, (str, bytes, bytearray)):
return [json_safe(item) for item in data]
if isinstance(data, (datetime, date)):
return data.isoformat()
return data
@@ -0,0 +1,4 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
__title__ = "groq"
__version__ = "0.30.0" # x-release-please-version
@@ -0,0 +1,4 @@
File generated from our OpenAPI spec by Stainless.
This directory can be used to store custom files to expand the SDK.
It is ignored by Stainless code generation and its content (other than this keep file) won't be touched.
@@ -0,0 +1,89 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from .chat import (
Chat,
AsyncChat,
ChatWithRawResponse,
AsyncChatWithRawResponse,
ChatWithStreamingResponse,
AsyncChatWithStreamingResponse,
)
from .audio import (
Audio,
AsyncAudio,
AudioWithRawResponse,
AsyncAudioWithRawResponse,
AudioWithStreamingResponse,
AsyncAudioWithStreamingResponse,
)
from .files import (
Files,
AsyncFiles,
FilesWithRawResponse,
AsyncFilesWithRawResponse,
FilesWithStreamingResponse,
AsyncFilesWithStreamingResponse,
)
from .models import (
Models,
AsyncModels,
ModelsWithRawResponse,
AsyncModelsWithRawResponse,
ModelsWithStreamingResponse,
AsyncModelsWithStreamingResponse,
)
from .batches import (
Batches,
AsyncBatches,
BatchesWithRawResponse,
AsyncBatchesWithRawResponse,
BatchesWithStreamingResponse,
AsyncBatchesWithStreamingResponse,
)
from .embeddings import (
Embeddings,
AsyncEmbeddings,
EmbeddingsWithRawResponse,
AsyncEmbeddingsWithRawResponse,
EmbeddingsWithStreamingResponse,
AsyncEmbeddingsWithStreamingResponse,
)
__all__ = [
"Chat",
"AsyncChat",
"ChatWithRawResponse",
"AsyncChatWithRawResponse",
"ChatWithStreamingResponse",
"AsyncChatWithStreamingResponse",
"Embeddings",
"AsyncEmbeddings",
"EmbeddingsWithRawResponse",
"AsyncEmbeddingsWithRawResponse",
"EmbeddingsWithStreamingResponse",
"AsyncEmbeddingsWithStreamingResponse",
"Audio",
"AsyncAudio",
"AudioWithRawResponse",
"AsyncAudioWithRawResponse",
"AudioWithStreamingResponse",
"AsyncAudioWithStreamingResponse",
"Models",
"AsyncModels",
"ModelsWithRawResponse",
"AsyncModelsWithRawResponse",
"ModelsWithStreamingResponse",
"AsyncModelsWithStreamingResponse",
"Batches",
"AsyncBatches",
"BatchesWithRawResponse",
"AsyncBatchesWithRawResponse",
"BatchesWithStreamingResponse",
"AsyncBatchesWithStreamingResponse",
"Files",
"AsyncFiles",
"FilesWithRawResponse",
"AsyncFilesWithRawResponse",
"FilesWithStreamingResponse",
"AsyncFilesWithStreamingResponse",
]
@@ -0,0 +1,61 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from .audio import (
Audio,
AsyncAudio,
AudioWithRawResponse,
AsyncAudioWithRawResponse,
AudioWithStreamingResponse,
AsyncAudioWithStreamingResponse,
)
from .speech import (
Speech,
AsyncSpeech,
SpeechWithRawResponse,
AsyncSpeechWithRawResponse,
SpeechWithStreamingResponse,
AsyncSpeechWithStreamingResponse,
)
from .translations import (
Translations,
AsyncTranslations,
TranslationsWithRawResponse,
AsyncTranslationsWithRawResponse,
TranslationsWithStreamingResponse,
AsyncTranslationsWithStreamingResponse,
)
from .transcriptions import (
Transcriptions,
AsyncTranscriptions,
TranscriptionsWithRawResponse,
AsyncTranscriptionsWithRawResponse,
TranscriptionsWithStreamingResponse,
AsyncTranscriptionsWithStreamingResponse,
)
__all__ = [
"Speech",
"AsyncSpeech",
"SpeechWithRawResponse",
"AsyncSpeechWithRawResponse",
"SpeechWithStreamingResponse",
"AsyncSpeechWithStreamingResponse",
"Transcriptions",
"AsyncTranscriptions",
"TranscriptionsWithRawResponse",
"AsyncTranscriptionsWithRawResponse",
"TranscriptionsWithStreamingResponse",
"AsyncTranscriptionsWithStreamingResponse",
"Translations",
"AsyncTranslations",
"TranslationsWithRawResponse",
"AsyncTranslationsWithRawResponse",
"TranslationsWithStreamingResponse",
"AsyncTranslationsWithStreamingResponse",
"Audio",
"AsyncAudio",
"AudioWithRawResponse",
"AsyncAudioWithRawResponse",
"AudioWithStreamingResponse",
"AsyncAudioWithStreamingResponse",
]
@@ -0,0 +1,166 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from .speech import (
Speech,
AsyncSpeech,
SpeechWithRawResponse,
AsyncSpeechWithRawResponse,
SpeechWithStreamingResponse,
AsyncSpeechWithStreamingResponse,
)
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from .translations import (
Translations,
AsyncTranslations,
TranslationsWithRawResponse,
AsyncTranslationsWithRawResponse,
TranslationsWithStreamingResponse,
AsyncTranslationsWithStreamingResponse,
)
from .transcriptions import (
Transcriptions,
AsyncTranscriptions,
TranscriptionsWithRawResponse,
AsyncTranscriptionsWithRawResponse,
TranscriptionsWithStreamingResponse,
AsyncTranscriptionsWithStreamingResponse,
)
__all__ = ["Audio", "AsyncAudio"]
class Audio(SyncAPIResource):
@cached_property
def speech(self) -> Speech:
return Speech(self._client)
@cached_property
def transcriptions(self) -> Transcriptions:
return Transcriptions(self._client)
@cached_property
def translations(self) -> Translations:
return Translations(self._client)
@cached_property
def with_raw_response(self) -> AudioWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AudioWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AudioWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AudioWithStreamingResponse(self)
class AsyncAudio(AsyncAPIResource):
@cached_property
def speech(self) -> AsyncSpeech:
return AsyncSpeech(self._client)
@cached_property
def transcriptions(self) -> AsyncTranscriptions:
return AsyncTranscriptions(self._client)
@cached_property
def translations(self) -> AsyncTranslations:
return AsyncTranslations(self._client)
@cached_property
def with_raw_response(self) -> AsyncAudioWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncAudioWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncAudioWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncAudioWithStreamingResponse(self)
class AudioWithRawResponse:
def __init__(self, audio: Audio) -> None:
self._audio = audio
@cached_property
def speech(self) -> SpeechWithRawResponse:
return SpeechWithRawResponse(self._audio.speech)
@cached_property
def transcriptions(self) -> TranscriptionsWithRawResponse:
return TranscriptionsWithRawResponse(self._audio.transcriptions)
@cached_property
def translations(self) -> TranslationsWithRawResponse:
return TranslationsWithRawResponse(self._audio.translations)
class AsyncAudioWithRawResponse:
def __init__(self, audio: AsyncAudio) -> None:
self._audio = audio
@cached_property
def speech(self) -> AsyncSpeechWithRawResponse:
return AsyncSpeechWithRawResponse(self._audio.speech)
@cached_property
def transcriptions(self) -> AsyncTranscriptionsWithRawResponse:
return AsyncTranscriptionsWithRawResponse(self._audio.transcriptions)
@cached_property
def translations(self) -> AsyncTranslationsWithRawResponse:
return AsyncTranslationsWithRawResponse(self._audio.translations)
class AudioWithStreamingResponse:
def __init__(self, audio: Audio) -> None:
self._audio = audio
@cached_property
def speech(self) -> SpeechWithStreamingResponse:
return SpeechWithStreamingResponse(self._audio.speech)
@cached_property
def transcriptions(self) -> TranscriptionsWithStreamingResponse:
return TranscriptionsWithStreamingResponse(self._audio.transcriptions)
@cached_property
def translations(self) -> TranslationsWithStreamingResponse:
return TranslationsWithStreamingResponse(self._audio.translations)
class AsyncAudioWithStreamingResponse:
def __init__(self, audio: AsyncAudio) -> None:
self._audio = audio
@cached_property
def speech(self) -> AsyncSpeechWithStreamingResponse:
return AsyncSpeechWithStreamingResponse(self._audio.speech)
@cached_property
def transcriptions(self) -> AsyncTranscriptionsWithStreamingResponse:
return AsyncTranscriptionsWithStreamingResponse(self._audio.transcriptions)
@cached_property
def translations(self) -> AsyncTranslationsWithStreamingResponse:
return AsyncTranslationsWithStreamingResponse(self._audio.translations)
@@ -0,0 +1,233 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import Union
from typing_extensions import Literal
import httpx
from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from ..._utils import maybe_transform, async_maybe_transform
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from ..._response import (
BinaryAPIResponse,
AsyncBinaryAPIResponse,
StreamedBinaryAPIResponse,
AsyncStreamedBinaryAPIResponse,
to_custom_raw_response_wrapper,
to_custom_streamed_response_wrapper,
async_to_custom_raw_response_wrapper,
async_to_custom_streamed_response_wrapper,
)
from ...types.audio import speech_create_params
from ..._base_client import make_request_options
__all__ = ["Speech", "AsyncSpeech"]
class Speech(SyncAPIResource):
@cached_property
def with_raw_response(self) -> SpeechWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return SpeechWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> SpeechWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return SpeechWithStreamingResponse(self)
def create(
self,
*,
input: str,
model: Union[str, Literal["playai-tts", "playai-tts-arabic"]],
voice: str,
response_format: Literal["flac", "mp3", "mulaw", "ogg", "wav"] | NotGiven = NOT_GIVEN,
sample_rate: Literal[8000, 16000, 22050, 24000, 32000, 44100, 48000] | NotGiven = NOT_GIVEN,
speed: 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,
) -> BinaryAPIResponse:
"""
Generates audio from the input text.
