Skip to main content

API Reference

Clarifai Python SDK API Reference

This is the API Reference documentation extracted from the source code.

User​

 class User(user_id='', **kwargs)

User is a class that provides access to Clarifai API endpoints related to user information.

User.__init__()​

__init__(user_id='', **kwargs)

Initializes a User object.

Parameters​

  • user_id (str) – The user ID for the user to interact with.
  • **kwargs – Additional keyword arguments to be passed to the ClarifaiAuthHelper.

User.app()​

app(app_id, **kwargs)

Returns an App object for the specified app ID.

Parameters​

  • app_id (str) – The app ID for the app to interact with.
  • **kwargs – Additional keyword arguments to be passed to the App.

Returns​

An App object for the specified app ID.

Return type​

App

Example​

from clarifai.client.user import User
app = User("user_id").app("app_id")

User.create_app()​

create_app(app_id, base_workflow='Language-Understanding', **kwargs)

Creates an app for the user.

Parameters​

  • app_id (str) – The app ID for the app to create.
  • base_workflow (str) – The base workflow to use for the app.(Examples: ‘Universal’, ‘Empty’, ‘General’)
  • **kwargs – Additional keyword arguments to be passed to the App.

Returns​

An App object for the specified app ID.

Return type​

App

Example​

from clarifai.client.user import User
client = User(user_id="user_id")
app = client.create_app(app_id="app_id",base_workflow="Universal")

User.create_runner()​

create_runner(runner_id, labels=List[str], description='')

Creates a runner

Parameters​

  • runner_id (str) – The Id of runner to create.
  • labels (List[str]) – Labels to match runner.
  • description (str) – Description of Runner.

Returns​

A runner object for the specified Runner ID.

Return type​

Runner

Example​

from clarifai.client.user import User
client = User(user_id="user_id")
runner = client.create_runner(runner_id="runner_id", labels=["label to link runner"], description="laptop runner")

User.delete_app()​

delete_app(app_id)

Deletes an app for the user.

Parameters​

  • app_id (str) – The app ID for the app to delete.

Return type​

None

Example​

from clarifai.client.user import User
user = User("user_id").delete_app("app_id")

User.delete_runner()​

delete_runner(runner_id)

Deletes all specified runner ids.

Parameters​

  • runner_ids (str) – List of runners to delete.

Example​

from clarifai.client.user import User
client = User(user_id="user_id")
client.delete_runner(runner_id="runner_id")

User.list_apps()​

list_apps(filter_by={})

Lists all the apps for the user.

Parameters​

  • filter_by (dict) – A dictionary of filters to be applied to the list of apps.

Returns​

A list of App objects for the user.

Return type​

List of App

Example​

from clarifai.client.user import User
apps = User("user_id").list_apps()

User.list_runners()​

list_runners(filter_by={})

List all runners for the user.

Parameters​

  • filter_by (dict) – A dictionary of filters to apply to the list of runners.

Returns​

A list of Runner objects for the runners.

Return type​

List[Runner]

Example​

from clarifai.client.user import User
client = User(user_id="user_id")
all_runners= client.list_runners()

User.runner()​

runner(runner_id)

Returns a Runner object if exists.

Parameters​

  • runner_id (str) – The runner ID to interact with.

Returns​

A Runner object for the existing runner ID.

Return type​

Runner

Example​

from clarifai.client.user import User
client = User(user_id="user_id")
runner = client.runner(runner_id="runner_id")

App​

class App(url_init='', app_id='', **kwargs)

App is a class that provides access to Clarifai API endpoints related to App information.

App.__init__()​

__init__(url_init='', app_id='', **kwargs)

Initializes an App object.

Parameters​

  • url_init (str) – The URL to initialize the app object.
  • app_id (str) – The App ID for the App to interact with.
  • **kwargs – Additional keyword arguments to be passed to the ClarifaiAuthHelper:
    • name (str): The name of the app.
    • description (str): The description of the app.

App.create_dataset()​

create_dataset(dataset_id, **kwargs)

Creates a dataset for the app.

Parameters​

  • dataset_id (str) – The dataset ID for the dataset to create.
  • **kwargs – Additional keyword arguments to be passed to the Dataset.

Returns​

A Dataset object for the specified dataset ID.

