openai/openai-python · error · RuntimeError

Could not resolve inner type variable at index {index} for {

Error message

Could not resolve inner type variable at index {index} for {typ}

What it means

extract_type_var_from_base resolves the type argument filling a TypeVar in a generic base class (used to infer response types from isomorphic/generic aliases). If the concrete type does not carry the metadata needed to resolve the TypeVar at the requested index — e.g. the class is generic in a different order, is a non-generic subclass, or typing internals do not expose __orig_bases__/args — it raises this RuntimeError. It is essentially an internal typing-inference failure, most commonly seen in tests of the util itself or in exotic generic hierarchies passed to type-inference helpers.

Source

Thrown at src/openai/_utils/_typing.py:156

                "This should never happen;\n"
                f"Does {cls} inherit from one of {generic_bases} ?"
            )

        extracted = extract_type_arg(target_base_class, index)
        if is_typevar(extracted):
            # If the extracted type argument is itself a type variable
            # then that means the subclass itself is generic, so we have
            # to resolve the type argument from the class itself, not
            # the base class.
            #
            # Note: if there is more than 1 type argument, the subclass could
            # change the ordering of the type arguments, this is not currently
            # supported.
            return extract_type_arg(typ, index)

        return extracted

    raise RuntimeError(failure_message or f"Could not resolve inner type variable at index {index} for {typ}")

View on GitHub (pinned to 9917c6e28e)

Solutions

1. Match the TypeVar order of the base class exactly when subclassing generic bases
2. Use typing.TypeVar with the same variance/position; avoid reordering type arguments in subclasses
3. If you control the helper, use explicit type annotations instead of runtime inference
4. Pin or align with the SDK version whose generic layout your code was written against

Example fix

# before
class Wrapper(MyBase[B, A]): ...  # A/B order swapped vs base

# after
class Wrapper(MyBase[A, B]): ...  # same order as MyBase's declaration

from openai._utils import extract_type_var_from_base
try:
    extract_type_var_from_base(cls, TypeVar("T"))
except RuntimeError:
    use_explicit_annotation = True

try:
    extract_type_var_from_base(cls, TV, index=0)
except RuntimeError:
    typ = explicit_type_map.get(cls, fallback)

When it happens

Trigger: Calling extract_type_var_from_base on a class whose generic base either lacks the TypeVar at that index or reorders type arguments in an unsupported way; subclasses that parameterize generics in a different order than declared; passing a plain (non-generic) class.

Common situations: Building custom generic response wrappers around SDK models; refactoring shared generic base classes and changing TypeVar ordering; SDK upgrades that change internal response typing.

Related errors

• Subclasses of HTTP response classes cannot be passed to `cas
• Pydantic models must subclass our base model type, e.g. `fro
• Unsupported type, expected {cast_to} to be a subclass of {Ba
• Subclasses of HTTP response classes cannot be passed to `cas
• Pydantic models must subclass our base model type, e.g. `fro

AI-assisted analysis of openai/openai-python@9917c6e28e (2026-08-28). Data as JSON: /api/errors/3d512d3d3911f981. Report an issue: GitHub.