diff --git a/README.md b/README.md index d792f8c0..2bf5146d 100644 --- a/README.md +++ b/README.md @@ -53,6 +53,32 @@ Some models, like [methexis-inc/img2prompt](https://replicate.com/methexis-inc/i "an astronaut riding a horse" ``` +> [!NOTE] +> You can also use the Replicate client asynchronously by prepending `async_` to the method name. +> +> Here's an example of how to run several predictions concurrently and wait for them all to complete: +> +> ```python +> import asyncio +> import replicate +> +> # https://replicate.com/stability-ai/sdxl +> model_version = "stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b" +> prompts = [ +> f"A chariot pulled by a team of {count} rainbow unicorns" +> for count in ["two", "four", "six", "eight"] +> ] +> +> async with asyncio.TaskGroup() as tg: +> tasks = [ +> tg.create_task(replicate.async_run(model_version, input={"prompt": prompt})) +> for prompt in prompts +> ] +> +> results = await asyncio.gather(*tasks) +> print(results) +> ``` + ## Run a model in the background You can start a model and run it in the background: diff --git a/pyproject.toml b/pyproject.toml index 3879798a..5af35433 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -37,6 +37,7 @@ packages = ["replicate"] [tool.mypy] plugins = "pydantic.mypy" exclude = ["tests/"] +enable_incomplete_feature = ["Unpack"] [tool.pylint.main] disable = [ @@ -48,6 +49,7 @@ disable = [ "W0622", # Redefining built-in "R0903", # Too few public methods ] +good-names = ["id"] [tool.ruff] select = [ diff --git a/replicate/__init__.py b/replicate/__init__.py index fd625e4f..d78432d9 100644 --- a/replicate/__init__.py +++ b/replicate/__init__.py @@ -1,7 +1,10 @@ from replicate.client import Client default_client = Client() + run = default_client.run +async_run = default_client.async_run + collections = default_client.collections hardware = default_client.hardware deployments = default_client.deployments diff --git a/replicate/client.py b/replicate/client.py index d78f6324..70a7b075 100644 --- a/replicate/client.py +++ b/replicate/client.py @@ -1,35 +1,37 @@ import os import random -import re import time from datetime import datetime from typing import ( Any, + Dict, Iterable, Iterator, Mapping, Optional, + Type, Union, ) import httpx +from typing_extensions import Unpack from replicate.__about__ import __version__ from replicate.collection import Collections from replicate.deployment import Deployments -from replicate.exceptions import ModelError, ReplicateError -from replicate.hardware import Hardwares +from replicate.exceptions import ReplicateError +from replicate.hardware import HardwareNamespace as Hardware from replicate.model import Models from replicate.prediction import Predictions -from replicate.schema import make_schema_backwards_compatible +from replicate.run import async_run, run from replicate.training import Trainings -from replicate.version import Version class Client: """A Replicate API client library""" __client: Optional[httpx.Client] = None + __async_client: Optional[httpx.AsyncClient] = None def __init__( self, @@ -42,46 +44,45 @@ def __init__( super().__init__() self._api_token = api_token - self._base_url = ( - base_url - or os.environ.get("REPLICATE_API_BASE_URL") - or "https://api.replicate.com" - ) - self._timeout = timeout or httpx.Timeout( - 5.0, read=30.0, write=30.0, connect=5.0, pool=10.0 - ) - self._transport = kwargs.pop("transport", httpx.HTTPTransport()) + self._base_url = base_url + self._timeout = timeout self._client_kwargs = kwargs self.poll_interval = float(os.environ.get("REPLICATE_POLL_INTERVAL", "0.5")) @property def _client(self) -> httpx.Client: - if self.__client is None: - headers = { - "User-Agent": f"replicate-python/{__version__}", - } - - api_token = self._api_token or os.environ.get("REPLICATE_API_TOKEN") - - if api_token is not None and api_token != "": - headers["Authorization"] = f"Token {api_token}" - - self.__client = httpx.Client( + if not self.__client: + self.__client = _build_httpx_client( + httpx.Client, + self._api_token, + self._base_url, + self._timeout, **self._client_kwargs, - base_url=self._base_url, - headers=headers, - timeout=self._timeout, - transport=RetryTransport(wrapped_transport=self._transport), - ) + ) # type: ignore[assignment] + return self.__client # type: ignore[return-value] - return self.__client + @property + def _async_client(self) -> httpx.AsyncClient: + if not self.__async_client: + self.__async_client = _build_httpx_client( + httpx.AsyncClient, + self._api_token, + self._base_url, + self._timeout, + **self._client_kwargs, + ) # type: ignore[assignment] + return self.__async_client # type: ignore[return-value] def _request(self, method: str, path: str, **kwargs) -> httpx.Response: resp = self._client.request(method, path, **kwargs) + _raise_for_status(resp) + + return resp - if 400 <= resp.status_code < 600: - raise ReplicateError(resp.json()["detail"]) + async def _async_request(self, method: str, path: str, **kwargs) -> httpx.Response: + resp = await self._async_client.request(method, path, **kwargs) + _raise_for_status(resp) return resp @@ -100,11 +101,11 @@ def deployments(self) -> Deployments: return Deployments(client=self) @property - def hardware(self) -> Hardwares: + def hardware(self) -> Hardware: """ Namespace for operations related to hardware. """ - return Hardwares(client=self) + return Hardware(client=self) @property def models(self) -> Models: @@ -127,55 +128,29 @@ def trainings(self) -> Trainings: """ return Trainings(client=self) - def run(self, model_version: str, **kwargs) -> Union[Any, Iterator[Any]]: # noqa: ANN401 + def run( + self, + ref: str, + input: Optional[Dict[str, Any]] = None, + **params: Unpack["Predictions.CreatePredictionParams"], + ) -> Union[Any, Iterator[Any]]: # noqa: ANN401 """ Run a model and wait for its output. - - Args: - model_version: The model version to run, in the format `owner/name:version` - kwargs: The input to the model, as a dictionary - Returns: - The output of the model """ - # Split model_version into owner, name, version in format owner/name:version - match = re.match( - r"^(?P[^/]+)/(?P[^:]+):(?P.+)$", model_version - ) - if not match: - raise ReplicateError( - f"Invalid model_version: {model_version}. Expected format: owner/name:version" - ) - - owner = match.group("owner") - name = match.group("name") - version_id = match.group("version") - prediction = self.predictions.create(version=version_id, **kwargs) + return run(self, ref, input, **params) - if owner and name: - # FIXME: There should be a method for fetching a version without first fetching its model - resp = self._request( - "GET", f"/v1/models/{owner}/{name}/versions/{version_id}" - ) - version = Version(**resp.json()) - - # Return an iterator of the output - schema = make_schema_backwards_compatible( - version.openapi_schema, version.cog_version - ) - output = schema["components"]["schemas"]["Output"] - if ( - output.get("type") == "array" - and output.get("x-cog-array-type") == "iterator" - ): - return prediction.output_iterator() - - prediction.wait() - - if prediction.status == "failed": - raise ModelError(prediction.error) + async def async_run( + self, + ref: str, + input: Optional[Dict[str, Any]] = None, + **params: Unpack["Predictions.CreatePredictionParams"], + ) -> Union[Any, Iterator[Any]]: # noqa: ANN401 + """ + Run a model and wait for its output asynchronously. + """ - return prediction.output + return await async_run(self, ref, input, **params) # Adapted from https://github.com/encode/httpx/issues/108#issuecomment-1132753155 @@ -305,3 +280,49 @@ async def aclose(self) -> None: def close(self) -> None: self._wrapped_transport.close() # type: ignore + + +def _build_httpx_client( + client_type: Type[Union[httpx.Client, httpx.AsyncClient]], + api_token: Optional[str] = None, + base_url: Optional[str] = None, + timeout: Optional[httpx.Timeout] = None, + **kwargs, +) -> Union[httpx.Client, httpx.AsyncClient]: + headers = { + "User-Agent": f"replicate-python/{__version__}", + } + + if ( + api_token := api_token or os.environ.get("REPLICATE_API_TOKEN") + ) and api_token != "": + headers["Authorization"] = f"Token {api_token}" + + base_url = ( + base_url or os.environ.get("REPLICATE_BASE_URL") or "https://api.replicate.com" + ) + if base_url == "": + base_url = "https://api.replicate.com" + + timeout = timeout or httpx.Timeout( + 5.0, read=30.0, write=30.0, connect=5.0, pool=10.0 + ) + + transport = kwargs.pop("transport", None) or ( + httpx.HTTPTransport() + if client_type is httpx.Client + else httpx.AsyncHTTPTransport() + ) + + return client_type( + base_url=base_url, + headers=headers, + timeout=timeout, + transport=RetryTransport(wrapped_transport=transport), # type: ignore[arg-type] + **kwargs, + ) + + +def _raise_for_status(resp: httpx.Response) -> None: + if 400 <= resp.status_code < 600: + raise ReplicateError(resp.json()["detail"]) diff --git a/replicate/collection.py b/replicate/collection.py index f9dcbb33..56001d15 100644 --- a/replicate/collection.py +++ b/replicate/collection.py @@ -1,14 +1,11 @@ -from typing import TYPE_CHECKING, Dict, List, Optional, Union +from typing import Any, Dict, List, Optional, Union from typing_extensions import deprecated -from replicate.model import Model, Models +from replicate.model import Model from replicate.pagination import Page from replicate.resource import Namespace, Resource -if TYPE_CHECKING: - from replicate.client import Client - class Collection(Resource): """ @@ -56,15 +53,37 @@ class Collections(Namespace): A namespace for operations related to collections of models. """ - model = Collection + def list( + self, + cursor: Union[str, "ellipsis"] = ..., # noqa: F821 + ) -> Page[Collection]: + """ + List collections of models. + + Parameters: + cursor: The cursor to use for pagination. Use the value of `Page.next` or `Page.previous`. + Returns: + Page[Collection]: A page of of model collections. + Raises: + ValueError: If `cursor` is `None`. + """ + + if cursor is None: + raise ValueError("cursor cannot be None") + + resp = self._client._request( + "GET", "/v1/collections" if cursor is ... else cursor + ) - _models: Models + obj = resp.json() + obj["results"] = [_json_to_collection(result) for result in obj["results"]] - def __init__(self, client: "Client") -> None: - self._models = Models(client) - super().