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

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 credentials from OpenAI or Azure OpenAI
  6. Try out the example use cases!

You can find technical documentation about the OpenAI connector on Mendix Docs.


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 detailed documentation about the OpenAI Connector on Mendix Docs.

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: 2.2.0
Framework Version: 9.24.0
Release Notes: We created two additional examples demonstrating new use cases of vector embeddings. The first example shows how you can identify and visualize clusters within a textual dataset. The second use case implements a semantic search based on similarity of vector embeddings. Lastly, we made small improvements to the existing examples.
Version: 2.1.0
Framework Version: 9.24.0
Release Notes: We made a number of small improvements to clarify the working of the underlying interactions with the large language models. In the example implementations “Product description” and “Complexity reduction”, the user prompt and system prompt are now shown in the UI before the model is invoked. These prompts were also improved to protect against prompt injections. Furthermore, we have extended the chat implementation with optional JSON mode. It is now possible to instruct the model to respond with JSON in the chatbot-like setting, also taking into account the chat history.
Version: 2.0.0
Framework Version: 9.24.0
Release Notes: We added two example implementations based on the Embeddings API. In a smaller technical example, the Embeddings API is invoked for a list of String inputs and their embedding vectors are retrieved and shown in the UI. In a second, more complex example, an implementation of retrieval augmented generation (RAG) is demonstrated. For this implementation use case to work, you will need to provide an external PostgreSQL database that has the ‘pgvector’ extension installed. You’ll find detailed instructions on this in the UI of the running app.
Version: 1.3.0
Framework Version: 9.24.0
Release Notes: We have added two showcase implementations for JSON mode of chat completions: one to generate JSON strings based on user input prompts, plus an example implementation that generates small batches of demo data (Car records) to be stored in the app database. Furthermore, the side menu is now compatible with Mx10 and we did some general styling improvements.
Version: 1.2.1
Framework Version: 9.24.0
Release Notes: New Years Cleaning: We removed unused Marketplace modules and cleaned up the jar files in the userlib folder so that the Showcase app is now out of the box compatible with Mendix Studio Pro 10.6.0.