Return type​

Dataset

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
dataset = app.create_dataset(dataset_id="dataset_id")

App.create_model()​

create_model(model_id, \*\*kwargs)

Creates a model for the app.

Parameters​

  • model_id (str) – The model ID for the model to create.
  • **kwargs – Additional keyword arguments to be passed to the Model.

Returns​

A Model object for the specified model ID.

Return type​

Model

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
model = app.create_model(model_id="model_id")

App.create_module()​

create_module(module_id, description, **kwargs)

Creates a module for the app.

Parameters​

  • module_id (str) – The module ID for the module to create.
  • description (str) – The description of the module to create.
  • **kwargs – Additional keyword arguments to be passed to the module.

Returns​

A Module object for the specified module ID.

Return type​

Module

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
module = app.create_module(module_id="module_id")

App.create_workflow()​

create_workflow(workflow_id, **kwargs)

Creates a workflow for the app.

Parameters​

  • workflow_id (str) – The workflow ID for the workflow to create.
  • **kwargs – Additional keyword arguments to be passed to the workflow.

Returns​

A Workflow object for the specified workflow ID.

Return type​

Workflow

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
workflow = app.create_workflow(workflow_id="workflow_id")

App.dataset()​

dataset(dataset_id, **kwargs)

Returns a Dataset object for the existing dataset ID.

Parameters​

  • dataset_id (str) – The dataset ID for the dataset to interact with.

Returns​

A Dataset object for the existing dataset ID.

Return type​

Dataset

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
dataset = app.dataset(dataset_id="dataset_id")

App.delete_dataset()​

delete_dataset(dataset_id)

Deletes a dataset for the user.

Parameters​

  • dataset_id (str) – The dataset ID for the app to delete.

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
app.delete_dataset(dataset_id="dataset_id")

App.delete_model()​

delete_model(model_id)

Deletes a model for the user.

Parameters​

  • model_id (str) – The model ID for the app to delete.

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
app.delete_model(model_id="model_id")

App.delete_module()​

delete_module(module_id)

Deletes a module for the user.

Parameters​

  • module_id (str) – The module ID for the app to delete.

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
app.delete_module(module_id="module_id")

App.delete_workflow()​

delete_workflow(workflow_id)

Deletes a workflow for the user.

Parameters​

  • workflow_id (str) – The workflow ID for the app to delete.

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
app.delete_workflow(workflow_id="workflow_id")

App.inputs()​

inputs()

Returns an Input object.

Returns​

An input object.

Return type​

Inputs

App.list_concepts()​

list_concepts()

Lists all the concepts for the app.

App.list_datasets()​

list_datasets()

Lists all the datasets for the app.

Returns​

A list of Dataset objects for the datasets in the app.

Return type​

List[Dataset]

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
all_datasets = app.list_datasets()

App.list_installed_module_versions()​

list_installed_module_versions(filter_by={})

Lists all installed module versions in the app.

Parameters​

filter_by (dict) – A dictionary of filters to apply to the list of installed module versions.

Returns​

A list of Module objects for the installed module versions in the app.

Return type​

List[Module]

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
all_installed_module_versions = app.list_installed_module_versions()

App.list_models()​

list_models(filter_by={}, only_in_app=True)

Lists all the available models for the user.

Parameters​

  • filter_by (dict) – A dictionary of filters to apply to the list of models.
  • only_in_app (bool) – If True, only return models that are in the app.

Returns​

A list of Model objects for the models in the app.

Return type​

List[Model]

Example​

from clarifai.client.user import User
app = User(user_id="user_id").app(app_id="app_id")
all_models = app.list_models()

App.list_modules()​

list_modules(filter_by={}, only_in_app=True)

Lists all the available modules for the user.

Parameters​

  • filter_by (dict) – A dictionary of filters to apply to the list of modules.
  • only_in_app (bool) – If True, only return modules that are in the app.
Returns​

A list of Module objects for the modules in the app.

Return type​

List[Module]

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
all_modules = app.list_modules()

App.list_workflows()​

list_workflows(filter_by={}, only_in_app=True)

Lists all the available workflows for the user.

Parameters​

  • filter_by (dict) – A dictionary of filters to apply to the list of workflows.
  • only_in_app (bool) – If True, only return workflows that are in the app.

Returns​

A list of Workflow objects for the workflows in the app.

Return type​

List Workflow

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
all_workflows = app.list_workflows()

App.model()​

model(model_id, model_version_id='', **kwargs)

Returns a Model object for the existing model ID.

