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Kilo Code

Connect Kilo Code, the VS Code AI assistant, to LLMAI for intelligent code generation and assistance.

Model slugs in examples are illustrative. Confirm current availability in the live catalog and your account's /v1/models before use.

What This Does

Kilo Code is an AI-powered coding assistant for VS Code that helps with code generation, explanations, debugging, and refactoring. By connecting Kilo Code to LLMAI, you access a wide range of models through a single endpoint with consolidated billing.


Setup

Step 1: Install Kilo Code

  1. Open VS Code
  2. Go to the Extensions marketplace (Cmd+Shift+X or Ctrl+Shift+X)
  3. Search for Kilo Code
  4. Click Install

Step 2: Open Kilo Code Settings

  1. Click the Kilo Code icon in the VS Code sidebar
  2. Click the settings icon or navigate to Configuration
  3. Find the Providers section

Step 3: Configure LLMAI

Set up Kilo Code with LLMAI:

FieldValue
API ProviderOpenAI Compatible
Base URLhttps://api.llmai.dev/v1
API KeyYour LLMAI API key
Modelkimi-k2.7-code or deepseek-v4-pro

Get your API key from console.llmai.dev/keys.

Step 4: Save and Verify

  1. Save the configuration
  2. Open the Kilo Code chat panel
  3. Send a test message to confirm the connection

Use CaseModelDescription
Code generation & refactoringkimi-k2.7-codeMoonshot's code-tuned K2.7 — best for code generation
Code generationdeepseek-v4-proBest for writing and modifying code
Code explanationskimi-k2.6Superior reasoning for complex logic
Large filesminimax-m3Extended context window
Quick assistanceglm-5.1Fast and economical

Troubleshooting

API key rejected

Model not recognized

  • Select OpenAI Compatible provider type
  • Use exact model slugs from the Models reference

No response from AI

Slow responses

  • Switch to glm-5.1 for faster responses
  • Check your network connection

Notes

  • Kilo Code supports inline code suggestions and chat-based interactions
  • All token consumption is billed to your LLMAI account
  • Usage statistics appear in real-time on your LLMAI dashboard
  • Consider using different models for different tasks to optimize cost and performance

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