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FME Hub user gimmy15+ just uploaded a new transformer to the FME Hub.Telegram Message sender:this transformer sends messages (attribute text or images) to chats.Previously you need to create a Telegram Bot and get the Token.Developed by Genegis GI s.r.l.Would you like to know more? Click here to find out more details!

FME Hub user kevs-2021 just uploaded a new transformer to the FME Hub.Colors surface, 3D and faces from a RGB or RGBA value.It is an improved version of the SurfaceColorSetter.Would you like to know more? Click here to find out more details!

FME Hub user oliver.morris just uploaded a new transformer to the FME Hub.OverviewThis transformer works with the Google AI and its Gemini multi-modal models the support image analysis. This enables FME to pass images to the Gemini models and respond with text.An API Key is required via https://aistudio.google.com/app/apikey, currently Google is not charging for API calls to the two models!More information about the model, including limitations: https://ai.google.dev/gemini-api/docsCurrently this transformer supports JPG, JPEG and PNG file formats of up to 5MB in size but of any dimensions.This is a ‘no cost’ Publisher Tensing License: It has no license restrictions.If you have any questions regarding this transformer please email uk@avineon-tensing.comTensing is a partner of Safe Software and a Value Added Reseller, with over 80 FME Certified Professionals and FME Certified Trainers in the Netherlands, UK, France, Belgium, US and India. Tensing provides bespoke training services, cons

FME Hub user geospatialize just uploaded a new transformer to the FME Hub.OverviewCustom transformer designed to address a common issue when working with resolved domain columns in FME. When a reader is set to resolve domains, but the coded value is not found in the corresponding domain, the "_resolved" field is populated as null. This can lead to inconsistencies and require manual intervention to handle the null values. The ResolvedDomainPopulator automatically populates these null values in the "_resolved" columns with the corresponding values from the original columns. It ensures data consistency and eliminates the need for additional transformers or manual effort to handle the null values. However, it is important to note that this transformer assumes that all resolvable domains have been properly resolved before its application. It does not perform the actual resolution process itself. To maintain data integrity, ensure that the domain resolution process is completed using appropr

FME Hub user keziaatsafe just uploaded a new transformer to the FME Hub.DetailsThe transformer is designed to require only the essential parameters to update a Task to a Case in Cityworks with an option to include additional parameters. An HTTPCaller is used to make the call to the Cityworks API, followed by a JSONExtractor to extract valuable information from the response. Further configuration of the JSONExtractor can allow you to pull out more attributes from the response based on your custom needs. Similarly, additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. The User Parameter for_ca_task_id may need configuration to reflect the details of your Cityworks instance.Would you like to know more? Click here to find out more details!

FME Hub user keziaatsafe just uploaded a new transformer to the FME Hub.DescriptionThis transformer leverages the Cityworks REST API to create a Case within Cityworks from FME. It is designed to be used with an authenticated web connection to Cityworks.DetailsThe transformer is designed to require only the essential parameters to create a Case in Cityworks with an option to include additional parameters. An HTTPCaller is used to make the call to the Cityworks API, followed by a JSONExtractor to extract valuable information from the response. Further configuration of the JSONExtractor can allow you to pull out more attributes from the response based on your custom needs. Similarly, additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. The User Parameter for_case_type may need configuration to reflect the details of your Cityworks instance.Would you like to know more? Click here to find out more details!

FME Hub user keziaatsafe just uploaded a new transformer to the FME Hub.DescriptionThis transformer leverages the Cityworks REST API to add a Task to a Case within Cityworks from FME. It is designed to be used with an authenticated web connection to Cityworks.DetailsThe transformer is designed to require only the essential parameters to add a Task to a Case in Cityworks with an option to include additional parameters. An HTTPCaller is used to make the call to the Cityworks API, followed by a JSONExtractor to extract valuable information from the response. Further configuration of the JSONExtractor can allow you to pull out more attributes from the response based on your custom needs. Similarly, additional parameters can be provided in the Additional Request Parameters field to send a more detailed request to Cityworks. The User Parameter for_task_id may need configuration to reflect the details of your Cityworks instance.Would you like to know more? Click here to find out more details!

FME Hub user nils95 just uploaded a new transformer to the FME Hub.Calculates the angle in degrees for every polygon node.INPUT:PolygonsNeeded attribute: "OBJECTID"OUTPUT:Points with calculated angle between lines Attribute: "OBJECTID_pt" (OBJECTID of the associated polygon as attribute)Would you like to know more? Click here to find out more details!

