anatools.anaclient.anaclient module¶

The client module is used for connecting to Rendered.ai’s Platform API.

exception AuthFailedError¶: Bases: Exception

class client(workspaceId=None, environment='prod', email=None, password=None, APIKey=None, local=False, interactive=True, verbose=None)¶

Bases: object

add_organization_member(email, role, organizationId=None)¶

Add a user to an existing organization.

Parameters

email (str) – Email of user to add.
role (str) – Role for user.
organizationId (str) – Organization ID to add members too. Uses current if not specified.

Returns

Response status if user got added to workspace succesfully.

Return type

str

build_managed_channel(channelfile)¶

Build the Docker image of a channel.

Parameters: channelfile (str) – The channel file for the channel to build.
Returns: A boolean that indicates if the channel Docker image was successfully built.
Return type: bool

cancel_dataset(datasetId, workspaceId=None)¶

Stop a running job.

Parameters

datasetId (str) – Dataset ID of the running job to stop.
workspaceId (str) – Workspace ID of the running job. If none is provided, the default workspace will get used.

Returns

Success or error message about stopping the job execution.

Return type

str

check_logout()¶

create_analytics(datasetId, type, range=[], images=True, workspaceId=None)¶

Generate analytics for a dataset.

Parameters

datasetId (str) – Dataset ID to download image annotation for.
type (str) – The type of analytics to generate. Choose one from the list that get_analytics_types method returns.
range (list[int]) – The range of runs to generate analytics for.
images (bool) – If true, images specific to the analytics type will be created along with metrics data.
workspaceId (str) – Workspace ID of the dataset to generate the analytics for. If none is provided, the current workspace will get used.

Returns

The analyticsId for the analytics job.

Return type

str

create_annotation(datasetId, format, map, workspaceId=None)¶

Generates annotations for an existing dataset.

Parameters

datasetId (str) – Dataset ID to generate annotation for.
format (str) – Annotation format. Call get_annotation_formats() to find supported formats.
map (str) – The map file used for annotations. Call get_annotation_maps() to find supported maps.
workspaceId (str) – Workspace ID of the dataset to generate annotation for. If none is provided, the current workspace will get used.

Returns

The annotationsId for the annotation job.

Return type

str

create_api_key(name, expires=None, organizationId=None)¶

Creates a new API Key for the user account for the current organization. User will only see this key once, so make sure to save it.: To use the api key on login, ensure it is set as an environment variable called RENDEREDAI_API_KEY on next use of anatools or send it as an init parameter called APIKey. This call can only be used when logged in with email/password.

Parameters

name (str) – Name of the API Key.
organizationId (str) – Organization ID to set the API Key access at. If no organization is provided, it will use the current context.
expires (str) – Expiration date to set for the API Key. If none provided, a default expiration a week out will get set.

Returns

API Key in plain-text or failure message about API key creation

Return type

str

create_dataset(name, graphId, description='', runs=1, priority=1, seed=1, workspaceId=None)¶

Create a new dataset based off an existing staged graph. This will start a new job.

Parameters

name (str) – Name for dataset.
graphId (str) – ID of the staged graph to create dataset from.
description (str) – Description for new dataset.
runs (int) – Number of times a channel will run within a single job. This is also how many different images will get created within the dataset.
priority (int) – Job priority.
seed (int) – Seed number.
workspaceId (str) – Workspace ID of the staged graph’s workspace. If none is provided, the current workspace will get used.

Returns

Success or failure message about dataset creation.

Return type

str

create_gan_dataset(modelId, datasetId, workspaceId=None)¶

Create a new GAN dataset based off an existing dataset. This will start a new job.

Parameters

modelId (str) – Model ID to use for the GAN.
datasetId (str) – Dataset ID to input into the GAN.
workspaceId (str) – Workspace ID where the dataset exists.

Returns

The datsetId for the GAN Dataset job.

Return type

str

create_inpaint(volumeId, location, files=[], destination=None)¶

Creates an inpaint job.

Parameters

volumeId (str) – Volume ID
location (str) – Directory location of the input files
files (list) – List of files to inpaint, leave empty to inpaint all files in directory
destination (str) – Destination of the inpaint

Returns

Inpaint ID

Return type

str

create_llm_prompt(prompt, baseChannel, nodeType, nodeName)¶

Creates an LLM prompt.

Parameters

prompt (str) – The prompt to create
baseChannel (str) – The base channel to use for examples
nodeType (str) – The type of node to create
nodeName (str) – The name of the node to create

Returns

Prompt ID

Return type

str

create_managed_channel(name, description=None, organizationId=None, volumes=[], instance='p2.xlarge', timeout=120, interfaceVersion=1)¶

Create a managed channel for your organization.

Parameters

name (str) – Channel name.
description (str) – Description of the channel
organizationId (str) – Organization ID. Defaults to current if not specified.
volumes (list[str]) – List of the data volume names to associate with this channel.
instance (str) – AWS Instance type.
timeout (int) – Maximum runtime of a channel run.
interface (int) – The ana interface version number.

