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FME Hub user wghmapgear just uploaded a new transformer to the FME Hub.GeoApps Dataset CreatorWith this transformer, you can easily create a new dataset within GeoApps and add the records in it. This connection is for example useful for automated data upload from external systems or automation of repeated configurations.PrerequisitesTo use this transformer, you need to have an active GeoApps subscription and a user account with enough permissions to run the jobs. In addition, you need to first set up a web connection to GeoApps from FME. You can find the web connection in the FME Hub at https://hub.safe.com/publishers/mapgear/web-connections/geoapps.How to use?Add the transformer in your workspace, and configure the parameters. You need to set up two parameters: the tenant name, and the web connection to GeoApps.Questions?Do you need any help? Feel free to contact us at support@geoapps.nl.Would you like to know more? Click here to find out more details!
FME Hub user wghmapgear just uploaded a new transformer to the FME Hub.GeoApps VersionWith this transformer, you can easily request the version of GeoApps. This connection is useful for verification of your connection.PrerequisitesTo use this transformer, you need to have an active GeoApps subscription and a user account with enough permissions to run the jobs. In addition, you need to first set up a web connection to GeoApps from FME. You can find the web connection in the FME Hub at https://hub.safe.com/publishers/mapgear/web-connections/geoapps.How to use?Add the transformer in your workspace, and configure the parameters. You need to set up two parameters: the tenant name, and the web connection to GeoApps. After setting up, you receive three output parameters: major, minor and patch version level.Questions?Do you need any help? Feel free to contact us at support@geoapps.nl.Would you like to know more? Click here to find out more details!
FME Hub user vosgeo-analyses just uploaded a new transformer to the FME Hub.KLIC Transformer (version 1)By: Vos Geo-analyses (Roelof Vos) This transformer reads a previously downloaded KLIC file. The KLIC is downloaded from Kadaster.nl and shows all cables and pipelines in the specified area.The goal of this transformer is to read the .xml file, connect and expose all relevant data to each geometry and write it with a pre-defined style to a GeoPackage, or provide it to the end user as a raw output.Input Use a Creator with one creation instance to kick off the transformer.The KLIC file can be zipped or unzipped. The transformer can also process unzipped files within the same folder. KLIC files must begin with the name "Levering_". User parameters The KLIC transformer works with three user parameters: 1. KLIC_FOLDER: specify where you saved your KLIC downloads on your computer. From here the transformer will load all data with a Directory and File Pathnames reader. 2. Destination_writer:
FME Hub user davekazemi just uploaded a new transformer to the FME Hub.OverviewThe Process Monitor is a custom FME transformer that monitors running processes on your system, waiting until processes matching a specific name reach a defined threshold or until a timeout occurs. Designed primarily for coordinating asynchronous workflows, it allows you to ensure prerequisite tasks have completed before continuing execution.This transformer is particularly valuable when using WorkspaceRunner with asynchronous execution enabled, as it can pause the workflow until all child processes have completed. The transformer provides visual and audible notifications upon completion and logs monitoring status to the FME log.Key features include configurable process name targeting, adjustable checking intervals, timeout protection, and automated notifications. It's an essential tool for managing complex parallel processing workflows and ensuring proper sequence of operations in resource-intensive FME tas
FME Hub user daveatsafe just uploaded a new transformer to the FME Hub.Evaluates expressions on measure values, including algebraic operations and conditional statements. Supports linear geometries only:LinesArcsPathsClothoidsFeatures with aggregate or non-linear geometry will be output through the <Rejected> port.Typical UsesScaling measure valuesOffsetting measure valuesCreating new measures from mathematical operations on one or more existing measuresOperationThe transformer works almost the same as the ExpressionEvaluator, but allows the user to include existing measure names in the expressions, enclosed in square brackets.All operations supported in the ExpressionEvaluator are also supported by the MeasureExpressionEvaluator Would you like to know more? Click here to find out more details!