Args:
input: The text to generate audio for.
model: One of the [available TTS models](/docs/text-to-speech).
voice: The voice to use when generating the audio. List of voices can be found
[here](/docs/text-to-speech).
response_format: The format of the generated audio. Supported formats are
`flac, mp3, mulaw, ogg, wav`.
sample_rate: The sample rate for generated audio
speed: The speed of the generated audio.
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
"""
extra_headers = {"Accept": "audio/wav", **(extra_headers or {})}
return self._post(
"/openai/v1/audio/speech",
body=maybe_transform(
{
"input": input,
"model": model,
"voice": voice,
"response_format": response_format,
"sample_rate": sample_rate,
"speed": speed,
},
speech_create_params.SpeechCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BinaryAPIResponse,
)
class AsyncSpeech(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncSpeechWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncSpeechWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncSpeechWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncSpeechWithStreamingResponse(self)
async def create(
self,
*,
input: str,
model: Union[str, Literal["playai-tts", "playai-tts-arabic"]],
voice: str,
response_format: Literal["flac", "mp3", "mulaw", "ogg", "wav"] | NotGiven = NOT_GIVEN,
sample_rate: Literal[8000, 16000, 22050, 24000, 32000, 44100, 48000] | NotGiven = NOT_GIVEN,
speed: 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,
) -> AsyncBinaryAPIResponse:
"""
Generates audio from the input text.
Args:
input: The text to generate audio for.
model: One of the [available TTS models](/docs/text-to-speech).
voice: The voice to use when generating the audio. List of voices can be found
[here](/docs/text-to-speech).
response_format: The format of the generated audio. Supported formats are
`flac, mp3, mulaw, ogg, wav`.
sample_rate: The sample rate for generated audio
speed: The speed of the generated audio.
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
"""
extra_headers = {"Accept": "audio/wav", **(extra_headers or {})}
return await self._post(
"/openai/v1/audio/speech",
body=await async_maybe_transform(
{
"input": input,
"model": model,
"voice": voice,
"response_format": response_format,
"sample_rate": sample_rate,
"speed": speed,
},
speech_create_params.SpeechCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=AsyncBinaryAPIResponse,
)
class SpeechWithRawResponse:
def __init__(self, speech: Speech) -> None:
self._speech = speech
self.create = to_custom_raw_response_wrapper(
speech.create,
BinaryAPIResponse,
)
class AsyncSpeechWithRawResponse:
def __init__(self, speech: AsyncSpeech) -> None:
self._speech = speech
self.create = async_to_custom_raw_response_wrapper(
speech.create,
AsyncBinaryAPIResponse,
)
class SpeechWithStreamingResponse:
def __init__(self, speech: Speech) -> None:
self._speech = speech
self.create = to_custom_streamed_response_wrapper(
speech.create,
StreamedBinaryAPIResponse,
)
class AsyncSpeechWithStreamingResponse:
def __init__(self, speech: AsyncSpeech) -> None:
self._speech = speech
self.create = async_to_custom_streamed_response_wrapper(
speech.create,
AsyncStreamedBinaryAPIResponse,
)
@@ -0,0 +1,494 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import List, Union, Mapping, cast
from typing_extensions import Literal
import httpx
from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven, FileTypes
from ..._utils import extract_files, maybe_transform, deepcopy_minimal, async_maybe_transform
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from ..._response import (
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
async_to_streamed_response_wrapper,
)
from ...types.audio import transcription_create_params
from ..._base_client import make_request_options
from ...types.audio.transcription import Transcription
__all__ = ["Transcriptions", "AsyncTranscriptions"]
class Transcriptions(SyncAPIResource):
@cached_property
def with_raw_response(self) -> TranscriptionsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return TranscriptionsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> TranscriptionsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return TranscriptionsWithStreamingResponse(self)
def create(
self,
*,
model: Union[str, Literal["whisper-large-v3", "whisper-large-v3-turbo"]],
file: FileTypes | NotGiven = NOT_GIVEN,
language: Union[
str,
Literal[
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"uk",
"el",
"ms",
"cs",
"ro",
"da",
"hu",
"ta",
"no",
"th",
"ur",
"hr",
"bg",
"lt",
"la",
"mi",
"ml",
"cy",
"sk",
"te",
"fa",
"lv",
"bn",
"sr",
"az",
"sl",
"kn",
"et",
"mk",
"br",
"eu",
"is",
"hy",
"ne",
"mn",
"bs",
"kk",
"sq",
"sw",
"gl",
"mr",
"pa",
"si",
"km",
"sn",
"yo",
"so",
"af",
"oc",
"ka",
"be",
"tg",
"sd",
"gu",
"am",
"yi",
"lo",
"uz",
"fo",
"ht",
"ps",
"tk",
"nn",
"mt",
"sa",
"lb",
"my",
"bo",
"tl",
"mg",
"as",
"tt",
"haw",
"ln",
"ha",
"ba",
"jv",
"su",
"yue",
],
]
| NotGiven = NOT_GIVEN,
prompt: str | NotGiven = NOT_GIVEN,
response_format: Literal["json", "text", "verbose_json"] | NotGiven = NOT_GIVEN,
temperature: float | NotGiven = NOT_GIVEN,
timestamp_granularities: List[Literal["word", "segment"]] | NotGiven = NOT_GIVEN,
url: str | 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,
) -> Transcription:
"""
Transcribes audio into the input language.