__init__(client) + return Page[Collection](**obj) - def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Collection]: # noqa: F821 + async def async_list( + self, + cursor: Union[str, "ellipsis"] = ..., # noqa: F821 + ) -> Page[Collection]: """ List collections of models. @@ -79,11 +98,14 @@ def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Collection]: # noq if cursor is None: raise ValueError("cursor cannot be None") - resp = self._client._request( + resp = await self._client._async_request( "GET", "/v1/collections" if cursor is ... else cursor ) - return Page[Collection](self._client, self, **resp.json()) + obj = resp.json() + obj["results"] = [_json_to_collection(result) for result in obj["results"]] + + return Page[Collection](**obj) def get(self, slug: str) -> Collection: """Get a model by name. @@ -96,16 +118,21 @@ def get(self, slug: str) -> Collection: resp = self._client._request("GET", f"/v1/collections/{slug}") - return self._prepare_model(resp.json()) + return _json_to_collection(resp.json()) + + async def async_get(self, slug: str) -> Collection: + """Get a model by name. + + Args: + name: The name of the model, in the format `owner/model-name`. + Returns: + The model. + """ + + resp = await self._client._async_request("GET", f"/v1/collections/{slug}") + + return _json_to_collection(resp.json()) - def _prepare_model(self, attrs: Union[Collection, Dict]) -> Collection: - if isinstance(attrs, Resource): - if attrs.models is not None: - attrs.models = [self._models._prepare_model(m) for m in attrs.models] - elif isinstance(attrs, dict): - if "models" in attrs: - attrs["models"] = [ - self._models._prepare_model(m) for m in attrs["models"] - ] - return super()._prepare_model(attrs) +def _json_to_collection(json: Dict[str, Any]) -> Collection: + return Collection(**json) diff --git a/replicate/deployment.py b/replicate/deployment.py index 5b0077ce..7002a585 100644 --- a/replicate/deployment.py +++ b/replicate/deployment.py @@ -1,12 +1,23 @@ -from typing import TYPE_CHECKING, Any, Dict, List, Optional +from typing import TYPE_CHECKING, Any, Dict -from replicate.files import upload_file -from replicate.json import encode_json -from replicate.prediction import Prediction +from typing_extensions import Unpack, deprecated + +from replicate.prediction import ( + Prediction, + _create_prediction_body, + _json_to_prediction, +) from replicate.resource import Namespace, Resource +try: + from pydantic import v1 as pydantic # type: ignore +except ImportError: + pass # type: ignore + + if TYPE_CHECKING: from replicate.client import Client + from replicate.prediction import Predictions class Deployment(Resource): @@ -14,9 +25,9 @@ class Deployment(Resource): A deployment of a model hosted on Replicate. """ - _namespace: "Deployments" + _client: "Client" = pydantic.PrivateAttr() - username: str + owner: str """ The name of the user or organization that owns the deployment. """ @@ -26,9 +37,21 @@ class Deployment(Resource): The name of the deployment. """ + @property + @deprecated("Use `deployment.owner` instead.") + def username(self) -> str: + """ + The name of the user or organization that owns the deployment. + This attribute is deprecated and will be removed in future versions. + """ + return self.owner + @property def id(self) -> str: - return f"{self.username}/{self.name}" + """ + Return the qualified deployment name, in the format `owner/name`. + """ + return f"{self.owner}/{self.name}" @property def predictions(self) -> "DeploymentPredictions": @@ -44,7 +67,7 @@ class Deployments(Namespace): Namespace for operations related to deployments. """ - model = Deployment + _client: "Client" def get(self, name: str) -> Deployment: """ @@ -56,10 +79,29 @@ def get(self, name: str) -> Deployment: The model. """ - # TODO: fetch model from server - # TODO: support permanent IDs - username, name = name.split("/") - return self._prepare_model({"username": username, "name": name}) + owner, name = name.split("/", 1) + + deployment = Deployment(owner=owner, name=name) + deployment._client = self._client + + return deployment + + async def async_get(self, name: str) -> Deployment: + """ + Get a deployment by name. + + Args: + name: The name of the deployment, in the format `owner/model-name`. + Returns: + The model. + """ + + owner, name = name.split("/", 1) + + deployment = Deployment(owner=owner, name=name) + deployment._client = self._client + + return deployment class DeploymentPredictions(Namespace): @@ -67,7 +109,7 @@ class DeploymentPredictions(Namespace): Namespace for operations related to predictions in a deployment. """ - model = Prediction + _deployment: Deployment def __init__(self, client: "Client", deployment: Deployment) -> None: super().__init__(client=client) @@ -76,48 +118,37 @@ def __init__(self, client: "Client", deployment: Deployment) -> None: def create( self, input: Dict[str, Any], - *, - webhook: Optional[str] = None, - webhook_completed: Optional[str] = None, - webhook_events_filter: Optional[List[str]] = None, - stream: Optional[bool] = None, + **params: Unpack["Predictions.CreatePredictionParams"], ) -> Prediction: """ Create a new prediction with the deployment. - - Args: - input: The input data for the prediction. - webhook: The URL to receive a POST request with prediction updates. - webhook_completed: The URL to receive a POST request when the prediction is completed. - webhook_events_filter: List of events to trigger webhooks. - stream: Set to True to enable streaming of prediction output. - - Returns: - Prediction: The created prediction object. """ - body = { - "input": encode_json(input, upload_file=upload_file), - } + body = _create_prediction_body(version=None, input=input, **params) - if webhook is not None: - body["webhook"] = webhook + resp = self._client._request( + "POST", + f"/v1/deployments/{self._deployment.owner}/{self._deployment.name}/predictions", + json=body, + ) - if webhook_completed is not None: - body["webhook_completed"] = webhook_completed + return _json_to_prediction(self._client, resp.json()) - if webhook_events_filter is not None: - body["webhook_events_filter"] = webhook_events_filter + async def async_create( + self, + input: Dict[str, Any], + **params: Unpack["Predictions.CreatePredictionParams"], + ) -> Prediction: + """ + Create a new prediction with the deployment. + """ - if stream is not None: - body["stream"] = stream + body = _create_prediction_body(version=None, input=input, **params) - resp = self._client._request( + resp = await self._client._async_request( "POST", - f"/v1/deployments/{self._deployment.username}/{self._deployment.name}/predictions", + f"/v1/deployments/{self._deployment.owner}/{self._deployment.name}/predictions", json=body, ) - obj = resp.json() - obj["deployment"] = self._deployment - del obj["version"] - return self._prepare_model(obj) + + return _json_to_prediction(self._client, resp.json()) diff --git a/replicate/hardware.py b/replicate/hardware.py index e5ea81a2..1ded9cb7 100644 --- a/replicate/hardware.py +++ b/replicate/hardware.py @@ -1,9 +1,12 @@ -from typing import List +from typing import TYPE_CHECKING, Any, Dict, List from typing_extensions import deprecated from replicate.resource import Namespace, Resource +if TYPE_CHECKING: + pass + class Hardware(Resource): """ @@ -29,13 +32,11 @@ def id(self) -> str: return self.sku -class Hardwares(Namespace): +class HardwareNamespace(Namespace): """ Namespace for operations related to hardware. """ - model = Hardware - def list(self) -> List[Hardware]: """ List all hardware available for you to run models on Replicate. @@ -45,4 +46,23 @@ def list(self) -> List[Hardware]: """ resp = self._client._request("GET", "/v1/hardware") - return [self._prepare_model(obj) for obj in resp.json()] + obj = resp.json() + + return [_json_to_hardware(entry) for entry in obj] + + async def async_list(self) -> List[Hardware]: + """ + List all hardware available for you to run models on Replicate. + + Returns: + List[Hardware]: A list of hardware. + """ + + resp = await self._client._async_request("GET", "/v1/hardware") + obj = resp.json() + + return [_json_to_hardware(entry) for entry in obj] + + +def _json_to_hardware(json: Dict[str, Any]) -> Hardware: + return Hardware(**json) diff --git a/replicate/model.py b/replicate/model.py index e9c8288a..775025d8 100644 --- a/replicate/model.py +++ b/replicate/model.py @@ -1,6 +1,6 @@ -from typing import Dict, Optional, Union +from typing import TYPE_CHECKING, Any, Dict, Literal, Optional, Union -from typing_extensions import deprecated +from typing_extensions import NotRequired, TypedDict, Unpack, deprecated from replicate.exceptions import ReplicateException from replicate.pagination import Page @@ -8,13 +8,22 @@ from replicate.resource import Namespace, Resource from replicate.version import Version, Versions +try: + from pydantic import v1 as pydantic # type: ignore +except ImportError: + pass # type: ignore + + +if TYPE_CHECKING: + from replicate.client import Client + class Model(Resource): """ A machine learning model hosted on Replicate. """ - _namespace: "Models" + _client: "Client" = pydantic.PrivateAttr() url: str """ @@ -36,7 +45,7 @@ class Model(Resource): The description of the model. """ - visibility: str + visibility: Literal["public", "private"] """ The visibility of the model. Can be 'public' or 'private'. """ @@ -78,6 +87,9 @@ class Model(Resource): @property def id(self) -> str: + """ + Return the qualified model name, in the format `owner/name`. + """ return f"{self.owner}/{self.name}" @property @@ -116,7 +128,7 @@ def reload(self) -> None: Load this object from the server. """ - obj = self._namespace.get(f"{self.owner}/{self.name}") # pylint: disable=no-member + obj = self._client.models.get(f"{self.owner}/{self.name}") for name, value in obj.dict().items(): setattr(self, name, value) @@ -144,7 +156,39 @@ def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Model]: # noqa: F8 raise ValueError("cursor cannot be None") resp = self._client._request("GET", "/v1/models" if cursor is ... else cursor) - return Page[Model](self._client, self, **resp.json()) + + obj = resp.json() + obj["results"] = [ + _json_to_model(self._client, result) for result in obj["results"] + ] + + return Page[Model](**obj) + + async def async_list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Model]: # noqa: F821 + """ + List all public models. + + Parameters: + cursor: The cursor to use for pagination. Use the value of `Page.next` or `Page.previous`. + Returns: + Page[Model]: A page of of models. + Raises: + ValueError: If `cursor` is `None`. + """ + + if cursor is None: + raise ValueError("cursor cannot be None") + + resp = await self._client._async_request( + "GET", "/v1/models" if cursor is ... else cursor + ) + + obj = resp.json() + obj["results"] = [ + _json_to_model(self._client, result) for result in obj["results"] + ] + + return Page[Model](**obj) def get(self, key: str) -> Model: """ @@ -157,80 +201,117 @@ def get(self, key: str) -> Model: """ resp = self._client._request("GET", f"/v1/models/{key}") - return self._prepare_model(resp.json()) - def create( # pylint: disable=arguments-differ disable=too-many-arguments + return _json_to_model(self._client, resp.json()) + + async def async_get(self, key: str) -> Model: + """ + Get a model by name. + + Args: + key: The qualified name of the model, in the format `owner/model-name`. + Returns: + The model. + """ + + resp = await self._client._async_request("GET", f"/v1/models/{key}") + + return _json_to_model(self._client, resp.json()) + + class CreateModelParams(TypedDict): + """Parameters for creating a model.""" + + hardware: str + """The SKU for the hardware used to run the model. + + Possible values can be found by calling `replicate.hardware.list()`.""" + + visibility: Literal["public", "private"] + """Whether the model should be public or private.""" + + description: NotRequired[str] + """The description of the model.""" + + github_url: NotRequired[str] + """A URL for the model's source code on GitHub.""" + + paper_url: NotRequired[str] + """A URL for the model's paper.""" + + license_url: NotRequired[str] + """A URL for the model's license.""" + + cover_image_url: NotRequired[str] + """A URL for the model's cover image.""" + + def create( self, owner: str, name: str, - *, - visibility: str, - hardware: str, - description: Optional[str] = None, - github_url: Optional[str] = None, - paper_url: Optional[str] = None, - license_url: Optional[str] = None, - cover_image_url: Optional[str] = None, + **params: Unpack["Models.CreateModelParams"], ) -> Model: """ Create a model. - - Args: - owner: The name of the user or organization that will own the model. - name: The name of the model. - visibility: Whether the model should be public or private. - hardware: The SKU for the hardware used to run the model. Possible values can be found by calling `replicate.hardware.list()`. - description: A description of the model. - github_url: A URL for the model's source code on GitHub. - paper_url: A URL for the model's paper. - license_url: A URL for the model's license. - cover_image_url: A URL for the model's cover image. - - Returns: - The created model. """ - body = { - "owner": owner, - "name": name, - "visibility": visibility, - "hardware": hardware, - } + body = _create_model_body(owner, name, **params) + resp = self._client._request("POST", "/v1/models", json=body) - if description is not None: - body["description"] = description + return _json_to_model(self._client, resp.json()) - if github_url is not None: - body["github_url"] = github_url + async def async_create( + self, owner: str, name: str, **params: Unpack["Models.CreateModelParams"] + ) -> Model: + """ + Create a model. + """ - if paper_url is not None: - body["paper_url"] = paper_url + body = body = _create_model_body(owner, name, **params) + resp = await self._client._async_request("POST", "/v1/models", json=body) - if license_url is not None: - body["license_url"] = license_url + return _json_to_model(self._client, resp.json()) - if cover_image_url is not None: - body["cover_image_url"] = cover_image_url - resp = self._client._request("POST", "/v1/models", json=body) +def _create_model_body( # pylint: disable=too-many-arguments + owner: str, + name: str, + *, + visibility: str, + hardware: str, + description: Optional[str] = None, + github_url: Optional[str] = None, + paper_url: Optional[str] = None, + license_url: Optional[str] = None, + cover_image_url: Optional[str] = None, +) -> Dict[str, Any]: + body = { + "owner": owner, + "name": name, + "visibility": visibility, + "hardware": hardware, + } + + if description is not None: + body["description"] = description - return self._prepare_model(resp.json()) + if github_url is not None: + body["github_url"] = github_url - def _prepare_model(self, attrs: Union[Model, Dict]) -> Model: - if isinstance(attrs, dict): - if attrs is not None: - if "default_example" in attrs and attrs["default_example"]: - attrs["default_example"].pop("version") + if paper_url is not None: + body["paper_url"] = paper_url - if "latest_version" in attrs and attrs["latest_version"] == {}: - attrs.pop("latest_version") + if license_url is not None: + body["license_url"] = license_url - model = super()._prepare_model(attrs) + if cover_image_url is not None: + body["cover_image_url"] = cover_image_url - if model.default_example is not None: - model.default_example._client = self._client + return body - if model.latest_version is not None: - model.latest_version._client = self._client - return model +def _json_to_model(client: "Client", json: Dict[str, Any]) -> Model: + model = Model(**json) + model._client = client + if model.default_example is not None: + model.default_example._client = client + return model diff --git a/replicate/pagination.py b/replicate/pagination.py index 2dd9d66b..b70b97b1 100644 --- a/replicate/pagination.py +++ b/replicate/pagination.py @@ -1,11 +1,9 @@ from typing import ( TYPE_CHECKING, - Dict, Generic, List, Optional, TypeVar, - Union, ) try: @@ -13,12 +11,12 @@ except ImportError: import pydantic # type: ignore -from replicate.resource import Namespace, Resource +from replicate.resource import Resource T = TypeVar("T", bound=Resource) if TYPE_CHECKING: - from .client import Client + pass class Page(pydantic.BaseModel, Generic[T]): @@ -26,9 +24,6 @@ class Page(pydantic.BaseModel, Generic[T]): A page of results from the API. """ - _client: "Client" = pydantic.PrivateAttr() - _namespace: Namespace = pydantic.PrivateAttr() - previous: Optional[str] = None """A pointer to the previous page of results""" @@ -38,24 +33,6 @@ class Page(pydantic.BaseModel, Generic[T]): results: List[T] """The results on this page""" - def __init__( - self, - client: "Client", - namespace: Namespace[T], - *, - results: Optional[List[Union[T, Dict]]] = None, - **kwargs, - ) -> None: - self._client = client - self._namespace = namespace - - super().__init__( - results=[self._namespace._prepare_model(r) for r in results] - if results - else None, - **kwargs, - ) - def __iter__(self): # noqa: ANN204 return iter(self.results) diff --git a/replicate/prediction.py b/replicate/prediction.py index 7f83a436..e1c97d83 100644 --- a/replicate/prediction.py +++ b/replicate/prediction.py @@ -1,7 +1,9 @@ import re import time from dataclasses import dataclass -from typing import Any, Dict, Iterator, List, Optional, Union +from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional, Union + +from typing_extensions import NotRequired, TypedDict, Unpack from replicate.exceptions import ModelError from replicate.files import upload_file @@ -10,19 +12,27 @@ from replicate.resource import Namespace, Resource from replicate.version import Version +try: + from pydantic import v1 as pydantic # type: ignore +except ImportError: + import pydantic # type: ignore + +if TYPE_CHECKING: + from replicate.client import Client + class Prediction(Resource): """ A prediction made by a model hosted on Replicate. """ - _namespace: "Predictions" + _client: "Client" = pydantic.PrivateAttr() id: str """The unique ID of the prediction.""" - version: Optional[Version] - """The version of the model used to create the prediction.""" + version: str + """An identifier for the version of the model used to create the prediction.""" status: str """The status of the prediction.""" @@ -84,8 +94,8 @@ def parse(cls, logs: str) -> Optional["Prediction.Progress"]: """Parse the progress from the logs of a prediction.""" lines = logs.split("\n") - for i in reversed(range(len(lines))): - line = lines[i].strip() + for idx in reversed(range(len(lines))): + line = lines[idx].strip() if cls._pattern.match(line): matches = cls._pattern.findall(line) if len(matches) == 1: @@ -109,9 +119,27 @@ def wait(self) -> None: Wait for prediction to finish. """ while self.status not in ["succeeded", "failed", "canceled"]: - time.sleep(self._client.poll_interval) # pylint: disable=no-member + time.sleep(self._client.poll_interval) self.reload() + def cancel(self) -> None: + """ + Cancels a running prediction. + """ + + canceled = self._client.predictions.cancel(self.id) + for name, value in canceled.dict().items(): + setattr(self, name, value) + + def reload(self) -> None: + """ + Load this prediction from the server. + """ + + updated = self._client.predictions.get(self.id) + for name, value in updated.dict().items(): + setattr(self, name, value) + def output_iterator(self) -> Iterator[Any]: """ Return an iterator of the prediction output. @@ -135,29 +163,12 @@ def output_iterator(self) -> Iterator[Any]: for output in new_output: yield output - def cancel(self) -> None: - """ - Cancels a running prediction. - """ - self._client._request("POST", f"/v1/predictions/{self.id}/cancel") # pylint: disable=no-member - - def reload(self) -> None: - """ - Load this prediction from the server. - """ - - obj = self._namespace.get(self.id) # pylint: disable=no-member - for name, value in obj.dict().items(): - setattr(self, name, value) - class Predictions(Namespace): """ Namespace for operations related to predictions. """ - model = Prediction - def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Prediction]: # noqa: F821 """ List your predictions. @@ -176,9 +187,44 @@ def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Prediction]: # noq resp = self._client._request( "GET", "/v1/predictions" if cursor is ... else cursor ) - return Page[Prediction](self._client, self, **resp.json()) - def get(self, id: str) -> Prediction: # pylint: disable=invalid-name + obj = resp.json() + obj["results"] = [ + _json_to_prediction(self._client, result) for result in obj["results"] + ] + + return Page[Prediction](**obj) + + async def async_list( + self, + cursor: Union[str, "ellipsis"] = ..., # noqa: F821 + ) -> Page[Prediction]: + """ + List your predictions. + + Parameters: + cursor: The cursor to use for pagination. Use the value of `Page.next` or `Page.previous`. + Returns: + Page[Prediction]: A page of of predictions. + Raises: + ValueError: If `cursor` is `None`. + """ + + if cursor is None: + raise ValueError("cursor cannot be None") + + resp = await self._client._async_request( + "GET", "/v1/predictions" if cursor is ... else cursor + ) + + obj = resp.json() + obj["results"] = [ + _json_to_prediction(self._client, result) for result in obj["results"] + ] + + return Page[Prediction](**obj) + + def get(self, id: str) -> Prediction: """ Get a prediction by ID. @@ -189,62 +235,151 @@ def get(self, id: str) -> Prediction: # pylint: disable=invalid-name """ resp = self._client._request("GET", f"/v1/predictions/{id}") - obj = resp.json() - # HACK: resolve this? make it lazy somehow? - del obj["version"] - return self._prepare_model(obj) + + return _json_to_prediction(self._client, resp.json()) + + async def async_get(self, id: str) -> Prediction: + """ + Get a prediction by ID. + + Args: + id: The ID of the prediction. + Returns: + Prediction: The prediction object. + """ + + resp = await self._client._async_request("GET", f"/v1/predictions/{id}") + + return _json_to_prediction(self._client, resp.json()) + + class CreatePredictionParams(TypedDict): + """Parameters for creating a prediction.""" + + webhook: NotRequired[str] + """The URL to receive a POST request with prediction updates.""" + + webhook_completed: NotRequired[str] + """The URL to receive a POST request when the prediction is completed.""" + + webhook_events_filter: NotRequired[List[str]] + """List of events to trigger webhooks.""" + + stream: NotRequired[bool] + """Enable streaming of prediction output.""" def create( self, version: Union[Version, str], - input: Dict[str, Any], - *, - webhook: Optional[str] = None, - webhook_completed: Optional[str] = None, - webhook_events_filter: Optional[List[str]] = None, - stream: Optional[bool] = None, + input: Optional[Dict[str, Any]], + **params: Unpack["Predictions.CreatePredictionParams"], ) -> Prediction: """ Create a new prediction for the specified model version. + """ - Args: - version: The model version to use for the prediction. - input: The input data for the prediction. - webhook: The URL to receive a POST request with prediction updates. - webhook_completed: The URL to receive a POST request when the prediction is completed. - webhook_events_filter: List of events to trigger webhooks. - stream: Set to True to enable streaming of prediction output. + body = _create_prediction_body( + version, + input, + **params, + ) + resp = self._client._request( + "POST", + "/v1/predictions", + json=body, + ) - Returns: - Prediction: The created prediction object. - """ + return _json_to_prediction(self._client, resp.json()) - body = { - "version": version if isinstance(version, str) else version.id, - "input": encode_json(input, upload_file=upload_file), - } + async def async_create( + self, + version: Union[Version, str], + input: Optional[Dict[str, Any]], + **params: Unpack["Predictions.CreatePredictionParams"], + ) -> Prediction: + """ + Create a new prediction for the specified model version. + """ - if webhook is not None: - body["webhook"] = webhook + body = _create_prediction_body( + version, + input, + **params, + ) + resp = await self._client._async_request( + "POST", + "/v1/predictions", + json=body, + ) - if webhook_completed is not None: - body["webhook_completed"] = webhook_completed + return _json_to_prediction(self._client, resp.json()) - if webhook_events_filter is not None: - body["webhook_events_filter"] = webhook_events_filter + def cancel(self, id: str) -> Prediction: + """ + Cancel a prediction. - if stream is not None: - body["stream"] = stream + Args: + id: The ID of the prediction to cancel. + Returns: + Prediction: The canceled prediction object. + """ resp = self._client._request( "POST", - "/v1/predictions", - json=body, + f"/v1/predictions/{id}/cancel", ) - obj = resp.json() - if isinstance(version, Version): - obj["version"] = version - else: - del obj["version"] - return self._prepare_model(obj) + return _json_to_prediction(self._client, resp.json()) + + async def async_cancel(self, id: str) -> Prediction: + """ + Cancel a prediction. + + Args: + id: The ID of the prediction to cancel. + Returns: + Prediction: The canceled prediction object. + """ + + resp = await self._client._async_request( + "POST", + f"/v1/predictions/{id}/cancel", + ) + + return _json_to_prediction(self._client, resp.json()) + + +def _create_prediction_body( # pylint: disable=too-many-arguments + version: Optional[Union[Version, str]], + input: Optional[Dict[str, Any]], + webhook: Optional[str] = None, + webhook_completed: Optional[str] = None, + webhook_events_filter: Optional[List[str]] = None, + stream: Optional[bool] = None, +) -> Dict[str, Any]: + body = {} + + if input is not None: + body["input"] = encode_json(input, upload_file=upload_file) + + if version is not None: + body["version"] = version.id if isinstance(version, Version) else version + + if webhook is not None: + body["webhook"] = webhook + + if webhook_completed is not None: + body["webhook_completed"] = webhook_completed + + if webhook_events_filter is not None: + body["webhook_events_filter"] = webhook_events_filter + + if stream is not None: + body["stream"] = stream + + return body + + +def _json_to_prediction(client: "Client", json: Dict[str, Any]) -> Prediction: + prediction = Prediction(**json) + prediction._client = client + return prediction diff --git a/replicate/resource.py b/replicate/resource.py index 9c5ae52b..b7789ee9 100644 --- a/replicate/resource.py +++ b/replicate/resource.py @@ -1,7 +1,5 @@ import abc -from typing import TYPE_CHECKING, Dict, Generic, TypeVar, Union, cast - -from replicate.exceptions import ReplicateException +from typing import TYPE_CHECKING try: from pydantic import v1 as pydantic # type: ignore @@ -17,38 +15,13 @@ class Resource(pydantic.BaseModel): A base class for representing a single object on the server. """ - _client: "Client" = pydantic.PrivateAttr() - _namespace: "Namespace" = pydantic.PrivateAttr() - - -Model = TypeVar("Model", bound=Resource) - -class Namespace(abc.ABC, Generic[Model]): +class Namespace(abc.ABC): """ A base class for representing objects of a particular type on the server. """ _client: "Client" - model: Model def __init__(self, client: "Client") -> None: self._client = client - - def _prepare_model(self, attrs: Union[Model, Dict]) -> Model: - """ - Create a model from a set of attributes. - """ - if isinstance(attrs, Resource): - attrs._client = self._client - attrs._namespace = self - return cast(Model, attrs) - - if isinstance(attrs, dict) and self.model is not None and callable(self.model): - model = self.model(**attrs) - model._client = self._client - model._namespace = self - return model - - name = self.model.__name__ if hasattr(self.model, "__name__") else "model" - raise ReplicateException(f"Can't create {name} from {attrs}") diff --git a/replicate/run.py b/replicate/run.py new file mode 100644 index 00000000..a909d6e8 --- /dev/null +++ b/replicate/run.py @@ -0,0 +1,112 @@ +import asyncio +import re +from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional, Union + +from typing_extensions import Unpack + +from replicate.exceptions import ModelError, ReplicateError +from replicate.schema import make_schema_backwards_compatible +from replicate.version import Versions + +if TYPE_CHECKING: + from replicate.client import Client + from replicate.prediction import Predictions + + +def run( + client: "Client", + ref: str, + input: Optional[Dict[str, Any]] = None, + **params: Unpack["Predictions.CreatePredictionParams"], +) -> Union[Any, Iterator[Any]]: # noqa: ANN401 + """ + Run a model and wait for its output. + """ + + # Split ref into owner, name, version in format owner/name:version + match = re.match(r"^(?P[^/]+)/(?P[^:]+):(?P.+)$", ref) + if not match: + raise ReplicateError( + f"Invalid reference to model version: {ref}. Expected format: owner/name:version" + ) + + owner = match.group("owner") + name = match.group("name") + version_id = match.group("version") + + prediction = client.predictions.create( + version=version_id, input=input or {}, **params + ) + + if owner and name: + version = Versions(client, model=(owner, name)).get(version_id) + + # Return an iterator of the output + schema = make_schema_backwards_compatible( + version.openapi_schema, version.cog_version + ) + output = schema["components"]["schemas"]["Output"] + if ( + output.get("type") == "array" + and output.get("x-cog-array-type") == "iterator" + ): + return prediction.output_iterator() + + prediction.wait() + + if prediction.status == "failed": + raise ModelError(prediction.error) + + return prediction.output + + +async def async_run( + client: "Client", + ref: str, + input: Optional[Dict[str, Any]] = None, + **params: Unpack["Predictions.CreatePredictionParams"], +) -> Union[Any, Iterator[Any]]: # noqa: ANN401 + """ + Run a model and wait for its output asynchronously. + """ + + # Split ref into owner, name, version in format owner/name:version + match = re.match(r"^(?P[^/]+)/(?P[^:]+):(?P.