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* test(proxy): move proxy_server, _experimental and db tests into tests/unit/proxy Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(proxy): keep tuple identity in proxy state restore and fix misc target paths Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yuneng <yuneng@berri.ai> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
121 lines
3.8 KiB
Python
121 lines
3.8 KiB
Python
"""Behavior pins for ``proxy_server.py`` embeddings routes.
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Pins (PR2):
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- POST /v1/embeddings
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- POST /embeddings
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- POST /engines/{model:path}/embeddings
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- POST /openai/deployments/{model:path}/embeddings
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"""
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from __future__ import annotations
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from litellm.proxy import common_request_processing, proxy_server
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from .conftest import normalize # type: ignore[import-not-found]
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HAPPY_RESPONSE = {
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"object": "list",
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"model": "text-embedding-ada-002",
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"data": [{"embedding": [0.0, 0.1, 0.2], "index": 0, "object": "embedding"}],
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"usage": {"prompt_tokens": 1, "total_tokens": 1},
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}
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@pytest.fixture
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def patched_embedding(monkeypatch):
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router = MagicMock()
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router.model_names = ["text-embedding-ada-002"]
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router.get_deployment_by_model_group_name = MagicMock(return_value=None)
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monkeypatch.setattr(proxy_server, "llm_router", router)
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monkeypatch.setattr(
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proxy_server, "proxy_logging_obj", MagicMock(post_call_failure_hook=AsyncMock())
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)
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async def _fake_process(self, *args, **kwargs):
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return dict(HAPPY_RESPONSE)
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monkeypatch.setattr(
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common_request_processing.ProxyBaseLLMRequestProcessing,
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"base_process_llm_request",
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_fake_process,
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)
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yield
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@pytest.fixture
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def embedding_pipeline_raises(monkeypatch):
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router = MagicMock()
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router.model_names = []
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monkeypatch.setattr(proxy_server, "llm_router", router)
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monkeypatch.setattr(
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proxy_server, "proxy_logging_obj", MagicMock(post_call_failure_hook=AsyncMock())
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)
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from litellm.proxy._types import ProxyException
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async def _raise(self, *args, **kwargs):
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raise ValueError("boom")
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async def _handler(self, *, e, user_api_key_dict, proxy_logging_obj, version=None):
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return ProxyException(
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message="boom", type="bad_request_error", param="model", code=400
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)
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monkeypatch.setattr(
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common_request_processing.ProxyBaseLLMRequestProcessing,
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"base_process_llm_request",
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_raise,
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)
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monkeypatch.setattr(
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common_request_processing.ProxyBaseLLMRequestProcessing,
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"_handle_llm_api_exception",
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_handler,
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)
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yield
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_EMBED_PATHS = [
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"/v1/embeddings",
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"/embeddings",
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"/engines/text-embedding-ada-002/embeddings",
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"/openai/deployments/text-embedding-ada-002/embeddings",
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]
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@pytest.mark.parametrize("path", _EMBED_PATHS)
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def test_embeddings_happy_path(client, auth_as, patched_embedding, path):
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"""Pins all four ``POST .../embeddings`` aliases (happy path).
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Covers ``POST /v1/embeddings``, ``POST /embeddings``,
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``POST /engines/{model:path}/embeddings``, and
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``POST /openai/deployments/{model:path}/embeddings``.
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"""
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payload = {"model": "text-embedding-ada-002", "input": "hello"}
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with auth_as():
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response = client.post(path, json=payload)
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assert response.status_code == 200
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assert normalize(response.json()) == {
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"object": "list",
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"model": "text-embedding-ada-002",
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"data": [{"embedding": [0.0, 0.1, 0.2], "index": 0, "object": "embedding"}],
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"usage": {"prompt_tokens": 1, "total_tokens": 1},
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}
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@pytest.mark.parametrize("path", _EMBED_PATHS)
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def test_embeddings_pipeline_error(client, auth_as, embedding_pipeline_raises, path):
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"""Pins all four ``POST .../embeddings`` aliases (error path).
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Covers ``POST /v1/embeddings``, ``POST /embeddings``,
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``POST /engines/{model:path}/embeddings``, and
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``POST /openai/deployments/{model:path}/embeddings``.
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"""
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payload = {"model": "text-embedding-ada-002", "input": "boom"}
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with auth_as():
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response = client.post(path, json=payload)
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assert response.status_code == 400
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assert response.content # non-empty error body
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