Args:
model: ID of the model to use. `whisper-large-v3` and `whisper-large-v3-turbo` are
currently available.
file:
The audio file object (not file name) to transcribe, in one of these formats:
flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. Either a file or a URL must
be provided. Note that the file field is not supported in Batch API requests.
language: The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will
improve accuracy and latency.
prompt: An optional text to guide the model's style or continue a previous audio
segment. The [prompt](/docs/speech-text) should match the audio language.
response_format: The format of the transcript output, in one of these options: `json`, `text`, or
`verbose_json`.
temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the
output more random, while lower values like 0.2 will make it more focused and
deterministic. If set to 0, the model will use
[log probability](https://en.wikipedia.org/wiki/Log_probability) to
automatically increase the temperature until certain thresholds are hit.
timestamp_granularities: The timestamp granularities to populate for this transcription.
`response_format` must be set `verbose_json` to use timestamp granularities.
Either or both of these options are supported: `word`, or `segment`. Note: There
is no additional latency for segment timestamps, but generating word timestamps
incurs additional latency.
url: The audio URL to translate/transcribe (supports Base64URL). Either a file or a
URL must be provided. For Batch API requests, the URL field is required since
the file field is not supported.
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
"""
body = deepcopy_minimal(
{
"model": model,
"file": file,
"language": language,
"prompt": prompt,
"response_format": response_format,
"temperature": temperature,
"timestamp_granularities": timestamp_granularities,
"url": url,
}
)
files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
# It should be noted that the actual Content-Type header that will be
# sent to the server will contain a `boundary` parameter, e.g.
# multipart/form-data; boundary=---abc--
extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
return self._post(
"/openai/v1/audio/transcriptions",
body=maybe_transform(body, transcription_create_params.TranscriptionCreateParams),
files=files,
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Transcription,
)
class AsyncTranscriptions(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncTranscriptionsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncTranscriptionsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncTranscriptionsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncTranscriptionsWithStreamingResponse(self)
async def create(
self,
*,
model: Union[str, Literal["whisper-large-v3", "whisper-large-v3-turbo"]],
file: FileTypes | NotGiven = NOT_GIVEN,
language: Union[
str,
Literal[
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"uk",
"el",
"ms",
"cs",
"ro",
"da",
"hu",
"ta",
"no",
"th",
"ur",
"hr",
"bg",
"lt",
"la",
"mi",
"ml",
"cy",
"sk",
"te",
"fa",
"lv",
"bn",
"sr",
"az",
"sl",
"kn",
"et",
"mk",
"br",
"eu",
"is",
"hy",
"ne",
"mn",
"bs",
"kk",
"sq",
"sw",
"gl",
"mr",
"pa",
"si",
"km",
"sn",
"yo",
"so",
"af",
"oc",
"ka",
"be",
"tg",
"sd",
"gu",
"am",
"yi",
"lo",
"uz",
"fo",
"ht",
"ps",
"tk",
"nn",
"mt",
"sa",
"lb",
"my",
"bo",
"tl",
"mg",
"as",
"tt",
"haw",
"ln",
"ha",
"ba",
"jv",
"su",
"yue",
],
]
| NotGiven = NOT_GIVEN,
prompt: str | NotGiven = NOT_GIVEN,
response_format: Literal["json", "text", "verbose_json"] | NotGiven = NOT_GIVEN,
temperature: float | NotGiven = NOT_GIVEN,
timestamp_granularities: List[Literal["word", "segment"]] | NotGiven = NOT_GIVEN,
url: str | 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,
) -> Transcription:
"""
Transcribes audio into the input language.
Args:
model: ID of the model to use. `whisper-large-v3` and `whisper-large-v3-turbo` are
currently available.
file:
The audio file object (not file name) to transcribe, in one of these formats:
flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. Either a file or a URL must
be provided. Note that the file field is not supported in Batch API requests.
language: The language of the input audio. Supplying the input language in
[ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will
improve accuracy and latency.
prompt: An optional text to guide the model's style or continue a previous audio
segment. The [prompt](/docs/speech-text) should match the audio language.
response_format: The format of the transcript output, in one of these options: `json`, `text`, or
`verbose_json`.
temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the
output more random, while lower values like 0.2 will make it more focused and
deterministic. If set to 0, the model will use
[log probability](https://en.wikipedia.org/wiki/Log_probability) to
automatically increase the temperature until certain thresholds are hit.
timestamp_granularities: The timestamp granularities to populate for this transcription.
`response_format` must be set `verbose_json` to use timestamp granularities.
Either or both of these options are supported: `word`, or `segment`. Note: There
is no additional latency for segment timestamps, but generating word timestamps
incurs additional latency.
url: The audio URL to translate/transcribe (supports Base64URL). Either a file or a
URL must be provided. For Batch API requests, the URL field is required since
the file field is not supported.
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
"""
body = deepcopy_minimal(
{
"model": model,
"file": file,
"language": language,
"prompt": prompt,
"response_format": response_format,
"temperature": temperature,
"timestamp_granularities": timestamp_granularities,
"url": url,
}
)
files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
# It should be noted that the actual Content-Type header that will be
# sent to the server will contain a `boundary` parameter, e.g.
# multipart/form-data; boundary=---abc--
extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
return await self._post(
"/openai/v1/audio/transcriptions",
body=await async_maybe_transform(body, transcription_create_params.TranscriptionCreateParams),
files=files,
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Transcription,
)
class TranscriptionsWithRawResponse:
def __init__(self, transcriptions: Transcriptions) -> None:
self._transcriptions = transcriptions
self.create = to_raw_response_wrapper(
transcriptions.create,
)
class AsyncTranscriptionsWithRawResponse:
def __init__(self, transcriptions: AsyncTranscriptions) -> None:
self._transcriptions = transcriptions
self.create = async_to_raw_response_wrapper(
transcriptions.create,
)
class TranscriptionsWithStreamingResponse:
def __init__(self, transcriptions: Transcriptions) -> None:
self._transcriptions = transcriptions
self.create = to_streamed_response_wrapper(
transcriptions.create,
)
class AsyncTranscriptionsWithStreamingResponse:
def __init__(self, transcriptions: AsyncTranscriptions) -> None:
self._transcriptions = transcriptions
self.create = async_to_streamed_response_wrapper(
transcriptions.create,
)
@@ -0,0 +1,254 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import Union, Mapping, cast
from typing_extensions import Literal
import httpx
from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven, FileTypes
from ..._utils import extract_files, maybe_transform, deepcopy_minimal, async_maybe_transform
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from ..._response import (
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
async_to_streamed_response_wrapper,
)
from ...types.audio import translation_create_params
from ..._base_client import make_request_options
from ...types.audio.translation import Translation
__all__ = ["Translations", "AsyncTranslations"]
class Translations(SyncAPIResource):
@cached_property
def with_raw_response(self) -> TranslationsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return TranslationsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> TranslationsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return TranslationsWithStreamingResponse(self)
def create(
self,
*,
model: Union[str, Literal["whisper-large-v3", "whisper-large-v3-turbo"]],
file: FileTypes | NotGiven = NOT_GIVEN,
prompt: str | NotGiven = NOT_GIVEN,
response_format: Literal["json", "text", "verbose_json"] | NotGiven = NOT_GIVEN,
temperature: float | NotGiven = NOT_GIVEN,
url: str | 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,
) -> Translation:
"""Translates audio into English.
Args:
model: ID of the model to use.
`whisper-large-v3` and `whisper-large-v3-turbo` are
currently available.
file: The audio file object (not file name) translate, in one of these formats: flac,
mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
prompt: An optional text to guide the model's style or continue a previous audio
segment. The [prompt](/docs/guides/speech-to-text/prompting) should be in
English.
response_format: The format of the transcript output, in one of these options: `json`, `text`, or
`verbose_json`.
temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the
output more random, while lower values like 0.2 will make it more focused and
deterministic. If set to 0, the model will use
[log probability](https://en.wikipedia.org/wiki/Log_probability) to
automatically increase the temperature until certain thresholds are hit.
url: The audio URL to translate/transcribe (supports Base64URL). Either file or url
must be provided. When using the Batch API only url is supported.
