Anthropic SDK Patterns
Overview
Production-ready patterns for the Anthropic SDK covering client management, error handling, type safety, and multi-tenant configurations.
Prerequisites
- Completed
anth-install-auth setup
- Familiarity with async/await patterns
- TypeScript 5+ or Python 3.10+
Pattern 1: Typed Wrapper with Retry
import Anthropic from '@anthropic-ai/sdk';
import type { Message, MessageCreateParams } from '@anthropic-ai/sdk/resources/messages';
class ClaudeService {
private client: Anthropic;
constructor(apiKey?: string) {
this.client = new Anthropic({
apiKey: apiKey || process.env.ANTHROPIC_API_KEY,
maxRetries: 3,
timeout: 60_000,
});
}
async complete(
prompt: string,
options: Partial<MessageCreateParams> = {}
): Promise<string> {
const message = await this.client.messages.create({
model: options.model || 'claude-sonnet-4-20250514',
max_tokens: options.max_tokens || 1024,
messages: [{ role: 'user', content: prompt }],
...options,
});
const textBlock = message.content.find((b) => b.type === 'text');
if (!textBlock || textBlock.type !== 'text') {
throw new Error(`No text in response: ${message.stop_reason}`);
}
return textBlock.text;
}
async *stream(prompt: string, model = 'claude-sonnet-4-20250514'): AsyncGenerator<string> {
const stream = this.client.messages.stream({
model,
max_tokens: 4096,
messages: [{ role: 'user', content: prompt }],
});
for await (const event of stream) {
if (event.type === 'content_block_delta' && event.delta.type === 'text_delta') {
yield event.delta.text;
}
}
}
}
Pattern 2: Multi-Turn Conversation Manager
import anthropic
from dataclasses import dataclass, field
@dataclass
class Conversation:
client: anthropic.Anthropic = field(default_factory=anthropic.Anthropic)
model: str = "claude-sonnet-4-20250514"
system: str = ""
messages: list = field(default_factory=list)
max_tokens: int = 4096
def say(self, user_message: str) -> str:
self.messages.append({"role": "user", "content": user_message})
response = self.client.messages.create(
model=self.model,
max_tokens=self.max_tokens,
system=self.system,
messages=self.messages,
)
assistant_text = response.content[0].text
self.messages.append({"role": "assistant", "content": assistant_text})
return assistant_text
@property
def token_count(self) -> int:
"""Estimate total tokens in conversation."""
return sum(len(str(m["content"])) // m .messages)
conv = Conversation(system=)
(conv.say())
(conv.say())
Pattern 3: Structured Output with Prefill
import json
import anthropic
client = anthropic.Anthropic()
def extract_structured(text: str, schema_description: str) -> dict:
"""Force JSON output using assistant prefill technique."""
message = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=1024,
messages=[
{"role": "user", "content": f"Extract data from this text as JSON.\n\nSchema: {schema_description}\n\nText: {text}"},
{"role": "assistant", "content": "{"}
]
)
json_str = "{" + message.content[0].text
return json.loads(json_str)
data = extract_structured(
"John Smith, 35, lives in NYC and works at Google as a PM.",
'{"name": str, "age": int, "city": str, "company": str, "role": str}'
)
Pattern 4: Multi-Tenant Client Factory
const clients = new Map<string, Anthropic>();
export function getClientForTenant(tenantId: string): Anthropic {
if (!clients.has(tenantId)) {
const apiKey = getApiKeyForTenant(tenantId);
clients.set(tenantId, new Anthropic({ apiKey }));
}
return clients.get(tenantId)!;
}
Pattern 5: Token-Aware Request Sizing
count = client.messages.count_tokens(
model="claude-sonnet-4-20250514",
messages=[{"role": "user", "content": long_document}],
system="You are a summarizer."
)
print(f"Input will use {count.input_tokens} tokens")
remaining_budget = 200_000 - count.input_tokens
max_tokens = min(4096, remaining_budget)
Error Handling
| Pattern | Use Case | Benefit |
|---|
SDK maxRetries | 429 / 5xx errors | Built-in exponential backoff |
| Prefill technique | Force JSON output | No regex parsing needed |
| Token counting | Long documents | Prevent context overflow |
| Client factory | Multi-tenant SaaS | Key isolation per customer |
Resources
Next Steps
Apply patterns in anth-core-workflow-a for tool use workflows.