Returns

channel data

Return type

list[dict]

create_managed_gan(name, description, modelfile, flags=None, organizationId=None)¶

Uploades a GAN model to the microservice. The model will be owned by the specified organization. If organizationId is not given the model will be owned by that of the analcient.

Parameters

name (str) – A name for model.
description (str) – Details about the model.
modelfile (str) – The file of the model - relative to the local directry.
flags (str) – Parameters for use when running the model.
organizationId (str) – Id of organization that owns the model, that of the anaclient if not given.

Returns

modleId – The unique identifier for this model.

Return type

str

create_managed_map(name, description, mapfile, organizationId=None)¶

Uploades an annotation map to the microservice. The map will be owned by the specified organization. If not organizationId is given the model will be owned by that of the analcient.

Parameters

name (str) – A name for map.
description (str) – Details about the map.
mapfile (str) – The map file - relative to the local directry.
organizationId (str) – Id of organization that owns the map, that of the anaclient if not given.

Returns

mapId – The unique identifier for this map.

Return type

str

create_managed_volume(name, description=None, organizationId=None)¶

Creates a new volume with the specified name in the organization. By default the permission on the volume is set to write.

Parameters

name (str) – The name of the new volume. Note: this name needs to be unique per organization.
description (str) – Description of the volume
organizationId (str) – The ID of the organization that the managed volume will belong to.

Returns

volumeId

Return type

str

create_ml_inference(datasetId, modelId, mapId, workspaceId=None)¶

Create a new machine learning inference job.

Parameters

datasetId (str) – Dataset ID
modelId (str) – Model ID
mapId (str) – Map ID
workspaceId (str) – Workspace ID

Returns

Inference ID

Return type

str

create_ml_model(datasetId, architectureId, name, description, parameters, workspaceId=None)¶

Creates a new machine learning model.

Parameters

architectureId (str) – Architecture ID
datasetId (str) – Dataset ID
name (str) – Model name
description (str) – Model description
paramters (str) – JSON string of model parameters
workspaceId (str) – Workspace ID

Returns

Machine learning model ID

Return type

str

create_remote_development(channelId, organizationId=None, channelVersion=None, instanceType=None)¶

Creates a remote development environment.

This method initiates a remote development session on the specified channel, optionally within a given organization. If no organizationId is provided, it defaults to the organization associated with the current user.

Parameters

channelId (str) – The ID of the channel to use for creating the remote development session.
channelVersion (str, optional) – The version of the channel to use. If not provided, defaults to the latest version.
organizationId (str, optional) – The ID of the organization where the session will be created. If not provided, defaults to the user’s organization.
instanceType (str, optional) – The type of instance to use for the remote development session. If not provided, defaults to the instance type specified in the channel.

Returns

A message indicating that the session is being created, along with a link to access the session.

Return type

str

Notes

This function checks if the user is logged out before proceeding.
Calls ana_api.createRemoteDevelopment to initiate the session.
Displays a warning message indicating that the feature is experimental.

Example Output¶

⚠️ Warning: This feature is very experimental. Use with caution! ⚠️ 🚀 Your environment will be available here shortly: 🔗 <editorUrl> 🌐

create_staged_graph(name, channelId, graph, description=None, workspaceId=None)¶

Generates a new staged graph based off provided parameters. Must provide valid json string to create a new staged graph.

Parameters

name (str) – Name for the that will get generated.
channelId (str) – Id of channel to generate the staged graph with.
graph (str) – The graph as a dictionary or JSON string. While YAML files are used in channel development, the Platform SDK and API only support JSON. Ensure that the YAML file is valid in order for the yaml.safe_load to convert YAML to a dictionary for you. Otherwise, provide a graph in JSON format.
description (str) – Description of staged graph. Optional.
workspaceId (str) – Workspace ID create the staged graph in. If none is provided, the default workspace will get used.

Returns

The staged graph id if it was created sucessfully or an error message.

Return type

str

create_umap(datasetIds, samples, workspaceId=None)¶

Creates a UMAP dataset comparison job on the platform.

Parameters

datasetIds ([str]) – Dataset ID to retrieve information for.
samples ([int]) – Samples to take from each dataset.
workspaceId (str) – Workspace ID where the datasets exists.

Returns

The UMAP Job ID.

Return type

str

create_workspace(name, channelIds=[], volumeIds=[], code=None)¶

Create a new workspace with specific channels.

Parameters

name (str) – New workspace name.
channelIds (list[str]) – List of channel ids to add to workspace.
volumeIds (list[str]) – List of volume ids that the workspace will have access to.
code (str) – Content code that used for creating a workspace

Returns

Workspace ID if creation was successful. Otherwise returns message.

Return type

str

delete_analytics(analyticsId, workspaceId=None)¶

Deletes a dataset’s analytics.

