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fix(pattern_match_deployments.py): default to user input if unable to… (#6632)
* fix(pattern_match_deployments.py): default to user input if unable to map based on wildcards * test: fix test * test: reset test name * test: update conftest to reload proxy server module between tests * ci(config.yml): move langfuse out of local_testing reduce ci/cd time * ci(config.yml): cleanup langfuse ci/cd tests * fix: update test to not use global proxy_server app module * ci: move caching to a separate test pipeline speed up ci pipeline * test: update conftest to check if proxy_server attr exists before reloading * build(conftest.py): don't block on inability to reload proxy_server * ci(config.yml): update caching unit test filter to work on 'cache' keyword as well * fix(encrypt_decrypt_utils.py): use function to get salt key * test: mark flaky test * test: handle anthropic overloaded errors * refactor: create separate ci/cd pipeline for proxy unit tests make ci/cd faster * ci(config.yml): add litellm_proxy_unit_testing to build_and_test jobs * ci(config.yml): generate prisma binaries for proxy unit tests * test: readd vertex_key.json * ci(config.yml): remove `-s` from proxy_unit_test cmd speed up test * ci: remove any 'debug' logging flag speed up ci pipeline * test: fix test * test(test_braintrust.py): rerun * test: add delay for braintrust test
This commit is contained in:
Krish Dholakia
GitHub
parent
44840d615d
commit
27e18358ab
77 changed files with 2861 additions and 76 deletions
318
tests/proxy_unit_tests/test_proxy_exception_mapping.py
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318
tests/proxy_unit_tests/test_proxy_exception_mapping.py
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@ -0,0 +1,318 @@
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# test that the proxy actually does exception mapping to the OpenAI format
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import json
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import os
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import sys
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from unittest import mock
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from dotenv import load_dotenv
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load_dotenv()
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import asyncio
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import io
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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 openai
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import pytest
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from fastapi import Response
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from fastapi.testclient import TestClient
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import litellm
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from litellm.proxy.proxy_server import ( # Replace with the actual module where your FastAPI router is defined
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initialize,
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router,
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save_worker_config,
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)
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invalid_authentication_error_response = Response(
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status_code=401,
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content=json.dumps({"error": "Invalid Authentication"}),
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)
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context_length_exceeded_error_response_dict = {
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"error": {
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"message": "AzureException - Error code: 400 - {'error': {'message': \"This model's maximum context length is 4096 tokens. However, your messages resulted in 10007 tokens. Please reduce the length of the messages.\", 'type': 'invalid_request_error', 'param': 'messages', 'code': 'context_length_exceeded'}}",
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"type": None,
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"param": None,
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"code": 400,
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},
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}
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context_length_exceeded_error_response = Response(
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status_code=400,
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content=json.dumps(context_length_exceeded_error_response_dict),
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)
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@pytest.fixture
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def client():
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filepath = os.path.dirname(os.path.abspath(__file__))
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config_fp = f"{filepath}/test_configs/test_bad_config.yaml"
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asyncio.run(initialize(config=config_fp))
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from litellm.proxy.proxy_server import app
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return TestClient(app)
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# raise openai.AuthenticationError
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def test_chat_completion_exception(client):
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try:
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# Your test data
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test_data = {
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"model": "gpt-3.5-turbo",
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"messages": [
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{"role": "user", "content": "hi"},
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],
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"max_tokens": 10,
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}
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response = client.post("/chat/completions", json=test_data)
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json_response = response.json()
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print("keys in json response", json_response.keys())
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assert json_response.keys() == {"error"}
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print("ERROR=", json_response["error"])
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assert isinstance(json_response["error"]["message"], str)
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assert (
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"litellm.AuthenticationError: AuthenticationError"
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in json_response["error"]["message"]
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)
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code_in_error = json_response["error"]["code"]
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# OpenAI SDK required code to be STR, https://github.com/BerriAI/litellm/issues/4970
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# If we look on official python OpenAI lib, the code should be a string:
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# https://github.com/openai/openai-python/blob/195c05a64d39c87b2dfdf1eca2d339597f1fce03/src/openai/types/shared/error_object.py#L11
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# Related LiteLLM issue: https://github.com/BerriAI/litellm/discussions/4834
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assert type(code_in_error) == str
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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assert isinstance(openai_exception, openai.AuthenticationError)
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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# raise openai.AuthenticationError
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@mock.patch(
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"litellm.proxy.proxy_server.llm_router.acompletion",
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return_value=invalid_authentication_error_response,
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)
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def test_chat_completion_exception_azure(mock_acompletion, client):
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try:
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# Your test data
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test_data = {
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"model": "azure-gpt-3.5-turbo",
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"messages": [
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{"role": "user", "content": "hi"},
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],
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"max_tokens": 10,
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}
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response = client.post("/chat/completions", json=test_data)
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mock_acompletion.assert_called_once_with(
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**test_data,
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litellm_call_id=mock.ANY,
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litellm_logging_obj=mock.ANY,
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request_timeout=mock.ANY,
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metadata=mock.ANY,
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proxy_server_request=mock.ANY,
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)
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json_response = response.json()
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print("keys in json response", json_response.keys())
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assert json_response.keys() == {"error"}
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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print(openai_exception)
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assert isinstance(openai_exception, openai.AuthenticationError)
