Specify the virtual path of the TruCap+ application. This setting helps define the web application's root directory, enabling correct routing and navigation.

Specify the Application Programming Interface (API) service path, indicating the location where API requests are processed and data is exchanged between TruCap+ and external systems.

Specify the interval, in milliseconds, between successive heartbeat signals sent by a running service. Heartbeat signals are essential for monitoring the availability and responsiveness of services.

Specify the amount of time, in milliseconds, a process sleeps after completing a task before proceeding to the next task. This setting aids in managing the pace of task execution and resource allocation.

Specify how often the application should refresh its service settings. This parameter ensures that any changes in service configurations are promptly updated and applied.

Specify the location where the LeadTools service cache is stored. This cache assists in optimizing image processing and retrieval.

Specify the maximum number of retry attempts the application should make when communicating with a queue server. If the server becomes unresponsive, the system will attempt to reconnect according to this parameter.

Specify the time interval between each retry attempt to reconnect with a queue server. This interval ensures a controlled approach to reestablishing communication.

Specify the percentage above which a data point is considered to be in the positive class or for prediction purposes. This setting is vital for determining classification and prediction outcomes.

Specify a time span, in days, for the automatic deletion of older archived logs. Logs that were created before this specified time limit will be purged, ensuring that only recent and relevant logs are retained for reference.

Specify a time span, in days, for the removal of older archived notifications. This ensures that outdated notifications are purged, maintaining the relevance of archived data.

Specify a time span, in days, for the deletion of older archived service logs related to heartbeat activity. This ensures that service-related logs are regularly maintained and that historical data remains relevant.

Specify the time of day when the automated purging of logs will be executed. Administrators can set a specific time for this process to occur regularly, ensuring that older data is purged according to the specified time spans.

Specify the minimum duration, measured in minutes, within which a document assigned to a user is to remain blocked. During this period, the user is expected to complete the necessary actions related to the document, ensuring timely processing and preventing potential conflicts with other users.

Specify the refresh interval duration for the Document Monitor page. Users can enter the desired duration in seconds or use the provided icon to conveniently set the duration. This refresh time determines how frequently the Document Monitor page updates to display the latest document statuses, ensuring users have up-to-date information.

Specify the base path, which indicates the root directory on the hosted server where the processed documents will be stored. This path serves as the foundation directory for all processed documents.

Specify the virtual directory path corresponding to the base path. This virtual path aids in creating a user-friendly way to access the stored documents, enhancing ease of navigation and retrieval.

Specify the time interval at which the system will automatically check for newly arrived files in the queue, waiting to be encrypted. Users can input the desired time duration in minutes, or use the provided icons to increment or decrement the value.

Specify the maximum number of files that the system is allowed to select for encryption. By setting this limit, users can control the quantity of files processed for encryption at any given time. The numeric value can be directly entered or adjusted using the provided icons.

Enabling this toggle button initiates the encryption of messages that have entered the queue. When activated, messages within the queue will be encrypted to enhance data security during transit and processing.

Specify the URL of the Azure Form Recognizer service endpoint. The endpoint serves as the connection point between TruCap+ and the Azure Form Recognizer service, enabling the extraction of structured data from various types of documents.

Specify the service key that is essential for authentication and secure communication between TruCap+ and the Azure service. It acts as a unique identifier for accessing the service and enabling ML-based data extraction.

Specify the TruAI authentication endpoint URL.

Specify the TruAI authentication username.

Specify the TruAI authentication password.

Specify an endpoint URL that provides a balance sheet summary. The TruAI Balance Sheet Endpoint is potentially used to retrieve relevant financial data or insights for further processing and analysis.

Specify the file path to the license file associated with Lead Tools. The license file is essential for the legal and authorized use of Lead Tools within the application.

Specify the developer key associated with Lead Tools. The developer key is used for authentication purposes and validates the application's access to Lead Tools functionalities.

