LangChain Multi-Env Setup (Python)

Overview

A team ships a LangChain 1.0 service to staging with python-dotenv loading .env.staging into os.environ. Security audits — docker exec STAGING-POD env prints ANTHROPIC_API_KEY=sk-ant-api03-... in plain text. Anyone with kubectl exec, any sidecar, any core dump, any error tracker that auto-captures process env sees the key. This is pain P37: secrets loaded from .env in production containers leak via env.

A second failure chains. A developer runs the staging deploy from a shell where LANGCHAIN_ENV=production was set hours earlier. The loader picks the prod .env, staging answers with a prompt commit tuned only for the prod model tier, latency doubles. Two root causes: no type-safe env gate, no startup validation that would have caught the mismatched model id.

Both are one refactor: