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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,
Literal,
Mapping,
TypeVar,
Callable,
Iterator,
Optional,
AsyncIterator,
overload,
)
from typing_extensions import Self, Unpack, ParamSpec, override, deprecated
import httpx
from replicate.lib.cog import _get_api_token_from_environment
from replicate.lib._files import FileEncodingStrategy
from replicate.lib._predictions_run import Model, Version, ModelVersionIdentifier
from replicate.types.prediction_create_params import PredictionCreateParamsWithoutVersion
from . import _exceptions
from ._qs import Querystring
from .types import client_search_params
from ._types import (
Body,
Omit,
Query,
Headers,
Timeout,
NotGiven,
Transport,
ProxiesTypes,
RequestOptions,
omit,
not_given,
)
from ._utils import (
is_given,
maybe_transform,
get_async_library,
async_maybe_transform,
)
from ._compat import cached_property
from ._version import __version__
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 as Stream, AsyncStream as AsyncStream
from ._exceptions import APIStatusError, ReplicateError
from ._base_client import (
DEFAULT_MAX_RETRIES,
SyncAPIClient,
AsyncAPIClient,
make_request_options,
)
from .types.search_response import SearchResponse
if TYPE_CHECKING:
from .resources import files, models, account, hardware, webhooks, trainings, collections, deployments, predictions
from .resources.files import FilesResource, AsyncFilesResource
from .resources.account import AccountResource, AsyncAccountResource
from .resources.hardware import HardwareResource, AsyncHardwareResource
from .resources.trainings import TrainingsResource, AsyncTrainingsResource
from .resources.collections import CollectionsResource, AsyncCollectionsResource
from .resources.predictions import PredictionsResource, AsyncPredictionsResource
from .resources.models.models import ModelsResource, AsyncModelsResource
from .resources.webhooks.webhooks import WebhooksResource, AsyncWebhooksResource
from .resources.deployments.deployments import DeploymentsResource, AsyncDeploymentsResource
if TYPE_CHECKING:
from .lib._predictions_use import Function, FunctionRef, AsyncFunction
Input = ParamSpec("Input")
Output = TypeVar("Output")
__all__ = [
"Timeout",
"Transport",
"ProxiesTypes",
"RequestOptions",
"Replicate",
"AsyncReplicate",
"Client",
"AsyncClient",
]
class Replicate(SyncAPIClient):
# client options
bearer_token: str
def __init__(
self,
*,
bearer_token: str | None = None,
base_url: str | httpx.URL | None = None,
timeout: 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 Replicate client instance.
This automatically infers the `bearer_token` argument from the `REPLICATE_API_TOKEN` environment variable if it is not provided.
"""
if bearer_token is None:
bearer_token = _get_api_token_from_environment()
if bearer_token is None:
raise ReplicateError(
"The bearer_token client option must be set either by passing bearer_token to the client or by setting the REPLICATE_API_TOKEN environment variable"
)
self.bearer_token = bearer_token
if base_url is None:
base_url = os.environ.get("REPLICATE_BASE_URL")
if base_url is None:
base_url = f"https://api.replicate.com/v1"
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 collections(self) -> CollectionsResource:
from .resources.collections import CollectionsResource
return CollectionsResource(self)
@cached_property
def deployments(self) -> DeploymentsResource:
from .resources.deployments import DeploymentsResource
return DeploymentsResource(self)
@cached_property
def hardware(self) -> HardwareResource:
from .resources.hardware import HardwareResource
return HardwareResource(self)
@cached_property
def account(self) -> AccountResource:
from .resources.account import AccountResource
return AccountResource(self)
@cached_property
def models(self) -> ModelsResource:
from .resources.models import ModelsResource
return ModelsResource(self)
@cached_property
def predictions(self) -> PredictionsResource:
from .resources.predictions import PredictionsResource
return PredictionsResource(self)
@cached_property
def trainings(self) -> TrainingsResource:
from .resources.trainings import TrainingsResource
return TrainingsResource(self)
@cached_property
def webhooks(self) -> WebhooksResource:
from .resources.webhooks import WebhooksResource
return WebhooksResource(self)
@cached_property
def files(self) -> FilesResource:
from .resources.files import FilesResource
return FilesResource(self)
@cached_property
def with_raw_response(self) -> ReplicateWithRawResponse:
return ReplicateWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> ReplicateWithStreamedResponse:
return ReplicateWithStreamedResponse(self)
@cached_property
def poll_interval(self) -> float:
return float(os.environ.get("REPLICATE_POLL_INTERVAL", "0.5"))
@property
@override
def qs(self) -> Querystring:
return Querystring(array_format="comma")
@property
@override
def auth_headers(self) -> dict[str, str]:
bearer_token = self.bearer_token
return {"Authorization": f"Bearer {bearer_token}"}
@property
@override
def default_headers(self) -> dict[str, str | Omit]:
return {
**super().default_headers,
"X-Stainless-Async": "false",
**self._custom_headers,
}
def run(
self,
ref: Union[Model, Version, ModelVersionIdentifier, str],
*,
file_encoding_strategy: Optional["FileEncodingStrategy"] = None,
use_file_output: bool = True,
wait: Union[int, bool, NotGiven] = not_given,
**params: Unpack[PredictionCreateParamsWithoutVersion],
) -> Any:
"""
Run a model prediction.