Parameters​

  • model_id (str) – The model ID for the model to interact with.
  • model_version_id (str) – The model version ID for the model version to interact with.
Returns​

A Model object for the existing model ID.

Return type​

Model

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
model_v1 = app.model(model_id="model_id", model_version_id="model_version_id")

App.module()​

module(module_id, module_version_id='', **kwargs)

Returns a Module object for the existing module ID.

Parameters​

  • module_id (str) – The module ID for the module to interact with.
  • module_version_id (str) – The module version ID for the module version to interact with.

Returns​

A Module object for the existing module ID.

Return type​

Module

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
module = app.module(module_id="module_id", module_version_id="module_version_id")

App.workflow()​

workflow(workflow_id, **kwargs)

Returns a workflow object for the existing workflow ID.

Parameters​

  • workflow_id (str) – The workflow ID for the workflow to interact with.

Returns​

A Workflow object for the existing workflow ID.

Return type​

Workflow

Example​

from clarifai.client.app import App
app = App(app_id="app_id", user_id="user_id")
workflow = app.workflow(workflow_id="workflow_id")

Dataset​

class Dataset(url_init='', dataset_id='', **kwargs)

Dataset.__init__()​

Dataset is a class that provides access to Clarifai API endpoints related to Dataset information.

__init__(url_init='', dataset_id='', **kwargs)

Initializes a Dataset object.

Parameters​

  • url_init (str) – The URL to initialize the dataset object.
  • dataset_id (str) – The Dataset ID within the App to interact with.
  • **kwargs – Additional keyword arguments to be passed to the ClarifaiAuthHelper.

Dataset.export()​

export(save_path, archive_url=None, local_archive_path=None, split=None)

Exports the Clarifai protobuf dataset to a local archive.

Parameters​

  • save_path (str) – The path to save the archive to.
  • archive_url (str) – The URL to the Clarifai protobuf archive.
  • local_archive_path (str) – The path to the local Clarifai protobuf archive.
  • split (str) – Export dataset inputs in the directory format {split}/{input_type}. Default is all.

Example​

from clarifai.client.dataset import Dataset
Dataset().export(save_path='output.zip', local_archive_path='clarifai-data-protobuf.zip')

Note: Currently only supports export of dataset inputs.

Dataset.upload_dataset()​

upload_dataset(task, split, module_dir=None, dataset_loader=None, chunk_size=128)

Uploads a dataset to the app.

Parameters​

  • task (str) – task type(text_clf, visual-classification, visual_detection, visual_segmentation, visual-captioning)
  • split (str) – split type(train, test, val)
  • module_dir (str) – path to the module directory
  • dataset_loader (str) – name of the dataset loader
  • chunk_size (int) – chunk size for concurrent upload of inputs and annotations

Dataset.upload_from_csv()​

upload_from_csv(csv_path, input_type='text', labels=True, chunk_size=128)

Uploads dataset from a CSV file.

Parameters​

  • csv_path (str) – path to the csv file
  • input_type (str) – type of the dataset(text, image)
  • labels (bool) – True if csv file has labels column
  • chunk_size (int) – chunk size for concurrent upload of inputs and annotations

Example​

from clarifai.client.dataset import Dataset
dataset = Dataset(user_id = 'user_id', app_id = 'demo_app', dataset_id = 'demo_dataset')
dataset.upload_from_csv(csv_path='csv_path', labels=True)

Note: csv file should have either one(input) or two columns(input, labels).

Dataset.upload_from_folder()​

upload_from_folder(folder_path, input_type, labels=False, chunk_size=128)

Upload dataset from folder.

Parameters​

  • folder_path (str) – Path to the folder containing images.
  • input_type (str) – type of the dataset(text, image)
  • labels (bool) – True if folder name is the label for the inputs
  • chunk_size (int) – chunk size for concurrent upload of inputs and annotations

Example​

from clarifai.client.dataset import Dataset
dataset = Dataset(user_id = 'user_id', app_id = 'demo_app', dataset_id = 'demo_dataset')
dataset.upload_from_folder(folder_path='folder_path', input_type='text', labels=True)

Note: The filename is used as the input_id.

Input​

class Inputs(user_id='', app_id='', logger_level='INFO', **kwargs)

Inputs is a class that provides access to Clarifai API endpoints related to Input information.

