Use AlphaNeural with Continue (VS Code and JetBrains)

Continue supports OpenAI API compatible providers by letting you set a custom apiBase. AlphaNeural is OpenAI-compatible, so the integration is mostly configuration.

Create a local secret for your AlphaNeural key

Continue can load secrets from .env files (workspace or global), then reference them from config.yaml.

Pick one of these locations (searched in this order):

• <workspace-root>/.env

• <workspace-root>/.continue/.env

• ~/.continue/.env (global)

Example ~/.continue/.env:

ALPHANEURAL_API_KEY=your_key_here

Configure Continue to use AlphaNeural

Edit (or create) your local config file:

• macOS/Linux: ~/.continue/config.yaml

• Windows: %USERPROFILE%\.continue\config.yaml

Minimal config using AlphaNeural as an OpenAI-compatible provider:

name: AlphaNeural
version: 0.0.1
schema: v1

models:
  - name: AlphaNeural Chat
    provider: openai
    model: qwen3
    apiBase: https://proxy.alfnrl.io/v1
    apiKey: ${{ secrets.ALPHANEURAL_API_KEY }}
    roles: [chat, edit, apply]

  - name: AlphaNeural Autocomplete
    provider: openai
    model: qwen3
    apiBase: https://proxy.alfnrl.io/v1
    apiKey: ${{ secrets.ALPHANEURAL_API_KEY }}
    roles: [autocomplete]

• Continue’s OpenAI provider supports overriding apiBase for OpenAI-compatible servers.

• Continue lets you reference secrets from .env using the secrets namespace.

• roles controls where the model is available (chat vs autocomplete, etc).

Reload Continue

If your model does not show up, reload VS Code so extensions re-read the config.

• Command palette: type Reload Window

For JetBrains, restarting the IDE is the simplest equivalent.

Select the model and run a smoke test

Open the Continue sidebar, choose AlphaNeural Chat, then try:

• “Summarise this file and suggest improvements”

• “Explain this stack trace and propose a fix”

Optional. Enable tools and vision explicitly

If Agent mode is disabled or tools are flaky, you can force capabilities in the model block.

capabilities: [tool_use, image_input]

This is especially useful when you are routing through proxies where capability auto-detection is imperfect.