Args:
ref: Reference to the model or version to run. Can be:
- A string containing a version ID (e.g. "5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa")
- A string with owner/name format (e.g. "replicate/hello-world")
- A string with owner/name:version format (e.g. "replicate/hello-world:5c7d5dc6...")
- A Model instance with owner and name attributes
- A Version instance with id attribute
- A ModelVersionIdentifier dictionary with owner, name, and/or version keys
file_encoding_strategy: Strategy for encoding file inputs, options are "base64" or "url"
use_file_output: If True (default), convert output URLs to FileOutput objects
wait: If True (default), wait for the prediction to complete. If False, return immediately.
If an integer, wait up to that many seconds.
**params: Additional parameters to pass to the prediction creation endpoint including
the required "input" dictionary with model-specific parameters
Returns:
The prediction output, which could be a basic type (str, int, etc.), a FileOutput object,
a list of FileOutput objects, or a dictionary of FileOutput objects, depending on what
the model returns.
Raises:
ModelError: If the model run fails
ValueError: If the reference format is invalid
TypeError: If both wait and prefer parameters are provided
"""
from .lib._predictions_run import run
return run(
self,
ref,
wait=wait,
use_file_output=use_file_output,
file_encoding_strategy=file_encoding_strategy,
**params,
)
@overload
def use(
self,
ref: Union[str, "FunctionRef[Input, Output]"],
*,
hint: Optional[Callable["Input", "Output"]] = None,
streaming: Literal[False] = False,
) -> "Function[Input, Output]": ...
@overload
def use(
self,
ref: Union[str, "FunctionRef[Input, Output]"],
*,
hint: Optional[Callable["Input", "Output"]] = None,
streaming: Literal[True],
) -> "Function[Input, Iterator[Output]]": ...
def use(
self,
ref: Union[str, "FunctionRef[Input, Output]"],
*,
hint: Optional[Callable["Input", "Output"]] = None,
streaming: bool = False,
) -> Union["Function[Input, Output]", "Function[Input, Iterator[Output]]"]:
"""
Use a Replicate model as a function.
Example:
flux_dev = replicate.use("black-forest-labs/flux-dev")
output = flux_dev(prompt="make me a sandwich")
"""
from .lib._predictions_use import use as _use
# TODO: Fix mypy overload matching for streaming parameter
return _use(self, ref, hint=hint, streaming=streaming) # type: ignore[call-overload, no-any-return]
@deprecated("replicate.stream() is deprecated. Use replicate.use() with streaming=True instead")
def stream(
self,
ref: str,
*,
input: dict[str, Any],
) -> Iterator[str]:
"""
Run a model and stream its output (deprecated).
.. deprecated::
Use :meth:`use` with ``streaming=True`` instead:
.. code-block:: python
model = replicate.use("anthropic/claude-4.5-sonnet", streaming=True)
for event in model(input={"prompt": "Hello"}):
print(str(event), end="")
Args:
ref: Reference to the model to run. Can be a string with owner/name format
(e.g., "anthropic/claude-4.5-sonnet") or owner/name:version format.
input: Dictionary of input parameters for the model. The required keys depend
on the specific model being run.
