23 docs tagged with "Data Store"

The no-code Data Store steps allow you to easily retrieve or modify data from Data Store tables using an SQL query. The steps send a query to a database, which then processes it and returns the result.

The Data Store module is a web interface for managing database (DB) tables in the Work.AI platform. A field scheme defines the Data Store table structure and column data format.

With the introduction of the BEP execution platform:

Data Store plugins can be of two types:

The Data Store REST API provides remote Data Store management. Generally, the Data Store REST API service works with JSON data.

By default, WorkFusion security blocks all Data Store (DS) API calls from Manual Tasks, except Allowed Data Store Queries. Therefore, if you develop a custom Manual Task that uses DS API calls from JavaScript, you must create such allowed queries.

The article is a runbook that describes how to create complex custom configurations for Manual Tasks in MT Designer and how to resolve related issues. Before proceeding, review the instructions for simpler use cases in Design Manual Task forms.

To update the database connections for the CT vault, do as follows:

In the article, the standardized Data Store schema is understood as equivalent to the ODF 2 example project's Data Store schema. With few exceptions, it utilizes concepts from Transaction and Multi-process layers of the ODF 2 architecture. If you do not use the Multi-process layer, you can ignore some entities, and this won't impact the framework integrity. In extreme scenarios, when even the Transaction layer is not used, the Data Store schema should be designed from scratch.

Data flow

ORMLite is a framework that provides lightweight Object Relational Mapping between Java classes and SQL databases. There are certainly more mature ORMs that provide this functionality, including **Hibernate** and **iBatis**. However, ORMLite is a simple yet powerful wrapper around the JDBC functions.

Design concepts

Global variables store common values used in different Business Processes (BPs) without hard-coding them in Bot Tasks. In particular, global variables can store the following information:

Work.AI generates a considerable amount of data. Much of it results from completed Business Processes (BP) or internal maintenance. Accumulation of obsolete data can lead to the following issues:

With ODF 2, we encourage you to use Data Stores as a universal and effective way to have different steps of Business Processes within your AI Agent exchange data. The section provides a reference on how to organize your Data Model through AI Agent automation.

The article dwells on the obsolete approach of OCR usage in the scope of the ODF 2 framework.

In ORMLite, the lazy loading of mapped collections is implemented in a non-standard way. Instead of loading the content once during the first access, it loads it every time the collection is accessed.

The Work.AI platform provides a framework that allows users to configure an AI Agent without any additional knowledge about its implementation.

The monitor design assumes continuous managed loops generation during a scheduled period of time. For certain business needs, you may require to stop your Business Process (BP) immediately upon some trigger. Moreover, it is desired that the BP does not ruin transactions that already came out of the monitor's loop and are processed further.

The Taxonomy Answer Type can be used for classification of products, businesses, and articles. In WorkFusion, you can use this answer type along with Data Stores.

Problem context

JNW Toolkit contains three Maven modules that providу functionality for working with Data Stores.

Bot Task JUnit is a JUnit 5 API for running and testing Bot Tasks. You can use it for running Tasks locally from an IDE of choice during development and/or for executing tests in a CI/CD pipeline.