Anthropic Messages API — Streaming & Advanced Patterns
Overview
The Messages API is the only inference endpoint. Every Claude interaction goes through client.messages.create(). This skill covers streaming, system prompts, vision, and structured output.
Prerequisites
- Completed
clade-install-auth - Familiarity with
clade-hello-world
Instructions
Step 1: Streaming Responses
import Anthropic from '@claude-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 haiku about TypeScript.' }],
});
for await (const event of stream) {
if (event.type === 'content_block_delta' && event.delta.type === 'text_delta') {
process.stdout.write(event.delta.text);
}
}
const finalMessage = await stream.finalMessage();
console.log('\n\nTokens:', finalMessage.usage);
Step 2: Vision — Sending Images
const message = await 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: fs.readFileSync('screenshot.png').toString('base64'),
},
},
{ type: 'text', text: 'Describe what you see in this image.' },
],
}],
});
Step 3: JSON / Structured Output
const message = await client.messages.create({
model: 'claude-sonnet-4-20250514',
max_tokens: 1024,
system: `Respond with valid JSON only. Schema: { "summary": string, "sentiment": "positive"|"negative"|"neutral", "confidence": number }`,
messages: [{ role: 'user', content: 'Analyze: "This product exceeded my expectations!"' }],
});
const result = JSON.parse(message.content[0].text);
// { summary: "Very positive review", sentiment: "positive", confidence: 0.95 }
Python Streaming
import anthropic
client = anthropic.Anthropic()
with client.messages.stream(
model="claude-sonnet-4-20250514",
max_tokens=1024,
messages=[{"role": "user", "content": "Write a haiku about Python."}],
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)
print(f"\nTokens: {stream.get_final_message().usage}")
Output
- Non-streaming: Full
Messageobject withcontent,usage,stop_reason - Streaming events:
message_start— message metadatacontent_block_start— new content block beginningcontent_block_delta— incremental text (text_delta) or tool input (input_json_delta)message_delta— finalstop_reasonand usagemessage_stop— stream complete
Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| overloaded_error (529) | Anthropic API temporarily overloaded | Retry with exponential backoff; use client.messages.create with built-in retries |
| rate_limit_error (429) | Exceeded RPM or TPM | Check retry-after header. See clade-rate-limits |
| invalid_request_error | Image too large or bad format | Max 20 images per request. Supported: PNG, JPEG, GIF, WebP. Max 5MB each |
Key Parameters
| Parameter | Type | Description |
|-----------|------|-------------|
| model | string | Required. Model ID (e.g. claude-sonnet-4-20250514) |
| max_tokens | int | Required. Maximum output tokens (1–8192 typical) |
| messages | array | Required. Alternating user/assistant messages |
| system | string | Optional. System prompt for behavior/persona |
| temperature | float | Optional. 0.0–1.0, default 1.0 |
| top_p | float | Optional. Nucleus sampling threshold |
| stop_sequences | string[] | Optional. Custom stop strings |
| stream | boolean | Optional. Enable SSE streaming |
Examples
See Step 1 (streaming), Step 2 (vision with base64 images), and Step 3 (structured JSON output) above. Python streaming example included.
Resources
Next Steps
See clade-embeddings-search for tool use and function calling patterns.