mirror of
https://github.com/BerriAI/litellm.git
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6a0d03914c
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
476 lines
15 KiB
Python
476 lines
15 KiB
Python
import asyncio
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import json
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import os
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import traceback
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from dotenv import load_dotenv
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load_dotenv()
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import io
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from typing import Optional, Dict
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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import litellm
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from litellm.types.rerank import RerankResponse
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from litellm import RateLimitError, Timeout, completion, completion_cost, embedding
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from litellm.integrations.custom_logger import CustomLogger
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
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def assert_response_shape(response, custom_llm_provider):
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expected_response_shape = {"id": str, "results": list, "meta": dict}
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expected_results_shape = {
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"index": int,
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"relevance_score": float,
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"document": Optional[Dict[str, str]],
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}
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expected_meta_shape = {"api_version": dict, "billed_units": dict}
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expected_api_version_shape = {"version": str}
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expected_billed_units_shape = {"search_units": int}
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assert isinstance(response.id, expected_response_shape["id"])
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assert isinstance(response.results, expected_response_shape["results"])
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for result in response.results:
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assert isinstance(result["index"], expected_results_shape["index"])
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assert isinstance(
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result["relevance_score"], expected_results_shape["relevance_score"]
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)
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if "document" in result:
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assert isinstance(result["document"], Dict)
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assert isinstance(result["document"]["text"], str)
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assert isinstance(response.meta, expected_response_shape["meta"])
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if custom_llm_provider == "cohere":
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assert isinstance(
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response.meta["api_version"], expected_meta_shape["api_version"]
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)
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assert isinstance(
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response.meta["api_version"]["version"],
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expected_api_version_shape["version"],
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)
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assert isinstance(
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response.meta["billed_units"], expected_meta_shape["billed_units"]
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)
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assert isinstance(
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response.meta["billed_units"]["search_units"],
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expected_billed_units_shape["search_units"],
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)
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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@pytest.mark.flaky(retries=3, delay=1)
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async def test_basic_rerank(sync_mode):
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litellm.set_verbose = True
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if sync_mode is True:
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response = litellm.rerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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else:
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response = await litellm.arerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("async re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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print("response", response.model_dump_json(indent=4))
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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@pytest.mark.skip(reason="Skipping test due to 503 Service Temporarily Unavailable")
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async def test_basic_rerank_together_ai(sync_mode):
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try:
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if sync_mode is True:
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response = litellm.rerank(
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model="together_ai/Salesforce/Llama-Rank-V1",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="together_ai")
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else:
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response = await litellm.arerank(
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model="together_ai/Salesforce/Llama-Rank-V1",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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print("async re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="together_ai")
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except Exception as e:
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if "Service unavailable" in str(e):
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pytest.skip("Skipping test due to 503 Service Temporarily Unavailable")
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raise e
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("version", ["v1", "v2"])
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async def test_rerank_custom_api_base(version):
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mock_response = AsyncMock()
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litellm.cohere_key = "test_api_key"
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def return_val():
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return {
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"id": "cmpl-mockid",
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"results": [{"index": 0, "relevance_score": 0.95}],
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"meta": {
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"api_version": {"version": "1.0"},
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"billed_units": {"search_units": 1},
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},
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}
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mock_response.json = return_val
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mock_response.headers = {"key": "value"}
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mock_response.status_code = 200
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expected_payload = {
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"model": "Salesforce/Llama-Rank-V1",
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"query": "hello",
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"top_n": 3,
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"documents": ["hello", "world"],
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}
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api_base = "https://exampleopenaiendpoint-production.up.railway.app/"
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if version == "v1":
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api_base += "v1/rerank"
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with patch(
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"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.post",
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return_value=mock_response,
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) as mock_post:
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response = await litellm.arerank(
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model="cohere/Salesforce/Llama-Rank-V1",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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api_base=api_base,
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)
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print("async re rank response: ", response)
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# Assert
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mock_post.assert_called_once()
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print("call args", mock_post.call_args)
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args_to_api = mock_post.call_args.kwargs["data"]
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_url = mock_post.call_args.kwargs["url"]
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print("Arguments passed to API=", args_to_api)
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print("url = ", _url)
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assert (
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_url