Parameters

analyticsId (str) – Analytics ID for the analytics to delete.
workspaceId (str) – Workspace ID where the analytics exist. If none is provided, the current workspace will get used.

Returns

If true, successfully deleted the analytics.

Return type

bool

delete_annotation(annotationId, workspaceId=None)¶

Delete a dataset annotation.

Parameters

annotationId (str) – AnnoationId of the annotation job.
workspaceId (str) – Workspace ID of the dataset to generate annotation for. If none is provided, the current workspace will get used.

Returns

If true, successfully deleted the annotation.

Return type

bool

delete_api_key(name)¶

Deletes the API key from user account. This call can only be used when logged in with email/password.

Parameters: name (str) – Name of the API Key to delete.
Returns: Success or failure message about API key deletion
Return type: bool

delete_dataset(datasetId, workspaceId=None)¶

Delete an existing dataset.

Parameters

datasetId (str) – Dataset ID of dataset to delete.
workspaceId (str) – Workspace ID that the dataset is in. If none is provided, the current workspace will get used.

Returns

Success or failure message about dataset deletion.

Return type

str

delete_gan_dataset(datasetId, workspaceId=None)¶

Deletes a GAN dataset job.

Parameters

datasetId (str) – Dataset ID for the GAN dataset.
workspaceId (str) – Workspace ID where the dataset exists.

Returns

Returns true if the GAN dataset was successfully deleted.

Return type

bool

delete_gan_model(modelId)¶

Delete the GAN model and remove access to it from all shared organizations. This can only be done by a user in the organization that owns the model.

Parameters: modelId (str) – The ID of a specific GAN model.
Returns: Status
Return type: str

delete_inpaint(volumeId, inpaintId)¶

Deletes or cancels an inpaint job.

Parameters

volumeId (str) – Volume ID
inpaintId (str) – Inpaint ID

Returns

Success / Failure

Return type

bool

delete_llm_prompt(promptId)¶

Deletes an LLM prompt.

Parameters: promptId (str) – The ID of a prompt.
Returns: Success code
Return type: bool

delete_managed_channel(channelId)¶

Delete a managed channel of your organization.

Parameters: channelId (str) – Id of channel to delete.
Returns: Status
Return type: str

delete_managed_gan(modelId)¶

Removes the managed map

Parameters: modelId (str) – The ID of a specific Model to delete.
Returns: Status
Return type: bool

delete_managed_map(mapId)¶

Removes the managed map

Parameters: mapId (str) – The ID of a specific Map to delete.
Returns: Status
Return type: bool

delete_managed_volume(volumeId)¶

Removes the volume from the organization. Note that this will delete any remote data in the volume and channels that rely on this volume will need to be updated.

Parameters: volumeId (str) – The ID of a specific Volume to delete.
Returns: Status
Return type: str

delete_ml_inference(inferenceId, workspaceId=None)¶

Deletes or cancels a machine learning inference job.

Parameters

inferenceId (str) – Inference ID
workspaceId (str) – Workspace ID

Returns

Success / failure

Return type

bool

delete_ml_model(modelId, workspaceId=None)¶

Deletes or cancels a machine learning model.

Parameters

modelId (str) – Model ID
workspaceId (str) – Workspace ID

Returns

Success / failure

Return type

bool

delete_remote_development(editorSessionId, organizationId=None)¶

Deletes a remote development session.

This method removes a specific editor session, optionally within a given organization. If no organizationId is provided, it defaults to the organization associated with the current user.

Parameters

editorSessionId (str) – The ID of the editor session to be deleted.
organizationId (str, optional) – The ID of the organization where the editor session is running. If not provided, defaults to the user’s organization.

Returns

A dictionary representing the result of the session deletion, or session details upon deletion.

Return type

dict

Notes

This function checks if the user is logged out before proceeding.
Calls ana_api.deleteRemoteDevelopment to perform the deletion.

delete_staged_graph(graphId, workspaceId=None)¶

Delete a staged graph in a workspace.

Parameters

graphId (str) – Staged Graph id to delete.
workspaceId (str) – Workspace ID of the staged graph’s workspace. If none is provided, the current workspace will get used.

Returns

A success or error message based on staged graph’s delete.

Return type

str

delete_umap(umapId, workspaceId=None)¶

Deletes/cancels a UMAP dataset comparison on the platform.

Parameters

umapId (str) – UMAP Job ID.
workspaceId (str) – Workspace ID where the datasets exists.

Returns

Status.

Return type

bool

delete_volume_data(volumeId, files=[])¶

Delete data from a volume.

Parameters

volumeId (str) – VolumeId to delete files from.
files (str) – The specific files to delete from the volume. If left empty, no files are deleted.

Returns

Status

Return type

str

delete_workspace(workspaceId=None, prompt=True)¶

Delete an existing workspace.

Parameters

workspaceId (str) – Workspace ID for workspace to get deleted. Deletes current workspace if not specified.
prompt (bool) – Set to True if avoiding prompts for deleting workspace.

