feat: add S3ArtifactService with native async and atomic versioning

[miyannishar]

Summary

Adds S3ArtifactService — a BaseArtifactService implementation backed by Amazon S3, providing production-ready artifact storage for AWS deployments.

This supersedes #36 (my earlier attempt, closed for inactivity) and #29 (by @wmsnp). The final implementation takes the best from both: native async from #29 and the optional dependency pattern + test suite from #36.

Changes

• src/google/adk_community/artifacts/s3_artifact_service.py — full implementation
• tests/unittests/artifacts/test_s3_artifact_service.py — 13 unit tests with async mock infrastructure (no AWS credentials required)
• src/google/adk_community/artifacts/__init__.py — export S3ArtifactService
• src/google/adk_community/artifacts/README.md — usage documentation
• pyproject.toml — add s3 optional dependency group
• src/google/adk_community/__init__.py — register artifacts subpackage

Design Decisions

Concern	Approach
Async I/O	aioboto3 for native async (no asyncio.to_thread wrappers)
Race conditions	IfNoneMatch="*" on put_object for atomic versioning
Optional dependency	aioboto3 only required via pip install google-adk-community[s3]
Metadata	JSON-serialised in S3 user-metadata with safe decode fallback
Batch operations	delete_objects in 1000-key chunks per S3 limits
Version listing	Parallel head_object calls via asyncio.gather
S3-compatible	Works with MinIO, DigitalOcean Spaces, etc. via aws_configs

Usage

from google.adk_community.artifacts import S3ArtifactService

artifact_service = S3ArtifactService(
    bucket_name="my-adk-artifacts",
    aws_configs={"region_name": "us-east-1"},
)

Test Plan

pip install google-adk-community[s3,test]
pytest tests/unittests/artifacts/ -v

• 13 unit tests covering CRUD, versioning, user-scoped artifacts, metadata, empty artifacts, text encoding, and conflict retry
• All tests pass without AWS credentials (full async mock infrastructure)
• Existing tests unaffected

Closes #37
Closes #71

[google-cla]

Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA).

View this failed invocation of the CLA check for more information.

For the most up to date status, view the checks section at the bottom of the pull request.

[DeanChensj]

@gemini-cli /review

[github-actions]

🤖 Hi @DeanChensj, I've received your request, and I'm working on it now! You can track my progress in the logs for more details.

[DeanChensj]

btw, could you send out the CI fix in a separate PR? Thanks!

[DeanChensj]

@gemini-cli /review

[github-actions]

🤖 Hi @DeanChensj, I've received your request, and I'm working on it now! You can track my progress in the logs for more details.

[github-actions]

Thanks for the PR! The implementation of S3ArtifactService using aioboto3 and atomic versioning is solid.

I've left a few comments regarding:

1. Potential race condition in _get_session initialization.
2. High concurrency in list_artifact_versions when gathering head_object tasks.
3. S3 metadata size limits when flattening custom metadata.
4. An out-of-scope change in redis_session_service.py.

Overall, the test coverage is excellent and the design is well-aligned with the project's optional dependency pattern.

[miyannishar]

Done! Moved the CI fix (Redis temp-state filtering + --extra s3 in workflow) to a separate PR: #125. This PR now only contains the S3ArtifactService implementation.

Also addressed all the review comments in the latest push:

• ✅ asyncio.Lock for async-safe session init
• ✅ S3 metadata 2KB size validation
• ✅ asyncio.Semaphore(10) for bounded head_object concurrency