Remove/update some TODO comments (#2731)

Author: dmontagu

pydantic_ai_slim/pydantic_ai/messages.py

@@ -966,7 +966,7 @@ def new_event_body():
                 body.setdefault('tool_calls', []).append(
                     {
                         'id': part.tool_call_id,
-                        'type': 'function',  # TODO https://github.com/pydantic/pydantic-ai/issues/888
+                        'type': 'function',
                         'function': {
                             'name': part.tool_name,
                             **({'arguments': part.args} if settings.include_content else {}),

pydantic_ai_slim/pydantic_ai/models/gemini.py

@@ -735,7 +735,6 @@ def _part_discriminator(v: Any) -> str:
 
 # See <https://ai.google.dev/api/caching#Part>
 # we don't currently support other part types
-# TODO discriminator
 _GeminiPartUnion = Annotated[
     Annotated[_GeminiTextPart, pydantic.Tag('text')]
     | Annotated[_GeminiFunctionCallPart, pydantic.Tag('function_call')]

pydantic_evals/pydantic_evals/dataset.py

@@ -161,11 +161,6 @@ def __init__(
         self.evaluators = list(evaluators)
 
 
-# TODO: Consider making one or more of the following changes to this type:
-#  * Add `task: Callable[[InputsT], Awaitable[OutputT]` as a field
-#  * Add `inputs_type`, `output_type`, etc. as kwargs on `__init__`
-#  * Rename to `Evaluation`
-# TODO: Allow `task` to be sync _or_ async
 class Dataset(BaseModel, Generic[InputsT, OutputT, MetadataT], extra='forbid', arbitrary_types_allowed=True):
     """A dataset of test [cases][pydantic_evals.Case].
 
@@ -634,7 +629,7 @@ def model_json_schema_with_evaluators(
             def _make_typed_dict(cls_name_prefix: str, fields: dict[str, Any]) -> Any:
                 td = TypedDict(f'{cls_name_prefix}_{name}', fields)  # pyright: ignore[reportArgumentType]
                 config = ConfigDict(extra='forbid', arbitrary_types_allowed=True)
-                # TODO: Replace with pydantic.with_config after pydantic 2.11 is released
+                # TODO: Replace with pydantic.with_config once pydantic 2.11 is the min supported version
                 td.__pydantic_config__ = config  # pyright: ignore[reportAttributeAccessIssue]
                 return td
 
@@ -859,7 +854,6 @@ async def _run_task(
             for k, v in node.attributes.items():
                 if not isinstance(v, int | float):
                     continue
-                # TODO: Revisit this choice to strip the prefix..
                 if k.startswith('gen_ai.usage.details.'):
                     task_run.increment_metric(k.removeprefix('gen_ai.usage.details.'), v)
                 elif k.startswith('gen_ai.usage.'):

pydantic_evals/pydantic_evals/evaluators/evaluator.py

@@ -55,7 +55,7 @@ class EvaluationReason:
 """Type for the output of an evaluator, which can be a scalar, an EvaluationReason, or a mapping of names to either."""
 
 
-# TODO(DavidM): Add bound=EvaluationScalar to the following typevar after we upgrade to pydantic 2.11
+# TODO(DavidM): Add bound=EvaluationScalar to the following typevar once pydantic 2.11 is the min supported version
 EvaluationScalarT = TypeVar('EvaluationScalarT', default=EvaluationScalar, covariant=True)
 """Type variable for the scalar result type of an evaluation."""
 

pydantic_evals/pydantic_evals/evaluators/spec.py

@@ -17,7 +17,7 @@
 if TYPE_CHECKING:
     # This import seems to fail on Pydantic 2.10.1 in CI
     from pydantic import ModelWrapValidatorHandler
-    # TODO: Try removing this when we update to pydantic 2.11
+    # TODO: Remove this once pydantic 2.11 is the min supported version
 
 
 class EvaluatorSpec(BaseModel):

pydantic_graph/pydantic_graph/nodes.py

@@ -121,7 +121,6 @@ def get_node_def(cls, local_ns: dict[str, Any] | None) -> NodeDef[StateT, DepsT,
             if return_type_origin is End:
                 end_edge = edge
             elif return_type_origin is BaseNode:
-                # TODO: Should we disallow this?
                 returns_base_node = True
             elif issubclass(return_type_origin, BaseNode):
                 next_node_edges[return_type.get_node_id()] = edge