Returns:
An iterator that yields output strings as they are generated by the model
"""
from .lib._stream import stream as _stream # pyright: ignore[reportDeprecated]
return _stream(type(self), ref, input=input) # type: ignore[return-value, arg-type]
def copy(
self,
*,
bearer_token: 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__(
bearer_token=bearer_token or self.bearer_token,
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
def search(
self,
*,
query: str,
limit: int | Omit = omit,
# 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,
) -> SearchResponse:
"""
Search for public models, collections, and docs using a text query.
For models, the response includes all model data, plus a new `metadata` object
with the following fields:
- `generated_description`: A longer and more detailed AI-generated description
of the model
- `tags`: An array of tags for the model
- `score`: A score for the model's relevance to the search query
Example cURL request:
```console
curl -s \\
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \\
"https://api.replicate.com/v1/search?query=nano+banana"
```
Note: This search API is currently in beta and may change in future versions.
Args:
query: The search query string
limit: Maximum number of model results to return (1-50, defaults to 20)
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.get(
"/search",
options=make_request_options(
extra_headers=extra_headers,
extra_query=extra_query,
extra_body=extra_body,
timeout=timeout,
query=maybe_transform(
{
"query": query,
"limit": limit,
},
client_search_params.ClientSearchParams,
),
),
cast_to=SearchResponse,
)
@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 AsyncReplicate(AsyncAPIClient):
# client options
bearer_token: str
def __init__(
self,
*,
bearer_token: str | None = None,
base_url: str | httpx.URL | None = None,
timeout: 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 AsyncReplicate client instance.
This automatically infers the `bearer_token` argument from the `REPLICATE_API_TOKEN` environment variable if it is not provided.
"""
if bearer_token is None:
bearer_token = _get_api_token_from_environment()
if bearer_token is None:
raise ReplicateError(
"The bearer_token client option must be set either by passing bearer_token to the client or by setting the REPLICATE_API_TOKEN environment variable"
)
self.bearer_token = bearer_token
if base_url is None:
base_url = os.environ.get("REPLICATE_BASE_URL")
if base_url is None:
base_url = f"https://api.replicate.com/v1"
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 collections(self) -> AsyncCollectionsResource:
from .resources.collections import AsyncCollectionsResource
return AsyncCollectionsResource(self)
@cached_property
def deployments(self) -> AsyncDeploymentsResource:
from .resources.deployments import AsyncDeploymentsResource
return AsyncDeploymentsResource(self)
@cached_property
def hardware(self) -> AsyncHardwareResource:
from .resources.hardware import AsyncHardwareResource
return AsyncHardwareResource(self)
@cached_property
def account(self) -> AsyncAccountResource:
from .resources.account import AsyncAccountResource
return AsyncAccountResource(self)
@cached_property
def models(self) -> AsyncModelsResource:
from .resources.models import AsyncModelsResource
return AsyncModelsResource(self)
@cached_property
def predictions(self) -> AsyncPredictionsResource:
from .resources.predictions import AsyncPredictionsResource
return AsyncPredictionsResource(self)
@cached_property
def trainings(self) -> AsyncTrainingsResource:
from .resources.trainings import AsyncTrainingsResource
return AsyncTrainingsResource(self)
@cached_property
def webhooks(self) -> AsyncWebhooksResource:
from .resources.webhooks import AsyncWebhooksResource
return AsyncWebhooksResource(self)
@cached_property
def files(self) -> AsyncFilesResource:
from .resources.files import AsyncFilesResource
return AsyncFilesResource(self)
@cached_property
def with_raw_response(self) -> AsyncReplicateWithRawResponse:
return AsyncReplicateWithRawResponse(self)
@cached_property
def with_streaming_response(self) -> AsyncReplicateWithStreamedResponse:
return AsyncReplicateWithStreamedResponse(self)
@cached_property
def poll_interval(self) -> float:
return float(os.environ.get("REPLICATE_POLL_INTERVAL", "0.5"))
@property
@override
def qs(self) -> Querystring:
return Querystring(array_format="comma")
@property
@override
def auth_headers(self) -> dict[str, str]:
bearer_token = self.bearer_token
return {"Authorization": f"Bearer {bearer_token}"}
@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,
}
async def run(
self,
ref: Union[Model, Version, ModelVersionIdentifier, str],
*,
use_file_output: bool = True,
file_encoding_strategy: Optional["FileEncodingStrategy"] = None,
wait: Union[int, bool, NotGiven] = not_given,
**params: Unpack[PredictionCreateParamsWithoutVersion],
) -> Any:
"""
Run a model prediction asynchronously.
