Added LiteLLM to the stack
This commit is contained in:
@@ -0,0 +1,478 @@
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import json
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import os
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import sys
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from unittest.mock import ANY
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import pytest
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import respx
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from fastapi.testclient import TestClient
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from pytest_mock import MockerFixture
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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 import Router
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from litellm.proxy._types import LiteLLM_UserTableFiltered, UserAPIKeyAuth
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from litellm.proxy.hooks import get_proxy_hook
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from litellm.proxy.management_endpoints.internal_user_endpoints import ui_view_users
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from litellm.proxy.proxy_server import app
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client = TestClient(app)
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from litellm.caching.caching import DualCache
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from litellm.proxy.proxy_server import hash_token
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from litellm.proxy.utils import ProxyLogging
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@pytest.fixture
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def llm_router() -> Router:
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llm_router = Router(
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model_list=[
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{
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"model_name": "azure-gpt-3-5-turbo",
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"litellm_params": {
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"model": "azure/chatgpt-v-2",
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"api_key": "azure_api_key",
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"api_base": "azure_api_base",
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"api_version": "azure_api_version",
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},
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"model_info": {
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"id": "azure-gpt-3-5-turbo-id",
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},
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},
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{
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"model_name": "gpt-3.5-turbo",
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"litellm_params": {
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"model": "openai/gpt-3.5-turbo",
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"api_key": "openai_api_key",
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},
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"model_info": {
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"id": "gpt-3.5-turbo-id",
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},
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},
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{
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"model_name": "gemini-2.0-flash",
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"litellm_params": {
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"model": "gemini/gemini-2.0-flash",
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},
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"model_info": {
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"id": "gemini-2.0-flash-id",
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},
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},
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]
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)
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return llm_router
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def setup_proxy_logging_object(monkeypatch, llm_router: Router) -> ProxyLogging:
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proxy_logging_object = ProxyLogging(
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user_api_key_cache=DualCache(default_in_memory_ttl=1)
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)
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proxy_logging_object._add_proxy_hooks(llm_router)
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monkeypatch.setattr(
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"litellm.proxy.proxy_server.proxy_logging_obj", proxy_logging_object
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)
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return proxy_logging_object
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def test_invalid_purpose(mocker: MockerFixture, monkeypatch, llm_router: Router):
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"""
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Asserts 'create_file' is called with the correct arguments
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"""
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# Create a simple test file content
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test_file_content = b"test audio content"
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test_file = ("test.wav", test_file_content, "audio/wav")
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response = client.post(
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"/v1/files",
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files={"file": test_file},
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data={
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"purpose": "my-bad-purpose",
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"target_model_names": ["azure-gpt-3-5-turbo", "gpt-3.5-turbo"],
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},
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headers={"Authorization": "Bearer test-key"},
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)
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assert response.status_code == 400
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print(f"response: {response.json()}")
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assert "Invalid purpose: my-bad-purpose" in response.json()["error"]["message"]
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def test_mock_create_audio_file(mocker: MockerFixture, monkeypatch, llm_router: Router):
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"""
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Asserts 'create_file' is called with the correct arguments
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"""
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import litellm
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from litellm import Router
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from litellm.proxy.utils import ProxyLogging
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# Mock create_file as an async function
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mock_create_file = mocker.patch("litellm.files.main.create_file", new=mocker.AsyncMock())
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proxy_logging_obj = ProxyLogging(
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user_api_key_cache=DualCache(default_in_memory_ttl=1)
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)
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proxy_logging_obj._add_proxy_hooks(llm_router)
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# Add managed_files hook to ensure the test reaches the mocked function
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from litellm.llms.base_llm.files.transformation import BaseFileEndpoints
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class DummyManagedFiles(BaseFileEndpoints):
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async def acreate_file(self, llm_router, create_file_request, target_model_names_list, litellm_parent_otel_span, user_api_key_dict):
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# Handle both dict and object forms of create_file_request
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if isinstance(create_file_request, dict):
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file_data = create_file_request.get("file")
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purpose_data = create_file_request.get("purpose")
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else:
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file_data = create_file_request.file
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purpose_data = create_file_request.purpose
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# Call the mocked litellm.files.main.create_file to ensure asserts work
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await litellm.files.main.create_file(
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custom_llm_provider="azure",
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model="azure/chatgpt-v-2",
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api_key="azure_api_key",
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file=file_data,
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purpose=purpose_data,
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)
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await litellm.files.main.create_file(
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custom_llm_provider="openai",
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model="openai/gpt-3.5-turbo",
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api_key="openai_api_key",
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file=file_data,
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purpose=purpose_data,
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)
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# Return a dummy response object as needed by the test
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from litellm.types.llms.openai import OpenAIFileObject
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return OpenAIFileObject(
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id="dummy-id",
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object="file",
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bytes=len(file_data[1]) if file_data else 0,
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created_at=1234567890,
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filename=file_data[0] if file_data else "test.wav",
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purpose=purpose_data,
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status="uploaded",
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)
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async def afile_retrieve(self, file_id, litellm_parent_otel_span):
