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Merge 940810f526 into b82af5b826

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Ishaan Jaff 2025-04-24 00:54:40 -07:00 • committed by GitHub
commit 5aae062946
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5 changed files with 98 additions and 16 deletions
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35
litellm/litellm_core_utils/prompt_templates/factory.py
View file

@ -1041,10 +1041,10 @@ def convert_to_gemini_tool_call_invoke(
if tool_calls is not None:
for tool in tool_calls:
if "function" in tool:
gemini_function_call: Optional[
VertexFunctionCall
] = _gemini_tool_call_invoke_helper(
function_call_params=tool["function"]
gemini_function_call: Optional[VertexFunctionCall] = (
_gemini_tool_call_invoke_helper(
function_call_params=tool["function"]
)
)
if gemini_function_call is not None:
_parts_list.append(
@ -1139,7 +1139,7 @@ def convert_to_gemini_tool_call_result(
def convert_to_anthropic_tool_result(
message: Union[ChatCompletionToolMessage, ChatCompletionFunctionMessage]
message: Union[ChatCompletionToolMessage, ChatCompletionFunctionMessage],
) -> AnthropicMessagesToolResultParam:
"""
OpenAI message with a tool result looks like:
@ -1449,9 +1449,9 @@ def anthropic_messages_pt( # noqa: PLR0915
)
if "cache_control" in _content_element:
_anthropic_content_element[
"cache_control"
] = _content_element["cache_control"]
_anthropic_content_element["cache_control"] = (
_content_element["cache_control"]
)
user_content.append(_anthropic_content_element)
elif m.get("type", "") == "text":
m = cast(ChatCompletionTextObject, m)
@ -1502,9 +1502,9 @@ def anthropic_messages_pt( # noqa: PLR0915
)
if "cache_control" in _content_element:
_anthropic_content_text_element[
"cache_control"
] = _content_element["cache_control"]
_anthropic_content_text_element["cache_control"] = (
_content_element["cache_control"]
)
user_content.append(_anthropic_content_text_element)
@ -2244,6 +2244,7 @@ from litellm.types.llms.bedrock import ToolBlock as BedrockToolBlock
from litellm.types.llms.bedrock import (
ToolInputSchemaBlock as BedrockToolInputSchemaBlock,
)
from litellm.types.llms.bedrock import ToolJsonSchemaBlock as BedrockToolJsonSchemaBlock
from litellm.types.llms.bedrock import ToolResultBlock as BedrockToolResultBlock
from litellm.types.llms.bedrock import (
ToolResultContentBlock as BedrockToolResultContentBlock,
@ -2499,7 +2500,7 @@ def _convert_to_bedrock_tool_call_invoke(
def _convert_to_bedrock_tool_call_result(
message: Union[ChatCompletionToolMessage, ChatCompletionFunctionMessage]
message: Union[ChatCompletionToolMessage, ChatCompletionFunctionMessage],
) -> BedrockContentBlock:
"""
OpenAI message with a tool result looks like:
@ -2672,7 +2673,7 @@ def get_user_message_block_or_continue_message(
def return_assistant_continue_message(
assistant_continue_message: Optional[
Union[str, ChatCompletionAssistantMessage]
] = None
] = None,
) -> ChatCompletionAssistantMessage:
if assistant_continue_message and isinstance(assistant_continue_message, str):
return ChatCompletionAssistantMessage(
@ -3470,7 +3471,13 @@ def _bedrock_tools_pt(tools: List) -> List[BedrockToolBlock]:
for _, value in defs_copy.items():
unpack_defs(value, defs_copy)
unpack_defs(parameters, defs_copy)
tool_input_schema = BedrockToolInputSchemaBlock(json=parameters)
tool_input_schema = BedrockToolInputSchemaBlock(
json=BedrockToolJsonSchemaBlock(
type=parameters.get("type", ""),
properties=parameters.get("properties", {}),
required=parameters.get("required", []),
)
)
tool_spec = BedrockToolSpecBlock(
inputSchema=tool_input_schema, name=name, description=description
)