Returns

Success or failure message if workspace was sucessfully removed.

Return type

str

deploy_managed_channel(channelId=None, channelfile=None, image=None)¶

Deploy the Docker image of a channel.

Parameters

channelId (str) – Channel ID that you are pushing the image to. If the channelId isn’t specified, it will use the image name to lookup the channelId.
channelfile (str) – Name of the channel file to look for.
image (str) – The Docker image name. This should match the channel name when running ana. If image is not specified, it will use the channel name for the channelId.

Returns

deploymentId for current round of deployment or an error message if something went wrong

Return type

str

download_annotation(datasetId, annotationId, workspaceId=None)¶

Downloads annotations archive.

Parameters

datasetId (str) – Dataset ID to download image annotation for.
annotationId (str) – Id of previously generated image annotation.
workspaceId (str) – Workspace ID of the dataset to generate annotation for. If none is provided, the current workspace will get used.

Returns

The name of the archive file that got downloaded.

Return type

str

download_dataset(datasetId, workspaceId=None, localDir=None)¶

Download a dataset.

Parameters

datasetId (str) – Dataset ID of dataset to download.
workspaceId (str) – Workspace ID that the dataset is in. If none is provided, the default workspace will get used.
localDir (str) – Path for where to download the dataset. If none is provided, current working directory will be used.

Returns

Success or failure message about dataset download.

Return type

str

download_managed_gan(modelId, localDir=None)¶

Download the managed gan model file from your organization.

Parameters

modelId (str) – ModelId to download.
localDir (str) – Path for where to download the gan model. If none is provided, current working directory will be used.

Returns

The name of the managed gan model that got downloaded.

Return type

str

download_managed_map(mapId, localDir=None)¶

Download the managed annotation map file from your organization.

Parameters

mapId (str) – MapId to download.
localDir (str) – Path for where to download the managed annotation map. If none is provided, current working directory will be used.

Returns

The name of the managed map file that got downloaded.

Return type

str

download_ml_inference(inferenceId, localDir=None, workspaceId=None)¶

Download the inference detections.

Parameters

inferencId (str) – Inference ID
localDir (str) – Local directory to save the model
workspaceId (str) – Workspace ID

Returns

Success / failure

Return type

bool

download_ml_model(modelId, localDir=None, workspaceId=None)¶

Download the machine learning model.

Parameters

modelId (str) – Model ID
localDir (str) – Local directory to save the model
workspaceId (str) – Workspace ID

Returns

Success / failure

Return type

bool

download_staged_graph(graphId, workspaceId=None)¶

Download a staged graph.

Parameters

graphId (str) – Graph ID of the staged graph to download.
workspaceId (str) – Workspace ID of the staged graph’s workspace. If none is provided, the default workspace will get used.

Returns

A download URL that can be used in the browser or a failure message.

Return type

str

download_volume_data(volumeId, files=[], localDir=None, recursive=True, sync=False)¶

Download data from a volume.

Parameters

volumeId (str) – VolumeId to download data of.
files (str) – The specific files or directories to retrieve from the volume, if you wish to retrieve all then leave the list empty.
localDir (str) – The location of the local directory to download the files to. If not specified, this will download the files to the current directory.
recursive (bool) – Recursively download files from the volume.
sync (bool) – Syncs data between the local directory and the remote location. Only creates folders in the destination if they contain one or more files.

Returns

Status

Return type

str

edit_dataset(datasetId, description=None, name=None, workspaceId=None)¶

Update dataset description.

Parameters

datasetId (str) – Dataset ID to update description for.
description (str) – New description.
name (str) – New name for dataset.
workspaceId (str) – Workspace ID of the dataset to get updated. If none is provided, the current workspace will get used.

Returns

Success or failure message about dataset update.

Return type

str

edit_managed_channel(channelId, name=None, description=None, volumes=None, instance=None, timeout=None, status=None, interfaceVersion=None, preview=None)¶

Edit a managed channel for your organization.

Parameters

channelId (str) – ChannelId ID of the channel to edit.
name (name) – The new name to give the channel.
description (str) – Description of the channel
volumes (list[str]) – Data volumes for the channel.
instance (str) – Instance type to run the channel on.
timeout (int) – Maximum runtime for the channel run.
status (str) – The status of the channel.
interface (int) – The ana interface version number.
preview (bool) – Enable or disable the preview for the channel.

Returns

If true, the channel was successfully edited.

Return type

bool

edit_managed_gan(modelId, name=None, description=None, flags=None)¶

Edits the name, description, and flags of a managed gan.

Parameters

modelId (str) – The modelId that will be updated.
name (str) – The new name of the managed gan. Note: this name needs to be unique per organization.
description (str) – Description of the managed gan
flags (str) – Flags for the model

Returns

Status

Return type

bool

edit_managed_map(mapId, name=None, description=None)¶

Edits the name of a managed map.

Parameters

mapId (str) – The mapId that will be updated.
name (str) – The new name of the managed map. Note: this name needs to be unique per organization.
description (str) – Description of the managed map

Returns

Status

Return type

bool

edit_managed_volume(volumeId, name=None, description=None, permission=None)¶

Edits the volume in your current organization.

Parameters

volumeId (str) – The volumeId that will be updated.
name (str) – The new name of the new volume. Note: this name needs to be unique per organization.
description (str) – Description of the volume
permission (str) – Permission to set for the volume. Choose from: read, write, or view.

Returns

Status True or False

Return type

str

edit_ml_model(modelId, name, description, workspaceId=None)¶

Edit the name or description of a machine learning model.

Parameters

modelId (str) – Model ID
name (str) – Model name
description (str) – Model description
workspaceId (str) – Workspace ID

Returns

Success / failure

Return type

bool

edit_organization(name, organizationId=None)¶

Update the organization name. Uses current organization if no organizationId provided.

Parameters

name (str) – Name to update organization to.
organizationId (str) – Organization Id to update.

Returns

True if organization was edited successfully, False otherwise.

Return type

bool

edit_organization_member(email, role, organizationId=None)¶

Edit a member’s role.

Parameters

email (str) – Member email to edit.
role (str) – Role to assign.
organizationId (str) – Organization ID to remove member from. Edits member in current organization if not specified.

Returns

Response if member got edited succesfully.

Return type

str

edit_staged_graph(graphId, description=None, name=None, workspaceId=None)¶

Update staged graph description and name.

Parameters

graphId (str) – Staged Graph id to update.
description (str) – New description to update.
name (str) – New name to update.
workspaceId (str) – Workspace ID of the staged graph’s workspace. If none is provided, the current workspace will get used.

Returns

A success or error message based on staged graph’s update.

Return type

str

edit_workspace(name=None, channelIds=None, volumeIds=None, ganIds=None, mapIds=None, workspaceId=None)¶

Edit workspace information.

Parameters

name (str) – New name to replace old one.
channelIds (list[str]) – Names of channels that the workspace will have access to.
volumeIds (list[str]) – List of volume ids that the workspace will have access to.
ganIds (list[str]) – List of GAN ids that the workspace will have access to.
mapIds (list[str]) – List of map ids that the workspace will have access to.
workspaceId (str) – Workspace ID for workspace to update.

Returns

Success or failure message if workspace was sucessfully updated.

Return type

bool

get_analytics(analyticsId, workspaceId=None)¶

Retrieve information about a specific analytics job. If an analytics job is of type objectMetrics or meanBrightness, then images will get downloaded to current working directory.

Parameters

analyticsId (str) – Analytics Job ID.
workspaceId (str) – Workspace ID where the analytics exist. If none is provided, the current workspace will get used.

Returns

Analytics job information.

Return type

list[dict]

get_analytics_types()¶

Retrieve the analytics types available on the Platform.

Returns: The analytics types available on the Platform.
Return type: list[str]

get_annotation_formats()¶

Retrieves the annotation formats supported by the Platform.

Returns: The annotation formats supported by the Platform.
Return type: str

get_annotation_maps(organizationId=None, workspaceId=None, mapId=None)¶

Retrieves annotation maps.

Parameters

organizationId (str) – Organization ID to retrieve maps for. If not specified then the current organization is used.
workspaceId (str) – Workspace ID to retrieve maps for. If not specified then the current workspace is used.
mapId (str) – Annotation map ID to retrieve

Returns

The requested annotation maps.

Return type

str

get_annotations(datasetId=None, annotationId=None, workspaceId=None)¶

Retrieve information about existing annotations generated for a dataset. Querying requires both datasetId and annotationId.

Parameters

datasetId (str) – Dataset ID to generate annotations for.
annotationId (str) – Annotation ID for a specific annotations job.
workspaceId (str) – Workspace ID where the annotations exist. If none is provided, the current workspace will get used.

Returns

Annotation information.

Return type

list[dict]

get_api_key_data(name)¶

Returns information about specific api key. This call will return data only when logged in with email/password.

Parameters: name (str) – Name of the API Key.
Returns: Information about API Key
Return type: [dict]

get_api_keys()¶

Queries the api keys associated with user’s account. This call will return data only when logged in with email/password.

Returns: Names of API keys associated with user’s account.
Return type: [dict]

get_channel_documentation(channelId, localDir=None)¶

Downloads a markdown file for channel documentation.

Parameters

channelID (str) – The channelId of the channel
localDir (str) – The location to download the file to.

Returns

The list of filenames downloaded.

Return type

list[str]

get_channels(organizationId=None, workspaceId=None, channelId=None)¶

Shows all channels available to the user. Can filter by organizationId, workspaceId, or channelId.

Parameters

organizationId (str) – Filter channel list on what’s available to the organization.
workspaceId (str) – Filter channel list on what’s available to the workspace.
channelId (str) – Filter channel list on the specific channelId.