Specify the file path to the JavaScript (JS) license file for Lead Tools. This file is necessary for enabling JavaScript-related functionalities of Lead Tools.

Specify the JS developer key that corresponds to the JS license file. It facilitates secure access to JavaScript-related features.

Specify the host path for the document service associated with Lead Tools. The document service host path is a crucial element in establishing connectivity and communication with the Lead Tools document-related services.

Select the type of logger that will be used for generating logs. Users can choose between two options:

• Database: Select this option, if you want to generate logs in a database-based logger.

• File: Select this option, if you want to generate logs in a file-based logger, such as a .txt file.
  

Specify the path where the generated log files will be stored.

Specify the number of backup files that should be maintained once the log file size reaches the defined limit.

Specify the maximum allowable size for a log file before a new log file is generated.

Enabling this option generates log files that are displayed on the console.

Enabling this option generates log files in a file-based format.

Enabling this option generates log files in a database.

When enabled, this option logs internal logger-related exceptions in the system.

Enabling this option causes logs to be saved in an encrypted format for added security.

Users can choose between two options for the level at which internal logger-related exceptions are set:

• Debug: To set the internal logger related exceptions at the debug level.

• Info: To set the internal logger related exceptions at the info level.

Specify the number of log entries that are buffered before they are written to the disk.

Specify the number of audit trail entries that are buffered before they are written to the disk.

This parameter enables users to set the time interval at which the Training Data Utility (TDU) service should be scheduled to run. The TDU service handles training data preparation for LC and NLP models. The interval is specified in minutes.

This parameter allows users to set the time interval at which the Model Trainer Utility (MTU) service is scheduled to run. The MTU service focuses on model training optimization. The interval is specified in minutes.

Specify the maximum degree of image rotation for augmenting training data. The ML model training process may involve training on images at multiple rotation angles to enhance model robustness.

Specify the maximum percentage by which images can be shifted either to the left or right. Image shifting can contribute to generating diverse training samples for the ML model.

Specifies the maximum number of records that a Logo Classification (LC) model sub-folder should contain. This helps in managing the size and organization of training data.

Specifies the maximum records within a sub-folder for the Natural Language Processing (NLP) model. This ensures effective training data management.

Heartbeat interval indicates the time interval, measured in seconds, between consecutive heartbeat counts for a running ML service. Heartbeats indicate the status and responsiveness of the service.

Specifies the interval, measured in seconds, after which the ML model undergoes a refresh. Model refreshes are important for updating and adapting the model based on new data and insights.

Specifies the interval, in seconds, for refreshing mapped ML models. Mapped models are associated with specific projects or contexts.

Specifies the time interval, measured in seconds, for allocating ML models to a project. This interval defines how often the allocation process occurs.

Specifies the maximum number of ML models that can be allocated to a single project. This setting helps in optimizing resource allocation.

Specifies the time, in seconds, before a previously allocated ML model becomes available for allocation again. It essentially sets a waiting period before reuse.

Specifies the duration, in minutes, after which a heartbeat from a mapped ML model instance will time out. Heartbeats indicate the operational status of the model instance.

Specifies the maximum amount of time, in minutes, that a call task will wait for an available model instance.

Specifies the IP address of the server where the Auto Correction service is running. It establishes the connection to the server hosting the Auto Correction functionality.

Specifies the port number associated with the Auto Correction service on the server. The port acts as an entry point for communication with the Auto Correction functionality.

Specifies the IP address of the server hosting the Shadow Removal service. It facilitates communication and data exchange with the Shadow Removal module.

Specifies the port number used to connect to the Shadow Removal service on the specified server. The port enables communication between TruCap+ and the Shadow Removal functionality.

Specify the URL of the SMS engine used for hosting SMS services. It serves as the entry point for sending SMS notifications.

Specifies the user name associated with the SMS service. It identifies the user account responsible for sending SMS notifications.

Specify the password linked to the user account specified. The password authenticates the user account for sending SMS messages.

