scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-09-16 23:41:43 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 227

fix: handle raw Pydantic v2 models from openai SDK in output transformation

Browse source 
The openai SDK returns ResponseOutputMessage and ResponseOutputText as
raw Pydantic v2 models that lack .get() (unlike LiteLLM's own wrapper
objects). Add a _to_dict() helper that normalizes plain dicts,
BaseLiteLLMOpenAIResponseObject (has .get()), and raw Pydantic models
(has .model_dump()) into a consistent dict interface.
This commit is contained in:
Aneesh-Fiddler 2026-04-30 11:04:08 +05:30
parent 53102529ca
commit c319a19c25
1 changed files with 39 additions and 15 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

54
litellm/integrations/opentelemetry.py
View file

@ -1794,15 +1794,13 @@ class OpenTelemetry(CustomLogger):
# _tool_calls_kv_pair.
tool_calls = []
for out_item in output_items:
if (
hasattr(out_item, "get")
and out_item.get("type") == "function_call"
):
item_d = self._to_dict(out_item)
if item_d and item_d.get("type") == "function_call":
tool_calls.append(
{
"function": {
"name": out_item.get("name", ""),
"arguments": out_item.get("arguments", ""),
"name": item_d.get("name", ""),
"arguments": item_d.get("arguments", ""),
}
}
)
@ -1919,6 +1917,31 @@ class OpenTelemetry(CustomLogger):
transformed.append(transformed_msg)
return transformed
@staticmethod
def _to_dict(obj) -> Optional[dict]:
"""Normalize an object to a plain dict.
Handles three forms that appear in practice:
1. Plain ``dict`` — returned as-is.
2. LiteLLM's ``BaseLiteLLMOpenAIResponseObject`` — exposes a
``.get()`` method that delegates to ``__dict__``.
3. Raw Pydantic v2 models from the ``openai`` SDK (e.g.
``ResponseOutputMessage``, ``ResponseOutputText``) — these do
**not** have ``.get()`` but do have ``.model_dump()``.
Returns ``None`` for anything else so callers can skip it.
"""
if isinstance(obj, dict):
return obj
if hasattr(obj, "get"):
# BaseLiteLLMOpenAIResponseObject duck-type
return obj # type: ignore[return-value]
if hasattr(obj, "model_dump"):
# Raw Pydantic v2 model (e.g. openai SDK types)
return obj.model_dump() # type: ignore[union-attr]
return None
def _transform_responses_api_output_to_otel(self, output: List) -> List[dict]:
"""
Transform Responses API output items into OTEL GenAI 1.38 format.
@ -1928,24 +1951,25 @@ class OpenTelemetry(CustomLogger):
``content`` list of ``OutputText`` objects with ``type="output_text"``
and ``text`` fields.
Items may be plain dicts or Pydantic model instances (e.g.
``ResponseOutputMessage``, ``ResponseFunctionToolCall``). Both
expose a ``.get()`` method via ``BaseLiteLLMOpenAIResponseObject``,
so we use ``hasattr(item, "get")`` rather than ``isinstance(item,
dict)`` to accept either form.
Items may be plain dicts, LiteLLM wrapper objects (with ``.get()``),
or raw Pydantic v2 models from the ``openai`` SDK (with
``.model_dump()``). We normalize each item to a dict via
``_to_dict`` before processing.
This method converts them to the same ``{"role": ..., "parts": [...]}``
format used by ``_transform_choices_to_otel_semantic_conventions``.
"""
transformed = []
for item in output:
if not hasattr(item, "get"):
for raw_item in output:
item = self._to_dict(raw_item)
if item is None:
continue
if item.get("type") == "message":
role = item.get("role", "assistant")
parts = []
for content in item.get("content", []):
if not hasattr(content, "get"):
for raw_content in item.get("content", []):
content = self._to_dict(raw_content)
if content is None:
continue
if content.get("type") == "output_text":
text = content.get("text", "")