Returns

List of channels associated with user, workspace, organization or channelId.

Return type

list[dict]

get_dataset_log(datasetId, runId, saveLogFile=False, workspaceId=None)¶

Shows dataset log information to the user.

Parameters

datasetId (str) – The dataset the run belongs to.
runId (str) – The run to retrieve the log for.
saveLogFile (bool) – If True, saves log file to current working directory.
workspaceId (str) – The workspace the run belongs to.

Returns

Get log information by runId

Return type

list[dict]

get_dataset_runs(datasetId, state=None, workspaceId=None)¶

Shows all dataset run information to the user. Can filter by state.

Parameters

datasetId (str) – The dataset to retrieve logs for.
state (str) – Filter run list by status.
workspaceId (str) – The workspace the dataset is in.

Returns

List of run associated with datasetId.

Return type

list[dict]

get_datasets(datasetId=None, name=None, email=None, workspaceId=None)¶

Queries the workspace datasets based off provided parameters. Checks on datasetId, name, owner in this respective order within the specified workspace. If only workspace ID is provided, this will return all the datasets in a workspace.

Parameters

datasetId (str) – Dataset ID to filter.
name (str) – Dataset name.
email (str) – Owner of the dataset.
workspaceId (str) – Workspace ID of the dataset’s workspace. If none is provided, the current workspace will get used.

Returns

Information about the dataset based off the query parameters provided or a failure message.

Return type

str

get_default_graph(channelId)¶

Gets the default graph for a channel.

Parameters: channelId – Id of channel to get the default graph for.
Returns: json data representing the graph.
Return type: json

get_deployment_status(deploymentId, stream=False)¶

Retrieves status for a channel’s deployment.

Parameters

deploymentId (str) – The deploymentId to retrieve status for
stream (bool) – Flag to print information to the terminal so the user can avoid constant polling to retrieve status.

Returns

Deployment status.

Return type

list[dict]

get_gan_datasets(datasetId=None, gandatasetId=None, workspaceId=None)¶

Retrieve information about GAN dataset jobs.

Parameters

datasetId (str) – Dataset ID to retrieve information for.
gandatasetId (str) – Gan dataset ID to retrieve.
workspaceId (str) – Workspace ID where the dataset exists.

Returns

Information about the GAN Dataset.

Return type

list[dict]

get_gan_models(organizationId=None, workspaceId=None, modelId=None)¶

Retrieve information about GAN models

Parameters

organizationId (str) – Organization ID that owns the models
workspaceId (str) – Workspace ID that contains the models
modelId (str) – Model ID to retrieve information for.

Returns

GAN Model information.

Return type

list[dict]

get_inpaint_logs(volumeId, inpaintId)¶

Fetches the logs for the inpaint job.

Parameters

volumeId (str) – Volume ID
inpaintId (str) – Inpaint ID

Returns

logs

Return type

str

get_inpaints(volumeId, inpaintId=None)¶

Fetches the inpaint jobs in the volume.

Parameters

volumeId (str) – Volume ID
inpaintId (str) – Inpaint ID

Returns

Inpaint jobs info

Return type

dict

get_llm_base_channels()¶

Gets a list of the base channels

Returns: A list of the base channels
Return type: list[str]

get_llm_channel_node_types()¶

Gets a dictionary of base channels. For each channel there is a list of valid node types.

Returns: A dictionary of base channels and their valid node types
Return type: dict

get_llm_response(promptId)¶

Retrieves the response to an LLM prompt.

Parameters: promptId (str) – The ID of a prompt.
Returns: Prompt response info
Return type: dict

get_managed_channels(channelId=None, organizationId=None)¶

Get information for all managed channels that you own within your organization.

Parameters

channelId (str) – Channel Id to filter.
organizationId (str) – Organization ID. Defaults to current if not specified.

Returns

channel data

Return type

list[dict]

get_managed_gans(organizationId=None, modelId=None)¶

Retrieves the managed GANs for an organization.

Parameters

organizationId (str) – The ID of the organization that the managed GAN belongs to.
modelId (str) – The ID of a specific model.

Returns

Model Info

Return type

list[dict]

get_managed_maps(organizationId=None, mapId=None)¶

Retrieves the map(s) managed by the organization

Parameters

organizationId (str) – Organization ID to retrieve maps for. If not specified then the current organization is used.
mapId (str) – Annotation map ID to retrieve

Returns

The requested annotation maps.

Return type

str

get_managed_volumes(volumeId=None, organizationId=None)¶

Retrieves the managed volumes for an organization.

Parameters

volumeId (str) – The ID of a specific Volume.
organizationId (str) – The ID of the organization that the managed volume belongs to.

Returns

Volume Info

Return type

list[dict]

get_ml_architectures()¶

Retrieves the machine learning model architectures available on the platform.

Parameters: None –
Returns: Machine learning model architectures
Return type: dict

get_ml_inference_metrics(inferenceId, workspaceId=None)¶

Get the metrics from an inference job.