Args:
ref: Reference to the model or version to run. Can be:
- A string containing a version ID (e.g. "5c7d5dc6dd8bf75c1acaa8565735e7986bc5b66206b55cca93cb72c9bf15ccaa")
- A string with owner/name format (e.g. "replicate/hello-world")
- A string with owner/name:version format (e.g. "replicate/hello-world:5c7d5dc6...")
- A Model instance with owner and name attributes
- A Version instance with id attribute
- A ModelVersionIdentifier dictionary with owner, name, and/or version keys
use_file_output: If True (default), convert output URLs to AsyncFileOutput objects
file_encoding_strategy: Strategy for encoding file inputs, options are "base64" or "url"
wait: If True (default), wait for the prediction to complete. If False, return immediately.
If an integer, wait up to that many seconds.
**params: Additional parameters to pass to the prediction creation endpoint including
the required "input" dictionary with model-specific parameters
Returns:
The prediction output, which could be a basic type (str, int, etc.), an AsyncFileOutput object,
a list of AsyncFileOutput objects, or a dictionary of AsyncFileOutput objects, depending on what
the model returns.
Raises:
ModelError: If the model run fails
ValueError: If the reference format is invalid
TypeError: If both wait and prefer parameters are provided
"""
from .lib._predictions_run import async_run
return await async_run(
self,
ref,
wait=wait,
use_file_output=use_file_output,
file_encoding_strategy=file_encoding_strategy,
**params,
)
@overload
def use(
self,
ref: Union[str, "FunctionRef[Input, Output]"],
*,
hint: Optional[Callable["Input", "Output"]] = None,
streaming: Literal[False] = False,
) -> "AsyncFunction[Input, Output]": ...
@overload
def use(
self,
ref: Union[str, "FunctionRef[Input, Output]"],
*,
hint: Optional[Callable["Input", "Output"]] = None,
streaming: Literal[True],
) -> "AsyncFunction[Input, AsyncIterator[Output]]": ...
def use(
self,
ref: Union[str, "FunctionRef[Input, Output]"],
*,
hint: Optional[Callable["Input", "Output"]] = None,
streaming: bool = False,
) -> Union["AsyncFunction[Input, Output]", "AsyncFunction[Input, AsyncIterator[Output]]"]:
"""
Use a Replicate model as an async function.
Example:
flux_dev = replicate.use("black-forest-labs/flux-dev", use_async=True)
output = await flux_dev(prompt="make me a sandwich")
"""
from .lib._predictions_use import use as _use
# TODO: Fix mypy overload matching for streaming parameter
return _use(self, ref, hint=hint, streaming=streaming) # type: ignore[call-overload, no-any-return]
@deprecated("replicate.stream() is deprecated. Use replicate.use() with streaming=True instead")
async def stream(
self,
ref: str,
*,
input: dict[str, Any],
) -> AsyncIterator[str]:
"""
Run a model and stream its output asynchronously (deprecated).
.. deprecated::
Use :meth:`use` with ``streaming=True`` instead:
.. code-block:: python
model = replicate.use("anthropic/claude-4.5-sonnet", streaming=True)
async for event in model(input={"prompt": "Hello"}):
print(str(event), end="")
Args:
ref: Reference to the model to run. Can be a string with owner/name format
(e.g., "anthropic/claude-4.5-sonnet") or owner/name:version format.
input: Dictionary of input parameters for the model. The required keys depend
on the specific model being run.