Inputs.__init__()​

__init__(user_id='', app_id='', logger_level='INFO', **kwargs)

Initializes an Input object.

Parameters​

  • user_id (str) – A user ID for authentication.
  • app_id (str) – An app ID for the application to interact with.
  • **kwargs – Additional keyword arguments to be passed to the Input

Inputs.delete_inputs()​

delete_inputs(inputs)

Delete list of input objects from the app.

Parameters​

  • input_ids (Input) – List of input objects to delete.

Example​

from clarifai.client.user import User
input_obj = User(user_id="user_id").app(app_id="app_id").inputs()
input_obj.delete_inputs(input_obj.list_inputs())

Inputs.get_annotation_proto()​

get_annotation_proto(input_id, label, annotations)

Create an annotation proto for each bounding box, label input pair.

Parameters​

  • input_id (str) – The input ID for the annotation to create.
  • label (str) – annotation label
  • annotations (List) – a list of a single bbox’s coordinates. # Annotations ordering: [xmin, ymin, xmax, ymax]

Returns​

An annotation object for the specified input ID.

Example​

from clarifai.client.input import Input
input_obj = Input()
input_obj.get_annotation_proto(input_id='demo', label='demo', annotations=[x_min, y_min, x_max, y_max])

Inputs.get_image_inputs_from_folder()​

get_image_inputs_from_folder(folder_path, dataset_id=None, labels=False)

Create input protos for image data type from folder.

Parameters​

  • folder_path (str) – Path to the folder containing images.

Returns​

A list of Input objects for the specified folder.

Return type​

List of Input

Example​

from clarifai.client.input import Input
input_obj = Input()
input_protos = input_obj.get_image_inputs_from_folder(folder_path='demo_folder')

Inputs.get_input_from_bytes()​

get_input_from_bytes(input_id, image_bytes=None, video_bytes=None, audio_bytes=None, dataset_id=None, **kwargs)

Create input proto from bytes.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • image_bytes (str) – The bytes for the image.
  • video_bytes (str) – The bytes for the video.
  • audio_bytes (str) – The bytes for the audio.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.

Returns​

An Input object for the specified input ID.

Return type​

Input

Example​

from clarifai.client.input import Input
input_obj = Input()
image = open('demo.jpg', 'rb').read()
video = open('demo.mp4', 'rb').read()
input_proto = input_obj.get_input_from_bytes(input_id = 'demo',image_bytes =image, video_bytes=video)

Inputs.get_input_from_file()​

get_input_from_file(input_id, image_file=None, video_file=None, audio_file=None, dataset_id=None, **kwargs)

Create input proto from files.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • image_file (str) – The url for the image.
  • video_file (str) – The url for the video.
  • audio_file (str) – The url for the audio.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.

Returns​

An Input object for the specified input ID.

Return type​

Input

Example​

from clarifai.client.input import Input
input_obj = Input()
input_proto = input_obj.get_input_from_file(input_id = 'demo', video_file='file_path')

Inputs.get_input_from_url()​

get_input_from_url(input_id, image_url=None, video_url=None, audio_url=None, text_url=None, dataset_id=None, **kwargs)

Create input proto from URL.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • image_url (str) – The url for the image.
  • video_url (str) – The url for the video.
  • audio_url (str) – The url for the audio.
  • text_url (str) – The url for the text.
  • dataset_id (str): The dataset ID for the dataset to add the input to.

Returns​

An Input object for the specified input ID.

Return type​

Input

Example​

from clarifai.client.input import Input
input_obj = Input()
input_proto = input_obj.get_input_from_url(input_id = 'demo', image_url='https://samples.clarifai.com/metro-north.jpg')

Inputs.get_inputs_from_csv()​

get_inputs_from_csv(csv_path='', input_type= 'text', csv_type='raw', dataset_id=None, labels=True)

Create input protos from CSV.

Parameters​

  • csv_path (str) – Path to the csv file.
  • input_type (str) – Type of input. Options: ‘text’, ‘image’, ‘video’, ‘audio’.
  • csv_type (str) – Type of csv file. Options: ‘raw’, ‘url’, ‘file_path’.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.
  • labels (str) – True if csv file has labels column.