Parameters

inferenceId (str) – Inference ID
workspaceId (str) – Workspace ID

Returns

Metric data

Return type

dict

get_ml_inferences(inferenceId=None, datasetId=None, modelId=None, workspaceId=None)¶

Get the inferences of a machine learning model.

Parameters

inferenceId (str) – Inference ID
datasetId (str) – Dataset ID
modelId (str) – Model ID
workspaceId (str) – Workspace ID

Returns

Inference data

Return type

dict

get_ml_models(workspaceId=None, datasetId=None, modelId=None)¶

Retrieves the machine learning model architectures available on the platform.

Parameters

workspaceId (str) – Workspace ID
datasetId (str) – Dataset ID
modelId (str) – Model ID

Returns

Machine learning model architectures

Return type

dict

get_organization()¶

Get organization id of current organization.

Returns: Organization ID of current workspace.
Return type: str

get_organization_invites(organizationId=None)¶

Get invitations of an organization.

Parameters: organizationId (str) – Organization ID. Defaults to current if not specified.
Returns: Information about invitations of an organization.
Return type: list[dict]

get_organization_members(organizationId=None)¶

Get users of an organization.

Parameters: organizationId (str) – Organization ID. Defaults to current if not specified.
Returns: Information about users of an organization.
Return type: list[dict]

get_organizations(organizationId=None)¶

Shows the organizations the user belongs to and the user’s role in that organization.

Returns: Information about the organizations you belong to.
Return type: list[dict]

get_staged_graphs(graphId=None, name=None, email=None, workspaceId=None)¶

Queries the workspace staged graphs based off provided parameters. Checks on graphId, name, or owner in this respective order within the specified workspace. If only workspace ID is provided, this will return all the staged graphs in a workspace.

Parameters

graphid (str) – Staged GraphID to filter on. Optional.
name (str) – Name of the staged graph to filter on. Optional.
email (str) – Owner of staged graphs to filter on. Optional.
workspaceId (str) – Workspace ID to filter on. If none is provided, the default workspace will get used.

Returns

A list of staged graphs based off provided query parameters if any parameters match.

Return type

list[dict]

get_system_status(serviceId=None, display=True)¶

Fetches the system status, if no serviceId is provided it will fetch all services.

Parameters

serviceId (str) – The identifier of the service to fetch the status of.
display (bool) – Boolean for either displaying the status or returning as a dict.

get_umaps(umapId=None, datasetId=None, workspaceId=None)¶

Retrieves information about UMAP dataset comparison from the platform.

Parameters

umapId (str) – UMAP Job ID.
datasetId (str) – Dataset Id to filter on.
workspaceId (str) – Workspace ID where the datasets exists.

Returns

UMAP information.

Return type

dict

get_volume_data(volumeId, files=[], dir='')¶

Retrieves information about data from a volume.

Parameters

volumeId (str) – VolumeId to remove access to.
files (str) – The specific files or directories to retrieve information about from the volume, if you wish to retrieve all then leave the list empty.
dir (str) – Specific volume directory to retrieve information about. Optional.

Returns

Status

Return type

str

get_volumes(volumeId=None, workspaceId=None, organizationId=None)¶

Retrieves all volumes the user has access to.

Parameters

volumeId (str) – The ID of a specific Volume.
organizationId (str) – The ID of the organization that the volume belongs to.

Returns

Volume Info

Return type

list[dict]

get_workspace()¶

Get Workspace ID of current workspace.

Returns: Workspace ID of current workspace.
Return type: str

get_workspaces(organizationId=None, workspaceId=None)¶

Shows list of workspaces with id, name, and owner data.

Parameters

organizationId (str) – Organization ID to filter on. Optional
workspaceId (str) – Workspace ID to filter on. Optional

Returns

Workspace data for all workspaces for a user.

Return type

list[dict]

list_remote_development(organizationId=None)¶

Shows all the active development sessions in the organization.

Parameters: organizationId (str) – The ID of the organization to list the active development sessions. If not provided, defaults to the user’s organization
Returns: List of remote development environments running in the organization.
Return type: list[dict]

login(workspaceId=None, environment='prod', email=None, password=None, local=False, interactive=True, verbose=None)¶

Log in to the SDK.

Parameters

workspaceId (str) – ID of the workspace to log in to. Uses default if not specified.
environment (str) – Environment to log into. Defaults to production.
email (str) – Email for the login. Will prompt if not provided.
password (str) – Password to login. Will prompt if not provided.
local (bool) – Used for development to indicate pointing to local API.
interactive (bool) – Set to False for muting the login messages.
verbose (str) – Flag to turn on verbose logging. Use ‘debug’ to view log output.

logout()¶: Logs out of the ana sdk and removes credentials from ana.

mount_volumes(volumes)¶

Retrieves credentials for mounting volumes.