Specifies the sender ID that appears on the recipient's mobile device when receiving the SMS notification. It serves as an identifier for the sender.

Specifies the count of missed heartbeat after which an alert is triggered. Heartbeats serve as a mechanism to monitor system health, and this parameter determines the threshold for receiving alerts.

Specifies the interval in minutes at which a repeat alert message is sent for missed heartbeats. This parameter ensures continuous notification until the issue is addressed.

Sets the duration in minutes during which missed heartbeats are tracked. This parameter establishes the time window for monitoring system health.

Specify the time in seconds for which the OCR manager will wait for the response from all the configured OCR engines. If a response is not received within this time, then the OCR manager returns with whatever results it already has.

Specifies the maximum allowable pixel difference between zones when calculating offsets. The offset calculation determines the spatial relationship between different zones on a page.

Specifies the binding type to establish a connection with the Inbuilt OCR Service. This parameter specifies whether the connection should be established using HTTP or HTTPS protocols.

Specify the service URL to connect with the Inbuilt OCR Service. The URL serves as the address for interacting with the OCR service.

Specify the ontology copilot API authentication endpoint URL.

Choose the execution library type that will be utilized for processing documents during the preprocessing stage. Users can select the desired library type from a provided dropdown list of options. The selected library type will determine the tool used for executing preprocessing tasks on documents.

Specify the time interval, measured in minutes, at which the productivity-related data updates are generated and displayed. Users can directly input the desired time interval or use the provided controls to increment or decrement the value.

Specify the time interval at which synchronization of Python machine learning models will take place in a production environment. Users can input the desired interval duration, determining how frequently the application will synchronize and update the deployed Python models used for various data processing tasks.

Specify a percentage threshold for CPU utilization. If the actual CPU usage surpasses this threshold, a notification alert is automatically generated and sent to the user. The defined threshold percentage can be entered directly or adjusted using the intuitive icon-based controls.

Specify a threshold percentage for RAM utilization. When the RAM usage crosses this threshold, a notification alert is triggered. The defined RAM threshold percentage can also be input manually or adjusted using the provided controls.

Specify a threshold percentage for disk space utilization. If the disk space usage exceeds the defined threshold, a notification alert is generated and sent. The percentage for disk threshold can be typed in directly or adjusted with the available controls.

The disk check interval determines how frequently the system evaluates the disk space usage. If the disk usage consistently goes beyond the threshold within the defined time interval, a notification alert is sent. Users can input the disk check interval in minutes or adjust it using the provided controls.

It sets the frequency at which the system monitors CPU and RAM utilization. If CPU and RAM utilization consistently exceeds their respective thresholds within this interval, notification alerts are issued. Users can enter the common check interval in minutes or use the provided controls for adjustment.

Attribute-value string that encapsulates the various table property values. These properties dictate how tables are treated and processed during data extraction operations.

Enabling this toggle switch activates the functionality to utilize translation services within the TruCap+ application.

S pecifies which external service will be used for text translation. Select the required translator service from the drop-down list. Available options are Azure and Google.

If the Azure translator service is chosen as the active translator service, users must provide the endpoint URL of the Azure translator service. This URL is used to connect to the Azure translation service for processing translation requests.

Specify the Azure translator key to authenticate and access the translation capabilities when using the Azure translator service.

Specify the region to be used for text translation. This region setting helps in determining the data center location for translation requests, if Azure translator service is used.

Enter the Google client id if you have selected Google translation service as an option from Active Translator Service parameter.

Specify the Google client secret key, which is used for secure authentication and communication with the translation service. If you have selected Google as an option from Active Translator Service parameter.

Specify the base URL that serves as the entry point for connecting the TruCap+ application to external Rest APIs. Users should input the complete base URL to ensure accurate communication and data exchange between TruCap+ and the target Rest API.

Specify the time duration, measured in seconds, which determines the time limit for processing a file through the Rest API integration. The setting indicates how long the system should wait for a response from the Rest API when processing a file.