Returns​

List of inputs

Return type​

inputs

Example​

from clarifai.client.input import Input
input_obj = Input()
input_protos = input_obj.get_inputs_from_csv(csv_path='filepath', input_type='text', csv_type='raw')

Inputs.get_mask_proto()​

get_mask_proto(input_id, label, polygons)

Create an annotation proto for each polygon box, label input pair.

Parameters​

  • input_id (str) – The input ID for the annotation to create.
  • label (str) – annotation label
  • polygons (List) – Polygon x,y points iterable

Returns​

An annotation object for the specified input ID.

Example​

from clarifai.client.input import Input
input_obj = Input()
input_obj.get_mask_proto(input_id='demo', label='demo', polygons=[[[x,y],...,[x,y]],...])

Inputs.get_text_input()​

get_text_input(input_id, raw_text, dataset_id=None, **kwargs)

Create input proto for text data type from raw text.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • raw_text (str) – The raw text input.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.
  • **kwargs – Additional keyword arguments to be passed to the Input

Returns​

An Input object for the specified input ID.

Return type​

Text

Example​

from clarifai.client.input import Input
input_obj = Input()
input_protos = input_obj.get_text_input(input_id = 'demo', raw_text = 'This is a test')

Inputs.get_text_inputs_from_folder()​

get_text_inputs_from_folder(folder_path, dataset_id=None, labels=False)

Create input protos for text data type from folder.

Parameters​

  • folder_path (str) – Path to the folder containing text.

Returns​

A list of Input objects for the specified folder.

Return type​

list of Input

Example​

from clarifai.client.input import Input
input_obj = Input()
input_protos = input_obj.get_text_inputs_from_folder(folder_path='demo_folder')

Inputs.list_inputs()​

list_inputs()

Lists all the inputs for the app.

Returns​

A list of Input objects for the app.

Return type​

list of Input

Example​

from clarifai.client.user import User
input_obj = User(user_id="user_id").app(app_id="app_id").inputs()
input_obj.list_inputs()

Inputs.upload_annotations()​

upload_annotations(batch_annot, show_log=True)

Upload image annotations to app.

Parameters​

  • batch_annot – annot batch protos

Returns​

Return type​

Inputs.upload_from_bytes()​

upload_from_bytes(input_id, image_bytes=None, video_bytes=None, audio_bytes=None, dataset_id=None, **kwargs)

Upload input from bytes.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • image_bytes (str) – The bytes for the image.
  • video_bytes (str) – The bytes for the video.
  • audio_bytes (str) – The bytes for the audio.
  • text_bytes(str) – The bytes for the text.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.

Returns​

Job id for the upload request.

Return type​

input_job_id

Example​

from clarifai.client.input import Input
input_obj = Input(user_id = 'user_id', app_id = 'demo_app')
image = open('demo.jpg', 'rb').read()
input_obj.upload_from_bytes(input_id='demo', image_bytes=image)

Inputs.upload_from_file()​

upload_from_file(input_id, image_file=None, video_file=None, audio_file=None, dataset_id=None, **kwargs)

Upload input from file.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • image_file (str) – The file for the image.
  • video_file (str) – The file for the video.
  • audio_file (str) – The file for the audio.
  • text_file(str) – The file for the text.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.

Returns​

Job id for the upload request.

Return type​

input_job_id

Example​

from clarifai.client.input import Input
input_obj = Input(user_id = 'user_id', app_id = 'demo_app')
input_obj.upload_from_file(input_id='demo', audio_file='demo.mp3')

Inputs.upload_from_url()​

upload_from_url(input_id, image_url=None, video_url=None, audio_url=None, text_url=None, dataset_id=None, **kwargs)

Upload input from URL.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • image_url (str) – The url for the image.
  • video_url (str) – The url for the video.
  • audio_url (str) – The url for the audio.
  • text_url (str) – The url for the text.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.

Returns​

job id for the upload request.

Return type​

input_job_id

Example​

from clarifai.client.input import Input
input_obj = Input(user_id = 'user_id', app_id = 'demo_app')
input_obj.upload_from_url(input_id='demo', image_url='https://samples.clarifai.com/metro-north.jpg')

Inputs.upload_inputs()​

upload_inputs(inputs, show_log=True)

Upload list of input objects to the app.

Parameters​

  • inputs (list) – List of input objects to upload.
  • show_log (bool) – Show upload status log.

Returns​

Job id for the upload request.

