Integração drop-in com o SDK da Anthropic

npm install @anthropic-ai/sdk

pip install anthropic

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.TOQAN_API_KEY,
  baseURL: 'https://router.toqan.ai/eu/v3/anthropic',
});

import os
import anthropic

client = anthropic.Anthropic(
    api_key=os.environ["TOQAN_API_KEY"],
    base_url="https://router.toqan.ai/eu/v3/anthropic",
)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.TOQAN_API_KEY,
  baseURL: 'https://router.toqan.ai/eu/v3/anthropic',
});

const message = await client.messages.create({
  model: 'anthropic/claude-sonnet-5',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Explain the Toqan Router AI Gateway in one paragraph.' },
  ],
});

const block = message.content[0];
if (block.type === 'text') {
  console.log(block.text);
}

import os
import anthropic

client = anthropic.Anthropic(
    api_key=os.environ["TOQAN_API_KEY"],
    base_url="https://router.toqan.ai/eu/v3/anthropic",
)

message = client.messages.create(
    model="anthropic/claude-sonnet-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Explain the Toqan Router AI Gateway in one paragraph."}],
)

print(message.content[0].text)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.TOQAN_API_KEY,
  baseURL: 'https://router.toqan.ai/eu/v3/anthropic',
});

const stream = client.messages.stream({
  model: 'anthropic/claude-sonnet-5',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Write a haiku about AI routing.' },
  ],
});

stream.on('text', (text) => {
  process.stdout.write(text);
});

await stream.finalMessage();

import os
import anthropic

client = anthropic.Anthropic(
    api_key=os.environ["TOQAN_API_KEY"],
    base_url="https://router.toqan.ai/eu/v3/anthropic",
)

with client.messages.stream(
    model="anthropic/claude-sonnet-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a haiku about AI routing."}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: process.env.TOQAN_API_KEY,
  baseURL: 'https://router.toqan.ai/eu/v3/anthropic',
});

const message = await client.messages.create({
  model: 'anthropic/claude-sonnet-5',
  max_tokens: 1024,
  tools: [
    {
      name: 'get_weather',
      description: 'Get the current weather for a location',
      input_schema: {
        type: 'object',
        properties: {
          location: { type: 'string', description: 'City name, e.g. Amsterdam' },
        },
        required: ['location'],
      },
    },
  ],
  messages: [
    { role: 'user', content: 'What is the weather in Amsterdam?' },
  ],
});

for (const block of message.content) {
  if (block.type === 'tool_use') {
    console.log(`Tool: ${block.name}`, block.input);
  }
}

import os
import anthropic

client = anthropic.Anthropic(
    api_key=os.environ["TOQAN_API_KEY"],
    base_url="https://router.toqan.ai/eu/v3/anthropic",
)

message = client.messages.create(
    model="anthropic/claude-sonnet-5",
    max_tokens=1024,
    tools=[
        {
            "name": "get_weather",
            "description": "Get the current weather for a location",
            "input_schema": {
                "type": "object",
                "properties": {
                    "location": {"type": "string", "description": "City name, e.g. Amsterdam"},
                },
                "required": ["location"],
            },
        }
    ],
    messages=[{"role": "user", "content": "What is the weather in Amsterdam?"}],
)

for block in message.content:
    if block.type == "tool_use":
        print(f"Tool: {block.name}", block.input)

const message = await client.messages.create({
  model: 'openai/gpt-5.6-sol',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Explain machine learning' }],
});

message = client.messages.create(
    model="openai/gpt-5.6-sol",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Explain machine learning"}],
)