8
litellm/types/llms/bedrock.py
View file

@ -125,8 +125,14 @@ class ConverseResponseBlock(TypedDict):
usage: ConverseTokenUsageBlock
class ToolJsonSchemaBlock(TypedDict, total=False):
type: Literal["object"]
properties: dict
required: List[str]
class ToolInputSchemaBlock(TypedDict):
json: Optional[dict]
json: Optional[ToolJsonSchemaBlock]
class ToolSpecBlock(TypedDict, total=False):

3
tests/llm_translation/base_llm_unit_tests.py
View file

@ -1055,6 +1055,7 @@ class BaseLLMChatTest(ABC):
def test_function_calling_with_tool_response(self):
from litellm.utils import supports_function_calling
from litellm import completion
litellm._turn_on_debug()
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
@ -1074,6 +1075,8 @@ class BaseLLMChatTest(ABC):
"name": "get_weather",
"description": "Get the weather in a city",
"parameters": {
"$id": "https://some/internal/name",
"$schema": "https://json-schema.org/draft-07/schema",
"type": "object",
"properties": {
"city": {

66
tests/llm_translation/test_bedrock_completion.py
View file

@ -1264,6 +1264,50 @@ def test_bedrock_tools_pt_invalid_names():
assert result[1]["toolSpec"]["name"] == "another_invalid_name"
def test_bedrock_tools_transformation_valid_params():
from litellm.types.llms.bedrock import ToolJsonSchemaBlock
tools = [
{
"type": "function",
"function": {
"name": "123-invalid@name",
"description": "Invalid name test",
"parameters": {
"$id": "https://some/internal/name",
"type": "object",
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"test": {"type": "string"},
},
"required": ["test"],
},
},
}
]
result = _bedrock_tools_pt(tools)
print("bedrock tools after prompt formatting=", result)
# Ensure the keys for properties in the response is a subset of keys in ToolJsonSchemaBlock
toolJsonSchema = result[0]["toolSpec"]["inputSchema"]["json"]
assert toolJsonSchema is not None
print("transformed toolJsonSchema keys=", toolJsonSchema.keys())
print("allowed ToolJsonSchemaBlock keys=", ToolJsonSchemaBlock.__annotations__.keys())
assert set(toolJsonSchema.keys()).issubset(set(ToolJsonSchemaBlock.__annotations__.keys()))
assert isinstance(result, list)
assert len(result) == 1
assert "toolSpec" in result[0]
assert result[0]["toolSpec"]["name"] == "a123_invalid_name"
assert result[0]["toolSpec"]["description"] == "Invalid name test"
assert "inputSchema" in result[0]["toolSpec"]
assert "json" in result[0]["toolSpec"]["inputSchema"]
assert result[0]["toolSpec"]["inputSchema"]["json"]["properties"]["test"]["type"] == "string"
assert "test" in result[0]["toolSpec"]["inputSchema"]["json"]["required"]
def test_not_found_error():
with pytest.raises(litellm.NotFoundError):
completion(
@ -2226,6 +2270,28 @@ class TestBedrockConverseChatNormal(BaseLLMChatTest):
"""
pass
class TestBedrockConverseNovaTestSuite(BaseLLMChatTest):
def get_base_completion_call_args(self) -> dict:
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
litellm.add_known_models()
return {
"model": "bedrock/us.amazon.nova-lite-v1:0",
"aws_region_name": "us-east-1",
}
def test_tool_call_no_arguments(self, tool_call_no_arguments):
"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
pass
def test_multilingual_requests(self):
"""
Bedrock API raises a 400 BadRequest error when the request contains invalid utf-8 sequences.
Todo: if litellm.modify_params is True ensure it's a valid utf-8 sequence
"""
pass
class TestBedrockRerank(BaseLLMRerankTest):
def get_custom_llm_provider(self) -> litellm.LlmProviders:

2
tests/llm_translation/test_bedrock_invoke_tests.py
View file

@ -32,7 +32,7 @@ class TestBedrockInvokeNovaJson(BaseLLMChatTest):
def test_tool_call_no_arguments(self, tool_call_no_arguments):
"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
pass
@pytest.fixture(autouse=True)
def skip_non_json_tests(self, request):
if not "json" in request.function.__name__.lower():