+)$", ref) + if not match: + raise ReplicateError( + f"Invalid reference to model version: {ref}. Expected format: owner/name:version" + ) + + owner = match.group("owner") + name = match.group("name") + version_id = match.group("version") + + prediction = await client.predictions.async_create( + version=version_id, input=input or {}, **params + ) + + if owner and name: + version = await Versions(client, model=(owner, name)).async_get(version_id) + + # Return an iterator of the output + schema = make_schema_backwards_compatible( + version.openapi_schema, version.cog_version + ) + output = schema["components"]["schemas"]["Output"] + if ( + output.get("type") == "array" + and output.get("x-cog-array-type") == "iterator" + ): + return prediction.output_iterator() + + while prediction.status not in ["succeeded", "failed", "canceled"]: + await asyncio.sleep(client.poll_interval) + prediction = await client.predictions.async_get(prediction.id) + + if prediction.status == "failed": + raise ModelError(prediction.error) + + return prediction.output + + +__all__: List = [] diff --git a/replicate/training.py b/replicate/training.py index 51806ab6..dab4724e 100644 --- a/replicate/training.py +++ b/replicate/training.py @@ -1,27 +1,46 @@ import re -from typing import Any, Dict, List, Optional, TypedDict, Union - -from typing_extensions import NotRequired, Unpack, overload +from typing import ( + TYPE_CHECKING, + Any, + Dict, + List, + Optional, + Tuple, + TypedDict, + Union, + overload, +) + +from typing_extensions import NotRequired, Unpack from replicate.exceptions import ReplicateException from replicate.files import upload_file from replicate.json import encode_json +from replicate.model import Model from replicate.pagination import Page from replicate.resource import Namespace, Resource from replicate.version import Version +try: + from pydantic import v1 as pydantic # type: ignore +except ImportError: + pass # type: ignore + +if TYPE_CHECKING: + from replicate.client import Client + class Training(Resource): """ A training made for a model hosted on Replicate. """ - _namespace: "Trainings" + _client: "Client" = pydantic.PrivateAttr() id: str """The unique ID of the training.""" - version: Optional[Version] + version: Union[str, Version] """The version of the model used to create the training.""" destination: Optional[str] @@ -62,15 +81,15 @@ class Training(Resource): def cancel(self) -> None: """Cancel a running training""" - self._client._request("POST", f"/v1/trainings/{self.id}/cancel") # pylint: disable=no-member + self._client.trainings.cancel(self.id) def reload(self) -> None: """ Load the training from the server. """ - obj = self._namespace.get(self.id) # pylint: disable=no-member - for name, value in obj.dict().items(): + updated = self._client.trainings.get(self.id) + for name, value in updated.dict().items(): setattr(self, name, value) @@ -79,19 +98,33 @@ class Trainings(Namespace): Namespace for operations related to trainings. """ - model = Training + def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Training]: # noqa: F821 + """ + List your trainings. - class CreateParams(TypedDict): - """Parameters for creating a prediction.""" + Parameters: + cursor: The cursor to use for pagination. Use the value of `Page.next` or `Page.previous`. + Returns: + Page[Training]: A page of trainings. + Raises: + ValueError: If `cursor` is `None`. + """ - version: Union[Version, str] - destination: str - input: Dict[str, Any] - webhook: NotRequired[str] - webhook_completed: NotRequired[str] - webhook_events_filter: NotRequired[List[str]] + if cursor is None: + raise ValueError("cursor cannot be None") - def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Training]: # noqa: F821 + resp = self._client._request( + "GET", "/v1/trainings" if cursor is ... else cursor + ) + + obj = resp.json() + obj["results"] = [ + _json_to_training(self._client, result) for result in obj["results"] + ] + + return Page[Training](**obj) + + async def async_list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Training]: # noqa: F821 """ List your trainings. @@ -106,12 +139,18 @@ def list(self, cursor: Union[str, "ellipsis"] = ...) -> Page[Training]: # noqa: if cursor is None: raise ValueError("cursor cannot be None") - resp = self._client._request( + resp = await self._client._async_request( "GET", "/v1/trainings" if cursor is ... else cursor ) - return Page[Training](self._client, self, **resp.json()) - def get(self, id: str) -> Training: # pylint: disable=invalid-name + obj = resp.json() + obj["results"] = [ + _json_to_training(self._client, result) for result in obj["results"] + ] + + return Page[Training](**obj) + + def get(self, id: str) -> Training: """ Get a training by ID. @@ -125,41 +164,105 @@ def get(self, id: str) -> Training: # pylint: disable=invalid-name "GET", f"/v1/trainings/{id}", ) - obj = resp.json() - # HACK: resolve this? make it lazy somehow? - del obj["version"] - return self._prepare_model(obj) + + return _json_to_training(self._client, resp.json()) + + async def async_get(self, id: str) -> Training: + """ + Get a training by ID. + + Args: + id: The ID of the training. + Returns: + Training: The training object. + """ + + resp = await self._client._async_request( + "GET", + f"/v1/trainings/{id}", + ) + + return _json_to_training(self._client, resp.json()) + + class CreateTrainingParams(TypedDict): + """Parameters for creating a training.""" + + destination: Union[str, Tuple[str, str], "Model"] + webhook: NotRequired[str] + webhook_completed: NotRequired[str] + webhook_events_filter: NotRequired[List[str]] @overload - def create( # pylint: disable=arguments-differ disable=too-many-arguments + def create( # pylint: disable=too-many-arguments self, - version: Union[Version, str], + version: str, input: Dict[str, Any], destination: str, - *, webhook: Optional[str] = None, - webhook_completed: Optional[str] = None, webhook_events_filter: Optional[List[str]] = None, + **kwargs, ) -> Training: ... @overload - def create( # pylint: disable=arguments-differ disable=too-many-arguments + def create( self, - *, - version: Union[Version, str], - input: Dict[str, Any], - destination: str, - webhook: Optional[str] = None, - webhook_completed: Optional[str] = None, - webhook_events_filter: Optional[List[str]] = None, + model: Union[str, Tuple[str, str], "Model"], + version: Union[str, Version], + input: Optional[Dict[str, Any]] = None, + **params: Unpack["Trainings.CreateTrainingParams"], ) -> Training: ... - def create( + def create( # type: ignore self, *args, - **kwargs: Unpack[CreateParams], # type: ignore[misc] + model: Optional[Union[str, Tuple[str, str], "Model"]] = None, + version: Optional[Union[str, Version]] = None, + input: Optional[Dict[str, Any]] = None, + **params: Unpack["Trainings.CreateTrainingParams"], + ) -> Training: + """ + Create a new training using the specified model version as a base. + """ + + # Support positional arguments for backwards compatibility + if args: + if shorthand := args[0] if len(args) > 0 else None: + url = _create_training_url_from_shorthand(shorthand) + + input = args[1] if len(args) > 1 else input + if len(args) > 2: + params["destination"] = args[2] + if len(args) > 3: + params["webhook"] = args[3] + if len(args) > 4: + params["webhook_completed"] = args[4] + if len(args) > 5: + params["webhook_events_filter"] = args[5] + + elif model and version: + url = _create_training_url_from_model_and_version(model, version) + elif model is None and isinstance(version, str): + url = _create_training_url_from_shorthand(version) + else: + raise ValueError("model and version or shorthand version must be specified") + + body = _create_training_body(input, **params) + resp = self._client._request( + "POST", + url, + json=body, + ) + + return _json_to_training(self._client, resp.json()) + + async def async_create( + self, + model: Union[str, Tuple[str, str], "Model"], + version: Union[str, Version], + input: Dict[str, Any], + **params: Unpack["Trainings.CreateTrainingParams"], ) -> Training: """ Create a new training using the specified model version as a base. @@ -175,53 +278,119 @@ def create( The training object. """ - # Support positional arguments for backwards compatibility - version = args[0] if args else kwargs.get("version") - if version is None: - raise ValueError( - "A version identifier must be provided as a positional or keyword argument." - ) - - destination = args[1] if len(args) > 1 else kwargs.get("destination") - if destination is None: - raise ValueError( - "A destination must be provided as a positional or keyword argument." - ) - - input = args[2] if len(args) > 2 else kwargs.get("input") - if input is None: - raise ValueError( - "An input must be provided as a positional or keyword argument." - ) - - body = { - "input": encode_json(input, upload_file=upload_file), - "destination": destination, - } - - for key in ["webhook", "webhook_completed", "webhook_events_filter"]: - value = kwargs.get(key) - if value is not None: - body[key] = value - - # Split version in format "username/model_name:version_id" - match = re.match( - r"^(?P[^/]+)/(?P[^:]+):(?P.+)$", - version.id if isinstance(version, Version) else version, + url = _create_training_url_from_model_and_version(model, version) + body = _create_training_body(input, **params) + resp = await self._client._async_request( + "POST", + url, + json=body, ) - if not match: - raise ReplicateException( - "version must be in format username/model_name:version_id" - ) - username = match.group("username") - model_name = match.group("model_name") - version_id = match.group("version_id") + + return _json_to_training(self._client, resp.json()) + + def cancel(self, id: str) -> Training: + """ + Cancel a training. + + Args: + id: The ID of the training to cancel. + Returns: + Training: The canceled training object. + """ resp = self._client._request( "POST", - f"/v1/models/{username}/{model_name}/versions/{version_id}/trainings", - json=body, + f"/v1/trainings/{id}/cancel", ) - obj = resp.json() - del obj["version"] - return self._prepare_model(obj) + + return _json_to_training(self._client, resp.json()) + + async def async_cancel(self, id: str) -> Training: + """ + Cancel a training. + + Args: + id: The ID of the training to cancel. + Returns: + Training: The canceled training object. + """ + + resp = await self._client._async_request( + "POST", + f"/v1/trainings/{id}/cancel", + ) + + return _json_to_training(self._client, resp.json()) + + +def _create_training_body( + input: Optional[Dict[str, Any]] = None, + *, + destination: Optional[Union[str, Tuple[str, str], "Model"]] = None, + webhook: Optional[str] = None, + webhook_completed: Optional[str] = None, + webhook_events_filter: Optional[List[str]] = None, +) -> Dict[str, Any]: + body = {} + + if input is not None: + body["input"] = encode_json(input, upload_file=upload_file) + + if destination is None: + raise ValueError( + "A destination must be provided as a positional or keyword argument." + ) + if isinstance(destination, Model): + destination = f"{destination.owner}/{destination.name}" + elif isinstance(destination, tuple): + destination = f"{destination[0]}/{destination[1]}" + body["destination"] = destination + + if webhook is not None: + body["webhook"] = webhook + + if webhook_completed is not None: + body["webhook_completed"] = webhook_completed + + if webhook_events_filter is not None: + body["webhook_events_filter"] = webhook_events_filter + + return body + + +def _create_training_url_from_shorthand(identifier: str) -> str: + # Split version in format "owner/model:version" + match = re.match( + r"^(?P[^/]+)/(?P[^:]+):(?P.