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== f"https://exampleopenaiendpoint-production.up.railway.app/{version}/rerank"
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)
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request_data = json.loads(args_to_api)
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assert request_data["query"] == expected_payload["query"]
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assert request_data["documents"] == expected_payload["documents"]
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assert request_data["top_n"] == expected_payload["top_n"]
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assert request_data["model"] == expected_payload["model"]
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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class TestLogger(CustomLogger):
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def __init__(self):
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self.kwargs = None
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self.response_obj = None
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super().__init__()
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async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
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print("in success event for rerank, kwargs = ", kwargs)
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print("in success event for rerank, response_obj = ", response_obj)
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self.kwargs = kwargs
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self.response_obj = response_obj
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@pytest.mark.asyncio()
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@pytest.mark.flaky(retries=3, delay=1)
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async def test_rerank_custom_callbacks():
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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custom_logger = TestLogger()
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litellm.callbacks = [custom_logger]
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response = await litellm.arerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=3,
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)
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await asyncio.sleep(8)
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print("async re rank response: ", response)
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assert custom_logger.kwargs is not None
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assert custom_logger.kwargs.get("response_cost") > 0.0
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assert custom_logger.response_obj is not None
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assert custom_logger.response_obj.results is not None
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def test_complete_base_url_cohere():
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from litellm.llms.custom_httpx.http_handler import HTTPHandler
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client = HTTPHandler()
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litellm.api_base = "http://localhost:4000"
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litellm.cohere_key = "test_api_key"
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litellm.set_verbose = True
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text = "Hello there!"
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list_texts = ["Hello there!", "How are you?", "How do you do?"]
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rerank_model = "rerank-multilingual-v3.0"
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with patch.object(client, "post") as mock_post:
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try:
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litellm.rerank(
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model=rerank_model,
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query=text,
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documents=list_texts,
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custom_llm_provider="cohere",
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client=client,
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)
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except Exception as e:
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print(e)
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print("mock_post.call_args", mock_post.call_args)
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mock_post.assert_called_once()
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# Default to the v2 client when calling the base /rerank
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assert "http://localhost:4000/v2/rerank" in mock_post.call_args.kwargs["url"]
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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@pytest.mark.parametrize(
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"top_n_1, top_n_2, expect_cache_hit",
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[
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(3, 3, True),
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(3, None, False),
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],
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)
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@pytest.mark.flaky(retries=3, delay=1)
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async def test_basic_rerank_caching(sync_mode, top_n_1, top_n_2, expect_cache_hit):
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from litellm.caching.caching import Cache
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litellm.set_verbose = True
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litellm.cache = Cache(type="local")
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if sync_mode is True:
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for idx in range(2):
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if idx == 0:
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top_n = top_n_1
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else:
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top_n = top_n_2
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response = litellm.rerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=top_n,
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)
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else:
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for idx in range(2):
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if idx == 0:
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top_n = top_n_1
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else:
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top_n = top_n_2
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response = await litellm.arerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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top_n=top_n,
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)
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await asyncio.sleep(1)
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if expect_cache_hit is True:
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assert "cache_key" in response._hidden_params
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else:
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assert "cache_key" not in response._hidden_params
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print("re rank response: ", response)
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assert response.id is not None
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assert response.results is not None
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assert_response_shape(response, custom_llm_provider="cohere")
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def test_rerank_response_assertions():
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r = RerankResponse(
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**{
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"id": "ab0fcca0-b617-11ef-b292-0242ac110002",
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"results": [
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{"index": 2, "relevance_score": 0.9958819150924683},
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{"index": 0, "relevance_score": 0.001293411129154265},
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{
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"index": 1,
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"relevance_score": 7.641685078851879e-05,
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},
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{
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"index": 3,
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"relevance_score": 7.621097756782547e-05,
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},
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],
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"meta": {
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"api_version": None,
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"billed_units": None,
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"tokens": None,
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"warnings": None,
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},
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}
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)
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assert_response_shape(r, custom_llm_provider="custom")
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def test_cohere_rerank_v2_client():
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from litellm.llms.custom_httpx.http_handler import HTTPHandler
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client = HTTPHandler()
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litellm.api_base = "http://localhost:4000"
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litellm.set_verbose = True
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text = "Hello there!"
