Lesson Content

The complete request structure.

A Messages API request (verify current parameter reference at docs.anthropic.com/en/api/messages):

{
"model": "claude-sonnet-4-6",
"max_tokens": 1024,
"system": "You are a helpful assistant for a software team.",
"messages": [
{"role": "user", "content": "Explain this function."},
{"role": "assistant", "content": "This function…"},
{"role": "user", "content": "What about the edge case?"}
],
"temperature": 0.0,
"stop_sequences": ["###END###"],
"metadata": {"user_id": "u_12345"}
}

Parameter reference.

model – Required. The Claude model ID. Always source from docs.anthropic.com/en/docs/about-claude/models. Do not hardcode from course examples.

max_tokens – Required in practice (technically optional in some SDK versions). Caps response length. Always set in production to prevent runaway token consumption.

system – Optional but almost always used in applications. The standing instruction context. Covered in depth in the next lesson.

messages – Required. Array of {role, content} objects. Alternates user/assistant turns. The full conversation history must be included – the API is stateless.

temperature – Controls output randomness. Range 0.0-1.0. For deterministic tasks (classification, extraction, structured output): 0.0. For creative tasks (writing, brainstorming): 0.7-1.0. Default is model-specific – set explicitly for production.

stop_sequences – Array of strings that, if generated, cause Claude to stop. Use for controlled output delimiters in structured outputs. Optional.

metadata.user_id – Associates requests with a user ID for Anthropic's safety systems. Not used by your application directly – passed to Anthropic. Recommended for user-facing applications.

The response structure.

{
"id": "msg_01XFDUDYJgAACzvnptvVoYEL",
"type": "message",
"role": "assistant",
"content": [{"type": "text", "text": "The function…"}],
"model": "claude-sonnet-4-6-20251001",
"stop_reason": "end_turn",
"stop_sequence": null,
"usage": {"input_tokens": 25, "output_tokens": 305}
}

stop_reason: end_turn (natural completion), max_tokens (hit limit), stop_sequence (hit a stop string), tool_use (requesting a tool call). If you see max_tokens frequently, your max_tokens ceiling is too low.

usage: Log this on every production request. Input + output tokens x price = request cost.