---
title: "Configure Generative AI Connection"
slug: "configure-generative-ai-connection"
description: "This article focuses on setting up your Test Modeller instance to utilize the Generative AI feature within the Curiosity Platform. "
tags: ["Integrations", "AI Accelerated", "Quality Modeller"]
updated: 2025-01-15T11:05:50Z
published: 2025-01-15T11:05:50Z
---

> ## Documentation Index
> Fetch the complete documentation index at: https://knowledge.curiositysoftware.ie/llms.txt
> Use this file to discover all available pages before exploring further.

# Configure Generative AI (Default) Connection

This article focuses on setting up your Quality Modeller instance to utilize the Generative AI feature within the Curiosity Platform. We will delve into the specifics of Generative AI and the Language Learning Models (LLMs) that we collaborate with for our cloud and on-premise deployments.

## Default Model

### Cloud Deployment

In the cloud version of Quality Modeller, Generative AI is pre-installed and automatically activated in your workspace. Should you wish to disable this feature, please contact your Curiosity account representative.

The cloud-based Quality Modeller utilizes OpenAI's GPT-4o. We advise you to review the [OpenAI privacy policy](https://openai.com/policies/privacy-policy) prior to leveraging any of the Generative AI capabilities with Quality Modeller.

### On-Premise Deployment

For on-premise deployments the Generative AI capability is disabled by default. To use this functionality it will need to be enabled in the docker-compose / environment variables for the installation.

Quality Modeller out-the-box supports Large Language Models from [OpenAI](https://openai.com/)and [Azure](https://azure.microsoft.com/en-gb/products/cognitive-services/openai-service). However, its flexible architecture means it can easily integrate with any homegrown LLM, or a specific LLM an organization is using within their infrastructure, depending on an organisations security policy.

Requirements for Configuring Generative AI

- Either an OpenAI or Azure OpenAI account.
- An API Key for the relevant models.
- A chat completions model (e.g. gpt-4o)

To configure the service, the following environment variables need to be set. This can be done by creating the **docker-compose-custom.yml** file to have the custom configuration. If you already have a **docker-compose-custom.yml** file with some custom configuration elements, we will simply be editing that file instead.

```shell
cp docker-compose-basic.yml docker-compose-custom.yml
```

Inside the **docker-compose-custom.yml** file, the **api** service's **environment** section needs to contain the environment variables listed below. If the **api** service does not exist in the YAML file, it needs to be added first - the **docker-compose-ad.yml** file can be used as an example for that.

| **Environment Variable** OPEN_AI_SOURCE | **Default Value** OpenAI | **Description** OpenAI to use OpenAI, Azure to use the Azure service. |
| --- | --- | --- |
| OPEN_AI_PROXY |  | Proxy URL if required to access the endpoints. |
| OPEN_AI_URL | [https://api.openai.com/v1/chat/completions](https://api.openai.com/v1/chat/completions) | Chat completions API endpoint |
| OPEN_AI_KEY |  | API Key for the chat completions model. |
| OPEN_AI_CHAT_MODEL | gpt-4o | Chat model. |
| GENERATIVE_AI_ENABLED | false | Generative AI enabled (true / false) for the instance. |
| GENERATIVE_AI_ENABLED_EMAILS |  | A comma separated list of emails whom should have access to generative AI feature. If empty all users will have access. |

## Related

- [Quality Modeller AI](/generative-ai.md)
- [ModelGPT - Create Models from Requirements](/modelgpt-create-models-from-requirements.md)
- [KnowledgeHub AI (unreleased)](/knowledgehub-ai.md)