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Litellm dev 04 05 2025 p2 (#9774)

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* test: move test to just checking async

* fix(transformation.py): handle function call with no schema

* fix(utils.py): handle pydantic base model in message tool calls

Fix https://github.com/BerriAI/litellm/issues/9321

* fix(vertex_and_google_ai_studio.py): handle tools=[]

Fixes https://github.com/BerriAI/litellm/issues/9080

* test: remove max token restriction

* test: fix basic test

* fix(get_supported_openai_params.py): fix check

* fix(converse_transformation.py): support fake streaming for meta.llama3-3-70b-instruct-v1:0

* fix: fix test

* fix: parse out empty dictionary on dbrx streaming + tool calls

* fix(handle-'strict'-param-when-calling-fireworks-ai): fireworks ai does not support 'strict' param

* fix: fix ruff check

'

* fix: handle no strict in function

* fix: revert bedrock change - handle in separate PR
This commit is contained in:
Krish Dholakia 2025-04-07 21:02:52 -07:00 • committed by GitHub
parent d8f47fc9e5
commit fcf17d114f
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10 changed files with 214 additions and 11 deletions
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25
litellm/llms/bedrock/chat/converse_transformation.py
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@ -30,6 +30,7 @@ from litellm.types.llms.openai import (
ChatCompletionToolParam,
ChatCompletionToolParamFunctionChunk,
ChatCompletionUserMessage,
OpenAIChatCompletionToolParam,
OpenAIMessageContentListBlock,
)
from litellm.types.utils import ModelResponse, PromptTokensDetailsWrapper, Usage
@ -211,6 +212,23 @@ class AmazonConverseConfig(BaseConfig):
)
return _tool
def _apply_tool_call_transformation(
self,
tools: List[OpenAIChatCompletionToolParam],
model: str,
non_default_params: dict,
optional_params: dict,
):
optional_params = self._add_tools_to_optional_params(
optional_params=optional_params, tools=tools
)
if (
"meta.llama3-3-70b-instruct-v1:0" in model
and non_default_params.get("stream", False) is True
):
optional_params["fake_stream"] = True
def map_openai_params(
self,
non_default_params: dict,
@ -286,8 +304,11 @@ class AmazonConverseConfig(BaseConfig):
if param == "top_p":
optional_params["topP"] = value
if param == "tools" and isinstance(value, list):
optional_params = self._add_tools_to_optional_params(
optional_params=optional_params, tools=value
self._apply_tool_call_transformation(
tools=cast(List[OpenAIChatCompletionToolParam], value),
model=model,
non_default_params=non_default_params,
optional_params=optional_params,
)
if param == "tool_choice":
_tool_choice_value = self.map_tool_choice_values(