Anthropic Hello World

Overview

Three minimal examples covering the Claude Messages API core surfaces: basic text completion, vision (image analysis), and streaming responses.

Prerequisites

• Completed anth-install-auth setup
• Valid ANTHROPIC_API_KEY in environment
• Python 3.8+ with anthropic package or Node.js 18+ with @anthropic-ai/sdk

Instructions

Example 1: Basic Text Message (Python)

import anthropic

client = anthropic.Anthropic()

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Explain quantum computing in 3 sentences."}
    ]
)

# Response structure
print(message.content[0].text)       # The actual text response
print(f"ID: {message.id}")           # msg_01XFDUDYJgAACzvnptvVoYEL
print(f"Model: {message.model}")     # claude-sonnet-4-20250514
print(f"Stop: {message.stop_reason}")# end_turn
print(f"Usage: {message.usage.input_tokens}in / {message.usage.output_tokens}out")

Example 2: Vision — Analyze an Image (TypeScript)

import Anthropic from '@anthropic-ai/sdk';
import * as fs from 'fs';

const client = new Anthropic();

// From file (base64)
const imageData = fs.readFileSync('chart.png').toString('base64');

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: imageData,
        },
      },
      { type: 'text', text: 'Describe what this chart shows.' },
    ],
  }],
});

console.log(message.content[0].type === 'text' ? message.content[0].text : '');

Example 3: Streaming Response (Python)

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 APIs."}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

# Get final message with full metadata
final = stream.get_final_message()
print(f"\nTokens used: {final.usage.input_tokens}+{final.usage.output_tokens}")

Output

• Working code file with Claude client initialization
• Successful API response with text content
• Console output showing model response and usage metadata

Examples

Use the text example first when verifying credentials: send a fixed, short prompt and confirm that message.content[0].text is present before integrating the client into application code. Use the vision example only after that check passes and replace chart.png with a non-sensitive local fixture. For an interactive command-line feature, use the streaming example so text is emitted incrementally, then read the final message to capture token usage for logs or cost controls.

Error Handling

Error	HTTP Code	Cause	Solution
authentication_error	401	Invalid API key	Check ANTHROPIC_API_KEY
invalid_request_error	400	Bad params (e.g., empty messages)	Validate request body
rate_limit_error	429	Too many requests	Implement backoff (see anth-rate-limits)
overloaded_error	529	API temporarily overloaded	Retry after 30-60s
api_error	500	Server error	Retry with exponential backoff

Key API Parameters

Parameter	Required	Description
model	Yes	Model ID: claude-sonnet-4-20250514, claude-haiku-4-20250514, claude-opus-4-20250514
max_tokens	Yes	Maximum output tokens (model-dependent max)
messages	Yes	Array of {role, content} objects
system	No	System prompt (string or content blocks)
temperature	No	0.0-1.0, default 1.0
top_p	No	Nucleus sampling (use temperature OR top_p)
stop_sequences	No	Array of strings that stop generation
stream	No	Enable SSE streaming

Resources

• Messages API Reference
• Messages Examples
• Vision Guide

Next Steps

Proceed to anth-local-dev-loop for development workflow setup.