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
"""
body = deepcopy_minimal(
{
"model": model,
"file": file,
"prompt": prompt,
"response_format": response_format,
"temperature": temperature,
"url": url,
}
)
files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
# It should be noted that the actual Content-Type header that will be
# sent to the server will contain a `boundary` parameter, e.g.
# multipart/form-data; boundary=---abc--
extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
return self._post(
"/openai/v1/audio/translations",
body=maybe_transform(body, translation_create_params.TranslationCreateParams),
files=files,
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Translation,
)
class AsyncTranslations(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncTranslationsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncTranslationsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncTranslationsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncTranslationsWithStreamingResponse(self)
async def create(
self,
*,
model: Union[str, Literal["whisper-large-v3", "whisper-large-v3-turbo"]],
file: FileTypes | NotGiven = NOT_GIVEN,
prompt: str | NotGiven = NOT_GIVEN,
response_format: Literal["json", "text", "verbose_json"] | NotGiven = NOT_GIVEN,
temperature: float | NotGiven = NOT_GIVEN,
url: str | 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,
) -> Translation:
"""Translates audio into English.
Args:
model: ID of the model to use.
`whisper-large-v3` and `whisper-large-v3-turbo` are
currently available.
file: The audio file object (not file name) translate, in one of these formats: flac,
mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
prompt: An optional text to guide the model's style or continue a previous audio
segment. The [prompt](/docs/guides/speech-to-text/prompting) should be in
English.
response_format: The format of the transcript output, in one of these options: `json`, `text`, or
`verbose_json`.
temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the
output more random, while lower values like 0.2 will make it more focused and
deterministic. If set to 0, the model will use
[log probability](https://en.wikipedia.org/wiki/Log_probability) to
automatically increase the temperature until certain thresholds are hit.
url: The audio URL to translate/transcribe (supports Base64URL). Either file or url
must be provided. When using the Batch API only url is supported.
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
"""
body = deepcopy_minimal(
{
"model": model,
"file": file,
"prompt": prompt,
"response_format": response_format,
"temperature": temperature,
"url": url,
}
)
files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
# It should be noted that the actual Content-Type header that will be
# sent to the server will contain a `boundary` parameter, e.g.
# multipart/form-data; boundary=---abc--
extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
return await self._post(
"/openai/v1/audio/translations",
body=await async_maybe_transform(body, translation_create_params.TranslationCreateParams),
files=files,
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Translation,
)
class TranslationsWithRawResponse:
def __init__(self, translations: Translations) -> None:
self._translations = translations
self.create = to_raw_response_wrapper(
translations.create,
)
class AsyncTranslationsWithRawResponse:
def __init__(self, translations: AsyncTranslations) -> None:
self._translations = translations
self.create = async_to_raw_response_wrapper(
translations.create,
)
class TranslationsWithStreamingResponse:
def __init__(self, translations: Translations) -> None:
self._translations = translations
self.create = to_streamed_response_wrapper(
translations.create,
)
class AsyncTranslationsWithStreamingResponse:
def __init__(self, translations: AsyncTranslations) -> None:
self._translations = translations
self.create = async_to_streamed_response_wrapper(
translations.create,
)
@@ -0,0 +1,429 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import Dict, Optional
from typing_extensions import Literal
import httpx
from ..types import batch_create_params
from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from .._utils import maybe_transform, async_maybe_transform
from .._compat import cached_property
from .._resource import SyncAPIResource, AsyncAPIResource
from .._response import (
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
async_to_streamed_response_wrapper,
)
from .._base_client import make_request_options
from ..types.batch_list_response import BatchListResponse
from ..types.batch_cancel_response import BatchCancelResponse
from ..types.batch_create_response import BatchCreateResponse
from ..types.batch_retrieve_response import BatchRetrieveResponse
__all__ = ["Batches", "AsyncBatches"]
class Batches(SyncAPIResource):
@cached_property
def with_raw_response(self) -> BatchesWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return BatchesWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> BatchesWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return BatchesWithStreamingResponse(self)
def create(
self,
*,
completion_window: str,
endpoint: Literal["/v1/chat/completions"],
input_file_id: str,
metadata: Optional[Dict[str, str]] | 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,
) -> BatchCreateResponse:
"""
Creates and executes a batch from an uploaded file of requests.
[Learn more](/docs/batch).
Args:
completion_window: The time frame within which the batch should be processed. Durations from `24h`
to `7d` are supported.
endpoint: The endpoint to be used for all requests in the batch. Currently
`/v1/chat/completions` is supported.
input_file_id: The ID of an uploaded file that contains requests for the new batch.
See [upload file](/docs/api-reference#files-upload) for how to upload a file.
Your input file must be formatted as a [JSONL file](/docs/batch), and must be
uploaded with the purpose `batch`. The file can be up to 100 MB in size.
metadata: Optional custom metadata for the batch.
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
"""
return self._post(
"/openai/v1/batches",
body=maybe_transform(
{
"completion_window": completion_window,
"endpoint": endpoint,
"input_file_id": input_file_id,
"metadata": metadata,
},
batch_create_params.BatchCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchCreateResponse,
)
def retrieve(
self,
batch_id: str,
*,
# 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,
) -> BatchRetrieveResponse:
"""
Retrieves a batch.
Args:
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 batch_id:
raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
return self._get(
f"/openai/v1/batches/{batch_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchRetrieveResponse,
)
def list(
self,
*,
# 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,
) -> BatchListResponse:
"""List your organization's batches."""
return self._get(
"/openai/v1/batches",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchListResponse,
)
def cancel(
self,
batch_id: str,
*,
# 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,
) -> BatchCancelResponse:
"""
Cancels a batch.
Args:
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 batch_id:
raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
return self._post(
f"/openai/v1/batches/{batch_id}/cancel",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchCancelResponse,
)
class AsyncBatches(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncBatchesWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncBatchesWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncBatchesWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncBatchesWithStreamingResponse(self)
async def create(
self,
*,
completion_window: str,
endpoint: Literal["/v1/chat/completions"],
input_file_id: str,
metadata: Optional[Dict[str, str]] | 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,
) -> BatchCreateResponse:
"""
Creates and executes a batch from an uploaded file of requests.
[Learn more](/docs/batch).
Args:
completion_window: The time frame within which the batch should be processed. Durations from `24h`
to `7d` are supported.
endpoint: The endpoint to be used for all requests in the batch. Currently
`/v1/chat/completions` is supported.
input_file_id: The ID of an uploaded file that contains requests for the new batch.
See [upload file](/docs/api-reference#files-upload) for how to upload a file.
Your input file must be formatted as a [JSONL file](/docs/batch), and must be
uploaded with the purpose `batch`. The file can be up to 100 MB in size.
metadata: Optional custom metadata for the batch.
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
"""
return await self._post(
"/openai/v1/batches",
body=await async_maybe_transform(
{
"completion_window": completion_window,
"endpoint": endpoint,
"input_file_id": input_file_id,
"metadata": metadata,
},
batch_create_params.BatchCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchCreateResponse,
)
async def retrieve(
self,
batch_id: str,
*,
# 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,
) -> BatchRetrieveResponse:
"""
Retrieves a batch.
Args:
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 batch_id:
raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
return await self._get(
f"/openai/v1/batches/{batch_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchRetrieveResponse,
)
async def list(
self,
*,
# 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,
) -> BatchListResponse:
"""List your organization's batches."""
return await self._get(
"/openai/v1/batches",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchListResponse,
)
async def cancel(
self,
batch_id: str,
*,
# 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,
) -> BatchCancelResponse:
"""
Cancels a batch.
