feat: generate TypedDict types for input-side models

[vdusek]

Summary

Adds TypedDict counterparts for generated Pydantic models so users passing plain dicts to resource-client methods get full type-checker support without having to import Pydantic models.

• Generate TypedDicts alongside Pydantic models via a second datamodel-code-generator invocation (--output-model-type typing.TypedDict) in poe generate-models / poe generate-models-from-file.
• Move generated output to a new src/apify_client/_generated/ subpackage (_models.py, _typeddicts.py). Top-level src/apify_client/_models.py and src/apify_client/_typeddicts.py become stable shim modules that re-export from _generated/ — public import paths stay the same.
• Extend scripts/postprocess_generated_models.py to prune and rename TypedDicts.
• Hand-maintain RequestInputDict / RequestDeleteInputDict for shapes not yet exposed by the OpenAPI spec.
• Update resource-client method signatures (actor, task, task collection, request queue) to accept both Pydantic models and TypedDicts.
• Update manual_regenerate_models.yaml workflow to commit the regenerated _generated/*.py files and mention TypedDicts in PR body.
• Update .rules.md to describe the new two-tier layout.

Closes #666.

[codecov]

Codecov Report

❌ Patch coverage is 97.59036% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 95.34%. Comparing base (3d4ce3f) to head (1eb5c1d).
⚠️ Report is 2 commits behind head on master.

Files with missing lines	Patch %	Lines
src/apify_client/_types.py	60.00%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #738      +/-   ##
==========================================
+ Coverage   95.26%   95.34%   +0.08%     
==========================================
  Files          45       48       +3     
  Lines        5115     5182      +67     
==========================================
+ Hits         4873     4941      +68     
+ Misses        242      241       -1     

Flag	Coverage Δ
integration	95.34% <97.59%> (+0.08%)	⬆️

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