Return type​

input_job_id

Inputs.upload_text()​

upload_text(input_id, raw_text, dataset_id=None, **kwargs)

Upload text from raw text.

Parameters​

  • input_id (str) – The input ID for the input to create.
  • raw_text (str) – The raw text.
  • dataset_id (str) – The dataset ID for the dataset to add the input to.

Returns​

Job id for the upload request.

Return type​

input_job_id (str)

Example​

from clarifai.client.input import Input
input_obj = Input(user_id = 'user_id', app_id = 'demo_app')
input_obj.upload_text(input_id = 'demo', raw_text = 'This is a test')

Lister​

class Lister(page_size=16)

Lister class for obtaining paginated results from the Clarifai API.

Lister.__init__()​

__init__(page_size=16)

Lister.list_all_pages_generator()​

list_all_pages_generator(endpoint, proto_message, request_data)

Lists all pages of a resource.

Parameters​

  • endpoint (Callable) – The endpoint to call.
  • proto_message (Any) – The proto message to use.
  • request_data (dict) – The request data to use.

Yields​

response_dict – The next item in the listing.

Model​

class Model(url_init='', model_id='', model_version={'id': ''}, output_config={'min_value': 0}, **kwargs)

Model is a class that provides access to Clarifai API endpoints related to Model information.

Model.__init__()​

__init__(url_init='', model_id='', model_version={'id': ''}, output_config={'min_value': 0}, **kwargs)

Initializes a Model object.

Parameters​

  • url_init (str) – The URL to initialize the model object.
  • model_id (str) – The Model ID to interact with.
  • model_version (dict) – The Model Version to interact with.
  • output_config (dict) – The output config to interact with.
    • min_value (float): The minimum value of the prediction confidence to filter.
    • max_concepts (int): The maximum number of concepts to return.
    • select_concepts (list[Concept]): The concepts to select.
    • sample_ms (int): The number of milliseconds to sample.
  • **kwargs – Additional keyword arguments to be passed to the ClarifaiAuthHelper.

Model.list_versions()​

list_versions()

Lists all the versions for the model.

Returns​

A list of Model objects for the versions of the model.

Return type​

List[Model]

Example​

from clarifai.client.model import Model
model = Model("model_url") # Example URL: https://clarifai.com/clarifai/main/models/general-image-recognition
            # or
model = Model(model_id='model_id', user_id='user_id', app_id='app_id')
all_model_versions = model.list_versions()

Model.predict()​

predict(inputs)

Predicts the model based on the given inputs.

Parameters​

  • inputs (list[Input]) – The inputs to predict, must be less than 128.

Model.predict_by_bytes()​

predict_by_bytes(input_bytes, input_type)

Predicts the model based on the given bytes.

Parameters​

  • input_bytes (bytes) – File Bytes to predict on.
  • input_type (str) – The type of input. Can be ‘image’, ‘text’, ‘video’ or ‘audio’.

Example​

from clarifai.client.model import Model
model = Model("https://clarifai.com/anthropic/completion/models/claude-v2")
model_prediction = model.predict_by_bytes(b'Write a tweet on future of AI', 'text')

Model.predict_by_filepath()​

predict_by_filepath(filepath, input_type)

Predicts the model based on the given file path.

Parameters​

  • filepath (str) – The file path to predict.
  • input_type (str) – The type of input. Can be ‘image’, ‘text’, ‘video’ or ‘audio.

Example​

from clarifai.client.model import Model
model = Model("model_url") # Example URL: https://clarifai.com/clarifai/main/models/general-image-recognition
          #  or
model = Model(model_id='model_id', user_id='user_id', app_id='app_id')
model_prediction = model.predict_by_filepath('/path/to/image.jpg', 'image')
model_prediction = model.predict_by_filepath('/path/to/text.txt', 'text')

Model.predict_by_url()​

predict_by_url(url, input_type)

Predicts the model based on the given URL.

Parameters​

  • url (str) – The URL to predict.
  • input_type (str) – The type of input. Can be ‘image’, ‘text’, ‘video’ or ‘audio.

Example​

from clarifai.client.model import Model
model = Model("model_url") # Example URL: https://clarifai.com/clarifai/main/models/general-image-recognition
          #  or
model = Model(model_id='model_id', user_id='user_id', app_id='app_id')
model_prediction = model.predict_by_url('url', 'image')

Workflow​

class Workflow(url_init='', workflow_id='', workflow_version={'id': ''}, output_config={'min_value': 0}, **kwargs)

Workflow is a class that provides access to Clarifai API endpoints related to Workflow information.

