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test(proxy): harden anthropic messages hook tests

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This commit is contained in:
JerryLee 2026-06-09 00:30:28 +10:00
parent 20adad495c
commit e717b149c7
1 changed files with 41 additions and 50 deletions
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91
tests/proxy_unit_tests/test_anthropic_messages_pre_call_hook.py
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@ -51,7 +51,7 @@ def client_no_auth(fake_env_vars):
@mock_patch_anthropic_messages()
def test_anthropic_messages_runs_proxy_async_pre_call_hook(
mock_anthropic_messages, client_no_auth
mock_anthropic_messages, client_no_auth, monkeypatch
):
hook_calls = []
@ -63,33 +63,28 @@ def test_anthropic_messages_runs_proxy_async_pre_call_hook(
data["metadata"] = {**(data.get("metadata") or {}), "source": "unit-test"}
return data
original_callbacks = litellm.callbacks
litellm.callbacks = [AnthropicMessagesPreCallHook()]
monkeypatch.setattr(litellm, "callbacks", [AnthropicMessagesPreCallHook()])
try:
response = client_no_auth.post(
"/v1/messages",
json={
"model": "gpt-3.5-turbo",
"max_tokens": 100,
"messages": [{"role": "user", "content": "hi"}],
},
)
response = client_no_auth.post(
"/v1/messages",
json={
"model": "test_openai_models",
"max_tokens": 100,
"messages": [{"role": "user", "content": "hi"}],
},
)
assert response.status_code == 200
assert response.json()["content"][0]["text"] == "Hello from LiteLLM"
assert hook_calls == ["anthropic_messages"]
mock_anthropic_messages.assert_called_once()
assert (
mock_anthropic_messages.call_args.kwargs["metadata"]["source"]
== "unit-test"
)
finally:
litellm.callbacks = original_callbacks
assert response.status_code == 200
assert response.json()["content"][0]["text"] == "Hello from LiteLLM"
assert hook_calls == ["anthropic_messages"]
mock_anthropic_messages.assert_called_once()
assert mock_anthropic_messages.call_args.kwargs["metadata"]["source"] == "unit-test"
@pytest.mark.asyncio
async def test_experimental_anthropic_messages_runs_proxy_async_pre_call_hook():
async def test_experimental_anthropic_messages_runs_proxy_async_pre_call_hook(
monkeypatch,
):
from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
anthropic_messages,
)
@ -108,32 +103,28 @@ async def test_experimental_anthropic_messages_runs_proxy_async_pre_call_hook():
data["temperature"] = 0.2
return data
original_callbacks = litellm.callbacks
original_flag = litellm.use_chat_completions_url_for_anthropic_messages
litellm.callbacks = [AnthropicMessagesPreCallHook()]
litellm.use_chat_completions_url_for_anthropic_messages = True
monkeypatch.setattr(litellm, "callbacks", [AnthropicMessagesPreCallHook()])
monkeypatch.setattr(
litellm, "use_chat_completions_url_for_anthropic_messages", True
)
try:
with mock.patch(
"litellm.llms.anthropic.experimental_pass_through.messages.handler.anthropic_messages_handler",
return_value=EXAMPLE_ANTHROPIC_MESSAGES_RESULT,
) as mock_handler:
response = await anthropic_messages(
model="openai/gpt-4o-mini",
max_tokens=100,
messages=[{"role": "user", "content": "hi"}],
metadata={"existing": "keep"},
custom_llm_provider="openai",
)
with mock.patch(
"litellm.llms.anthropic.experimental_pass_through.messages.handler.anthropic_messages_handler",
return_value=EXAMPLE_ANTHROPIC_MESSAGES_RESULT,
) as mock_handler:
response = await anthropic_messages(
model="openai/gpt-4o-mini",
max_tokens=100,
messages=[{"role": "user", "content": "hi"}],
metadata={"existing": "keep"},
custom_llm_provider="openai",
)
assert response == EXAMPLE_ANTHROPIC_MESSAGES_RESULT
assert hook_calls == [("anthropic_messages", "openai/gpt-4o-mini")]
mock_handler.assert_called_once()
assert mock_handler.call_args.kwargs["metadata"] == {
"existing": "keep",
"source": "experimental-unit-test",
}
assert mock_handler.call_args.kwargs["temperature"] == 0.2
finally:
litellm.callbacks = original_callbacks
litellm.use_chat_completions_url_for_anthropic_messages = original_flag
assert response == EXAMPLE_ANTHROPIC_MESSAGES_RESULT
assert hook_calls == [("anthropic_messages", "openai/gpt-4o-mini")]
mock_handler.assert_called_once()
assert mock_handler.call_args.kwargs["metadata"] == {
"existing": "keep",
"source": "experimental-unit-test",
}
assert mock_handler.call_args.kwargs["temperature"] == 0.2