Args:
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 batch_id:
raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}")
return await self._post(
f"/openai/v1/batches/{batch_id}/cancel",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BatchCancelResponse,
)
class BatchesWithRawResponse:
def __init__(self, batches: Batches) -> None:
self._batches = batches
self.create = to_raw_response_wrapper(
batches.create,
)
self.retrieve = to_raw_response_wrapper(
batches.retrieve,
)
self.list = to_raw_response_wrapper(
batches.list,
)
self.cancel = to_raw_response_wrapper(
batches.cancel,
)
class AsyncBatchesWithRawResponse:
def __init__(self, batches: AsyncBatches) -> None:
self._batches = batches
self.create = async_to_raw_response_wrapper(
batches.create,
)
self.retrieve = async_to_raw_response_wrapper(
batches.retrieve,
)
self.list = async_to_raw_response_wrapper(
batches.list,
)
self.cancel = async_to_raw_response_wrapper(
batches.cancel,
)
class BatchesWithStreamingResponse:
def __init__(self, batches: Batches) -> None:
self._batches = batches
self.create = to_streamed_response_wrapper(
batches.create,
)
self.retrieve = to_streamed_response_wrapper(
batches.retrieve,
)
self.list = to_streamed_response_wrapper(
batches.list,
)
self.cancel = to_streamed_response_wrapper(
batches.cancel,
)
class AsyncBatchesWithStreamingResponse:
def __init__(self, batches: AsyncBatches) -> None:
self._batches = batches
self.create = async_to_streamed_response_wrapper(
batches.create,
)
self.retrieve = async_to_streamed_response_wrapper(
batches.retrieve,
)
self.list = async_to_streamed_response_wrapper(
batches.list,
)
self.cancel = async_to_streamed_response_wrapper(
batches.cancel,
)
@@ -0,0 +1,33 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from .chat import (
Chat,
AsyncChat,
ChatWithRawResponse,
AsyncChatWithRawResponse,
ChatWithStreamingResponse,
AsyncChatWithStreamingResponse,
)
from .completions import (
Completions,
AsyncCompletions,
CompletionsWithRawResponse,
AsyncCompletionsWithRawResponse,
CompletionsWithStreamingResponse,
AsyncCompletionsWithStreamingResponse,
)
__all__ = [
"Completions",
"AsyncCompletions",
"CompletionsWithRawResponse",
"AsyncCompletionsWithRawResponse",
"CompletionsWithStreamingResponse",
"AsyncCompletionsWithStreamingResponse",
"Chat",
"AsyncChat",
"ChatWithRawResponse",
"AsyncChatWithRawResponse",
"ChatWithStreamingResponse",
"AsyncChatWithStreamingResponse",
]
@@ -0,0 +1,102 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from .completions import (
Completions,
AsyncCompletions,
CompletionsWithRawResponse,
AsyncCompletionsWithRawResponse,
CompletionsWithStreamingResponse,
AsyncCompletionsWithStreamingResponse,
)
__all__ = ["Chat", "AsyncChat"]
class Chat(SyncAPIResource):
@cached_property
def completions(self) -> Completions:
return Completions(self._client)
@cached_property
def with_raw_response(self) -> ChatWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return ChatWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> ChatWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return ChatWithStreamingResponse(self)
class AsyncChat(AsyncAPIResource):
@cached_property
def completions(self) -> AsyncCompletions:
return AsyncCompletions(self._client)
@cached_property
def with_raw_response(self) -> AsyncChatWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncChatWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncChatWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncChatWithStreamingResponse(self)
class ChatWithRawResponse:
def __init__(self, chat: Chat) -> None:
self._chat = chat
@cached_property
def completions(self) -> CompletionsWithRawResponse:
return CompletionsWithRawResponse(self._chat.completions)
class AsyncChatWithRawResponse:
def __init__(self, chat: AsyncChat) -> None:
self._chat = chat
@cached_property
def completions(self) -> AsyncCompletionsWithRawResponse:
return AsyncCompletionsWithRawResponse(self._chat.completions)
class ChatWithStreamingResponse:
def __init__(self, chat: Chat) -> None:
self._chat = chat
@cached_property
def completions(self) -> CompletionsWithStreamingResponse:
return CompletionsWithStreamingResponse(self._chat.completions)
class AsyncChatWithStreamingResponse:
def __init__(self, chat: AsyncChat) -> None:
self._chat = chat
@cached_property
def completions(self) -> AsyncCompletionsWithStreamingResponse:
return AsyncCompletionsWithStreamingResponse(self._chat.completions)
@@ -0,0 +1,829 @@
# 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, overload
from typing_extensions import Literal
import httpx
from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from ..._utils import maybe_transform, async_maybe_transform
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from ..._response import (
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
async_to_streamed_response_wrapper,
)
from ..._streaming import Stream, AsyncStream
from ...types.chat import completion_create_params
from ..._base_client import make_request_options
from ...types.chat.chat_completion import ChatCompletion
from ...types.chat.chat_completion_chunk import ChatCompletionChunk
from ...types.chat.chat_completion_tool_param import ChatCompletionToolParam
from ...types.chat.chat_completion_message_param import ChatCompletionMessageParam
from ...types.chat.chat_completion_tool_choice_option_param import ChatCompletionToolChoiceOptionParam
__all__ = ["Completions", "AsyncCompletions"]
class Completions(SyncAPIResource):
@cached_property
def with_raw_response(self) -> CompletionsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return CompletionsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> CompletionsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return CompletionsWithStreamingResponse(self)
@overload
def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: str,
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> ChatCompletion:
...
@overload
def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: str,
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: Literal[True],
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> Stream[ChatCompletionChunk]:
...
@overload
def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: str,
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: bool,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> ChatCompletion | Stream[ChatCompletionChunk]:
...
def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: Union[
str,
Literal[
"gemma2-9b-it",
"llama-3.3-70b-versatile",
"llama-3.1-8b-instant",
"llama-guard-3-8b",
"llama3-70b-8192",
"llama3-8b-8192",
],
],
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> ChatCompletion | Stream[ChatCompletionChunk]:
"""
Creates a model response for the given chat conversation.
Args:
messages: A list of messages comprising the conversation so far.
model: ID of the model to use. For details on which models are compatible with the Chat
API, see available [models](https://console.groq.com/docs/models)
exclude_domains: Deprecated: Use search_settings.exclude_domains instead. A list of domains to
exclude from the search results when the model uses a web search tool.
frequency_penalty: 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.
function_call: 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: Deprecated in favor of `tools`.
A list of functions the model may generate JSON inputs for.
include_domains: Deprecated: Use search_settings.include_domains instead. A list of domains to
include in the search results when the model uses a web search tool.
logit_bias: This is not yet supported by any of our models. Modify the likelihood of
specified tokens appearing in the completion.
logprobs: This is not yet supported by any of our models. 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`.
max_completion_tokens: The maximum number of tokens 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.
max_tokens: Deprecated in favor of `max_completion_tokens`. The maximum number of tokens
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.
metadata: This parameter is not currently supported.
n: How many chat completion choices to generate for each input message. Note that
the current moment, only n=1 is supported. Other values will result in a 400
response.
parallel_tool_calls: Whether to enable parallel function calling during tool use.
presence_penalty: 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.
reasoning_effort: this field is only available for qwen3 models. Set to 'none' to disable
reasoning. Set to 'default' or null to let Qwen reason.
reasoning_format: Specifies how to output reasoning tokens
response_format: 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. json_schema
response format is only supported on llama 4 models. 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.
search_settings: Settings for web search functionality when the model uses a web search tool.
seed: 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.
service_tier: The service tier to use for the request. Defaults to `on_demand`.
- `auto` will automatically select the highest tier available within the rate
limits of your organization.
- `flex` uses the flex tier, which will succeed or fail quickly.
stop: Up to 4 sequences where the API will stop generating further tokens. The
returned text will not contain the stop sequence.
store: This parameter is not currently supported.
stream: If set, partial message deltas will be sent. 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 code](/docs/text-chat#streaming-a-chat-completion).
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. We generally recommend altering this or top_p but not
both.
tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
not call any tool and instead generates a message. `auto` means the model can
pick between generating a message or calling one or more tools. `required` means
the model must call one or more tools. Specifying a particular tool via
`{"type": "function", "function": {"name": "my_function"}}` forces the model to
call that tool.