FME Hub user chrisatsafe just uploaded a new transformer to the FME Hub.Google Gemini Service ConnectorOverviewThe Google Gemini Service Connector is a Custom Transformer for FME that facilitates interaction with Google's Vertex AI Gemini Model via REST API. This transformer allows users to leverage the advanced capabilities of Gemini, Google's large language model, to generate text-based outputs by providing specific prompts and configuring various parameters. This enables a broad range of applications, from content generation to data enrichment across different industries.For more information, please see the Gemini API documentation.Note: by default, this transformer is configured to use the Auto Updated Gemini model.Would you like to know more? Click here to find out more details!

FME Hub user chrisatsafe just uploaded a new web_connection to the FME Hub.Web Service Setup InstructionsCreate an Auth client ID. See Creating OAuth 2.0 to Access Google Protocols for more information. Fill in your client id and client secret into the Google Cloud Al Auth webservice. See the Managing Web Services documentation for more details on how to manage the webservice Would you like to know more? Click here to find out more details!

FME Hub user chriswilson just uploaded a new transformer to the FME Hub.Python caller that takes in 'attr_name' and 'attr_value' attributes, searches for attr_name in the incoming feature's attribute list and will update the values of any matched attributes.Relies on firstly features being counted - hence also taking in a _count attribute that will be used to group features - and then all of their attribute names having been exposed as 'attr_name' and values as 'attr_value' in an AttributeExploder previously, then some other work having occurred to for example join or modify those attributes (e.g. mapping attribute values to domain codes) and also some tidying of that work so that duplicate records or null values are removed from 'attr_name' and 'attr_value', so that the result is you have at least some attributes from your original features that need to be updated but you don't know which ones that will be going into the process run. Hence this is a dynamic transformer.For example in

FME Hub user konnorporter just uploaded a new transformer to the FME Hub.Takes a set of points with a start/end point and creates a minimum spanning length network/tree.The parameter Start/End Node determines which node(s) to use as a seed for the algorithm.0 or any false-ish value means not a starting node, while 1 (or any positive result) results in that feature being used as a starting node.Placing a 0 in that parameter, or giving a parameter that is false-ish, will result in the first node being used as the seed.Choosing multiple starting points will result in a forest of Minimum Spanning Trees, i.e. several disconnected networks. This is useful for if you want to add more nodes to a pre-existing network, by setting all the nodes in that network to 1, and the nodes yet to be added to 0.Would you like to know more? Click here to find out more details!

FME Hub user haider just uploaded a new transformer to the FME Hub.Transposes attributes so that the values in any selected Column Attribute are transposed into their own individual columns. The corresponding selected Row Attribute(s) will also be transposed in accordance with the selected column and its attributes. Aggregation works by grouping the results into desired Group-By column categories. This transformer also allows you to add a suffix to the end of the newly transposed column names in order to maintain clarity and produce distinction between previously defined data columns.(Example):The table below shows the inputs offered by the transformer:The data structure below shows the data before it is transposed. The next image shows the state of data after it has gone through the transformer using the inputs specified in Image 1. This displays the tranposing + aggregation behavior of the transformer.NotesThe transformer will not preserve geometry. It only works on tabular data. New

FME Hub user haider just uploaded a new transformer to the FME Hub.Transposes attributes so that the values in any selected Column Attribute are transposed into their own individual columns. The corresponding selected Row Attribute(s) will also be transposed in accordance with the selected column and its attributes. Aggregation works by grouping the results into desired Group-By categories. This transformer also allows you to add a suffix to the end of the newly transposed column names in order to maintain clarity and distinction between previously defined data. ### Examples The table below shows the original input features:- Column Attribute -> Allows you to choose one column to tranpose their values into individual columns. (REQUIRED)- Row Attribute(s) -> Allows you to choose multiple columns so that their values can be transposed under the new column headers after transposition. (REQUIRED)- Group By Attribute(s) -> Allows you to specify the columns that need to be aggregate

FME Hub user dmitribagh just uploaded a new transformer to the FME Hub.takes the extents and a simple text input in a form of comma- or semicolon-separated list of objects which a user would like to extract from OpenStreetMap database.This is a highly experimental transformer and should rather serve for inspiration and experimentation than real work - the current results generated by OpenAI API do not always return the expected or satisfactory results.As an experimental transformer, it wasn't passed through a thorough QC process, it does not handle all possible errors or exceptions. Feel free to look inside and edit the transformer as much as your imagination allows and adjust it for your needs.How does it work?The transformer populates a pre-created prompt with parameters such as extents of the are of interest, and the keywords defining the objects that will be read from the OSM database. The prompt is submitted to OpenAI API, which turns it into a Overpass QL (Query Language) query.

FME Hub user abizien just uploaded a new transformer to the FME Hub.Use ip-api.com API to geolocate IP addresses.The API accept 45 requests per minute from an IP address. Entities are decelerated by this transformer.Would you like to know more? Click here to find out more details!