+)$", identifier + ) + if not match: + raise ReplicateException("version must be in format owner/model:version") + + model_owner = match.group("model_owner") + model_name = match.group("model_name") + version_id = match.group("version_id") + + return f"/v1/models/{model_owner}/{model_name}/versions/{version_id}/trainings" + + +def _create_training_url_from_model_and_version( + model: Union[str, Tuple[str, str], "Model"], + version: Union[str, Version], +) -> str: + if isinstance(model, Model): + model_owner, model_name = model.owner, model.name + elif isinstance(model, tuple): + model_owner, model_name = model[0], model[1] + + if isinstance(version, Version): + version_id = version.id + else: + version_id = version + + return f"/v1/models/{model_owner}/{model_name}/versions/{version_id}/trainings" + + +def _json_to_training(client: "Client", json: Dict[str, Any]) -> Training: + training = Training(**json) + training._client = client + return training diff --git a/replicate/version.py b/replicate/version.py index 0496a6a4..0f4a5de2 100644 --- a/replicate/version.py +++ b/replicate/version.py @@ -1,15 +1,12 @@ import datetime -import warnings -from typing import TYPE_CHECKING, Any, Iterator, List, Union +from typing import TYPE_CHECKING, Any, Dict, Tuple, Union if TYPE_CHECKING: from replicate.client import Client from replicate.model import Model - -from replicate.exceptions import ModelError +from replicate.pagination import Page from replicate.resource import Namespace, Resource -from replicate.schema import make_schema_backwards_compatible class Version(Resource): @@ -17,8 +14,6 @@ class Version(Resource): A version of a model. """ - _namespace: "Versions" - id: str """The unique ID of the version.""" @@ -31,61 +26,30 @@ class Version(Resource): openapi_schema: dict """An OpenAPI description of the model inputs and outputs.""" - def predict(self, **kwargs) -> Union[Any, Iterator[Any]]: # noqa: ANN401 - """ - DEPRECATED: Use `replicate.run()` instead. - - Create a prediction using this model version. - - Args: - kwargs: The input to the model. - Returns: - The output of the model. - """ - - warnings.warn( - "version.predict() is deprecated. Use replicate.run() instead. It will be removed before version 1.0.", - DeprecationWarning, - stacklevel=1, - ) - - prediction = self._client.predictions.create(version=self, input=kwargs) # pylint: disable=no-member - # Return an iterator of the output - schema = make_schema_backwards_compatible(self.openapi_schema, self.cog_version) - output = schema["components"]["schemas"]["Output"] - if ( - output.get("type") == "array" - and output.get("x-cog-array-type") == "iterator" - ): - return prediction.output_iterator() - - prediction.wait() - if prediction.status == "failed": - raise ModelError(prediction.error) - return prediction.output - - def reload(self) -> None: - """ - Load this object from the server. - """ - - obj = self._namespace.get(self.id) # pylint: disable=no-member - for name, value in obj.dict().items(): - setattr(self, name, value) - class Versions(Namespace): """ Namespace for operations related to model versions. """ - model = Version + model: Tuple[str, str] - def __init__(self, client: "Client", model: "Model") -> None: + def __init__( + self, client: "Client", model: Union["Model", str, Tuple[str, str]] + ) -> None: super().__init__(client=client) - self._model = model - def get(self, id: str) -> Version: # pylint: disable=invalid-name + from replicate.model import Model # pylint: disable=import-outside-toplevel + + if isinstance(model, Model): + self.model = (model.owner, model.name) + elif isinstance(model, str): + owner, name = model.split("/", 1) + self.model = (owner, name) + else: + self.model = model + + def get(self, id: str) -> Version: """ Get a specific model version. @@ -94,19 +58,61 @@ def get(self, id: str) -> Version: # pylint: disable=invalid-name Returns: The model version. """ + resp = self._client._request( - "GET", f"/v1/models/{self._model.owner}/{self._model.name}/versions/{id}" + "GET", f"/v1/models/{self.model[0]}/{self.model[1]}/versions/{id}" ) - return self._prepare_model(resp.json()) - def list(self) -> List[Version]: + return _json_to_version(resp.json()) + + async def async_get(self, id: str) -> Version: + """ + Get a specific model version. + + Args: + id: The version ID. + Returns: + The model version. + """ + + resp = await self._client._async_request( + "GET", f"/v1/models/{self.model[0]}/{self.model[1]}/versions/{id}" + ) + + return _json_to_version(resp.json()) + + def list(self) -> Page[Version]: """ Return a list of all versions for a model. Returns: List[Version]: A list of version objects. """ + resp = self._client._request( - "GET", f"/v1/models/{self._model.owner}/{self._model.name}/versions" + "GET", f"/v1/models/{self.model[0]}/{self.model[1]}/versions" + ) + obj = resp.json() + obj["results"] = [_json_to_version(result) for result in obj["results"]] + + return Page[Version](**obj) + + async def async_list(self) -> Page[Version]: + """ + Return a list of all versions for a model. + + Returns: + List[Version]: A list of version objects. + """ + + resp = await self._client._async_request( + "GET", f"/v1/models/{self.model[0]}/{self.model[1]}/versions" ) - return [self._prepare_model(obj) for obj in resp.json()["results"]] + obj = resp.json() + obj["results"] = [_json_to_version(result) for result in obj["results"]] + + return Page[Version](**obj) + + +def _json_to_version(json: Dict[str, Any]) -> Version: + return Version(**json) diff --git a/tests/cassettes/run-concurrently.yaml b/tests/cassettes/run-concurrently.yaml new file mode 100644 index 00000000..8fc87b89 --- /dev/null +++ b/tests/cassettes/run-concurrently.yaml @@ -0,0 +1,8353 @@ +interactions: +- request: + body: '{"input": {"prompt": "A chariot pulled by a team of two rainbow unicorns"}, + "version": "39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b"}' + headers: + accept: + - '*/*' + accept-encoding: + - gzip, deflate + connection: + - keep-alive + content-length: + - '154' + content-type: + - application/json + host: + - api.replicate.com + user-agent: + - replicate-python/0.15.6 + method: POST + uri: https://api.replicate.com/v1/predictions + response: + content: '{"id":"ppn6sy3bpvltiyk3hsquxuvmee","version":"39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b","input":{"prompt":"A + chariot pulled by a team of two rainbow unicorns"},"logs":"","error":null,"status":"starting","created_at":"2023-11-08T22:22:15.305024023Z","urls":{"cancel":"https://api.replicate.com/v1/predictions/ppn6sy3bpvltiyk3hsquxuvmee/cancel","get":"https://api.replicate.com/v1/predictions/ppn6sy3bpvltiyk3hsquxuvmee"}} + + ' + headers: + CF-Cache-Status: + - DYNAMIC + CF-RAY: + - 823136b11854c6c5-SEA + Connection: + - keep-alive + Content-Length: + - '445' + Content-Type: + - application/json + Date: + - Wed, 08 Nov 2023 22:22:15 GMT + NEL: + - '{"success_fraction":0,"report_to":"cf-nel","max_age":604800}' + Report-To: + - '{"endpoints":[{"url":"https:\/\/a.nel.cloudflare.com\/report\/v3?s=VjEoQdik3RT6c10%2FbDVqrZUOFke1PedlfT0tIL40WSKNXbcT8qNCCdOcNGbuQxgEDRVcJ5nJolE7mhRGtCPo3R2EnlBbmln1WbfFuT8cmu6NJ5cxEUnNTzMwLgtks3uZDPdG"}],"group":"cf-nel","max_age":604800}' + Server: + - cloudflare + Strict-Transport-Security: + - max-age=15552000 + ratelimit-remaining: + - '599' + ratelimit-reset: + - '1' + via: + - 1.1 google + http_version: HTTP/1.1 + status_code: 201 +- request: + body: '' + headers: + accept: + - '*/*' + accept-encoding: + - gzip, deflate + connection: + - keep-alive + host: + - api.replicate.com + user-agent: + - replicate-python/0.15.6 + method: GET + uri: https://api.replicate.com/v1/models/stability-ai/sdxl/versions/39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b + response: + content: '{"id":"39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b","created_at":"2023-11-06T23:13:07.906314Z","cog_version":"0.8.6","openapi_schema":{"info":{"title":"Cog","version":"0.1.0"},"paths":{"/":{"get":{"summary":"Root","responses":{"200":{"content":{"application/json":{"schema":{"title":"Response + Root Get"}}},"description":"Successful Response"}},"operationId":"root__get"}},"/shutdown":{"post":{"summary":"Start + Shutdown","responses":{"200":{"content":{"application/json":{"schema":{"title":"Response + Start Shutdown Shutdown Post"}}},"description":"Successful Response"}},"operationId":"start_shutdown_shutdown_post"}},"/predictions":{"post":{"summary":"Predict","responses":{"200":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/PredictionResponse"}}},"description":"Successful + Response"},"422":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}},"description":"Validation + Error"}},"parameters":[{"in":"header","name":"prefer","schema":{"type":"string","title":"Prefer"},"required":false}],"description":"Run + a single prediction on the model","operationId":"predict_predictions_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/PredictionRequest"}}}}}},"/health-check":{"get":{"summary":"Healthcheck","responses":{"200":{"content":{"application/json":{"schema":{"title":"Response + Healthcheck Health Check Get"}}},"description":"Successful Response"}},"operationId":"healthcheck_health_check_get"}},"/predictions/{prediction_id}":{"put":{"summary":"Predict + Idempotent","responses":{"200":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/PredictionResponse"}}},"description":"Successful + Response"},"422":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}},"description":"Validation + Error"}},"parameters":[{"in":"path","name":"prediction_id","schema":{"type":"string","title":"Prediction + ID"},"required":true},{"in":"header","name":"prefer","schema":{"type":"string","title":"Prefer"},"required":false}],"description":"Run + a single prediction on the model (idempotent creation).","operationId":"predict_idempotent_predictions__prediction_id__put","requestBody":{"content":{"application/json":{"schema":{"allOf":[{"$ref":"#/components/schemas/PredictionRequest"}],"title":"Prediction + Request"}}},"required":true}}},"/predictions/{prediction_id}/cancel":{"post":{"summary":"Cancel","responses":{"200":{"content":{"application/json":{"schema":{"title":"Response + Cancel Predictions Prediction Id Cancel Post"}}},"description":"Successful + Response"},"422":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}},"description":"Validation + Error"}},"parameters":[{"in":"path","name":"prediction_id","schema":{"type":"string","title":"Prediction + ID"},"required":true}],"description":"Cancel a running prediction","operationId":"cancel_predictions__prediction_id__cancel_post"}}},"openapi":"3.0.2","components":{"schemas":{"Input":{"type":"object","title":"Input","properties":{"mask":{"type":"string","title":"Mask","format":"uri","x-order":3,"description":"Input + mask for inpaint mode. Black areas will be preserved, white areas will be inpainted."},"seed":{"type":"integer","title":"Seed","x-order":11,"description":"Random + seed. Leave blank to randomize the seed"},"image":{"type":"string","title":"Image","format":"uri","x-order":2,"description":"Input + image for img2img or inpaint mode"},"width":{"type":"integer","title":"Width","default":1024,"x-order":4,"description":"Width + of output image"},"height":{"type":"integer","title":"Height","default":1024,"x-order":5,"description":"Height + of output image"},"prompt":{"type":"string","title":"Prompt","default":"An astronaut + riding a rainbow unicorn","x-order":0,"description":"Input prompt"},"refine":{"allOf":[{"$ref":"#/components/schemas/refine"}],"default":"no_refiner","x-order":12,"description":"Which + refine style to use"},"scheduler":{"allOf":[{"$ref":"#/components/schemas/scheduler"}],"default":"K_EULER","x-order":7,"description":"scheduler"},"lora_scale":{"type":"number","title":"Lora + Scale","default":0.6,"maximum":1,"minimum":0,"x-order":16,"description":"LoRA + additive scale. 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If you + have other provisions for generating or deploying images safely, you can use + this to disable watermarking."},"high_noise_frac":{"type":"number","title":"High + Noise Frac","default":0.8,"maximum":1,"minimum":0,"x-order":13,"description":"For + expert_ensemble_refiner, the fraction of noise to use"},"negative_prompt":{"type":"string","title":"Negative + Prompt","default":"","x-order":1,"description":"Input Negative Prompt"},"prompt_strength":{"type":"number","title":"Prompt + Strength","default":0.8,"maximum":1,"minimum":0,"x-order":10,"description":"Prompt + strength when using img2img / inpaint. 1.0 corresponds to full destruction of + information in image"},"replicate_weights":{"type":"string","title":"Replicate + Weights","x-order":17,"description":"Replicate LoRA weights to use. Leave blank + to use the default weights."},"num_inference_steps":{"type":"integer","title":"Num + Inference Steps","default":50,"maximum":500,"minimum":1,"x-order":8,"description":"Number + of denoising steps"},"disable_safety_checker":{"type":"boolean","title":"Disable + Safety Checker","default":false,"x-order":18,"description":"Disable safety checker + for generated images. This feature is only available through the API. 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Content-Encoding: + - gzip + Content-Type: + - application/json + Date: + - Wed, 08 Nov 2023 22:23:22 GMT + NEL: + - '{"success_fraction":0,"report_to":"cf-nel","max_age":604800}' + Report-To: + - '{"endpoints":[{"url":"https:\/\/a.nel.cloudflare.com\/report\/v3?s=wMOScwNRMuRtutjxy%2B6dDiIGpNlRcPzd1HRC%2FHONsWciYitzJt5CvCqbfrQiQG%2BZIekfX%2Bb2GLa0EBYztvSyCRCEeufwM4B1DGlrM7mmjTVFOwTkJ%2BQq5lSjdOccyOXOWE7K"}],"group":"cf-nel","max_age":604800}' + Server: + - cloudflare + Strict-Transport-Security: + - max-age=15552000 + Transfer-Encoding: + - chunked + ratelimit-remaining: + - '59999' + ratelimit-reset: + - '1' + via: + - 1.1 google + http_version: HTTP/1.1 + status_code: 200 +version: 1 diff --git a/tests/test_client.py b/tests/test_client.py index 42cf28da..95636771 100644 --- a/tests/test_client.py +++ b/tests/test_client.py @@ -3,18 +3,31 @@ import httpx import pytest +import respx @pytest.mark.asyncio async def test_authorization_when_setting_environ_after_import(): import replicate + router = respx.Router() + router.route( + method="GET", + url="https://api.replicate.com/", + headers={"Authorization": "Token test-set-after-import"}, + ).mock( + return_value=httpx.Response( + 200, + json={}, + ) + ) + token = "test-set-after-import" # noqa: S105 with mock.patch.dict( os.environ, {"REPLICATE_API_TOKEN": token}, ): - client: httpx.Client = replicate.default_client._client - assert "Authorization" in client.headers - assert client.headers["Authorization"] == f"Token {token}" + client = replicate.Client(transport=httpx.MockTransport(router.handler)) + resp = client._request("GET", "/") + assert resp.status_code == 200 diff --git a/tests/test_collection.py b/tests/test_collection.py index 1e178df1..9a6c0609 100644 --- a/tests/test_collection.py +++ b/tests/test_collection.py @@ -5,14 +5,18 @@ @pytest.mark.vcr("collections-list.yaml") @pytest.mark.asyncio -async def test_collections_list(): - page = replicate.collections.list() +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_models_get(async_flag): + if async_flag: + page = await replicate.collections.async_list() + else: + page = replicate.collections.list() assert page.next is None assert page.previous is None found = False - for collection in page: + for collection in page.results: if collection.slug == "text-to-image": found = True break @@ -22,8 +26,12 @@ async def test_collections_list(): @pytest.mark.vcr("collections-get.yaml") @pytest.mark.asyncio -async def test_collections_get(): - collection = replicate.collections.get("text-to-image") +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_collections_get(async_flag): + if async_flag: + collection = await replicate.collections.async_get("text-to-image") + else: + collection = replicate.collections.get("text-to-image") assert collection.slug == "text-to-image" assert collection.name == "Text to image" @@ -31,7 +39,7 @@ async def test_collections_get(): assert len(collection.models) > 0 found = False - for model in collection: + for model in collection.models: if model.name == "stable-diffusion": found = True break diff --git a/tests/test_deployment.py b/tests/test_deployment.py index 1b37444a..b8ee42f0 100644 --- a/tests/test_deployment.py +++ b/tests/test_deployment.py @@ -1,4 +1,5 @@ import httpx +import pytest import respx from replicate.client import Client @@ -31,17 +32,29 @@ router.route(host="api.replicate.com").pass_through() -def test_deployment_predictions_create(): +@pytest.mark.asyncio +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_deployment_predictions_create(async_flag): client = Client( api_token="test-token", transport=httpx.MockTransport(router.handler) ) - deployment = client.deployments.get("test/model") - prediction = deployment.predictions.create( - input={"text": "world"}, - webhook="https://example.com/webhook", - webhook_events_filter=["completed"], - ) + if async_flag: + deployment = await client.deployments.async_get("test/model") + + prediction = await deployment.predictions.async_create( + input={"text": "world"}, + webhook="https://example.com/webhook", + webhook_events_filter=["completed"], + ) + else: + deployment = client.deployments.get("test/model") + + prediction = deployment.predictions.create( + input={"text": "world"}, + webhook="https://example.com/webhook", + webhook_events_filter=["completed"], + ) assert router["deployments.predictions.create"].called assert prediction.id == "p1" diff --git a/tests/test_hardware.py b/tests/test_hardware.py index 15da0e79..0522c775 100644 --- a/tests/test_hardware.py +++ b/tests/test_hardware.py @@ -5,8 +5,12 @@ @pytest.mark.vcr("hardware-list.yaml") @pytest.mark.asyncio -async def test_hardware_list(mock_replicate_api_token): - hardware = replicate.hardware.list() +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_hardware_list(async_flag): + if async_flag: + hardware = await replicate.hardware.async_list() + else: + hardware = replicate.hardware.list() assert hardware is not None assert isinstance(hardware, list) diff --git a/tests/test_model.py b/tests/test_model.py index 62ae7e23..383e69ef 100644 --- a/tests/test_model.py +++ b/tests/test_model.py @@ -5,23 +5,34 @@ @pytest.mark.vcr("models-get.yaml") @pytest.mark.asyncio -async def test_models_get(mock_replicate_api_token): - sdxl = replicate.models.get("stability-ai/sdxl") +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_models_get(async_flag): + if async_flag: + sdxl = await replicate.models.async_get("stability-ai/sdxl") + else: + sdxl = replicate.models.get("stability-ai/sdxl") assert sdxl is not None assert sdxl.owner == "stability-ai" assert sdxl.name == "sdxl" assert sdxl.visibility == "public" - empty = replicate.models.get("mattt/empty") + if async_flag: + empty = await replicate.models.async_get("mattt/empty") + else: + empty = replicate.models.get("mattt/empty") assert empty.default_example is None @pytest.mark.vcr("models-list.yaml") @pytest.mark.asyncio -async def test_models_list(mock_replicate_api_token): - models = replicate.models.list() +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_models_list(async_flag): + if async_flag: + models = await replicate.models.async_list() + else: + models = replicate.models.list() assert len(models) > 0 assert models[0].owner is not None @@ -31,26 +42,43 @@ async def test_models_list(mock_replicate_api_token): @pytest.mark.vcr("models-list.yaml") @pytest.mark.asyncio -async def test_models_list_pagination(mock_replicate_api_token): - page1 = replicate.models.list() +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_models_list_pagination(async_flag): + if async_flag: + page1 = await replicate.models.async_list() + else: + page1 = replicate.models.list() assert len(page1) > 0 assert page1.next is not None - page2 = replicate.models.list(cursor=page1.next) + if async_flag: + page2 = await replicate.models.async_list(cursor=page1.next) + else: + page2 = replicate.models.list(cursor=page1.next) assert len(page2) > 0 assert page2.previous is not None @pytest.mark.vcr("models-create.yaml") @pytest.mark.asyncio -async def test_models_create(mock_replicate_api_token): - model = replicate.models.create( - owner="test", - name="python-example", - visibility="private", - hardware="cpu", - description="An example model", - ) +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_models_create(async_flag): + if async_flag: + model = await replicate.models.async_create( + owner="test", + name="python-example", + visibility="private", + hardware="cpu", + description="An example model", + ) + else: + model = replicate.models.create( + owner="test", + name="python-example", + visibility="private", + hardware="cpu", + description="An example model", + ) assert model.owner == "test" assert model.name == "python-example" @@ -59,13 +87,22 @@ async def test_models_create(mock_replicate_api_token): @pytest.mark.vcr("models-create.yaml") @pytest.mark.asyncio -async def test_models_create_with_positional_arguments(mock_replicate_api_token): - model = replicate.models.create( - "test", - "python-example", - visibility="private", - hardware="cpu", - ) +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_models_create_with_positional_arguments(async_flag): + if async_flag: + model = await replicate.models.async_create( + "test", + "python-example", + visibility="private", + hardware="cpu", + ) + else: + model = replicate.models.create( + "test", + "python-example", + visibility="private", + hardware="cpu", + ) assert model.owner == "test" assert model.name == "python-example" diff --git a/tests/test_prediction.py b/tests/test_prediction.py index c8012d45..b50259cb 100644 --- a/tests/test_prediction.py +++ b/tests/test_prediction.py @@ -5,7 +5,8 @@ @pytest.mark.vcr("predictions-create.yaml") @pytest.mark.asyncio -async def test_predictions_create(mock_replicate_api_token): +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_predictions_create(async_flag): input = { "prompt": "a studio photo of a rainbow colored corgi", "width": 512, @@ -13,14 +14,53 @@ async def test_predictions_create(mock_replicate_api_token): "seed": 42069, } - model = replicate.models.get("stability-ai/sdxl") - version = model.versions.get( - "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" - ) - prediction = replicate.predictions.create( - version=version, - input=input, - ) + if async_flag: + model = await replicate.models.async_get("stability-ai/sdxl") + version = await model.versions.async_get( + "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" + ) + prediction = await replicate.predictions.async_create( + version=version, + input=input, + ) + else: + model = replicate.models.get("stability-ai/sdxl") + version = model.versions.get( + "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" + ) + prediction = replicate.predictions.create( + version=version, + input=input, + ) + + assert prediction.id is not None + assert prediction.version == version.id + assert prediction.status == "starting" + + +@pytest.mark.vcr("predictions-create.yaml") +@pytest.mark.asyncio +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_predictions_create_with_positional_argument(async_flag): + version = "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" + + input = { + "prompt": "a studio photo of a rainbow colored corgi", + "width": 512, + "height": 512, + "seed": 42069, + } + + if async_flag: + prediction = await replicate.predictions.async_create( + version, + input, + ) + else: + prediction = replicate.predictions.create( + version, + input, + ) assert prediction.id is not None assert prediction.version == version @@ -29,17 +69,22 @@ async def test_predictions_create(mock_replicate_api_token): @pytest.mark.vcr("predictions-get.yaml") @pytest.mark.asyncio -async def test_predictions_get(mock_replicate_api_token): +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_predictions_get(async_flag): id = "vgcm4plb7tgzlyznry5d5jkgvu" - prediction = replicate.predictions.get(id) + if async_flag: + prediction = await replicate.predictions.async_get(id) + else: + prediction = replicate.predictions.get(id) assert prediction.id == id @pytest.mark.vcr("predictions-cancel.yaml") @pytest.mark.asyncio -async def test_predictions_cancel(mock_replicate_api_token): +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_predictions_cancel(async_flag): input = { "prompt": "a studio photo of a rainbow colored corgi", "width": 512, @@ -47,14 +92,24 @@ async def test_predictions_cancel(mock_replicate_api_token): "seed": 42069, } - model = replicate.models.get("stability-ai/sdxl") - version = model.versions.get( - "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" - ) - prediction = replicate.predictions.create( - version=version, - input=input, - ) + if async_flag: + model = await replicate.models.async_get("stability-ai/sdxl") + version = await model.versions.async_get( + "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" + ) + prediction = await replicate.predictions.async_create( + version=version, + input=input, + ) + else: + model = replicate.models.get("stability-ai/sdxl") + version = model.versions.get( + "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" + ) + prediction = replicate.predictions.create( + version=version, + input=input, + ) # id = prediction.id assert prediction.status == "starting" @@ -65,23 +120,35 @@ async def test_predictions_cancel(mock_replicate_api_token): @pytest.mark.vcr("predictions-stream.yaml") @pytest.mark.asyncio -async def test_predictions_stream(mock_replicate_api_token): +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_predictions_stream(async_flag): input = { "prompt": "write a sonnet about camelids", } - model = replicate.models.get("meta/llama-2-70b-chat") - version = model.versions.get( - "02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3" - ) - prediction = replicate.predictions.create( - version=version, - input=input, - stream=True, - ) + if async_flag: + model = await replicate.models.async_get("meta/llama-2-70b-chat") + version = await model.versions.async_get( + "02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3" + ) + prediction = await replicate.predictions.async_create( + version=version, + input=input, + stream=True, + ) + else: + model = replicate.models.get("meta/llama-2-70b-chat") + version = model.versions.get( + "02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3" + ) + prediction = replicate.predictions.create( + version=version, + input=input, + stream=True, + ) assert prediction.id is not None - assert prediction.version == version + assert prediction.version == version.id assert prediction.status == "starting" assert prediction.urls["stream"] is not None diff --git a/tests/test_run.py b/tests/test_run.py index ecb712f2..b458f853 100644 --- a/tests/test_run.py +++ b/tests/test_run.py @@ -1,3 +1,6 @@ +import asyncio +import sys + import httpx import pytest import respx @@ -9,8 +12,10 @@ @pytest.mark.vcr("run.yaml") @pytest.mark.asyncio -async def test_run(mock_replicate_api_token): - replicate.default_client.poll_interval = 0.001 +@pytest.mark.parametrize("async_flag", [True, False]) +async def test_run(async_flag, record_mode): + if record_mode == "none": + replicate.default_client.poll_interval = 0.001 version = "a00d0b7dcbb9c3fbb34ba87d2d5b46c56969c84a628bf778a7fdaec30b1b99c5" @@ -21,10 +26,16 @@ async def test_run(mock_replicate_api_token): "seed": 42069, } - output = replicate.run( - f"stability-ai/sdxl:{version}", - input=input, - ) + if async_flag: + output = await replicate.async_run( + f"stability-ai/sdxl:{version}", + input=input, + ) + else: + output = replicate.run( + f"stability-ai/sdxl:{version}", + input=input, + ) assert output is not None assert isinstance(output, list) @@ -32,6 +43,35 @@ async def test_run(mock_replicate_api_token): assert output[0].startswith("https://") +@pytest.mark.vcr("run-concurrently.yaml") +@pytest.mark.asyncio +@pytest.mark.skipif( + sys.version_info < (3, 11), reason="asyncio.TaskGroup requires Python 3.11" +) +async def test_run_concurrently(mock_replicate_api_token, record_mode): + if record_mode == "none": + replicate.default_client.poll_interval = 0.001 + + # https://replicate.com/stability-ai/sdxl + model_version = "stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b" + + prompts = [ + f"A chariot pulled by a team of {count} rainbow unicorns" + for count in ["two", "four", "six", "eight"] + ] + + async with asyncio.TaskGroup() as tg: + tasks = [ + tg.create_task(replicate.async_run(model_version, input={"prompt": prompt})) + for prompt in prompts + ] + + results = await asyncio.gather(*tasks) + assert len(results) == len(prompts) + assert all(isinstance(result, list) for result in results) + assert all(len(result) > 0 for result in results) + + @pytest.mark.vcr("run.yaml") @pytest.mark.asyncio async def test_run_with_invalid_identifier(mock_replicate_api_token): @@ -133,6 +173,7 @@ def prediction_with_status(status: str) -> dict: client = Client( api_token="test-token", transport=httpx.MockTransport(router.handler) ) + client.poll_interval = 0.001 output = client.run( "test/example:invalid",