OpenAI Showcase App

Content Type: Sample
Categories: Connectors,Artificial Intelligence


OpenAI Showcase App

Showcase application that shows how to use the OpenAI Connector, which can be used to integrate generative AI - the technology powering ChatGPT - into a Mendix app.

This project contains eight example use cases:

  • Interactive chatbot with history
  • Product description generation
  • Text complexity reduction
  • Text to JSON transformation
  • Demo data creation
  • Postcard (image) generation
  • Embedding vector generation
  • Retrieval Augmented Generation in a chatbot scenario
  • Clustering of unstructured text data
  • Semantic search (books, single-column)
  • Semantic search (tickets, single-column, multi-column and multi-language)
  • Function calling with chat completions
  • Vision with chat completions


How to get started

  1. Download the app package (.mpk file) from this page
  2. Open the app in Studio Pro (double-click the MPK to import it)
  3. Run the app & view it
  4. Log in
  5. Configure the connection with API credentials from an OpenAI account* or an Azure account.
  6. Try out the example use cases!


You can find technical documentation about the OpenAI Connector and PgVector Knowledge Base on MxDocs.


* If you have signed up for an OpenAI account and are using free trial credits, note that these are only valid for three months after the account has been created (not after the API key has been created). For more details, see the OpenAI API reference


Use this app as an example of what you can do with the OpenAI Connector and how to use the connector in your own project.

You can find technical documentation about the OpenAI Connector and PgVector Knowledge Base on MxDocs.

Note: Each version of the Showcase app is only guaranteed to be compatible with the corresponding version of the OpenAI connector that is included in the app package. If you update the connector without updating the Showcase app, this may result in breaking changes in the example implementations. We therefore recommend updating with the newest version of the Showcase app instead of the OpenAI connector module.


Version: 2.7.0
Framework Version: 9.24.0
Release Notes: The Showcase app has been updated to include the OpenAI Connector v2.7.0 and the PgVector KnowledgeBase v1.2.0. We added a data manipulation page to the semantic search ticket example. This illustrates how changes to Mendix objects influence their corresponding records in a knowledge base. The underlying microflows makes use of operations from the PgVector Knowledge Base. Furthermore, we created a new example demonstration chat completions with vision where users can either take a picture with their webcam or upload an image from their drive and ask questions about it. Lastly, we removed outdated OpenAI models from the models enumeration.
Version: 2.6.0
Framework Version: 9.24.0
Release Notes: The Showcase app has been updated to include the OpenAI Connector v2.6.0 and the PgVector KnowledgeBase v1.1.0. We've added an example to illustrate the new OpenAI Connector function calling capabilities, which enable the LLM to intelligently decide when to call a predefined function microflow to gather additional information to include in the assistant response. In this example, users can ask questions about tickets in the application database. Additionally, we have replaced parts of the implementations of the two similarity search examples by the new operations from the PgVector Knowledge Base. The association between the chunk objects and the Mendix objects for which the chunks were created is now set automatically when the chunks are retrieved.
Version: 2.5.0
Framework Version: 9.24.0
Release Notes: We have replaced all vector database interaction logic regarding storing and retrieval of knowledge base chunks by operations of the new PgVectorKnowledgeBase module. This means that no custom query coding is required anymore by developers. As a result the example queries have been removed from the pages. Also it is possible now to store connection details for multiple vector databases in the same Mendix app.
Version: 2.4.0
Framework Version: 9.24.0
Release Notes: We have enhanced the semantic search example by suggesting search terms to the user and adding tickets in different languages to the dataset. This shows that OpenAI's LLMs are capable of handling non-English language tasks. As of this release, we support the text-embedding-3-large model in all embeddings examples. This model is particularly suitable for tasks involving multiple languages. In addition, selected configurations are now saved in the database for each example and operation, in order to ensure consistency and reduce repeated setup effort.
Version: 2.3.0
Framework Version: 9.24.0
Release Notes: We created an additional example where we show semantic search through a dataset of IT helpdesk tickets. This example demonstrates how the OpenAI connector combined with vector database logic can be leveraged to perform semantic search on data records in an application. Two variations are demonstrated, one where a single column is embedded for the search, the other one uses a multi-column approach. Furthermore, the values of the OpenAI model enumerations have been updated. We added gpt-4-turbo-preview, gpt-4-1106-preview and text-embeddings-3-small and we removed legacy models gpt-3.5-turbo-16k and gpt-4-32k. Lastly, the database connector module has been updated to the newest released version.