Parameters: volumes ([str]) – Volumes to retrieve mount credentials for.
Returns: Credential information.
Return type: dict

refresh_token()¶

remove_organization_invitation(email, organizationId=None, invitationId=None)¶

Remove a invitation from an existing organization.

Parameters

email (str) – Invitation email to remove.
organizationId (str) – Organization ID to remove member from. Removes from current organization if not specified.
invitationId (str) – Invitation ID to remove invitation from. Removes from current organization if not specified.

Returns

Response status if member got removed from organization succesfully.

Return type

str

remove_organization_member(email, organizationId=None)¶

Remove a member from an existing organization.

Parameters

email (str) – Member email to remove.
organizationId (str) – Organization ID to remove member from. Removes from current organization if not specified.

Returns

Response status if member got removed from organization succesfully.

Return type

str

remove_workspace_invitation(email, workspaceId=None, invitationId=None)¶

Remove a invitation from an existing organization.

Parameters

email (str) – Invitation email to remove.
workspaceId (str) – Workspace ID to remove member from. Removes from current organization if not specified.
inviteId (str) – Invitation ID to remove invitation from. Removes from current organization if not specified.

Returns

Response status if member got removed from organization succesfully.

Return type

str

set_default_graph(channelId, workspaceId, graphId=None, stagedGraphId=None)¶

Sets the default graph for a channel. User must be in the organization that manages the channel.

Parameters

channel (str) – The name of the channel to update the default graph.
workspaceId (str) – The ID of the Workspace that the graph is in.
graphId (str) – The ID of the graph that you want to be the default for the channel. Optional.
stagedGraphId (str) – The ID of the staged graph that you want to be the default for the channel. Optional.

Returns

Status

Return type

str

set_organization(organizationId, workspaceId=None)¶

Set the organization (and optionally a workspace) to the one you wish to work in.

Parameters

organizationId (str) – Organization ID for the organization you wish to work in.
workspaceId (str) – Workspace ID for the workspace you wish to work in. Uses default workspace if this is not set.

set_workspace(workspaceId)¶

Set the workspace to the one you wish to work in.

Parameters: workspaceId (str) – Workspace ID for the workspace you wish to work in.

sign_in_apikey(interactive)¶

start_remote_development(editorSessionId, organizationId=None)¶

Starts a remote development session.

This method starts a specific editor session, optionally within a given organization. If no organizationId is provided, it defaults to the organization associated with the current user.

Parameters

editorSessionId (str) – The ID of the editor session to be started.
organizationId (str, optional) – The ID of the organization where the editor session is running. If not provided, defaults to the user’s organization.

Returns

A dictionary representing the result of the session start operation.

Return type

dict

Notes

This function checks if the user is logged out before proceeding.
Calls ana_api.startRemoteDevelopment to start the session.

stop_remote_development(editorSessionId, organizationId=None)¶

Stops a remote development session.

This method stops a specific editor session, optionally within a given organization. If no organizationId is provided, it defaults to the organization associated with the current user.

Parameters

editorSessionId (str) – The ID of the editor session to be stopped.
organizationId (str, optional) – The ID of the organization where the editor session is running. If not provided, defaults to the user’s organization.

Returns

A dictionary representing the result of the session stop operation.

Return type

dict

Notes

This function checks if the user is logged out before proceeding.
Calls ana_api.stopRemoteDevelopment to stop the session.

upload_channel_documentation(channelId, mdfile)¶

Uploads a markdown file for channel documentation.

Parameters

channelID (str) – The channelId of the channel
mdfile (str) – The filepath of the markdown file used for channel documentation.

Returns

Success/Failure of channel documenation upload.

Return type

bool

upload_dataset(filename, description=None, workspaceId=None)¶

Uploads user dataset using multipart upload with 8 threads.

Parameters

filename (str) – Path to the dataset folder or file for uploading. Must be zip or tar file types.
workspaceId (str) – WorkspaceId to upload dataset to. Defaults to current.
description (str) – Description for new dataset.

Returns

datasetId – The unique identifier for this dataset.

Return type

str

upload_ml_model(name, description, modelfile, parameters, workspaceId=None)¶

Upload a machine learning model.

Parameters

name (str) – Model name
description (str) – Model description
modelfile (str) – The filepath of the model file
parameters (str) – Model training parameters
workspaceId (str) – Workspace ID

Returns

Success / failure

Return type

bool

upload_volume_data(volumeId, files=[], localDir=None, sync=False)¶

Upload data to a volume.

Parameters

volumeId (str) – VolumeId to upload data to.
files (list[str]) – The specific files or directories to push to the volume from the localDir. If you wish to push all data in the root directory, then leave the list empty.
localDir (str) – The location of the local directory to upload the files from. If not specified, this will try to upload the files from the current directory.
sync (bool) – Recursively uploads new and updated files from the source to the destination. Only creates folders in the destination if they contain one or more files.

Returns

Status

Return type

str

anatools.anaclient.anaclient module¶

Example Output¶

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