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Litellm dev 02 10 2025 p1 (#8438)

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* fix(azure/chat/gpt_transformation.py): fix str compare to use int - ensure correct api version check is done

Resolves https://github.com/BerriAI/litellm/issues/8241#issuecomment-2647142891

* test(test_azure_openai.py): add better testing
This commit is contained in:
Krish Dholakia 2025-02-10 16:25:04 -08:00 • committed by GitHub
parent 6a4013a075
commit 47f46f92c8
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3 changed files with 68 additions and 27 deletions
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26
litellm/llms/azure/chat/gpt_transformation.py
View file

@ -113,6 +113,17 @@ class AzureOpenAIConfig(BaseConfig):
return False
def _is_response_format_supported_api_version(
self, api_version_year: str, api_version_month: str
) -> bool:
"""
- check if api_version is supported for response_format
"""
is_supported = int(api_version_year) <= 2024 and int(api_version_month) >= 8
return is_supported
def map_openai_params(
self,
non_default_params: dict,
@ -171,13 +182,20 @@ class AzureOpenAIConfig(BaseConfig):
_is_response_format_supported_model = (
self._is_response_format_supported_model(model)
)
should_convert_response_format_to_tool = (
api_version_year <= "2024" and api_version_month < "08"
) or not _is_response_format_supported_model
is_response_format_supported_api_version = (
self._is_response_format_supported_api_version(
api_version_year, api_version_month
)
)
is_response_format_supported = (
is_response_format_supported_api_version
and _is_response_format_supported_model
)
optional_params = self._add_response_format_to_tools(
optional_params=optional_params,
value=value,
should_convert_response_format_to_tool=should_convert_response_format_to_tool,
is_response_format_supported=is_response_format_supported,
)
elif param == "tools" and isinstance(value, list):
optional_params.setdefault("tools", [])

9
litellm/llms/base_llm/chat/transformation.py
View file

@ -20,6 +20,7 @@ from pydantic import BaseModel
from litellm._logging import verbose_logger
from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
from litellm.types.llms.openai import (
AllMessageValues,
ChatCompletionToolChoiceFunctionParam,
@ -27,9 +28,6 @@ from litellm.types.llms.openai import (
ChatCompletionToolParam,
ChatCompletionToolParamFunctionChunk,
)
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
from litellm.types.utils import ModelResponse
from litellm.utils import CustomStreamWrapper
@ -163,7 +161,7 @@ class BaseConfig(ABC):
self,
optional_params: dict,
value: dict,
should_convert_response_format_to_tool: bool,
is_response_format_supported: bool,
) -> dict:
"""
Follow similar approach to anthropic - translate to a single tool call.
@ -183,7 +181,8 @@ class BaseConfig(ABC):
elif "json_schema" in value:
json_schema = value["json_schema"]["schema"]
if json_schema and should_convert_response_format_to_tool:
if json_schema and not is_response_format_supported:
_tool_choice = ChatCompletionToolChoiceObjectParam(
type="function",
function=ChatCompletionToolChoiceFunctionParam(

60
tests/llm_translation/test_azure_openai.py
View file

@ -285,12 +285,27 @@ def test_azure_openai_gpt_4o_naming(monkeypatch):
assert "tool_calls" not in mock_post.call_args.kwargs
def test_azure_gpt_4o_with_tool_call_and_response_format():
@pytest.mark.parametrize(
"api_version",
[
"2024-10-21",
# "2024-02-15-preview",
],
)
def test_azure_gpt_4o_with_tool_call_and_response_format(api_version):
from litellm import completion
from typing import Optional
from pydantic import BaseModel
import litellm
from openai import AzureOpenAI
client = AzureOpenAI(
api_key="fake-key",
base_url="https://fake-azure.openai.azure.com",
api_version=api_version,
)
class InvestigationOutput(BaseModel):
alert_explanation: Optional[str] = None
investigation: Optional[str] = None
@ -322,25 +337,34 @@ def test_azure_gpt_4o_with_tool_call_and_response_format():
}
]
response = litellm.completion(
model="azure/gpt-4o",
messages=[
{
"role": "system",
"content": "You are a tool-calling AI assist provided with common devops and IT tools that you can use to troubleshoot problems or answer questions.\nWhenever possible you MUST first use tools to investigate then answer the question.",
},
{"role": "user", "content": "What is the current date and time in NYC?"},
],
drop_params=True,
temperature=0.00000001,
tools=tools,
tool_choice="auto",
response_format=InvestigationOutput, # commenting this line will cause the output to be correct
)
with patch.object(client.chat.completions.with_raw_response, "create") as mock_post:
response = litellm.completion(
model="azure/gpt-4o",
messages=[
{
"role": "system",
"content": "You are a tool-calling AI assist provided with common devops and IT tools that you can use to troubleshoot problems or answer questions.\nWhenever possible you MUST first use tools to investigate then answer the question.",
},
{
"role": "user",
"content": "What is the current date and time in NYC?",
},
],
drop_params=True,
temperature=0.00000001,
tools=tools,
tool_choice="auto",
response_format=InvestigationOutput, # commenting this line will cause the output to be correct
api_version=api_version,
client=client,
)
assert response.choices[0].finish_reason == "tool_calls"
mock_post.assert_called_once()
print(response.to_json())
if api_version == "2024-10-21":
assert "response_format" in mock_post.call_args.kwargs
else:
assert "response_format" not in mock_post.call_args.kwargs
def test_map_openai_params():