Streaming Output

Python

import anthropic

client = anthropic.Anthropic(api_key="your-api-key", base_url="https://aisupermarket.work")

with client.messages.stream(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a poem about winter"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

JavaScript

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

const client = new Anthropic({ apiKey: "your-api-key", baseURL: "https://aisupermarket.work" });

const stream = await client.messages.stream({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Write a poem about winter" }],
});

for await (const text of stream.textStream) {
  process.stdout.write(text);
}

curl

curl https://aisupermarket.work/v1/messages \
  -H "x-api-key: your-api-key" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "stream": true,
    "messages": [{"role": "user", "content": "Write a poem about winter"}]
  }'

Get the Final Result

Python

import anthropic

client = anthropic.Anthropic(api_key="your-api-key", base_url="https://aisupermarket.work")

with client.messages.stream(
    model="claude-opus-4-7",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

    # Get the full message object after the stream ends
    final_message = stream.get_final_message()
    print(f"\nTotal token count: {final_message.usage.input_tokens + final_message.usage.output_tokens}")

JavaScript

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

const client = new Anthropic({ apiKey: "your-api-key", baseURL: "https://aisupermarket.work" });

const stream = await client.messages.stream({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Hello" }],
});

for await (const text of stream.textStream) {
  process.stdout.write(text);
}

const finalMessage = await stream.getFinalMessage();
console.log(`\nTotal token count: ${finalMessage.usage.input_tokens + finalMessage.usage.output_tokens}`);

curl

# SSE streaming response. Each line starts with data:, and the final event includes usage information
curl https://aisupermarket.work/v1/messages \
  -H "x-api-key: your-api-key" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "stream": true,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

Async Streaming

Python

import asyncio
import anthropic

client = anthropic.AsyncAnthropic(api_key="your-api-key", base_url="https://aisupermarket.work")

async def main():
    async with client.messages.stream(
        model="claude-opus-4-7",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Write a poem"}],
    ) as stream:
        async for text in stream.text_stream:
            print(text, end="", flush=True)

asyncio.run(main())

JavaScript

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

const client = new Anthropic({ apiKey: "your-api-key", baseURL: "https://aisupermarket.work" });

// In Node.js, top-level await is enough; no extra wrapper is required
const stream = await client.messages.stream({
  model: "claude-opus-4-7",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Write a poem" }],
});

for await (const text of stream.textStream) {
  process.stdout.write(text);
}

curl

curl https://aisupermarket.work/v1/messages \
  -H "x-api-key: your-api-key" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-opus-4-7",
    "max_tokens": 1024,
    "stream": true,
    "messages": [{"role": "user", "content": "Write a poem"}]
  }'