litellm-mirror/tests/llm_translation/test_bedrock_invoke_tests.py
Krish Dholakia 05a973bf19 Litellm dev bedrock anthropic 3 7 v2 (#8843)
* feat(bedrock/converse/transformation.py): support claude-3-7-sonnet reasoning_Content transformation

Closes https://github.com/BerriAI/litellm/issues/8777

* fix(bedrock/): support returning `reasoning_content` on streaming for claude-3-7

Resolves https://github.com/BerriAI/litellm/issues/8777

* feat(bedrock/): unify converse reasoning content blocks for consistency across anthropic and bedrock

* fix(anthropic/chat/transformation.py): handle deepseek-style 'reasoning_content' extraction within transformation.py

simpler logic

* feat(bedrock/): fix streaming to return blocks in consistent format

* fix: fix linting error

* test: fix test

* feat(factory.py): fix bedrock thinking block translation on tool calling

allows passing the thinking blocks back to bedrock for tool calling

* fix(types/utils.py): don't exclude provider_specific_fields on model dump

ensures consistent responses

* fix: fix linting errors

* fix(convert_dict_to_response.py): pass reasoning_content on root

* fix: test

* fix(streaming_handler.py): add helper util for setting model id

* fix(streaming_handler.py): fix setting model id on model response stream chunk

* fix(streaming_handler.py): fix linting error

* fix(streaming_handler.py): fix linting error

* fix(types/utils.py): add provider_specific_fields to model stream response

* fix(streaming_handler.py): copy provider specific fields and add them to the root of the streaming response

* fix(streaming_handler.py): fix check

* fix: fix test

* fix(types/utils.py): ensure messages content is always openai compatible

* fix(types/utils.py): fix delta object to always be openai compatible

only introduce new params if variable exists

* test: fix bedrock nova tests

* test: skip flaky test

* test: skip flaky test in ci/cd
2025-02-26 16:05:33 -08:00

155 lines
5.6 KiB
Python

from base_llm_unit_tests import BaseLLMChatTest
import pytest
import sys
import os
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import litellm
from litellm.types.llms.bedrock import BedrockInvokeNovaRequest
class TestBedrockInvokeClaudeJson(BaseLLMChatTest):
def get_base_completion_call_args(self) -> dict:
litellm._turn_on_debug()
return {
"model": "bedrock/invoke/anthropic.claude-3-5-sonnet-20240620-v1:0",
}
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():
pytest.skip(
f"Skipping non-JSON test: {request.function.__name__} does not contain 'json'"
)
class TestBedrockInvokeNovaJson(BaseLLMChatTest):
def get_base_completion_call_args(self) -> dict:
litellm._turn_on_debug()
return {
"model": "bedrock/invoke/us.amazon.nova-micro-v1:0",
}
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():
pytest.skip(
f"Skipping non-JSON test: {request.function.__name__} does not contain 'json'"
)
def test_nova_invoke_remove_empty_system_messages():
"""Test that _remove_empty_system_messages removes empty system list."""
input_request = BedrockInvokeNovaRequest(
messages=[{"content": [{"text": "Hello"}], "role": "user"}],
system=[],
inferenceConfig={"temperature": 0.7},
)
litellm.AmazonInvokeNovaConfig()._remove_empty_system_messages(input_request)
assert "system" not in input_request
assert "messages" in input_request
assert "inferenceConfig" in input_request
def test_nova_invoke_filter_allowed_fields():
"""
Test that _filter_allowed_fields only keeps fields defined in BedrockInvokeNovaRequest.
Nova Invoke does not allow `additionalModelRequestFields` and `additionalModelResponseFieldPaths` in the request body.
This test ensures that these fields are not included in the request body.
"""
_input_request = {
"messages": [{"content": [{"text": "Hello"}], "role": "user"}],
"system": [{"text": "System prompt"}],
"inferenceConfig": {"temperature": 0.7},
"additionalModelRequestFields": {"this": "should be removed"},
"additionalModelResponseFieldPaths": ["this", "should", "be", "removed"],
}
input_request = BedrockInvokeNovaRequest(**_input_request)
result = litellm.AmazonInvokeNovaConfig()._filter_allowed_fields(input_request)
assert "additionalModelRequestFields" not in result
assert "additionalModelResponseFieldPaths" not in result
assert "messages" in result
assert "system" in result
assert "inferenceConfig" in result
def test_nova_invoke_streaming_chunk_parsing():
"""
Test that the AWSEventStreamDecoder correctly handles Nova's /bedrock/invoke/ streaming format
where content is nested under 'contentBlockDelta'.
"""
from litellm.llms.bedrock.chat.invoke_handler import AWSEventStreamDecoder
# Initialize the decoder with a Nova model
decoder = AWSEventStreamDecoder(model="bedrock/invoke/us.amazon.nova-micro-v1:0")
# Test case 1: Text content in contentBlockDelta
nova_text_chunk = {
"contentBlockDelta": {
"delta": {"text": "Hello, how can I help?"},
"contentBlockIndex": 0,
}
}
result = decoder._chunk_parser(nova_text_chunk)
assert result.choices[0].delta.content == "Hello, how can I help?"
assert result.choices[0].index == 0
assert not result.choices[0].finish_reason
assert result.choices[0].delta.tool_calls is None
# Test case 2: Tool use start in contentBlockDelta
nova_tool_start_chunk = {
"contentBlockDelta": {
"start": {"toolUse": {"name": "get_weather", "toolUseId": "tool_1"}},
"contentBlockIndex": 1,
}
}
result = decoder._chunk_parser(nova_tool_start_chunk)
assert result.choices[0].delta.content == ""
assert result.choices[0].index == 1
assert result.choices[0].delta.tool_calls is not None
assert result.choices[0].delta.tool_calls[0].type == "function"
assert result.choices[0].delta.tool_calls[0].function.name == "get_weather"
assert result.choices[0].delta.tool_calls[0].id == "tool_1"
# Test case 3: Tool use arguments in contentBlockDelta
nova_tool_args_chunk = {
"contentBlockDelta": {
"delta": {"toolUse": {"input": '{"location": "New York"}'}},
"contentBlockIndex": 2,
}
}
result = decoder._chunk_parser(nova_tool_args_chunk)
assert result.choices[0].delta.content == ""
assert result.choices[0].index == 2
assert result.choices[0].delta.tool_calls is not None
assert (
result.choices[0].delta.tool_calls[0].function.arguments
== '{"location": "New York"}'
)
# Test case 4: Stop reason in contentBlockDelta
nova_stop_chunk = {
"contentBlockDelta": {
"stopReason": "tool_use",
}
}
result = decoder._chunk_parser(nova_stop_chunk)
print(result)
assert result.choices[0].finish_reason == "tool_calls"