test - remove anthropic_adapter tests. no longer used

Author: ishaan-jaff

tests/llm_translation/test_anthropic_completion.py

@@ -30,7 +30,6 @@
     Router,
     adapter_completion,
 )
-from litellm.adapters.anthropic_adapter import anthropic_adapter
 from litellm.types.llms.anthropic import AnthropicResponse
 from litellm.types.utils import GenericStreamingChunk, ChatCompletionToolCallChunk
 from litellm.types.llms.openai import ChatCompletionToolCallFunctionChunk
@@ -40,65 +39,6 @@
 from base_llm_unit_tests import BaseLLMChatTest
 
 
-def test_anthropic_completion_messages_translation():
-    messages = [{"role": "user", "content": "Hey, how's it going?"}]
-
-    translated_messages = AnthropicExperimentalPassThroughConfig().translate_anthropic_messages_to_openai(messages=messages)  # type: ignore
-
-    assert translated_messages == [{"role": "user", "content": "Hey, how's it going?"}]
-
-
-def test_anthropic_completion_input_translation():
-    data = {
-        "model": "gpt-3.5-turbo",
-        "messages": [{"role": "user", "content": "Hey, how's it going?"}],
-    }
-    translated_input = anthropic_adapter.translate_completion_input_params(kwargs=data)
-
-    assert translated_input is not None
-
-    assert translated_input["model"] == "gpt-3.5-turbo"
-    assert translated_input["messages"] == [
-        {"role": "user", "content": "Hey, how's it going?"}
-    ]
-
-
-def test_anthropic_completion_input_translation_with_metadata():
-    """
-    Tests that cost tracking works as expected with LiteLLM Proxy
-
-    LiteLLM Proxy will insert litellm_metadata for anthropic endpoints to track user_api_key and user_api_key_team_id
-
-    This test ensures that the `litellm_metadata` is not present in the translated input
-    It ensures that `litellm.acompletion()` will receieve metadata which is a litellm specific param
-    """
-    data = {
-        "model": "gpt-3.5-turbo",
-        "messages": [{"role": "user", "content": "Hey, how's it going?"}],
-        "litellm_metadata": {
-            "user_api_key": "88dc28d0f030c55ed4ab77ed8faf098196cb1c05df778539800c9f1243fe6b4b",
-            "user_api_key_alias": None,
-            "user_api_end_user_max_budget": None,
-            "litellm_api_version": "1.40.19",
-            "global_max_parallel_requests": None,
-            "user_api_key_user_id": "default_user_id",
-            "user_api_key_org_id": None,
-            "user_api_key_team_id": None,
-            "user_api_key_team_alias": None,
-            "user_api_key_team_max_budget": None,
-            "user_api_key_team_spend": None,
-            "user_api_key_spend": 0.0,
-            "user_api_key_max_budget": None,
-            "user_api_key_metadata": {},
-        },
-    }
-    translated_input = anthropic_adapter.translate_completion_input_params(kwargs=data)
-
-    assert "litellm_metadata" not in translated_input
-    assert "metadata" in translated_input
-    assert translated_input["metadata"] == data["litellm_metadata"]
-
-
 def streaming_format_tests(chunk: dict, idx: int):
     """
     1st chunk -  chunk.get("type") == "message_start"
@@ -113,54 +53,6 @@ def streaming_format_tests(chunk: dict, idx: int):
         assert chunk.get("type") == "content_block_delta"
 
