What is an SDK? Client tooling does not replace service validation
Explain SDKs in model integration, distinguish APIs and models and verify types, retries and version changes.
Understand the concept
An SDK supplies libraries, types or examples for a platform. Model SDKs often wrap authentication, requests and responses but are not models or availability guarantees. Installation only establishes dependency access. Validate real calls, errors and changed defaults after upgrades.
Libraries reduce repeated code without changing service contracts
OpenAI’s Python SDK provides typed calls and error handling; API references define accepted requests. A library version may lag service features. HTTP bypasses some wrapper limits but needs manual parsing. Inspect retry and timeout defaults instead of copying minimal examples. Changing wrappers does not automatically improve model accuracy.
Test normal and error responses with one public sample
For public classification, check outputs and identifiers and test invalid-parameter handling. Do not swallow errors into empty strings that downstream treats as valid. Record library settings and compare equivalent HTTP when useful. No package installation or paid request occurred here. For streams, validate completion rather than only a few chunks.
Recheck defaults when upgrading client packages
Keep recovery versions and replay cases after dependency changes. Types, exception names and retry defaults can affect compatibility despite successful imports. Include integration and diagnosis, not example line counts. Mix SDK and HTTP where appropriate with consistent logging and errors. Maintain understanding of actual requests to distinguish local failures from remote service problems.
Checked sources
These sources support the concepts and methods described here. Examples and test scope are labeled separately; check the version of the tools you use.