Streaming and Vision: Real-time Responses and Image Understanding

Streaming Responses

By default, the API waits until the full response is generated before returning. Streaming mode lets you receive content incrementally as it is generated, creating a typewriter-like real-time output effect that significantly improves user experience.

Python Streaming Example

import anthropic

client = anthropic.Anthropic()

with client.messages.stream(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a short poem about coding"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

TypeScript Streaming Example

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

const client = new Anthropic();

const stream = client.messages.stream({
  model: "claude-sonnet-4-20250514",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Write a short poem about coding" }],
});

for await (const event of stream) {
  if (event.type === "content_block_delta" && event.delta.type === "text_delta") {
    process.stdout.write(event.delta.text);
  }
}

Key Event Types

• message_start: Message begins, includes model info
• content_block_start: Content block begins
• content_block_delta: Incremental text content (text_delta)
• content_block_stop: Content block ends
• message_delta: Message-level update (includes stop_reason and usage)
• message_stop: Message complete

Vision Capabilities

Claude supports image inputs and can analyze image content, extract text, understand charts, and more. Images are passed via image type content blocks.

Sending Base64 Images

import anthropic
import base64

client = anthropic.Anthropic()

with open("screenshot.png", "rb") as f:
    image_data = base64.standard_b64encode(f.read()).decode("utf-8")

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "image",
                "source": {
                    "type": "base64",
                    "media_type": "image/png",
                    "data": image_data
                }
            },
            {"type": "text", "text": "Describe what you see in this image"}
        ]
    }]
)

print(message.content[0].text)

Sending URL Images

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {
                "type": "image",
                "source": {
                    "type": "url",
                    "url": "https://example.com/chart.png"
                }
            },
            {"type": "text", "text": "Analyze the trends in this chart"}
        ]
    }]
)

Supported Image Formats

• JPEG, PNG, GIF, WebP
• Maximum 20MB per image
• Up to 20 images per request
• Recommended to keep the shorter side under 1568 pixels for optimal performance

Combining Streaming and Vision

You can use Streaming and Vision together to analyze images in real-time with incremental output:

with client.messages.stream(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": [
            {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": image_data}},
            {"type": "text", "text": "Describe this image in detail"}
        ]
    }]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

FAQ

Does streaming affect output quality?

No. Streaming only changes how content is delivered, not how it is generated. The final concatenated text is identical to non-streaming mode.

Can Vision recognize text in images?

Yes. Claude has excellent OCR capabilities and can extract text from screenshots, document photos, and handwritten notes. It also handles complex tables and formulas reasonably well.

How do I send multiple images?

Add multiple image type content blocks sequentially in the content array. Claude can understand multiple images simultaneously and perform comparative analysis.

How do I get token usage in streaming mode?

Token usage information is returned in the message_delta event, typically at the end of the stream. The Python SDK's stream.get_final_message() method provides the complete usage statistics directly.