Claude API

Why It Matters

Claude offers a distinct approach to large language models. Anthropic’s focus on Constitutional AI and safety produces a model that follows instructions carefully and handles nuanced requests thoughtfully. The extended context window (up to 200K tokens) enables use cases impossible with smaller context models, like analyzing entire codebases, processing long documents, or maintaining extensive conversation history.

For many production applications, Claude’s characteristics make it preferable to alternatives. Complex reasoning tasks, detailed analysis, and nuanced writing often benefit from Claude’s training approach. The longer context means fewer workarounds for document processing and reduced complexity in RAG systems.

For AI engineers, the Claude API represents an important alternative to OpenAI. Different models excel at different tasks, and many teams use both, routing requests based on task type. Understanding Claude’s API, capabilities, and pricing enables informed decisions about which model to use where.

Implementation Basics

The Claude API shares concepts with OpenAI but has its own patterns:

Messages API is the primary endpoint. Send a list of user and assistant messages along with a system prompt. Claude responds with generated text. The conversation format enables multi-turn dialogue and few-shot prompting.

System prompts set Claude’s behavior and context. Unlike OpenAI where system messages are part of the message array, Claude has a dedicated system parameter. Use it for persona, instructions, and background context.

Tool use enables structured outputs and function calling. Define tools with JSON schemas, and Claude will output tool calls when appropriate. Combine tools with regular responses for flexible interactions.

Streaming delivers tokens progressively. Handle server-sent events to display responses as they generate. Claude’s streaming events include both text deltas and metadata.

Start with the Python SDK (anthropic package). Use Claude Sonnet for balanced performance and cost, Claude Opus for complex reasoning tasks. Set appropriate max_tokens based on expected response length. Leverage the long context for document processing, but be mindful of cost, as token pricing applies to input context too.