FME Hub user daveatsafe just uploaded a new transformer to the FME Hub.Evaluates expressions on measure values, including algebraic operations and conditional statements.Typical UsesScaling measure valuesOffsetting measure valuesCreating new measures from mathematical operations on one or more existing measuresOperationThe transformer works almost the same as the ExpressionEvaluator, but allows the user to include existing measure names in the expressions, enclosed in square brackets.All operations supported in the ExpressionEvaluator are also supported by the MeasureExpressionEvaluator Would you like to know more? Click here to find out more details!
FME Hub user marco.lor just uploaded a new transformer to the FME Hub.This transformer create a new attribute SumTot with the sum of the selected attributes.Would you like to know more? Click here to find out more details!
FME Hub user marco.lor just uploaded a new transformer to the FME Hub.SumSelectedAttributesCreates a new attribute which sum the previously selected attributesWould you like to know more? Click here to find out more details!
FME Hub user davekazemi just uploaded a new transformer to the FME Hub.AdvanceGrouper TransformerOverviewThe AdvanceGrouper transformer is an enhanced version of the traditional Grouper transformer in FME, offering improved performance and additional functionality for feature grouping and sampling. This transformer provides flexible methods to group and sample features based on different criteria.Performance ImprovementsSignificantly reduced processing time compared to the standard GrouperOptimized memory usage (peak memory usage: ~1.4MB for 150,000 features)Efficient handling of large feature setsUsage NotesSupports processing of large feature sets (tested with 150,000+ features)Maintains feature order during processingCompatible with existing FME workflowsProvides visual feedback through the feature cache iconsWould you like to know more? Click here to find out more details!
FME Hub user uvmsci just uploaded a new transformer to the FME Hub.This custom transformer writes CityGRID model with linked units/terrains/images.Would you like to know more? Click here to find out more details!
FME Hub user uvmsci just uploaded a new transformer to the FME Hub.This custom transformer reads CityGRID data (xml or ini). All element and unit attributes are merged to geometries.Would you like to know more? Click here to find out more details!
FME Hub user uvmsci just uploaded a new transformer to the FME Hub.This custom transformer writes models into CityGRID database. Optionally terrains or images can be linked to the model(s).Would you like to know more? Click here to find out more details!
FME Hub user uvmsci just uploaded a new transformer to the FME Hub.Reads tables from CityGRID database (Oracle, MSSQL or PostgreSQL).Would you like to know more? Click here to find out more details!
FME Hub user danielmartins18 just uploaded a new transformer to the FME Hub.This transformer adds attachments to an ArcGIS Online feature service. The transformer does not store username and password, allowing to use a AGOL Web Connection existing on your workspace.Based on by "AGOLAttachmentAdder" created by Chris Duncan_Would you like to know more? Click here to find out more details!
FME Hub user rvoisin just uploaded a new transformer to the FME Hub.Citywide Service Request ConnectorDescriptionThis transformer handles the creation of Service Requests with the Citywide REST API. It can be used to access various POST actions, including create new Service Requests and attaching Notes, Files, and Attributes.UsageTo use this transformer, a JSON POST body must be assembled to be sent to the relevant endpoint. It preforms one function at a time, which can be selected under Basic Parameters. Several uses of this transformer must be chained together to accomplish the entire Service Request creation process.Basic ParametersSelect a Function - Select which REST API action to preform. Create New Service Request: creates a new Citywide Service Request. Commit Service Request Transaction: this step must be preformed in order for the new Service Request to be available in the Citywide Web UI or Citwide Mobile App. Add Note to Service Request: Attaches a note to a pre-existi
FME Hub user rvoisin just uploaded a new transformer to the FME Hub.Citywide GET ConnectorDescriptionThis transformer handles pagination for the Citywide REST API.UsageIf given a valid Citywide REST API GET endpoint, this transformer will loop through all available pages of results and return all results combined into a single JSON response as cw_response. Please note that querying for large data sets my result in slower response times. This transformer is not designed for use with Bulk Routes.ParametersWeb Connection - A valid Citywide web authentication connection.Location - The Citywide GET endpoint to be queried.Filter Field - Optional. A field name to be used for filtering.Filter Value - Optional. A field value to be used for filtering.Would you like to know more? Click here to find out more details!
