Documentation Index
Fetch the complete documentation index at:https://docs.llmrouter.app/llms.txt Use this file to discover all available models, tags, and features before exploring further.
TRAE Integration
TRAE (/treɪ/) is a developer-friendly IDE that offers AI Q&A, inline code completion, and powerful agentic programming workflows. Connecting TRAE to LLM Router gives you access to intelligent tag-based routing, automatic Skill injection, context optimization, Zero Data Retention (ZDR), and significant cost savings.Step 1: Install and Launch TRAE
Download and Install
Go to the TRAE website and download & install TRAE.
Step 2: Configure LLM Router in TRAE
Use your LLM Router API key to add models from LLM Router.Enter Configuration Details
- Provider: Select OpenAI Compatible (or OpenAI if available)
- Base URL:
https://api.llmrouter.app/v1 - API Key: Enter your LLM Router API Key (
sk_llmr_...) - Model: Enter any supported model in provider/model format, for example:
anthropic/claude-opus-4.6openai/gpt-5.4google/gemini-3.1-proxai/grok-4.20
Step 3: Get Started with TRAE + LLM Router
- Select your LLM Router model in TRAE.
- Start coding with AI assistance for:
- Feature implementation
- Code generation and refactoring
- Debugging and explanations
- Agentic workflows and automation
FAQ
Routing & Configuration
Routing rules, tags, and features like Zero Data Retention are managed in the LLM Router Dashboard. Any changes made there will automatically affect requests from TRAE.Connection Issues
- Double-check that your LLM Router API key is correct and active.
- Ensure the Base URL is set exactly to
https://api.llmrouter.app/v1 - Verify your internet connection.
- If issues persist, check the error message shown in TRAE.
Resources
- TRAE Website: trae.ai
- LLM Router Dashboard: Log in to manage your API keys, tags, Skills, and routing settings.