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Adding AI to IntelliJ IDEA using Continue and Generative APIs

Reviewed on 14 February 2025Published on 14 February 2025

AI-driven coding is revolutionizing software development by automating repetitive tasks, generating code snippets, improving code quality, and identifying potential bugs. By integrating AI-powered tools, developers can significantly enhance productivity and optimize workflows. This guide will help you integrate AI-powered code models into JetBrain’s IntelliJ IDEA using Continue and Scaleway’s Generative APIs.

Before you startLink to this anchor

To complete the actions presented below, you must have:

  • A Scaleway account logged into the console
  • Owner status or IAM permissions allowing you to perform actions in the intended Organization
  • A valid API key for API authentication
  • Installed IntelliJ IDEA on your local machine.

You can install Continue from the JetBrains marketplace:

  1. Open IntelliJ IDEA and go to Preferences (Ctrl+Alt+S on Windows/Linux, Cmd+, on macOS).
  2. Navigate to Plugins, then click Marketplace.
  3. Search for Continue and click Install.
  4. Restart IntelliJ IDEA after installation.

Configure Continue to use Scaleway’s Generative APIsLink to this anchor

Configure Continue through the graphical interfaceLink to this anchor

To link Continue with Scaleway’s Generative APIs, you can use built-in menus from Continue in IntelliJ IDEA.

  • Click Continue in the menu on the right. .
  • In the prompt section, click on Select model dropdown, then on Add Chat model.
  • Select Scaleway as provider.
  • Select the model you want to use (we recommend Qwen 2.5 Coder 32b to get started with).
  • Enter your Scaleway secret key.
    Tip

    To start with, we recommend you use a Scaleway secret key having access to your default Scaleway project.

These actions will edit automatically your config.json file. To edit it manually, see Configure Continue through configuration file.

Note

Embeddings and autocomplete models are not yet supported through graphical interface configuration. To enable them, you need to edit the configuration manually, see Configure Continue through configuration file.

Configure Continue through configuration fileLink to this anchor

To link Continue with Scaleway’s Generative APIs, you need to configure the settings file:

  1. Locate your Continue configuration directory:
    • Linux/macOS: ~/.continue/
    • Windows: %USERPROFILE%\.continue\
  2. Create a config.json file inside this directory.
  3. Add the following configuration:
    {
    "models": [
    {
    "model": "qwen2.5-coder-32b-instruct",
    "title": "Qwen2.5 Coder",
    "provider": "scaleway",
    "apiKey": "###SCW_SECRET_KEY###"
    }
    ],
    "embeddingsProvider": {
    "model": "bge-multilingual-gemma2",
    "provider": "scaleway",
    "apiKey": "###SCW_SECRET_KEY###"
    },
    "tabAutocompleteModel": {
    "model": "qwen2.5-coder-32b",
    "title": "Qwen2.5 Coder Autocomplete",
    "provider": "scaleway",
    "apiKey": "###SCW_SECRET_KEY###"
    }
    }
  4. Save the file and restart IntelliJ IDEA.
Tip

For more details on configuring config.json, refer to the official Continue documentation. If you want to limit access to a specific Scaleway Project, you should add the field "apiBase": "https://api.scaleway.ai/###PROJECT_ID###/v1/" for each model (ie. models, embeddingsProvider and tabAutocompleteModel) since the default URL https://api.scaleway.ai/v1/ can only be used with the default project.

Activate Continue in IntelliJ IDEALink to this anchor

After configuring the API, activate Continue in IntelliJ IDEA:

  • Open the Command Search (PressShift twice quickly on Windows/Linux/macOS).
  • Type "Continue" and select the appropriate command to enable AI-powered assistance.
Important

Enabling tab completion may lead to higher token consumption as the model generates predictions for every keystroke. Be mindful of your API usage and adjust settings accordingly to avoid unexpected costs. For more information, refer to the official Continue documentation.

Going furtherLink to this anchor

You can add additional parameters to configure your model behaviour by editing config.json. For instance, you can add the following systemMessage value to modify LLM messages "role":"system" and/or "role":"developer" and provide less verbose answers:

{
"models": [
{
"model": "...",
"systemMessage": "You are an expert software developer. You give concise responses."
}
]
}
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