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refactor: Extract helper methods to fix linting issues

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- Split _transform_request_helper into smaller focused methods
- Extract _prepare_request_params for parameter preparation logic
- Extract _process_tools_and_beta for tool processing logic
- Resolve PLR0915 (too many statements) linting issue
- Maintain all existing functionality and test compatibility
This commit is contained in:
Tim Elfrink 2025-09-15 11:06:03 +02:00
parent a34bb6f6d3
commit 352a0eedb5
1 changed files with 43 additions and 30 deletions
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73
litellm/llms/bedrock/chat/converse_transformation.py
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@ -762,34 +762,8 @@ class AmazonConverseConfig(BaseConfig):
return {}
def _transform_request_helper(
self,
model: str,
system_content_blocks: List[SystemContentBlock],
optional_params: dict,
messages: Optional[List[AllMessageValues]] = None,
headers: Optional[dict] = None,
) -> CommonRequestObject:
## VALIDATE REQUEST
"""
Bedrock doesn't support tool calling without `tools=` param specified.
"""
if (
"tools" not in optional_params
and messages is not None
and has_tool_call_blocks(messages)
):
if litellm.modify_params:
optional_params["tools"] = add_dummy_tool(
custom_llm_provider="bedrock_converse"
)
else:
raise litellm.UnsupportedParamsError(
message="Bedrock doesn't support tool calling without `tools=` param specified. Pass `tools=` param OR set `litellm.modify_params = True` // `litellm_settings::modify_params: True` to add dummy tool to the request.",
model="",
llm_provider="bedrock",
)
def _prepare_request_params(self, optional_params: dict, model: str) -> tuple[dict, dict, dict]:
"""Prepare and separate request parameters."""
inference_params = copy.deepcopy(optional_params)
supported_converse_params = list(
AmazonConverseConfig.__annotations__.keys()
@ -821,9 +795,10 @@ class AmazonConverseConfig(BaseConfig):
self._handle_top_k_value(model, inference_params)
)
original_tools = inference_params.pop("tools", [])
return inference_params, additional_request_params, request_metadata
# Initialize bedrock_tools
def _process_tools_and_beta(self, original_tools: list, model: str, headers: Optional[dict], additional_request_params: dict) -> tuple[List[ToolBlock], list]:
"""Process tools and collect anthropic_beta values."""
bedrock_tools: List[ToolBlock] = []
# Collect anthropic_beta values from user headers
@ -865,6 +840,44 @@ class AmazonConverseConfig(BaseConfig):
seen.add(beta)
additional_request_params["anthropic_beta"] = unique_betas
return bedrock_tools, anthropic_beta_list
def _transform_request_helper(
self,
model: str,
system_content_blocks: List[SystemContentBlock],
optional_params: dict,
messages: Optional[List[AllMessageValues]] = None,
headers: Optional[dict] = None,
) -> CommonRequestObject:
## VALIDATE REQUEST
"""
Bedrock doesn't support tool calling without `tools=` param specified.
"""
if (
"tools" not in optional_params
and messages is not None
and has_tool_call_blocks(messages)
):
if litellm.modify_params:
optional_params["tools"] = add_dummy_tool(
custom_llm_provider="bedrock_converse"
)
else:
raise litellm.UnsupportedParamsError(
message="Bedrock doesn't support tool calling without `tools=` param specified. Pass `tools=` param OR set `litellm.modify_params = True` // `litellm_settings::modify_params: True` to add dummy tool to the request.",
model="",
llm_provider="bedrock",
)
# Prepare and separate parameters
inference_params, additional_request_params, request_metadata = self._prepare_request_params(optional_params, model)
original_tools = inference_params.pop("tools", [])
# Process tools and collect beta values
bedrock_tools, anthropic_beta_list = self._process_tools_and_beta(original_tools, model, headers, additional_request_params)
bedrock_tool_config: Optional[ToolConfigBlock] = None
if len(bedrock_tools) > 0:
tool_choice_values: ToolChoiceValuesBlock = inference_params.pop(