 
-@pytest.mark.parametrize("stream", [True])  # False
-def test_anthropic_completion_e2e(stream):
-    litellm.set_verbose = True
-
-    litellm.adapters = [{"id": "anthropic", "adapter": anthropic_adapter}]
-
-    messages = [{"role": "user", "content": "Hey, how's it going?"}]
-    response = adapter_completion(
-        model="gpt-3.5-turbo",
-        messages=messages,
-        adapter_id="anthropic",
-        mock_response="This is a fake call",
-        stream=stream,
-    )
-
-    print("Response: {}".format(response))
-
-    assert response is not None
-
-    if stream is False:
-        assert isinstance(response, AnthropicResponse)
-    else:
-        """
-        - ensure finish reason is returned
-        - assert content block is started and stopped
-        - ensure last chunk is 'message_stop'
-        """
-        assert isinstance(response, litellm.types.utils.AdapterCompletionStreamWrapper)
-        finish_reason: Optional[str] = None
-        message_stop_received = False
-        content_block_started = False
-        content_block_finished = False
-        for idx, chunk in enumerate(response):
-            print(chunk)
-            streaming_format_tests(chunk=chunk, idx=idx)
-            if chunk.get("delta", {}).get("stop_reason") is not None:
-                finish_reason = chunk.get("delta", {}).get("stop_reason")
-            if chunk.get("type") == "message_stop":
-                message_stop_received = True
-            if chunk.get("type") == "content_block_stop":
-                content_block_finished = True
-            if chunk.get("type") == "content_block_start":
-                content_block_started = True
-        assert content_block_started and content_block_finished
-        assert finish_reason is not None
-        assert message_stop_received is True
-
-
 anthropic_chunk_list = [
     {
         "type": "content_block_start",
@@ -371,99 +263,6 @@ def test_anthropic_tool_streaming():
             assert tool_use["index"] == correct_tool_index
 
 
-def test_anthropic_tool_calling_translation():
-    kwargs = {
-        "model": "claude-3-5-sonnet-20240620",
-        "messages": [
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": "Would development of a software platform be under ASC 350-40 or ASC 985?",
-                    }
-                ],
-            },
-            {
-                "role": "assistant",
-                "content": [
-                    {
-                        "type": "tool_use",
-                        "id": "37d6f703-cbcc-497d-95a1-2aa24a114adc",
-                        "name": "TaskPlanningTool",
-                        "input": {
-                            "completed_steps": [],
-                            "next_steps": [
-                                {
-                                    "tool_name": "AccountingResearchTool",
-                                    "description": "Research ASC 350-40 to understand its scope and applicability to software development.",
-                                },
-                                {
-                                    "tool_name": "AccountingResearchTool",
-                                    "description": "Research ASC 985 to understand its scope and applicability to software development.",
-                                },
-                                {
-                                    "tool_name": "AccountingResearchTool",
-                                    "description": "Compare the scopes of ASC 350-40 and ASC 985 to determine which is more applicable to software platform development.",
-                                },
-                            ],
-                            "learnings": [],
-                            "potential_issues": [
-                                "The distinction between the two standards might not be clear-cut for all types of software development.",
-                                "There might be specific circumstances or details about the software platform that could affect which standard applies.",
-                            ],
-                            "missing_info": [
-                                "Specific details about the type of software platform being developed (e.g., for internal use or for sale).",
-                                "Whether the entity developing the software is also the end-user or if it's being developed for external customers.",
-                            ],
-                            "done": False,
-                            "required_formatting": None,
-                        },
-                    }
-                ],
-            },
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "tool_result",
-                        "tool_use_id": "eb7023b1-5ee8-43b8-b90f-ac5a23d37c31",
-                        "content": {
-                            "completed_steps": [],
-                            "next_steps": [
-                                {
-                                    "tool_name": "AccountingResearchTool",
-                                    "description": "Research ASC 350-40 to understand its scope and applicability to software development.",
-                                },
-                                {
-                                    "tool_name": "AccountingResearchTool",
-                                    "description": "Research ASC 985 to understand its scope and applicability to software development.",
-                                },
-                                {
-                                    "tool_name": "AccountingResearchTool",
-                                    "description": "Compare the scopes of ASC 350-40 and ASC 985 to determine which is more applicable to software platform development.",
-                                },
-                            ],
-                            "formatting_step": None,
-                        },
-                    }
-                ],
-            },
-        ],
-    }
-
-    from litellm.adapters.anthropic_adapter import anthropic_adapter
-
-    translated_params = anthropic_adapter.translate_completion_input_params(
-        kwargs=kwargs
-    )
-
-    print(translated_params["messages"])
-
-    assert len(translated_params["messages"]) > 0
-    assert translated_params["messages"][0]["role"] == "user"
-
-
 def test_process_anthropic_headers_empty():
     result = process_anthropic_headers({})
     assert result == {}, "Expected empty dictionary for no input"