API Methods under "predict" category

Methods:

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POSTlookupFeatures

Returns the feature group deployed in the feature store project.

POSTpredict

Returns a prediction for Predictive Modeling

POSTpredictMultiple

Returns a list of predictions for predictive modeling.

POSTpredictFromDatasets

Returns a list of predictions for Predictive Modeling.

POSTpredictLead

Returns the probability of a user being a lead based on their interaction with the service/product and their own attributes (e.g. income, assets, credit score, etc.). Note that the inputs to this method, wherever applicable, should be the column names in the dataset mapped to the column mappings in our system (e.g. column 'user_id' mapped to mapping 'LEAD_ID' in our system).

POSTpredictChurn

Returns the probability of a user to churn out in response to their interactions with the item/product/service. Note that the inputs to this method, wherever applicable, will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'churn_result' mapped to mapping 'CHURNED_YN' in our system).

POSTpredictTakeover

Returns a probability for each class label associated with the types of fraud or a 'yes' or 'no' type label for the possibility of fraud. Note that the inputs to this method, wherever applicable, will be the column names in the dataset mapped to the column mappings in our system (e.g., column 'account_name' mapped to mapping 'ACCOUNT_ID' in our system).

POSTpredictFraud

Returns the probability of a transaction performed under a specific account being fraudulent or not. Note that the inputs to this method, wherever applicable, should be the column names in your dataset mapped to the column mappings in our system (e.g. column 'account_number' mapped to the mapping 'ACCOUNT_ID' in our system).

POSTpredictClass

Returns a classification prediction

POSTpredictTarget

Returns a prediction from a classification or regression model. Optionally, includes explanations.

POSTgetAnomalies

Returns a list of anomalies from the training dataset.

POSTgetTimeseriesAnomalies

Returns a list of anomalous timestamps from the training dataset.

POSTisAnomaly

Returns a list of anomaly attributes based on login information for a specified account. Note that the inputs to this method, wherever applicable, should be the column names in the dataset mapped to the column mappings in our system (e.g. column 'account_name' mapped to mapping 'ACCOUNT_ID' in our system).

POSTgetEventAnomalyScore

Returns an anomaly score for an event.

POSTgetForecast

Returns a list of forecasts for a given entity under the specified project deployment. Note that the inputs to the deployed model will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'holiday_yn' mapped to mapping 'FUTURE' in our system).

POSTgetKNearest

Returns the k nearest neighbors for the provided embedding vector.

POSTgetMultipleKNearest

Returns the k nearest neighbors for the queries provided.

POSTgetLabels

Returns a list of scored labels for a document.

POSTgetEntitiesFromPDF

Extracts text from the provided PDF and returns a list of recognized labels and their scores.

POSTgetRecommendations

Returns a list of recommendations for a given user under the specified project deployment. Note that the inputs to this method, wherever applicable, will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'time' mapped to mapping 'TIMESTAMP' in our system).

POSTgetPersonalizedRanking

Returns a list of items with personalized promotions for a given user under the specified project deployment. Note that the inputs to this method, wherever applicable, should be the column names in the dataset mapped to the column mappings in our system (e.g. column 'item_code' mapped to mapping 'ITEM_ID' in our system).

POSTgetRankedItems

Returns a list of re-ranked items for a selected user when a list of items is required to be reranked according to the user's preferences. Note that the inputs to this method, wherever applicable, will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'item_code' mapped to mapping 'ITEM_ID' in our system).

POSTgetRelatedItems

Returns a list of related items for a given item under the specified project deployment. Note that the inputs to this method, wherever applicable, will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'item_code' mapped to mapping 'ITEM_ID' in our system).

POSTgetChatResponse

Return a chat response which continues the conversation based on the input messages and search results.

POSTgetChatResponseWithBinaryData

Return a chat response which continues the conversation based on the input messages and search results.

POSTgetConversationResponse

Return a conversation response which continues the conversation based on the input message and deployment conversation id (if exists).

POSTgetConversationResponseWithBinaryData

Return a conversation response which continues the conversation based on the input message and deployment conversation id (if exists).

POSTgetSearchResults

Return the most relevant search results to the search query from the uploaded documents.

POSTgetSentiment

Predicts sentiment on a document

POSTgetEntailment

Predicts the classification of the document

POSTgetClassification

Predicts the classification of the document

POSTgetSummary

Returns a JSON of the predicted summary for the given document. Note that the inputs to this method, wherever applicable, will be the column names in your dataset mapped to the column mappings in our system (e.g. column 'text' mapped to mapping 'DOCUMENT' in our system).

POSTpredictLanguage

Predicts the language of the text

POSTgetAssignments

Get all positive assignments that match a query.

POSTgetAlternativeAssignments

Get alternative positive assignments for given query. Optimal assignments are ignored and the alternative assignments are returned instead.

POSTcheckConstraints

Check for any constraints violated by the overrides.

POSTpredictWithBinaryData

Make predictions for a given blob, e.g. image, audio

POSTdescribeImage

Describe the similarity between an image and a list of categories.

POSTgetTextFromDocument

Generate text from a document

POSTtranscribeAudio

Transcribe the audio

POSTclassifyImage

Classify an image.

POSTclassifyPDF

Returns a classification prediction from a PDF

POSTgetCluster

Predicts the cluster for given data.

POSTgetObjectsFromImage

Classify an image.

POSTscoreImage

Score on image.

POSTtransferStyle

Change the source image to adopt the visual style from the style image.

POSTgenerateImage

Generate an image from text prompt.

POSTexecuteAgent

Executes a deployed AI agent function using the arguments as keyword arguments to the agent execute function.

POSTexecuteConversationAgent

Executes a deployed AI agent function using the arguments as keyword arguments to the agent execute function.

POSTlookupMatches

Lookup document retrievers and return the matching documents from the document retriever deployed with given query.

POSTexecuteAgentWithBinaryData

Executes a deployed AI agent function with binary data as inputs.