Returns:
An async iterator that yields output strings as they are generated by the model
"""
from .lib._stream import stream as _stream # pyright: ignore[reportDeprecated]
return _stream(type(self), ref, input=input) # type: ignore[return-value, arg-type]
def copy(
self,
*,
bearer_token: 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__(
bearer_token=bearer_token or self.bearer_token,
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
async def search(
self,
*,
query: str,
limit: int | Omit = omit,
# 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,
) -> SearchResponse:
"""
Search for public models, collections, and docs using a text query.
For models, the response includes all model data, plus a new `metadata` object
with the following fields:
- `generated_description`: A longer and more detailed AI-generated description
of the model
- `tags`: An array of tags for the model
- `score`: A score for the model's relevance to the search query
Example cURL request:
```console
curl -s \\
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \\
"https://api.replicate.com/v1/search?query=nano+banana"
```
Note: This search API is currently in beta and may change in future versions.
Args:
query: The search query string
limit: Maximum number of model results to return (1-50, defaults to 20)
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.get(
"/search",
options=make_request_options(
extra_headers=extra_headers,
extra_query=extra_query,
extra_body=extra_body,
timeout=timeout,
query=await async_maybe_transform(
{
"query": query,
"limit": limit,
},
client_search_params.ClientSearchParams,
),
),
cast_to=SearchResponse,
)
@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 ReplicateWithRawResponse:
_client: Replicate
def __init__(self, client: Replicate) -> None:
self._client = client
self.search = to_raw_response_wrapper(
client.search,
)
@cached_property
def collections(self) -> collections.CollectionsResourceWithRawResponse:
from .resources.collections import CollectionsResourceWithRawResponse
return CollectionsResourceWithRawResponse(self._client.collections)
@cached_property
def deployments(self) -> deployments.DeploymentsResourceWithRawResponse:
from .resources.deployments import DeploymentsResourceWithRawResponse
return DeploymentsResourceWithRawResponse(self._client.deployments)
@cached_property
def hardware(self) -> hardware.HardwareResourceWithRawResponse:
from .resources.hardware import HardwareResourceWithRawResponse
return HardwareResourceWithRawResponse(self._client.hardware)
@cached_property
def account(self) -> account.AccountResourceWithRawResponse:
from .resources.account import AccountResourceWithRawResponse
return AccountResourceWithRawResponse(self._client.account)
@cached_property
def models(self) -> models.ModelsResourceWithRawResponse:
from .resources.models import ModelsResourceWithRawResponse
return ModelsResourceWithRawResponse(self._client.models)
@cached_property
def predictions(self) -> predictions.PredictionsResourceWithRawResponse:
from .resources.predictions import PredictionsResourceWithRawResponse
return PredictionsResourceWithRawResponse(self._client.predictions)
@cached_property
def trainings(self) -> trainings.TrainingsResourceWithRawResponse:
from .resources.trainings import TrainingsResourceWithRawResponse
return TrainingsResourceWithRawResponse(self._client.trainings)
@cached_property
def webhooks(self) -> webhooks.WebhooksResourceWithRawResponse:
from .resources.webhooks import WebhooksResourceWithRawResponse
return WebhooksResourceWithRawResponse(self._client.webhooks)
@cached_property
def files(self) -> files.FilesResourceWithRawResponse:
from .resources.files import FilesResourceWithRawResponse
return FilesResourceWithRawResponse(self._client.files)
class AsyncReplicateWithRawResponse:
_client: AsyncReplicate
def __init__(self, client: AsyncReplicate) -> None:
self._client = client
self.search = async_to_raw_response_wrapper(
client.search,
)
@cached_property
def collections(self) -> collections.AsyncCollectionsResourceWithRawResponse:
from .resources.collections import AsyncCollectionsResourceWithRawResponse
return AsyncCollectionsResourceWithRawResponse(self._client.collections)
@cached_property
def deployments(self) -> deployments.AsyncDeploymentsResourceWithRawResponse:
from .resources.deployments import AsyncDeploymentsResourceWithRawResponse
return AsyncDeploymentsResourceWithRawResponse(self._client.deployments)
@cached_property
def hardware(self) -> hardware.AsyncHardwareResourceWithRawResponse:
You can’t perform that action at this time.