fix: coerce by_alias to bool in model_dump to prevent TypeError with DEBUG logging

[giulio-leone]

Summary

Fixes #2921 — model_dump() raises TypeError: argument 'by_alias': 'NoneType' object cannot be converted to 'PyBool' when DEBUG logging is enabled.

Root Cause

In _compat.py, model_dump() declares by_alias: bool | None = None but passes the value directly to Pydantic v2's model_dump():

# line 152 — passes None to pydantic-core Rust serializer
by_alias=by_alias,  # TypeError when by_alias is None

Fix

Omit by_alias from kwargs when None, preserving Pydantic's model-level default (e.g. ConfigDict(serialize_by_alias=True)). Only forward explicit True/False values:

kwargs = dict(mode=mode, exclude=exclude, ...)
if by_alias is not None:
    kwargs["by_alias"] = by_alias
return model.model_dump(**kwargs)

This preserves tri-state semantics:

• None → Pydantic uses its model default
• True/False → explicitly forwarded

Tests

Added test_model_dump_by_alias_none verifying:

• Default call (implicit by_alias=None) works
• Explicit by_alias=None works
• Explicit by_alias=False still forwarded correctly

[chatgpt-codex-connector]

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[chatgpt-codex-connector]

Preserve tri-state by_alias semantics in model_dump

Coercing by_alias with bool(by_alias) changes the meaning of the default None value from “use model default” to always False, so models that rely on alias serialization defaults (e.g., ConfigDict(serialize_by_alias=True) in Pydantic v2) will now silently emit field names instead of aliases when callers omit by_alias. This is a behavior regression from the previous pass-through and can produce incorrect serialized payloads in any call site using _compat.model_dump(..., by_alias=None) or the default.

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[giulio-leone]

Good catch — updated the fix to omit by_alias entirely when None instead of coercing with bool(). This preserves tri-state semantics so models with ConfigDict(serialize_by_alias=True) keep their default alias behavior.

[giulio-leone]

Friendly ping — CI is green, tests pass, rebased on latest. Ready for review whenever convenient. Happy to address any feedback. 🙏