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list_texts = ["Hello there!", "How are you?", "How do you do?"]
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rerank_model = "rerank-multilingual-v3.0"
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with patch.object(client, "post") as mock_post:
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mock_response = MagicMock()
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mock_response.text = json.dumps(
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{
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"id": "cmpl-mockid",
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"results": [
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{"index": 0, "relevance_score": 0.95},
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{"index": 1, "relevance_score": 0.75},
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{"index": 2, "relevance_score": 0.65},
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],
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"usage": {"prompt_tokens": 100, "total_tokens": 150},
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}
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)
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mock_response.status_code = 200
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mock_response.headers = {"Content-Type": "application/json"}
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mock_response.json = lambda: json.loads(mock_response.text)
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mock_post.return_value = mock_response
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response = litellm.rerank(
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model=rerank_model,
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query=text,
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documents=list_texts,
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custom_llm_provider="cohere",
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max_tokens_per_doc=3,
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top_n=2,
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api_key="fake-api-key",
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client=client,
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)
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# Ensure Cohere API is called with the expected params
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mock_post.assert_called_once()
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assert mock_post.call_args.kwargs["url"] == "http://localhost:4000/v2/rerank"
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request_data = json.loads(mock_post.call_args.kwargs["data"])
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assert request_data["model"] == rerank_model
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assert request_data["query"] == text
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assert request_data["documents"] == list_texts
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assert request_data["max_tokens_per_doc"] == 3
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assert request_data["top_n"] == 2
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# Ensure litellm response is what we expect
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assert response["results"] == mock_response.json()["results"]
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@pytest.mark.flaky(retries=3, delay=1)
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def test_rerank_cohere_api():
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response = litellm.rerank(
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model="cohere/rerank-english-v3.0",
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query="hello",
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documents=["hello", "world"],
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return_documents=True,
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top_n=3,
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)
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print("rerank response", response)
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assert response.results[0]["document"] is not None
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assert response.results[0]["document"]["text"] is not None
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assert response.results[0]["document"]["text"] == "hello"
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assert response.results[1]["document"]["text"] == "world"
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def test_rerank_infer_region_from_model_arn(monkeypatch):
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mock_response = MagicMock()
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monkeypatch.setenv("AWS_REGION_NAME", "us-east-1")
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args = {
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"model": "bedrock/arn:aws:bedrock:us-west-2::foundation-model/amazon.rerank-v1:0",
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"query": "hello",
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"documents": ["hello", "world"],
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}
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def return_val():
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return {
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"results": [
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{"index": 0, "relevanceScore": 0.6716859340667725},
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{"index": 1, "relevanceScore": 0.0004994205664843321},
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]
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}
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mock_response.json = return_val
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mock_response.headers = {"key": "value"}
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mock_response.status_code = 200
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client = HTTPHandler()
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with patch.object(client, "post", return_value=mock_response) as mock_post:
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litellm.rerank(
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model=args["model"],
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query=args["query"],
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documents=args["documents"],
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client=client,
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)
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mock_post.assert_called_once()
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print(f"mock_post.call_args: {mock_post.call_args.kwargs}")
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assert "us-west-2" in mock_post.call_args.kwargs["url"]
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assert "us-east-1" not in mock_post.call_args.kwargs["url"]
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