Workflow.__init__()​

__init__(url_init='', workflow_id='', workflow_version={'id': ''}, output_config={'min_value': 0}, **kwargs)

Initializes a Workflow object.

Parameters​

  • url_init (str) – The URL to initialize the workflow object.
  • workflow_id (str) – The Workflow ID to interact with.
  • workflow_version (dict) – The Workflow Version to interact with.
  • output_config (dict) – The output config to interact with.
    • min_value (float): The minimum value of the prediction confidence to filter.
    • max_concepts (int): The maximum number of concepts to return.
    • select_concepts (list[Concept]): The concepts to select.
    • sample_ms (int): The number of milliseconds to sample.
  • **kwargs – Additional keyword arguments to be passed to the ClarifaiAuthHelper.

Workflow.list_versions()​

list_versions()

Lists all the versions of the workflow.

Returns​

A list of Workflow objects.

Return type​

list[Workflow]

Example​

from clarifai.client.workflow import Workflow
workflow = Workflow(user_id='user_id', app_id='app_id', workflow_id='workflow_id')
workflow_versions = workflow.list_versions()

Workflow.predict()​

predict(inputs)

Predicts the workflow based on the given inputs.

Parameters​

  • inputs (list[Input]) – The inputs to predict.

Workflow.predict_by_bytes()​

predict_by_bytes(input_bytes, input_type)

Predicts the workflow based on the given bytes.

Parameters​

  • input_bytes (bytes) – Bytes to predict on.
  • input_type (str) – The type of input. Can be ‘image’, ‘text’, ‘video’ or ‘audio.

Workflow.predict_by_filepath()​

predict_by_filepath(filepath, input_type)

Predicts the workflow based on the given filepath.

Parameters​

  • filepath (str) – The filepath to predict.
  • input_type (str) – The type of input. Can be ‘image’, ‘text’, ‘video’ or ‘audio.

Example​

from clarifai.client.workflow import Workflow
workflow = Workflow("workflow_url") # Example: https://clarifai.com/clarifai/main/workflows/Face-Sentiment
           # or
workflow = Workflow(user_id='user_id', app_id='app_id', workflow_id='workflow_id')
workflow_prediction = workflow.predict_by_filepath('filepath', 'image')

Workflow.predict_by_url()​

predict_by_url(url, input_type)

Predicts the workflow based on the given URL.

Parameters​

  • url (str) – The URL to predict.
  • input_type (str) – The type of input. Can be ‘image’, ‘text’, ‘video’ or ‘audio.

Example​

from clarifai.client.workflow import Workflow
workflow = Workflow("workflow_url") # Example: https://clarifai.com/clarifai/main/workflows/Face-Sentiment
             # or
workflow = Workflow(user_id='user_id', app_id='app_id', workflow_id='workflow_id')
workflow_prediction = workflow.predict_by_url('url', 'image')

Module​

class Module(url_init='', module_id='', module_version={'id': ''}, \*\*kwargs)

Module is a class that provides access to Clarifai API endpoints related to Module information.

Module.__init__()​

__init__(url_init='', module_id='', module_version={'id': ''}, **kwargs)

Initializes a Module object.

Parameters​

  • url_init (str) – The URL to initialize the module object.
  • module_id (str) – The Module ID to interact with.
  • module_version (dict) – The Module Version to interact with.
  • **kwargs – Additional keyword arguments to be passed to the ClarifaiAuthHelper.

Module.list_versions()​

list_versions()

Lists all the module versions for the module.

Returns​

A list of Module objects for versions of the module.

Return type​

List[Module]

Example​

from clarifai.client.module import Module
module = Module(module_id='module_id', user_id='user_id', app_id='app_id')
all_Module_versions = module.list_versions()

Utils​

class Chunker(seq, size)

Split an input sequence into small chunks.

Chunker.__init__()​

__init__(seq, size)

Chunker.chunk()​

chunk()

Chunk input sequence.

Exceptions​

ApiError​

class ApiError(resource, params, method, response=None)

API Server error

ApiClientError​

class ApiClientError

API Client Error

UserError​

class UserError

User Error