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raise NotImplementedError("Not implemented for test")
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async def afile_list(self, purpose, litellm_parent_otel_span):
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raise NotImplementedError("Not implemented for test")
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async def afile_delete(self, file_id, litellm_parent_otel_span):
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raise NotImplementedError("Not implemented for test")
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async def afile_content(self, file_id, litellm_parent_otel_span):
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raise NotImplementedError("Not implemented for test")
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# Manually add the hook to the proxy_hook_mapping
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proxy_logging_obj.proxy_hook_mapping["managed_files"] = DummyManagedFiles()
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monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", llm_router)
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monkeypatch.setattr(
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"litellm.proxy.proxy_server.proxy_logging_obj", proxy_logging_obj
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)
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# Create a simple test file content
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test_file_content = b"test audio content"
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test_file = ("test.wav", test_file_content, "audio/wav")
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response = client.post(
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"/v1/files",
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files={"file": test_file},
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data={
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"purpose": "user_data",
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"target_model_names": "azure-gpt-3-5-turbo, gpt-3.5-turbo",
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},
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headers={"Authorization": "Bearer test-key"},
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)
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assert response.status_code == 200
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# Get all calls made to create_file
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calls = mock_create_file.call_args_list
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# Check for Azure call
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azure_call_found = False
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for call in calls:
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kwargs = call.kwargs
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if (
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kwargs.get("custom_llm_provider") == "azure"
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and kwargs.get("model") == "azure/chatgpt-v-2"
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and kwargs.get("api_key") == "azure_api_key"
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):
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azure_call_found = True
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break
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assert (
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azure_call_found
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), f"Azure call not found with expected parameters. Calls: {calls}"
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# Check for OpenAI call
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openai_call_found = False
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for call in calls:
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kwargs = call.kwargs
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if (
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kwargs.get("custom_llm_provider") == "openai"
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and kwargs.get("model") == "openai/gpt-3.5-turbo"
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and kwargs.get("api_key") == "openai_api_key"
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):
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openai_call_found = True
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break
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assert openai_call_found, "OpenAI call not found with expected parameters"
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@pytest.mark.skip(reason="mock respx fails on ci/cd - unclear why")
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def test_create_file_and_call_chat_completion_e2e(
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mocker: MockerFixture, monkeypatch, llm_router: Router
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):
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"""
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1. Create a file
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2. Call a chat completion with the file
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3. Assert the file is used in the chat completion
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"""
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# Create and enable respx mock instance
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mock = respx.mock()
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mock.start()
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try:
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from litellm.types.llms.openai import OpenAIFileObject
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monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", llm_router)
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proxy_logging_object = setup_proxy_logging_object(monkeypatch, llm_router)
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# Create a simple test file content
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test_file_content = b"test audio content"
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test_file = ("test.wav", test_file_content, "audio/wav")
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# Mock the file creation response
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mock_file_response = OpenAIFileObject(
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id="test-file-id",
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object="file",
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bytes=123,
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created_at=1234567890,
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filename="test.wav",
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purpose="user_data",
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status="uploaded",
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)
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mock_file_response._hidden_params = {"model_id": "gemini-2.0-flash-id"}
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mocker.patch.object(llm_router, "acreate_file", return_value=mock_file_response)
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# Mock the Gemini API call using respx
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mock_gemini_response = {
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"candidates": [
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{"content": {"parts": [{"text": "This is a test audio file"}]}}
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]
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}
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# Mock the Gemini API endpoint with a more flexible pattern
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gemini_route = mock.post(
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url__regex=r".*generativelanguage\.googleapis\.com.*"
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).mock(
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return_value=respx.MockResponse(status_code=200, json=mock_gemini_response),
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)
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# Print updated mock setup
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print("\nAfter Adding Gemini Route:")
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print("==========================")
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print(f"Number of mocked routes: {len(mock.routes)}")
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for route in mock.routes:
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print(f"Mocked Route: {route}")
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print(f"Pattern: {route.pattern}")
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## CREATE FILE
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file = client.post(
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"/v1/files",
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files={"file": test_file},
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data={
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"purpose": "user_data",
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"target_model_names": "gemini-2.0-flash, gpt-3.5-turbo",
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},
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headers={"Authorization": "Bearer test-key"},
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)
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print("\nAfter File Creation:")
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print("====================")
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print(f"File creation status: {file.status_code}")
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print(f"Recorded calls so far: {len(mock.calls)}")
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for call in mock.calls:
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print(f"Call made to: {call.request.method} {call.request.url}")
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assert file.status_code == 200
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assert file.json()["id"] != "test-file-id" # unified file id used
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## USE FILE IN CHAT COMPLETION
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try:
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completion = client.post(
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"/v1/chat/completions",
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json={
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"model": "gemini-2.0-flash",
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"modalities": ["text", "audio"],
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"audio": {"voice": "alloy", "format": "wav"},
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": "What is in this recording?"},
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{
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"type": "file",
