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Quick Start

From zero to your first routed AI response in under 5 minutes.

Step 1: Install Routerly​

# macOS / Linux
curl -fsSL https://www.routerly.ai/install.sh | bash

# Windows (PowerShell)
powershell -c "irm https://www.routerly.ai/install.ps1 | iex"

After the installer finishes, start the service if it isn't already running:

routerly start

Step 2: Create Your Admin Account​

Open the dashboard:

http://localhost:3000/dashboard

On first launch you will see the Setup screen. Enter an email address and password to create the admin account. This account has full control over all settings.

Step 3: Register a Model​

A model is a specific LLM available through a provider. You register it once with its API key; Routerly reuses it across all projects.

Via CLI:

# OpenAI
routerly model add --id gpt-5-mini --provider openai --api-key sk-YOUR_KEY

# Anthropic
routerly model add --id claude-haiku-4-5 --provider anthropic --api-key sk-ant-YOUR_KEY

# Ollama (local — no API key needed)
routerly model add --id ollama/qwen3:4b --provider ollama

Built-in pricing presets are available for well-known model IDs. If a preset is found, you do not need to specify --input-price / --output-price.

Via Dashboard → Models → + New Model: fill in the Model ID, Provider, and API Key. Pricing fields are pre-filled automatically for known models.

Step 4: Create a Project​

A project is an isolated workspace. It gets its own Bearer token and its own routing configuration.

routerly project add \
  --name "My App" \
  --slug my-app \
  --models gpt-5-mini

The command prints your project token — a string starting with sk-lr-. Save it; you'll use it in your application.

Token visibility

The project token is shown only once after creation. Store it securely. You can generate a new token from the dashboard at any time.

Step 5: Make Your First API Call​

Point any OpenAI-compatible SDK at Routerly and use your project token as the API key.

Python​

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:3000/v1",
    api_key="sk-lr-YOUR_PROJECT_TOKEN",
)

response = client.chat.completions.create(
    model="gpt-5-mini",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

TypeScript / Node.js​

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'http://localhost:3000/v1',
  apiKey: 'sk-lr-YOUR_PROJECT_TOKEN',
});

const response = await client.chat.completions.create({
  model: 'gpt-5-mini',
  messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0].message.content);

curl​

curl http://localhost:3000/v1/chat/completions \
  -H "Authorization: Bearer sk-lr-YOUR_PROJECT_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-5-mini","messages":[{"role":"user","content":"Hello!"}]}'

Step 6: Check Usage​

Open Usage in the dashboard or use the CLI:

routerly report usage          # aggregated by model, this month
routerly report calls --limit 10   # last 10 request records

Next Steps​