`none` is the default when no tools are present. `auto` is the default if tools
are present.
tools: 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: This is not yet supported by any of our models. 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: 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: A unique identifier representing your end-user, which can help us monitor and
detect abuse.
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
"""
return self._post(
"/openai/v1/chat/completions",
body=maybe_transform(
{
"messages": messages,
"model": model,
"exclude_domains": exclude_domains,
"frequency_penalty": frequency_penalty,
"function_call": function_call,
"functions": functions,
"include_domains": include_domains,
"logit_bias": logit_bias,
"logprobs": logprobs,
"max_completion_tokens": max_completion_tokens,
"max_tokens": max_tokens,
"metadata": metadata,
"n": n,
"parallel_tool_calls": parallel_tool_calls,
"presence_penalty": presence_penalty,
"reasoning_effort": reasoning_effort,
"reasoning_format": reasoning_format,
"response_format": response_format,
"search_settings": search_settings,
"seed": seed,
"service_tier": service_tier,
"stop": stop,
"store": store,
"stream": stream,
"temperature": temperature,
"tool_choice": tool_choice,
"tools": tools,
"top_logprobs": top_logprobs,
"top_p": top_p,
"user": user,
},
completion_create_params.CompletionCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=ChatCompletion,
stream=stream or False,
stream_cls=Stream[ChatCompletionChunk],
)
class AsyncCompletions(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncCompletionsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncCompletionsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncCompletionsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncCompletionsWithStreamingResponse(self)
@overload
async def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: str,
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> ChatCompletion:
...
@overload
async def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: str,
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: Literal[True],
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> AsyncStream[ChatCompletionChunk]:
...
@overload
async def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: str,
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: bool,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
...
async def create(
self,
*,
messages: Iterable[ChatCompletionMessageParam],
model: Union[
str,
Literal[
"gemma2-9b-it",
"llama-3.3-70b-versatile",
"llama-3.1-8b-instant",
"llama-guard-3-8b",
"llama3-70b-8192",
"llama3-8b-8192",
],
],
exclude_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
include_domains: Optional[List[str]] | NotGiven = NOT_GIVEN,
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN,
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
metadata: Optional[Dict[str, str]] | NotGiven = NOT_GIVEN,
n: Optional[int] | NotGiven = NOT_GIVEN,
parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
reasoning_effort: Optional[Literal["none", "default"]] | NotGiven = NOT_GIVEN,
reasoning_format: Optional[Literal["hidden", "raw", "parsed"]] | NotGiven = NOT_GIVEN,
response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
search_settings: Optional[completion_create_params.SearchSettings] | NotGiven = NOT_GIVEN,
seed: Optional[int] | NotGiven = NOT_GIVEN,
service_tier: Optional[Literal["auto", "on_demand", "flex", "performance"]] | NotGiven = NOT_GIVEN,
stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
store: Optional[bool] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
top_p: Optional[float] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
"""
Creates a model response for the given chat conversation.
Args:
messages: A list of messages comprising the conversation so far.
model: ID of the model to use. For details on which models are compatible with the Chat
API, see available [models](https://console.groq.com/docs/models)
exclude_domains: Deprecated: Use search_settings.exclude_domains instead. A list of domains to
exclude from the search results when the model uses a web search tool.
frequency_penalty: 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.
function_call: 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: Deprecated in favor of `tools`.
A list of functions the model may generate JSON inputs for.
include_domains: Deprecated: Use search_settings.include_domains instead. A list of domains to
include in the search results when the model uses a web search tool.
logit_bias: This is not yet supported by any of our models. Modify the likelihood of
specified tokens appearing in the completion.
logprobs: This is not yet supported by any of our models. 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`.
max_completion_tokens: The maximum number of tokens 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.
max_tokens: Deprecated in favor of `max_completion_tokens`. The maximum number of tokens
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.
metadata: This parameter is not currently supported.
n: How many chat completion choices to generate for each input message. Note that
the current moment, only n=1 is supported. Other values will result in a 400
response.
parallel_tool_calls: Whether to enable parallel function calling during tool use.
presence_penalty: 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.
reasoning_effort: this field is only available for qwen3 models. Set to 'none' to disable
reasoning. Set to 'default' or null to let Qwen reason.
reasoning_format: Specifies how to output reasoning tokens
response_format: 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. json_schema
response format is only supported on llama 4 models. 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.
search_settings: Settings for web search functionality when the model uses a web search tool.
seed: 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.
service_tier: The service tier to use for the request. Defaults to `on_demand`.
- `auto` will automatically select the highest tier available within the rate
limits of your organization.
- `flex` uses the flex tier, which will succeed or fail quickly.
stop: Up to 4 sequences where the API will stop generating further tokens. The
returned text will not contain the stop sequence.
store: This parameter is not currently supported.
stream: If set, partial message deltas will be sent. 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 code](/docs/text-chat#streaming-a-chat-completion).
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. We generally recommend altering this or top_p but not
both.
tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
not call any tool and instead generates a message. `auto` means the model can
pick between generating a message or calling one or more tools. `required` means
the model must call one or more tools. Specifying a particular tool via
`{"type": "function", "function": {"name": "my_function"}}` forces the model to
call that tool.
`none` is the default when no tools are present. `auto` is the default if tools
are present.
tools: 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: This is not yet supported by any of our models. 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: 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: A unique identifier representing your end-user, which can help us monitor and
detect abuse.
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
"""
return await self._post(
"/openai/v1/chat/completions",
body=await async_maybe_transform(
{
"messages": messages,
"model": model,
"exclude_domains": exclude_domains,
"frequency_penalty": frequency_penalty,
"function_call": function_call,
"functions": functions,
"include_domains": include_domains,
"logit_bias": logit_bias,
"logprobs": logprobs,
"max_completion_tokens": max_completion_tokens,
"max_tokens": max_tokens,
"metadata": metadata,
"n": n,
"parallel_tool_calls": parallel_tool_calls,
"presence_penalty": presence_penalty,
"reasoning_effort": reasoning_effort,
"reasoning_format": reasoning_format,
"response_format": response_format,
"search_settings": search_settings,
"seed": seed,
"service_tier": service_tier,
"stop": stop,
"store": store,
"stream": stream,
"temperature": temperature,
"tool_choice": tool_choice,
"tools": tools,
"top_logprobs": top_logprobs,
"top_p": top_p,
"user": user,
},
completion_create_params.CompletionCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=ChatCompletion,
stream=stream or False,
stream_cls=AsyncStream[ChatCompletionChunk],
)
class CompletionsWithRawResponse:
def __init__(self, completions: Completions) -> None:
self._completions = completions
self.create = to_raw_response_wrapper(
completions.create,
)
class AsyncCompletionsWithRawResponse:
def __init__(self, completions: AsyncCompletions) -> None:
self._completions = completions
self.create = async_to_raw_response_wrapper(
completions.create,
)
class CompletionsWithStreamingResponse:
def __init__(self, completions: Completions) -> None:
self._completions = completions
self.create = to_streamed_response_wrapper(
completions.create,
)
class AsyncCompletionsWithStreamingResponse:
def __init__(self, completions: AsyncCompletions) -> None:
self._completions = completions
self.create = async_to_streamed_response_wrapper(
completions.create,
)
@@ -0,0 +1,212 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import List, Union, Optional
from typing_extensions import Literal
import httpx
from ..types import embedding_create_params
from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from .._utils import maybe_transform, async_maybe_transform
from .._compat import cached_property
from .._resource import SyncAPIResource, AsyncAPIResource
from .._response import (
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
async_to_streamed_response_wrapper,
)
from .._base_client import make_request_options
from ..types.create_embedding_response import CreateEmbeddingResponse
__all__ = ["Embeddings", "AsyncEmbeddings"]
class Embeddings(SyncAPIResource):
@cached_property
def with_raw_response(self) -> EmbeddingsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return EmbeddingsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> EmbeddingsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return EmbeddingsWithStreamingResponse(self)
def create(
self,
*,
input: Union[str, List[str]],
model: Union[str, Literal["nomic-embed-text-v1_5"]],
encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> CreateEmbeddingResponse:
"""
Creates an embedding vector representing the input text.