FME Hub user rvoisin just uploaded a new web_connection to the FME Hub.This Web Service connects to the Citywide REST API.To use this connection, you will need your username and database name as well as your user API Key.Would you like to know more? Click here to find out more details!
FME Hub user sanaeatsafe just uploaded a new transformer to the FME Hub.DescriptionThe OllamaConnector allows you to interact with the Ollama API, enabling response generation and seamless integration with locally deployed large language models (LLMs) within an FME Workspace.Examples of local LLM models that might be used with the OllamaConnector are Llama, LLaVa, Phi, Gemma, Mistral, Moondream, Deepseek, and Starling. For more information, review the Ollama API documentationWould you like to know more? Click here to find out more details!
FME Hub user mark2atsafe just uploaded a new transformer to the FME Hub.This transformer fits a range of numbers into a different range (or scale), in a process called Normalization (specifically Unity Based Normalization), or Min-Max Feature Scaling.Input PortsInput: Incoming data. Values to be normalized must be numeric. Features with non-numeric values will be rejected and the results calculated from the remaining records.Output PortsOutput: The outgoing data with the result in a new attribute called _NormalizedValueRejected: Any features rejected by the process.Feature order is unaffected by any processes in this transformer.ParametersAttribute to Normalize: The attribute containing the values to be normalized.New Scale Minimum: The minimum value for the new scaleNew Scale Maximum: The maximum value for the new scaleExampleThe area of each country in the world is calculated and passed to the transformer.The area value is the attribute to be normalized. The new scale minimum is set
FME Hub user antoine just uploaded a new template to the FME Hub.FME Workspace DescriptionUse caseThis FME workspace is designed for processing, analyzing, and preparing data to feed a local ollama model with your own pdf. It is just a demo workspace to understand RAG concept and Ollama calls without python.RequirementsInstall OllamaLoad your embedding model plus your LLM model into it first.Key ComponentsChunk Processing:Splits the input data into smaller chunks for parallel processing.Utilizes transformers to manage chunk size and distribute data.Embedding:Embeds validation steps to identify and correct errors in data chunks.Isolates problematic chunks for further analysis or correction.Preprocessed Data Storage:Outputs results in formats compatible with Parquet and other storage types.Ensures streamlined data flow for further usage in external systems or analysis tools.SQL Integration : Vector space:Uses SQL queries to store and manage data in memory, enabling efficient data manipul
FME Hub user chrisatsafe just uploaded a new template to the FME Hub.# Agentic Schema Mapping (AI Assistant Schema Mapping)## OverviewThis template highlights the development of an FME Workspace that can be configured as either a Workspace App or Automation tailored for schema mapping and address data standardization from various data providers. These solutions demonstrate how FME can seamlessly handle schema mapping and data preparation for ingestion into downstream processes, using Agentic AI (Gemini) to expedite the process without the need to build a look up table for schema mapping or manually define schema definitions. This works with any AI provider that supports structured outputs. ### Key Features1. **Schema Mapping Address Data**: - Accepts incoming files with varied schemas. - Converts the data to CSV for prompt engineering. - Submits the data to Gemini for schema mapping. - Outputs results in: - **CSV** for tabular data.2. **Automation**: - Watches a designate
FME Hub user chrisatsafe just uploaded a new template to the FME Hub.Agentic Schema Mapping (AI Assistant Schema Mapping)OverviewThis template highlights the development of an FME Workspace that can be configured as either a Workspace App or Automation tailored for schema mapping and address data standardization from various data providers. These solutions demonstrate how FME can seamlessly handle schema mapping and data preparation for ingestion into downstream processes, using Agentic AI (Gemini) to expedite the process without the need to build a look up table for schema mapping or manually define schema definitions. This works with any AI provider that supports structured outputs. Key FeaturesSchema Mapping Address Data:Accepts incoming files with varied schemas.Converts the data to CSV for prompt engineering.Submits the data to Gemini for schema mapping.Outputs results in:GeoJSON for spatial data.Automation:Watches a designated directory for incoming files.Processes files automati
