Files
litellm/tests/llm_translation/base_rerank_unit_tests.py
T
Ishaan Jaff efa782d6d2 [Feat] Add Nvidia NIM Rerank Support (#15152)
* feat: add NvidiaNimRerankConfig

* fix: NvidiaNimRerankConfig

* fix: NvidiaNimRerankConfig

* fix routing to nvidia nim

* docs nvidia nim rerank

* TestNvidiaNim

* nvidia nim rerank fixes

* fix rerank

* transform_rerank_response

* Usage with LiteLLM Proxy

* fixes linting

* NvidiaNimRerankConfig.DEFAULT_NIM_RERANK_API_BASE

* fix Custom API Base URL

* fix rerank base

* fix main.py

* fix transform

* fix linting

* map_cohere_rerank_params

* ruff fix

* linting fixes

* ruff fix
2025-10-02 18:58:52 -07:00

148 lines
4.9 KiB
Python

import asyncio
import httpx
import json
import pytest
import sys
from typing import Any, Dict, List
from unittest.mock import MagicMock, Mock, patch
import os
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
import litellm
from litellm.exceptions import BadRequestError
from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
from litellm.utils import (
CustomStreamWrapper,
get_supported_openai_params,
get_optional_params,
)
# test_example.py
from abc import ABC, abstractmethod
def assert_response_shape(response, custom_llm_provider):
expected_response_shape = {"id": str, "results": list, "meta": dict}
expected_results_shape = {"index": int, "relevance_score": float}
expected_meta_shape = {"api_version": dict, "billed_units": dict}
expected_api_version_shape = {"version": str}
expected_billed_units_shape = {"search_units": int}
expected_billed_units_total_tokens_shape = {"total_tokens": int}
assert isinstance(response.id, expected_response_shape["id"])
assert isinstance(response.results, expected_response_shape["results"])
for result in response.results:
assert isinstance(result["index"], expected_results_shape["index"])
assert isinstance(
result["relevance_score"], expected_results_shape["relevance_score"]
)
assert isinstance(response.meta, expected_response_shape["meta"])
if custom_llm_provider == "cohere":
assert isinstance(
response.meta["api_version"], expected_meta_shape["api_version"]
)
assert isinstance(
response.meta["api_version"]["version"],
expected_api_version_shape["version"],
)
assert isinstance(
response.meta["billed_units"], expected_meta_shape["billed_units"]
)
if "total_tokens" in response.meta["billed_units"]:
assert isinstance(
response.meta["billed_units"]["total_tokens"],
expected_billed_units_total_tokens_shape["total_tokens"],
)
else:
assert isinstance(
response.meta["billed_units"]["search_units"],
expected_billed_units_shape["search_units"],
)
class BaseLLMRerankTest(ABC):
"""
Abstract base test class that enforces a common test across all test classes.
"""
@abstractmethod
def get_base_rerank_call_args(self) -> dict:
"""Must return the base rerank call args"""
pass
@abstractmethod
def get_custom_llm_provider(self) -> litellm.LlmProviders:
"""Must return the custom llm provider"""
pass
def get_expected_cost(self) -> float:
"""
Override this method to set the expected cost for the rerank call.
Default is None, which means the test will check cost > 0.
Return 0.0 for free models.
"""
return None
@pytest.mark.asyncio()
@pytest.mark.parametrize("sync_mode", [True, False])
async def test_basic_rerank(self, sync_mode):
litellm._turn_on_debug()
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
litellm.model_cost = litellm.get_model_cost_map(url="")
rerank_call_args = self.get_base_rerank_call_args()
custom_llm_provider = self.get_custom_llm_provider()
if sync_mode is True:
response = litellm.rerank(
**rerank_call_args,
query="hello",
documents=["hello", "world"],
top_n=2,
)
print("re rank response: ", response)
assert response.id is not None
assert response.results is not None
assert response._hidden_params["response_cost"] is not None
# Check expected cost
expected_cost = self.get_expected_cost()
if expected_cost is not None:
# If expected cost is specified, check exact match or >= for 0
if expected_cost == 0.0:
assert response._hidden_params["response_cost"] >= 0
else:
assert response._hidden_params["response_cost"] == expected_cost
else:
# Default behavior: cost should be greater than 0
assert response._hidden_params["response_cost"] > 0
assert_response_shape(
response=response, custom_llm_provider=custom_llm_provider.value
)
else:
response = await litellm.arerank(
**rerank_call_args,
query="hello",
documents=["hello", "world"],
top_n=2,
)
print("async re rank response: ", response)
assert response.id is not None
assert response.results is not None
assert_response_shape(
response=response, custom_llm_provider=custom_llm_provider.value
)