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* fix(anthropic_claude3_transformation.py): fix amazon anthropic claude 3 tool calling transformation on invoke route move to using anthropic config as base * fix(utils.py): expose anthropic config via providerconfigmanager * fix(llm_http_handler.py): support json mode on async completion calls * fix(invoke_handler/make_call): support json mode for anthropic called via bedrock invoke * fix(anthropic/): handle 'response_format: {"type": "text"}` + migrate amazon claude 3 invoke config to inherit from anthropic config Prevents error when passing in 'response_format: {"type": "text"} * test: fix test * fix(utils.py): fix base invoke provider check * fix(anthropic_claude3_transformation.py): don't pass 'stream' param * fix: fix linting errors * fix(converse_transformation.py): handle response_format type=text for converse
147 lines
5.3 KiB
Python
147 lines
5.3 KiB
Python
from base_llm_unit_tests import BaseLLMChatTest
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import pytest
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import sys
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import os
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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import litellm
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from litellm.types.llms.bedrock import BedrockInvokeNovaRequest
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class TestBedrockInvokeClaudeJson(BaseLLMChatTest):
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def get_base_completion_call_args(self) -> dict:
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litellm._turn_on_debug()
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return {
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"model": "bedrock/invoke/anthropic.claude-3-5-sonnet-20240620-v1:0",
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}
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def test_tool_call_no_arguments(self, tool_call_no_arguments):
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"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
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pass
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class TestBedrockInvokeNovaJson(BaseLLMChatTest):
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def get_base_completion_call_args(self) -> dict:
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return {
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"model": "bedrock/invoke/us.amazon.nova-micro-v1:0",
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}
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def test_tool_call_no_arguments(self, tool_call_no_arguments):
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"""Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
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pass
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@pytest.fixture(autouse=True)
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def skip_non_json_tests(self, request):
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if not "json" in request.function.__name__.lower():
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pytest.skip(
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f"Skipping non-JSON test: {request.function.__name__} does not contain 'json'"
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)
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def test_nova_invoke_remove_empty_system_messages():
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"""Test that _remove_empty_system_messages removes empty system list."""
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input_request = BedrockInvokeNovaRequest(
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messages=[{"content": [{"text": "Hello"}], "role": "user"}],
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system=[],
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inferenceConfig={"temperature": 0.7},
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)
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litellm.AmazonInvokeNovaConfig()._remove_empty_system_messages(input_request)
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assert "system" not in input_request
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assert "messages" in input_request
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assert "inferenceConfig" in input_request
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def test_nova_invoke_filter_allowed_fields():
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"""
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Test that _filter_allowed_fields only keeps fields defined in BedrockInvokeNovaRequest.
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Nova Invoke does not allow `additionalModelRequestFields` and `additionalModelResponseFieldPaths` in the request body.
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This test ensures that these fields are not included in the request body.
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"""
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_input_request = {
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"messages": [{"content": [{"text": "Hello"}], "role": "user"}],
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"system": [{"text": "System prompt"}],
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"inferenceConfig": {"temperature": 0.7},
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"additionalModelRequestFields": {"this": "should be removed"},
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"additionalModelResponseFieldPaths": ["this", "should", "be", "removed"],
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}
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input_request = BedrockInvokeNovaRequest(**_input_request)
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result = litellm.AmazonInvokeNovaConfig()._filter_allowed_fields(input_request)
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assert "additionalModelRequestFields" not in result
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assert "additionalModelResponseFieldPaths" not in result
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assert "messages" in result
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assert "system" in result
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assert "inferenceConfig" in result
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def test_nova_invoke_streaming_chunk_parsing():
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"""
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Test that the AWSEventStreamDecoder correctly handles Nova's /bedrock/invoke/ streaming format
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where content is nested under 'contentBlockDelta'.
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"""
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from litellm.llms.bedrock.chat.invoke_handler import AWSEventStreamDecoder
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# Initialize the decoder with a Nova model
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decoder = AWSEventStreamDecoder(model="bedrock/invoke/us.amazon.nova-micro-v1:0")
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# Test case 1: Text content in contentBlockDelta
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nova_text_chunk = {
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"contentBlockDelta": {
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"delta": {"text": "Hello, how can I help?"},
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"contentBlockIndex": 0,
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}
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}
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result = decoder._chunk_parser(nova_text_chunk)
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assert result.choices[0].delta.content == "Hello, how can I help?"
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assert result.choices[0].index == 0
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assert not result.choices[0].finish_reason
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assert result.choices[0].delta.tool_calls is None
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# Test case 2: Tool use start in contentBlockDelta
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nova_tool_start_chunk = {
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"contentBlockDelta": {
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"start": {"toolUse": {"name": "get_weather", "toolUseId": "tool_1"}},
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"contentBlockIndex": 1,
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}
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}
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result = decoder._chunk_parser(nova_tool_start_chunk)
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assert result.choices[0].delta.content == ""
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assert result.choices[0].index == 1
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assert result.choices[0].delta.tool_calls is not None
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assert result.choices[0].delta.tool_calls[0].type == "function"
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assert result.choices[0].delta.tool_calls[0].function.name == "get_weather"
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assert result.choices[0].delta.tool_calls[0].id == "tool_1"
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# Test case 3: Tool use arguments in contentBlockDelta
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nova_tool_args_chunk = {
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"contentBlockDelta": {
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"delta": {"toolUse": {"input": '{"location": "New York"}'}},
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"contentBlockIndex": 2,
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}
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}
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result = decoder._chunk_parser(nova_tool_args_chunk)
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assert result.choices[0].delta.content == ""
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assert result.choices[0].index == 2
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assert result.choices[0].delta.tool_calls is not None
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assert (
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result.choices[0].delta.tool_calls[0].function.arguments
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== '{"location": "New York"}'
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)
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# Test case 4: Stop reason in contentBlockDelta
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nova_stop_chunk = {
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"contentBlockDelta": {
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"stopReason": "tool_use",
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}
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}
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result = decoder._chunk_parser(nova_stop_chunk)
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print(result)
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assert result.choices[0].finish_reason == "tool_calls"
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