salesforce.local – einstein

Tools (47)

Extracted live via the executor SDK.

• authorization.generateTokenV2

  Returns an OAuth access token or a refresh token. You must pass a valid access token in the header of each API call.

• authorization.revokeRefreshTokenV2

  Delete a Refresh Token

• checkApiUsage.getApiUsagePlansV2

  Returns prediction usage on a monthly basis for the current calendar month and future months. Each apiusage object in the response corresponds to a calendar month in your plan.

• languageDatasets.deleteDataset

  Deletes the specified dataset and associated labels and examples.

• languageDatasets.get

  Returns the status of a language dataset or model deletion. When you delete a dataset or model, the deletion may not occur immediately. Use this call to find out when the deletion is complete.

• languageDatasets.getDataset

  Returns a single dataset.

• languageDatasets.listDatasets

  Returns a list of datasets and their labels that were created by the current user. The response is sorted by dataset ID.

• languageDatasets.uploadDatasetAsync

  Creates a dataset, labels, and examples from the specified .csv, .tsv, or .json file. The call returns immediately and continues to upload data in the background.

• languageDatasets.uploadDatasetSync

  Creates a dataset, labels, and examples from the specified .csv, .tsv, or .json file. The call returns after the dataset is created and all of the data is uploaded.

• languageExamples.getExamples

  Returns all the examples for the specified dataset,

• languageExamples.getExamplesByLabel

  Returns all the examples for the specified label. Returns both uploaded examples and feedback examples.

• languageExamples.provideFeedback

  Adds a feedback example to the dataset associated with the specified model.

• languageExamples.updateDatasetAsync

  Adds examples from a .csv, .tsv, or .json file to a dataset.

• languageModels.deleteModel

  Deletes the specified model.

• languageModels.getTrainedModelLearningCurve

  Returns the metrics for each epoch in a model.

• languageModels.getTrainedModelMetrics

  Returns the metrics for a model

• languageModels.getTrainedModels

  Returns all models for the specified dataset.

• languagePrediction.intentMultipart

  Returns an intent prediction for the given string.

• languagePrediction.sentimentMultipart

  Returns a sentiment prediction for the given string.

• languageTraining.getTrainStatusAndProgress

  Returns the status of a model's training process. Use the progress field to determine how far the training has progressed. When training completes successfully, the status is SUCCEEDED and the progress is 1.

• languageTraining.retrain

  Retrains a dataset and updates a model. Use this API call when you want to update a model and keep the model ID instead of creating a new model.

• languageTraining.train

  Trains a dataset and creates a model.

• visionDatasets.createDataset

  Creates a dataset and labels, if they're specified.

• visionDatasets.deleteDataset1

  Deletes the specified dataset and associated labels and examples.

• visionDatasets.get1

  Returns the status of an image dataset or model deletion. When you delete a dataset or model, the deletion may not occur immediately. Use this call to find out when the deletion is complete.

• visionDatasets.getDataset1

  Returns a single dataset.

• visionDatasets.listDatasets1

  Returns a list of datasets and their labels that were created by the current user. The response is sorted by dataset ID.

• visionDatasets.uploadDatasetAsync1

  Creates a dataset, labels, and examples from the specified .zip file. The call returns immediately and continues to upload the images in the background.

• visionDatasets.uploadDatasetSync1

  Creates a dataset, labels, and examples from the specified .zip file. The call returns after the dataset is created and all of the images are uploaded.

• visionExamples.addExample

  Adds an example with the specified label to a dataset.

• visionExamples.getExamples1

  Returns all the examples for the specified dataset. By default, returns examples created by uploading them from a .zip file.

• visionExamples.getExamplesByLabel1

  Returns all the examples for the specified label. Returns both uploaded examples and feedback examples.

• visionExamples.provideFeedback1

  Adds a feedback example to the dataset associated with the specified model.

• visionExamples.updateDatasetAsync1

  Adds feedback examples to the dataset associated with the specified object detection model.

• visionExamples.updateDatasetAsync2

  Adds examples from a .zip file to a dataset. You can use this call only with a dataset that was created from a .zip file.

• visionModels.deleteModel1

  Deletes the specified model.

• visionModels.getTrainedModelLearningCurve1

  Returns the metrics for each epoch in a model.

• visionModels.getTrainedModelMetrics1

  Returns the metrics for a model

• visionModels.getTrainedModels1

  Returns all models for the specified dataset.

• visionPrediction.detectMultipart

  Returns labels, probabilities, and bounding box coordinates for items detected in the specified local image file.

• visionPrediction.ocrMultipart

  Returns a prediction from an OCR model for the specified image URL or local image file.

• visionPrediction.predictMultipart

  Returns a prediction from an image or multi-label model for the specified image.

• visionTraining.getTrainStatusAndProgress1

  Returns the status of a model's training process. Use the progress field to determine how far the training has progressed. When training completes successfully, the status is SUCCEEDED and the progress is 1.

• visionTraining.retrain1

  Retrains a dataset and updates a model. Use this API call when you want to update a model and keep the model ID instead of creating a new model.

• visionTraining.train1

  Trains a dataset and creates a model.

• openapi.previewSpec

  Preview an OpenAPI document before adding it as a source

• openapi.addSource

  Add an OpenAPI source and register its operations as tools