Args:
input: Input text to embed, encoded as a string or array of tokens. To embed multiple
inputs in a single request, pass an array of strings or array of token arrays.
The input must not exceed the max input tokens for the model, cannot be an empty
string, and any array must be 2048 dimensions or less.
model: ID of the model to use.
encoding_format: The format to return the embeddings in. Can only be `float` or `base64`.
user: A unique identifier representing your end-user, which can help us monitor and
detect abuse.
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
"""
return self._post(
"/openai/v1/embeddings",
body=maybe_transform(
{
"input": input,
"model": model,
"encoding_format": encoding_format,
"user": user,
},
embedding_create_params.EmbeddingCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=CreateEmbeddingResponse,
)
class AsyncEmbeddings(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncEmbeddingsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncEmbeddingsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncEmbeddingsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncEmbeddingsWithStreamingResponse(self)
async def create(
self,
*,
input: Union[str, List[str]],
model: Union[str, Literal["nomic-embed-text-v1_5"]],
encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN,
user: Optional[str] | 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,
) -> CreateEmbeddingResponse:
"""
Creates an embedding vector representing the input text.
Args:
input: Input text to embed, encoded as a string or array of tokens. To embed multiple
inputs in a single request, pass an array of strings or array of token arrays.
The input must not exceed the max input tokens for the model, cannot be an empty
string, and any array must be 2048 dimensions or less.
model: ID of the model to use.
encoding_format: The format to return the embeddings in. Can only be `float` or `base64`.
user: A unique identifier representing your end-user, which can help us monitor and
detect abuse.
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
"""
return await self._post(
"/openai/v1/embeddings",
body=await async_maybe_transform(
{
"input": input,
"model": model,
"encoding_format": encoding_format,
"user": user,
},
embedding_create_params.EmbeddingCreateParams,
),
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=CreateEmbeddingResponse,
)
class EmbeddingsWithRawResponse:
def __init__(self, embeddings: Embeddings) -> None:
self._embeddings = embeddings
self.create = to_raw_response_wrapper(
embeddings.create,
)
class AsyncEmbeddingsWithRawResponse:
def __init__(self, embeddings: AsyncEmbeddings) -> None:
self._embeddings = embeddings
self.create = async_to_raw_response_wrapper(
embeddings.create,
)
class EmbeddingsWithStreamingResponse:
def __init__(self, embeddings: Embeddings) -> None:
self._embeddings = embeddings
self.create = to_streamed_response_wrapper(
embeddings.create,
)
class AsyncEmbeddingsWithStreamingResponse:
def __init__(self, embeddings: AsyncEmbeddings) -> None:
self._embeddings = embeddings
self.create = async_to_streamed_response_wrapper(
embeddings.create,
)
@@ -0,0 +1,513 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from typing import Mapping, cast
from typing_extensions import Literal
import httpx
from ..types import file_create_params
from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven, FileTypes
from .._utils import extract_files, maybe_transform, deepcopy_minimal, async_maybe_transform
from .._compat import cached_property
from .._resource import SyncAPIResource, AsyncAPIResource
from .._response import (
BinaryAPIResponse,
AsyncBinaryAPIResponse,
StreamedBinaryAPIResponse,
AsyncStreamedBinaryAPIResponse,
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
to_custom_raw_response_wrapper,
async_to_streamed_response_wrapper,
to_custom_streamed_response_wrapper,
async_to_custom_raw_response_wrapper,
async_to_custom_streamed_response_wrapper,
)
from .._base_client import make_request_options
from ..types.file_info_response import FileInfoResponse
from ..types.file_list_response import FileListResponse
from ..types.file_create_response import FileCreateResponse
from ..types.file_delete_response import FileDeleteResponse
__all__ = ["Files", "AsyncFiles"]
class Files(SyncAPIResource):
@cached_property
def with_raw_response(self) -> FilesWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return FilesWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> FilesWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return FilesWithStreamingResponse(self)
def create(
self,
*,
file: FileTypes,
purpose: Literal["batch"],
# 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,
) -> FileCreateResponse:
"""
Upload a file that can be used across various endpoints.
The Batch API only supports `.jsonl` files up to 100 MB in size. The input also
has a specific required [format](/docs/batch).
Please contact us if you need to increase these storage limits.
Args:
file: The File object (not file name) to be uploaded.
purpose: The intended purpose of the uploaded file. Use "batch" for
[Batch API](/docs/api-reference#batches).
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
"""
body = deepcopy_minimal(
{
"file": file,
"purpose": purpose,
}
)
files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
# It should be noted that the actual Content-Type header that will be
# sent to the server will contain a `boundary` parameter, e.g.
# multipart/form-data; boundary=---abc--
extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
return self._post(
"/openai/v1/files",
body=maybe_transform(body, file_create_params.FileCreateParams),
files=files,
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileCreateResponse,
)
def list(
self,
*,
# 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,
) -> FileListResponse:
"""Returns a list of files."""
return self._get(
"/openai/v1/files",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileListResponse,
)
def delete(
self,
file_id: str,
*,
# 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,
) -> FileDeleteResponse:
"""
Delete a file.
Args:
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 file_id:
raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}")
return self._delete(
f"/openai/v1/files/{file_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileDeleteResponse,
)
def content(
self,
file_id: str,
*,
# 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,
) -> BinaryAPIResponse:
"""
Returns the contents of the specified file.
Args:
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 file_id:
raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}")
extra_headers = {"Accept": "application/octet-stream", **(extra_headers or {})}
return self._get(
f"/openai/v1/files/{file_id}/content",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=BinaryAPIResponse,
)
def info(
self,
file_id: str,
*,
# 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,
) -> FileInfoResponse:
"""
Returns information about a file.
Args:
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 file_id:
raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}")
return self._get(
f"/openai/v1/files/{file_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileInfoResponse,
)
class AsyncFiles(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncFilesWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncFilesWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncFilesWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncFilesWithStreamingResponse(self)
async def create(
self,
*,
file: FileTypes,
purpose: Literal["batch"],
# 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,
) -> FileCreateResponse:
"""
Upload a file that can be used across various endpoints.
The Batch API only supports `.jsonl` files up to 100 MB in size. The input also
has a specific required [format](/docs/batch).
Please contact us if you need to increase these storage limits.
Args:
file: The File object (not file name) to be uploaded.
purpose: The intended purpose of the uploaded file. Use "batch" for
[Batch API](/docs/api-reference#batches).
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
"""
body = deepcopy_minimal(
{
"file": file,
"purpose": purpose,
}
)
files = extract_files(cast(Mapping[str, object], body), paths=[["file"]])
# It should be noted that the actual Content-Type header that will be
# sent to the server will contain a `boundary` parameter, e.g.
# multipart/form-data; boundary=---abc--
extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})}
return await self._post(
"/openai/v1/files",
body=await async_maybe_transform(body, file_create_params.FileCreateParams),
files=files,
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileCreateResponse,
)
async def list(
self,
*,
# 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,
) -> FileListResponse:
"""Returns a list of files."""
return await self._get(
"/openai/v1/files",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileListResponse,
)
async def delete(
self,
file_id: str,
*,
# 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,
) -> FileDeleteResponse:
"""
Delete a file.
Args:
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 file_id:
raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}")
return await self._delete(
f"/openai/v1/files/{file_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileDeleteResponse,
)
async def content(
self,
file_id: str,
*,
# 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,
) -> AsyncBinaryAPIResponse:
"""
Returns the contents of the specified file.
