> ## Documentation Index
> Fetch the complete documentation index at: https://docs.verlon.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Get started with Verlon AI in under 5 minutes

## Before you begin

1. Sign up for a free account at [verlon.ai/signup](https://verlon.ai/signup)
2. Get your API key from the [Dashboard](https://verlon.ai/dashboard)
3. Create your first gate with your desired model configuration

## Install an SDK

Verlon is a drop-in gateway: you call it with the official OpenAI SDK (or
[Anthropic SDK](/integrations/anthropic-sdk)) in any language — no
Verlon-specific client required.

<CodeGroup>
  ```bash npm theme={null}
  npm install openai
  ```

  ```bash pnpm theme={null}
  pnpm add openai
  ```

  ```bash pip theme={null}
  pip install openai
  ```
</CodeGroup>

## Make your first request

Point the client at Verlon and pass your gate's ID as the model — Verlon
routes the request to whatever model the gate is configured for, with
fallbacks, spending caps, and logging applied on the way through.

<CodeGroup>
  ```typescript TypeScript theme={null}
  import OpenAI from 'openai';

  const client = new OpenAI({
    apiKey: process.env.VERLON_API_KEY,
    baseURL: 'https://api.verlon.ai/v1',
  });

  const response = await client.chat.completions.create({
    model: 'your-gate-id', // your gate — Verlon routes it
    messages: [
      { role: 'user', content: 'Explain quantum computing in simple terms' }
    ],
  });

  console.log(response.choices[0].message.content);
  ```

  ```javascript JavaScript theme={null}
  const OpenAI = require('openai');

  const client = new OpenAI({
    apiKey: process.env.VERLON_API_KEY,
    baseURL: 'https://api.verlon.ai/v1',
  });

  const response = await client.chat.completions.create({
    model: 'your-gate-id', // your gate — Verlon routes it
    messages: [
      { role: 'user', content: 'Explain quantum computing in simple terms' }
    ],
  });

  console.log(response.choices[0].message.content);
  ```

  ```python Python theme={null}
  import os
  from openai import OpenAI

  client = OpenAI(
      api_key=os.environ["VERLON_API_KEY"],
      base_url="https://api.verlon.ai/v1",
  )

  response = client.chat.completions.create(
      model="your-gate-id",  # your gate — Verlon routes it
      messages=[
          {"role": "user", "content": "Explain quantum computing in simple terms"}
      ],
  )

  print(response.choices[0].message.content)
  ```

  ```bash cURL theme={null}
  curl https://api.verlon.ai/v1/chat/completions \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $VERLON_API_KEY" \
    -d '{
      "model": "your-gate-id",
      "messages": [
        {"role": "user", "content": "Explain quantum computing in simple terms"}
      ]
    }'
  ```
</CodeGroup>

<Tip>
  Already calling OpenAI or Anthropic directly? You don't need the gate ID at
  all to start — swap `baseURL` and `apiKey`, keep your model names, and Verlon
  picks up the traffic. See [Migrate an existing app](/getting-started/migrate).
</Tip>

## What's Next?

<CardGroup cols={2}>
  <Card title="OpenAI SDK Integration" icon="plug" href="/integrations/openai-sdk">
    Streaming, tool calling, and the full migration guide
  </Card>

  <Card title="Gates & Routing" icon="route" href="/platform/gates">
    Understand how gates provide smart routing and fallbacks
  </Card>

  <Card title="Agent Tracing" icon="chart-gantt" href="/platform/agent-gates">
    Trace agent runs with the Verlon SDK — tasks, tools, and sessions
  </Card>

  <Card title="Dashboard Guide" icon="gauge" href="/dashboard/creating-gates">
    Deep dive into creating and configuring gates
  </Card>
</CardGroup>