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"file": {
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"file_id": file.json()["id"],
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"filename": "my-test-name",
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"format": "audio/wav",
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},
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},
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],
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},
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],
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"drop_params": True,
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},
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headers={"Authorization": "Bearer test-key"},
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)
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except Exception as e:
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print(f"error: {e}")
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print("\nError occurred during chat completion:")
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print("=====================================")
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print("\nFinal Mock State:")
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print("=================")
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print(f"Total mocked routes: {len(mock.routes)}")
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for route in mock.routes:
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print(f"\nMocked Route: {route}")
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print(f" Called: {route.called}")
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print("\nActual Requests Made:")
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print("=====================")
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print(f"Total calls recorded: {len(mock.calls)}")
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for idx, call in enumerate(mock.calls):
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print(f"\nCall {idx + 1}:")
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print(f" Method: {call.request.method}")
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print(f" URL: {call.request.url}")
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print(f" Headers: {dict(call.request.headers)}")
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try:
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print(f" Body: {call.request.content.decode()}")
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except:
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print(" Body: <could not decode>")
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# Verify Gemini API was called
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assert gemini_route.called, "Gemini API was not called"
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# Print the call details
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print("\nGemini API Call Details:")
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print(f"URL: {gemini_route.calls.last.request.url}")
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print(f"Method: {gemini_route.calls.last.request.method}")
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print(f"Headers: {dict(gemini_route.calls.last.request.headers)}")
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print(f"Content: {gemini_route.calls.last.request.content.decode()}")
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print(f"Response: {gemini_route.calls.last.response.content.decode()}")
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assert "test-file-id" in gemini_route.calls.last.request.content.decode()
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finally:
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# Stop the mock
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mock.stop()
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@pytest.mark.skip(reason="function migrated to litellm/proxy/hooks/managed_files.py")
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def test_create_file_for_each_model(
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mocker: MockerFixture, monkeypatch, llm_router: Router
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):
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"""
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Test that create_file_for_each_model creates files for each target model and returns a unified file ID
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"""
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import asyncio
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from litellm import CreateFileRequest
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from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
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from litellm.proxy.openai_files_endpoints.files_endpoints import (
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create_file_for_each_model,
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)
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from litellm.proxy.utils import ProxyLogging
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from litellm.types.llms.openai import OpenAIFileObject, OpenAIFilesPurpose
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# Setup proxy logging
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proxy_logging_obj = ProxyLogging(
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user_api_key_cache=DualCache(default_in_memory_ttl=1)
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)
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proxy_logging_obj._add_proxy_hooks(llm_router)
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monkeypatch.setattr(
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"litellm.proxy.proxy_server.proxy_logging_obj", proxy_logging_obj
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)
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# Mock user API key dict
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user_api_key_dict = UserAPIKeyAuth(
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api_key="test-key",
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user_role=LitellmUserRoles.INTERNAL_USER,
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user_id="test-user",
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team_id="test-team",
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team_alias="test-team-alias",
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parent_otel_span=None,
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)
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# Create test file request
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test_file_content = b"test file content"
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test_file = ("test.txt", test_file_content, "text/plain")
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_create_file_request = CreateFileRequest(file=test_file, purpose="user_data")
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# Mock the router's acreate_file method
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mock_file_response = OpenAIFileObject(
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id="test-file-id",
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object="file",
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bytes=123,
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created_at=1234567890,
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filename="test.txt",
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purpose="user_data",
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status="uploaded",
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)
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mock_file_response._hidden_params = {"model_id": "test-model-id"}
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mocker.patch.object(llm_router, "acreate_file", return_value=mock_file_response)
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# Call the function
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target_model_names_list = ["azure-gpt-3-5-turbo", "gpt-3.5-turbo"]
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response = asyncio.run(
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create_file_for_each_model(
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llm_router=llm_router,
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_create_file_request=_create_file_request,
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target_model_names_list=target_model_names_list,
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purpose="user_data",
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proxy_logging_obj=proxy_logging_obj,
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user_api_key_dict=user_api_key_dict,
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)
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)
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# Verify the response
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assert isinstance(response, OpenAIFileObject)
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assert response.id is not None
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assert response.purpose == "user_data"
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assert response.filename == "test.txt"
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# Verify acreate_file was called for each model
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assert llm_router.acreate_file.call_count == len(target_model_names_list)
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# Get all calls made to acreate_file
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calls = llm_router.acreate_file.call_args_list
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# Verify Azure call
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azure_call_found = False
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for call in calls:
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kwargs = call.kwargs
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if (
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kwargs.get("model") == "azure-gpt-3-5-turbo"
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and kwargs.get("file") == test_file
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and kwargs.get("purpose") == "user_data"
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):
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||||
azure_call_found = True
|
||||
break
|
||||
assert azure_call_found, "Azure call not found with expected parameters"
|
||||
|
||||
# Verify OpenAI call
|
||||
openai_call_found = False
|
||||
for call in calls:
|
||||
kwargs = call.kwargs
|
||||
if (
|
||||
kwargs.get("model") == "gpt-3.5-turbo"
|
||||
and kwargs.get("file") == test_file
|
||||
and kwargs.get("purpose") == "user_data"
|
||||
):
|
||||
openai_call_found = True
|
||||
break
|
||||
assert openai_call_found, "OpenAI call not found with expected parameters"
|
||||
Reference in New Issue
Block a user