Claude API in Python with side-channel system text

This walkthrough rebuilds the path from raw materials to a working system for: Part 3 — Call the Claude API in Python (same messages, system on the side). The focus is operable steps, explicit checks, and code that you can drop into a repo without guessing intent. For Overview, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Document the happy path and the recovery path together. Retries, human gates, and dead-letter handling are part of the product, not later polish.

import anthropic

client = anthropic.Anthropic()  # key from env

resp = client.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=300,
    system="You are a concise Python assistant.",
    messages=[
        {
            "role": "user",
            "content": "Why is system a parameter "
                       "here, not a message?",
        },
    ],
)
print(resp.content[0].text)

msgs = []

def ask(text: str) -> str:
    msgs.append(
        {"role": "user", "content": text}
    )
    resp = client.messages.create(
        model="claude-sonnet-4-5",
        max_tokens=300,
        system="You are a concise assistant.",
        messages=msgs,  # full history
    )
    reply = resp.content[0].text
    msgs.append(
        {"role": "assistant", "content": reply}
    )
    return reply

print(ask("Define a context window."))
print(ask("Now for a five-year-old."))
print(ask("Which answer was shorter?"))

pip install -r requirements.txt
export ANTHROPIC_API_KEY="sk-ant..."
python examples/part03_claude.py

Operational checklist

Operational checklist works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope.

Keep configuration outside application code. Environment files, secret stores, and feature flags belong in one place operators can audit without reading the whole graph.

Pin the interpreter and dependency lockfile before teaching the loop. Drift between laptop and CI is the most common silent break for API demos.

Add a smoke test that exercises the critical path in CI with fixtures, not live paid APIs, whenever budgets allow.

Document the happy path and the recovery path together. Retries, human gates, and dead-letter handling are part of the product, not later polish.

Pin the interpreter and dependency lockfile before teaching the loop. Drift between laptop and CI is the most common silent break for API demos.

Before promoting the stack, freeze versions, capture a golden transcript for the critical path, and confirm rollback steps. Shared environments need rate limits, tenancy checks, and a clear owner for secret rotation. Prefer boring reliability over clever one-off demos.

Batch note for ded6445166ef: keep provider keys out of the repo, set a per-session token ceiling, and store transcripts next to the eval fixtures so later model swaps stay comparable.

hardening note 0 works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Record timings and token or query cost next to functional results. Cost visibility early prevents surprise bills when the path moves from demo to shared environments.

Hardening detail 0/872: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

For hardening note 1, define the inputs, the owner of the step, and the exit criteria before changing code. Operators should be able to re-run the step from a known checkpoint without guessing hidden state. Document the happy path and the recovery path together. Retries, human gates, and dead-letter handling are part of the product, not later polish.

Hardening detail 1/872: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

When working through hardening note 2, write down the contract first: required inputs, success signal, and what happens on partial failure. That checklist keeps later code changes honest. Treat this stage as a contract between inputs and validated outputs. Name the artifacts, define success checks, and refuse silent partial completion.

Hardening detail 2/872: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.

hardening note 3 works best when treated as a measurable surface. Capture one golden transcript, one failure case, and the rollback note before expanding scope. Keep configuration outside application code. Environment files, secret stores, and feature flags belong in one place operators can audit without reading the whole graph.

Hardening detail 3/872: measure wall time, error class, and token spend for this note, then decide whether to keep the change based on a fixed question set rather than anecdote.