FME Hub user abizien just uploaded a new transformer to the FME Hub.Runs a program or operating system command, and waits for it to exit before continuing the translation.The ouptut of the command is redirected in the "_output" attribute If the command line return an error, the entity get rejected.Would you like to know more? Click here to find out more details!

FME Hub user dmitribagh just uploaded a new transformer to the FME Hub.Takes a text input representing a geographic location, and creates a center point and a bounding box around it with a number of attributes characterizing the location.This is a highly experimental transformer and should rather serve for inspiration and experimentation than real work - the current results generated by OpenAI API do not always return the expected or satisfactory results.As an experimental transformer, it wasn't passed through a thorough QC process, it does not handle all possible errors or exceptions. Feel free to look inside and edit the transformer as much as your imagination allows and adjust it for your needs.How does it work?The transformer takes a text string or a text attribute as an input, and sends a detailed prompt to OpenAI API. The prompt includes the requirements to the found location and the necessary actions if the location is not found. It also describes the attributes that should be a

FME Hub user sashal just uploaded a new transformer to the FME Hub.Generate an Esri ArcGIS Enteprise Portal Token This transformer generates a token for ArcGIS Enterprise. The custom transformer uses the httpCaller transformer to make a REST API call to the ArcGIS REST API and outputs the token generated as an attribute. All attributes needed to populated the REST call are parameterized.Would you like to know more? Click here to find out more details!

FME Hub user sashal just uploaded a new transformer to the FME Hub.Manage an Existing Workflow Manager Job This transformer modifies status of one or more existing jobs in ArcGIS Workflow Manager. The custom transformer uses the httpCaller transformer to make a REST API call to the ArcGIS Workflow Manager REST API and outputs the job id of the job managed. All attributes needed to populated the REST call are parameterized.Would you like to know more? Click here to find out more details!

FME Hub user jakethepainter just uploaded a new template to the FME Hub.Sample of a workspace that uses HttpCaller to read AGOL attachments selectivelyWould you like to know more? Click here to find out more details!

FME Hub user mouheeb just uploaded a new transformer to the FME Hub.The "Arabic-to-English Speller" is a custom FME transformer that converts Arabic words to their English spellings. It takes an input attribute called "Arabic_Word" and generates an output attribute called "Spelled_Word" with the corresponding English spelling.Example:Input Attribute: Arabic_Word = "مرحبا"Output Attribute: Spelled_Word = "marhaba"The "Arabic-to-English Speller" simplifies the process of converting Arabic text to English spellings, making it useful for data integration, validation, and geospatial tasks.Would you like to know more? Click here to find out more details!

FME Hub user martin_ekstrand just uploaded a new transformer to the FME Hub.Makes scheduling cache rebuilds on Map or Image services posssbile by executing a rebuild cache job on a Map service or Image service in ArcGIS Enterprise using the ArcGIS Server REST API. Then checks the job's log if the job succeeded or failed.Runs one time per feature. You can have one feature per service name and set service name to an attribute containing your service name.May also be run in a check job status only mode for making a 2 step automation possible for large jobs- first submit the caching job and then run another workspace at a later date to check how the job wentWould you like to know more? Click here to find out more details!

FME Hub user chrisatsafe just uploaded a new transformer to the FME Hub.OverviewThe AmazonBedrockConnector transformer for FME enables users to seamlessly integrate AWS Bedrock services with their spatial data transformation workflows in FME. AWS Bedrock is a managed service provided by Amazon Web Services (AWS) that simplifies the process of deploying, managing, and scaling big data applications and workflows on the cloud. By leveraging the AmazonBedrockConnector, users can efficiently transfer data between FME and AWS Bedrock, facilitating a wide range of cloud-based data processing and analysis tasks.FeaturesEasy Integration: Connect to AWS Bedrock directly from within your FME workflows, allowing for smooth data exchange between your local and cloud environments.Scalable Data Processing: Utilize AWS Bedrock's scalable infrastructure to handle large datasets and complex spatial data processing tasks without the need for extensive hardware investments.Secure Data Management: Ensure y

FME Hub user sashal just uploaded a new transformer to the FME Hub.Add Linked Attachment to ArcGIS Workflow Manager JobThis transformer adds a linked attachment to Workflow Manager by using an httpCaller that posts to the ArcGIS Workflow Manager REST API. All attributes needed to populated the REST call are parameterized.Dependencies to using this transformer:ArcGIS Enterprise with ArcGIS Workflow Manager Server (version 10.9.1 or 11.x)Web Connection to ArcGIS Enterprise (how to establish FME Web Connetion to ArcGIS Enterprise Portal) User with web connection must have privileges to update Workflow ItemExisting Workflow Item in Workflow ManagerWould you like to know more? Click here to find out more details!