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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# raise openai.AuthenticationError
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@mock.patch(
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"litellm.proxy.proxy_server.llm_router.aembedding",
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return_value=invalid_authentication_error_response,
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)
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def test_embedding_auth_exception_azure(mock_aembedding, client):
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try:
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# Your test data
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test_data = {"model": "azure-embedding", "input": ["hi"]}
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response = client.post("/embeddings", json=test_data)
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mock_aembedding.assert_called_once_with(
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**test_data,
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metadata=mock.ANY,
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proxy_server_request=mock.ANY,
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)
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print("Response from proxy=", response)
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json_response = response.json()
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print("keys in json response", json_response.keys())
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assert json_response.keys() == {"error"}
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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print("Exception raised=", openai_exception)
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assert isinstance(openai_exception, openai.AuthenticationError)
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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# raise openai.BadRequestError
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# chat/completions openai
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def test_exception_openai_bad_model(client):
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try:
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# Your test data
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test_data = {
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"model": "azure/GPT-12",
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"messages": [
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{"role": "user", "content": "hi"},
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],
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"max_tokens": 10,
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}
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response = client.post("/chat/completions", json=test_data)
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json_response = response.json()
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print("keys in json response", json_response.keys())
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assert json_response.keys() == {"error"}
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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print("Type of exception=", type(openai_exception))
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assert isinstance(openai_exception, openai.BadRequestError)
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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# chat/completions any model
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def test_chat_completion_exception_any_model(client):
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try:
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# Your test data
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test_data = {
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"model": "Lite-GPT-12",
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"messages": [
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{"role": "user", "content": "hi"},
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],
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"max_tokens": 10,
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}
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response = client.post("/chat/completions", json=test_data)
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json_response = response.json()
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assert json_response.keys() == {"error"}
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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assert isinstance(openai_exception, openai.BadRequestError)
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_error_message = openai_exception.message
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assert (
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"/chat/completions: Invalid model name passed in model=Lite-GPT-12"
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in str(_error_message)
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)
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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# embeddings any model
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def test_embedding_exception_any_model(client):
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try:
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# Your test data
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test_data = {"model": "Lite-GPT-12", "input": ["hi"]}
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response = client.post("/embeddings", json=test_data)
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print("Response from proxy=", response)
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print(response.json())
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json_response = response.json()
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print("keys in json response", json_response.keys())
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assert json_response.keys() == {"error"}
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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print("Exception raised=", openai_exception)
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assert isinstance(openai_exception, openai.BadRequestError)
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_error_message = openai_exception.message
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assert "/embeddings: Invalid model name passed in model=Lite-GPT-12" in str(
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_error_message
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)
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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# raise openai.BadRequestError
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@mock.patch(
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"litellm.proxy.proxy_server.llm_router.acompletion",
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return_value=context_length_exceeded_error_response,
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)
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def test_chat_completion_exception_azure_context_window(mock_acompletion, client):
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try:
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# Your test data
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test_data = {
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"model": "working-azure-gpt-3.5-turbo",
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"messages": [
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{"role": "user", "content": "hi" * 10000},
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],
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"max_tokens": 10,
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}
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response = None
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response = client.post("/chat/completions", json=test_data)
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print("got response from server", response)
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mock_acompletion.assert_called_once_with(
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**test_data,
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litellm_call_id=mock.ANY,
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litellm_logging_obj=mock.ANY,
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request_timeout=mock.ANY,
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metadata=mock.ANY,
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proxy_server_request=mock.ANY,
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)
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json_response = response.json()
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print("keys in json response", json_response.keys())
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assert json_response.keys() == {"error"}
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assert json_response == context_length_exceeded_error_response_dict
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# make an openai client to call _make_status_error_from_response
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openai_client = openai.OpenAI(api_key="anything")
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openai_exception = openai_client._make_status_error_from_response(
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response=response
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)
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print("exception from proxy", openai_exception)
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assert isinstance(openai_exception, openai.BadRequestError)
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print("passed exception is of type BadRequestError")
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except Exception as e:
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pytest.fail(f"LiteLLM Proxy test failed. Exception {str(e)}")
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