[Python] Add typed decision questions and model adapters

[bvolpato]

Adds typed Choice, Boolean, and Score questions to Beam Python. EvaluateDecisions applies a DecisionModel adapter to each input element, so pipelines can change adapters while keeping their questions and downstream policy.

The transform reuses the adapter context across elements and bundles on each worker DoFn instance. Results retain the original input, timestamps, and windows, with model/provider identifiers and request latency. The transform records request metrics and closes the context during best-effort teardown.

The optional Jev adapter maps Boolean questions to Noul and validates responses. The fraud example's optional JSONL error output catches malformed-response validation failures. Setup errors and exhausted transport failures still fail that pipeline. Calls and retries block the processing thread, and the transform does not coordinate a global request-rate limit.

The README covers installation, local demos, and cloud options.

Local mocked validation and the routing and fraud demos passed. Python 3.12 ML CI passed with the optional SDK installed for the adapter tests. Provider calls were not repeated for the response-validation changes, and the routing example's BigQuery sink has not been tested against the live service.

Run the ML unit suite with:

./gradlew :sdks:python:test-suites:tox:py312:testPy312ML

---

• If this contribution is large, please file an Apache Individual Contributor License Agreement.
• Replace these instructions with a description of your change and why you have made it.
• Mention the appropriate issue in your description (for example: addresses #123 or fixes #456).
• Update CHANGES.md with noteworthy changes.

See CONTRIBUTING.md for contribution guidelines.

[github-actions]

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R: @jrmccluskey for label python.

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[bvolpato]

Run PythonDocs PreCommit

[jrmccluskey]

This is a neat framework! Just a few documentation nits and a question around the potential for malformed responses

[codecov]

Codecov Report

❌ Patch coverage is 66.47059% with 57 lines in your changes missing coverage. Please review.
✅ Project coverage is 56.36%. Comparing base (76f6e6d) to head (5655d4a).
⚠️ Report is 179 commits behind head on master.

Files with missing lines	Patch %	Lines
...hon/apache_beam/ml/inference/typesafe_inference.py	25.33%	56 Missing ⚠️
sdks/python/apache_beam/ml/inference/decision.py	98.94%	1 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##             master   #40220      +/-   ##
============================================
+ Coverage     56.16%   56.36%   +0.19%     
  Complexity     2288     2288              
============================================
  Files          1124     1127       +3     
  Lines        178336   178650     +314     
  Branches       1489     1488       -1     
============================================
+ Hits         100170   100691     +521     
+ Misses        75645    75435     -210     
- Partials       2521     2524       +3     

Flag	Coverage Δ
python	79.87% <66.47%> (+0.32%)	⬆️

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