Args:
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 file_id:
raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}")
extra_headers = {"Accept": "application/octet-stream", **(extra_headers or {})}
return await self._get(
f"/openai/v1/files/{file_id}/content",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=AsyncBinaryAPIResponse,
)
async def info(
self,
file_id: str,
*,
# 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,
) -> FileInfoResponse:
"""
Returns information about a file.
Args:
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 file_id:
raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}")
return await self._get(
f"/openai/v1/files/{file_id}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=FileInfoResponse,
)
class FilesWithRawResponse:
def __init__(self, files: Files) -> None:
self._files = files
self.create = to_raw_response_wrapper(
files.create,
)
self.list = to_raw_response_wrapper(
files.list,
)
self.delete = to_raw_response_wrapper(
files.delete,
)
self.content = to_custom_raw_response_wrapper(
files.content,
BinaryAPIResponse,
)
self.info = to_raw_response_wrapper(
files.info,
)
class AsyncFilesWithRawResponse:
def __init__(self, files: AsyncFiles) -> None:
self._files = files
self.create = async_to_raw_response_wrapper(
files.create,
)
self.list = async_to_raw_response_wrapper(
files.list,
)
self.delete = async_to_raw_response_wrapper(
files.delete,
)
self.content = async_to_custom_raw_response_wrapper(
files.content,
AsyncBinaryAPIResponse,
)
self.info = async_to_raw_response_wrapper(
files.info,
)
class FilesWithStreamingResponse:
def __init__(self, files: Files) -> None:
self._files = files
self.create = to_streamed_response_wrapper(
files.create,
)
self.list = to_streamed_response_wrapper(
files.list,
)
self.delete = to_streamed_response_wrapper(
files.delete,
)
self.content = to_custom_streamed_response_wrapper(
files.content,
StreamedBinaryAPIResponse,
)
self.info = to_streamed_response_wrapper(
files.info,
)
class AsyncFilesWithStreamingResponse:
def __init__(self, files: AsyncFiles) -> None:
self._files = files
self.create = async_to_streamed_response_wrapper(
files.create,
)
self.list = async_to_streamed_response_wrapper(
files.list,
)
self.delete = async_to_streamed_response_wrapper(
files.delete,
)
self.content = async_to_custom_streamed_response_wrapper(
files.content,
AsyncStreamedBinaryAPIResponse,
)
self.info = async_to_streamed_response_wrapper(
files.info,
)
@@ -0,0 +1,293 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
import httpx
from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from .._compat import cached_property
from .._resource import SyncAPIResource, AsyncAPIResource
from .._response import (
to_raw_response_wrapper,
to_streamed_response_wrapper,
async_to_raw_response_wrapper,
async_to_streamed_response_wrapper,
)
from ..types.model import Model
from .._base_client import make_request_options
from ..types.model_deleted import ModelDeleted
from ..types.model_list_response import ModelListResponse
__all__ = ["Models", "AsyncModels"]
class Models(SyncAPIResource):
@cached_property
def with_raw_response(self) -> ModelsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return ModelsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> ModelsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return ModelsWithStreamingResponse(self)
def retrieve(
self,
model: str,
*,
# 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,
) -> Model:
"""
Get a specific model
Args:
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 model:
raise ValueError(f"Expected a non-empty value for `model` but received {model!r}")
return self._get(
f"/openai/v1/models/{model}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Model,
)
def list(
self,
*,
# 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,
) -> ModelListResponse:
"""get all available models"""
return self._get(
"/openai/v1/models",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=ModelListResponse,
)
def delete(
self,
model: str,
*,
# 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,
) -> ModelDeleted:
"""
Delete a model
Args:
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 model:
raise ValueError(f"Expected a non-empty value for `model` but received {model!r}")
return self._delete(
f"/openai/v1/models/{model}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=ModelDeleted,
)
class AsyncModels(AsyncAPIResource):
@cached_property
def with_raw_response(self) -> AsyncModelsWithRawResponse:
"""
This property can be used as a prefix for any HTTP method call to return
the raw response object instead of the parsed content.
For more information, see https://www.github.com/groq/groq-python#accessing-raw-response-data-eg-headers
"""
return AsyncModelsWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncModelsWithStreamingResponse:
"""
An alternative to `.with_raw_response` that doesn't eagerly read the response body.
For more information, see https://www.github.com/groq/groq-python#with_streaming_response
"""
return AsyncModelsWithStreamingResponse(self)
async def retrieve(
self,
model: str,
*,
# 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,
) -> Model:
"""
Get a specific model
Args:
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 model:
raise ValueError(f"Expected a non-empty value for `model` but received {model!r}")
return await self._get(
f"/openai/v1/models/{model}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=Model,
)
async def list(
self,
*,
# 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,
) -> ModelListResponse:
"""get all available models"""
return await self._get(
"/openai/v1/models",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=ModelListResponse,
)
async def delete(
self,
model: str,
*,
# 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,
) -> ModelDeleted:
"""
Delete a model
Args:
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 model:
raise ValueError(f"Expected a non-empty value for `model` but received {model!r}")
return await self._delete(
f"/openai/v1/models/{model}",
options=make_request_options(
extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
),
cast_to=ModelDeleted,
)
class ModelsWithRawResponse:
def __init__(self, models: Models) -> None:
self._models = models
self.retrieve = to_raw_response_wrapper(
models.retrieve,
)
self.list = to_raw_response_wrapper(
models.list,
)
self.delete = to_raw_response_wrapper(
models.delete,
)
class AsyncModelsWithRawResponse:
def __init__(self, models: AsyncModels) -> None:
self._models = models
self.retrieve = async_to_raw_response_wrapper(
models.retrieve,
)
self.list = async_to_raw_response_wrapper(
models.list,
)
self.delete = async_to_raw_response_wrapper(
models.delete,
)
class ModelsWithStreamingResponse:
def __init__(self, models: Models) -> None:
self._models = models
self.retrieve = to_streamed_response_wrapper(
models.retrieve,
)
self.list = to_streamed_response_wrapper(
models.list,
)
self.delete = to_streamed_response_wrapper(
models.delete,
)
class AsyncModelsWithStreamingResponse:
def __init__(self, models: AsyncModels) -> None:
self._models = models
self.retrieve = async_to_streamed_response_wrapper(
models.retrieve,
)
self.list = async_to_streamed_response_wrapper(
models.list,
)
self.delete = async_to_streamed_response_wrapper(
models.delete,
)
@@ -0,0 +1,26 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from .model import Model as Model
from .shared import (
ErrorObject as ErrorObject,
FunctionDefinition as FunctionDefinition,
FunctionParameters as FunctionParameters,
)
from .embedding import Embedding as Embedding
from .model_deleted import ModelDeleted as ModelDeleted
from .completion_usage import CompletionUsage as CompletionUsage
from .file_create_params import FileCreateParams as FileCreateParams
from .file_info_response import FileInfoResponse as FileInfoResponse
from .file_list_response import FileListResponse as FileListResponse
from .batch_create_params import BatchCreateParams as BatchCreateParams
from .batch_list_response import BatchListResponse as BatchListResponse
from .model_list_response import ModelListResponse as ModelListResponse
from .file_create_response import FileCreateResponse as FileCreateResponse
from .file_delete_response import FileDeleteResponse as FileDeleteResponse
from .batch_cancel_response import BatchCancelResponse as BatchCancelResponse
from .batch_create_response import BatchCreateResponse as BatchCreateResponse
from .batch_retrieve_response import BatchRetrieveResponse as BatchRetrieveResponse
from .embedding_create_params import EmbeddingCreateParams as EmbeddingCreateParams
from .create_embedding_response import CreateEmbeddingResponse as CreateEmbeddingResponse
@@ -0,0 +1,9 @@
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from __future__ import annotations
from .translation import Translation as Translation
from .transcription import Transcription as Transcription
from .speech_create_params import SpeechCreateParams as SpeechCreateParams
from .translation_create_params import TranslationCreateParams as TranslationCreateParams
from .transcription_create_params import TranscriptionCreateParams as TranscriptionCreateParams

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