Read configured saved credentials in generated Python clients

[glenn-jocher]

Generated Python clients currently resolve explicit and environment API keys, so a user logged in through yolo login still has to supply credentials again to the standalone SDK. Add optional consumer configuration for reading that existing JSON settings key in the shared runtime used by both sync and async clients.

Resolution is explicit key → environment → saved key; an explicit empty string disables authentication. Reads preserve the settings writer's OS directory and fallback selection, never modify settings, and tolerate absent or malformed files. The SDK remains independent of the ML package and Torch. All behavior lives in the generator, so downstream regeneration retains it.

The new configuration is necessary to describe a consumer-owned credential file without hardcoding Ultralytics into the generic generator. The implementation extends the existing runtime and replaces the two client-level resolvers; no additional runtime files or credential stores.

Validation: 19 generator tests, typecheck, lint, unused-code check, generated Python Ruff, SDK tests on Python 3.11/3.14, and actual installed yolo login/logout with both SDK clients against a local HTTP server using isolated settings and dummy credentials. The HTTP validation also covers explicit/environment precedence, empty-string opt-out, malformed settings, unchanged files, and no ML imports.

Consumer configuration and automatic SDK-only release versioning follow in ultralytics/sdk; no API contract change is required.

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Generated Python SDK clients now optionally read saved JSON credentials through generator configuration, preserving explicit and environment key precedence while allowing yolo login credentials to be reused.

📊 Key Changes

• Added optional apiKey.settings configuration for the settings directory, environment override, filename, and JSON key.
• Moved API-key resolution into the shared generated runtime used by synchronous and asynchronous clients.
• Implemented precedence of explicit key, environment variable, then saved settings; an explicit empty string disables authentication.
• Added OS-specific settings paths, writer-compatible fallback directories, and safe handling for missing, malformed, or unreadable files without modifying them.
• Updated the Python generator test to verify resolver usage in generated clients and runtime environment-key handling.

🎯 Purpose & Impact

• Generated SDK users can reuse credentials stored by the configured settings writer without installing or importing the ML package or Torch.
• Both sync and async clients use the same saved-credential behavior, and regenerated SDKs retain the configuration-driven implementation.

[UltralyticsAssistant]

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[UltralyticsAssistant]

🔍 PR Review

_{Made with ❤️ by Ultralytics Actions}

Reviewed the configuration schema, generated runtime resolver, sync and async client wiring, fallback handling, and existing generator coverage. I found no concrete correctness, compatibility, security, or performance issue in the diff. LGTM.

[UltralyticsAssistant]

🎉 PR #47 has been merged—thank you, @glenn-jocher, for this valuable contribution!

“Great things are done by a series of small things brought together.” — Vincent van Gogh

This work brings together configurable saved-credential support, shared sync and async API-key resolution, explicit and environment-key precedence, and safe fallback handling—allowing generated Python SDKs to reuse yolo login credentials without requiring the ML package or Torch.