forked from phoenix/litellm-mirror
e9aa492af3
* fix(ollama.py): fix get model info request Fixes https://github.com/BerriAI/litellm/issues/6703 * feat(anthropic/chat/transformation.py): support passing user id to anthropic via openai 'user' param * docs(anthropic.md): document all supported openai params for anthropic * test: fix tests * fix: fix tests * feat(jina_ai/): add rerank support Closes https://github.com/BerriAI/litellm/issues/6691 * test: handle service unavailable error * fix(handler.py): refactor together ai rerank call * test: update test to handle overloaded error * test: fix test * Litellm router trace (#6742) * feat(router.py): add trace_id to parent functions - allows tracking retry/fallbacks * feat(router.py): log trace id across retry/fallback logic allows grouping llm logs for the same request * test: fix tests * fix: fix test * fix(transformation.py): only set non-none stop_sequences * Litellm router disable fallbacks (#6743) * bump: version 1.52.6 → 1.52.7 * feat(router.py): enable dynamically disabling fallbacks Allows for enabling/disabling fallbacks per key * feat(litellm_pre_call_utils.py): support setting 'disable_fallbacks' on litellm key * test: fix test * fix(exception_mapping_utils.py): map 'model is overloaded' to internal server error * test: handle gemini error * test: fix test * fix: new run
115 lines
3.5 KiB
Python
115 lines
3.5 KiB
Python
import asyncio
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import httpx
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import json
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import pytest
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import sys
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from typing import Any, Dict, List
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from unittest.mock import MagicMock, Mock, patch
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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 litellm
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from litellm.exceptions import BadRequestError
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
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from litellm.utils import (
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CustomStreamWrapper,
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get_supported_openai_params,
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get_optional_params,
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)
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# test_example.py
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from abc import ABC, abstractmethod
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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 = {"index": int, "relevance_score": float}
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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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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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class BaseLLMRerankTest(ABC):
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"""
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Abstract base test class that enforces a common test across all test classes.
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"""
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@abstractmethod
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def get_base_rerank_call_args(self) -> dict:
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"""Must return the base rerank call args"""
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pass
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@abstractmethod
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def get_custom_llm_provider(self) -> litellm.LlmProviders:
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"""Must return the custom llm provider"""
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pass
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@pytest.mark.asyncio()
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@pytest.mark.parametrize("sync_mode", [True, False])
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async def test_basic_rerank(self, sync_mode):
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rerank_call_args = self.get_base_rerank_call_args()
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custom_llm_provider = self.get_custom_llm_provider()
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if sync_mode is True:
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response = litellm.rerank(
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**rerank_call_args,
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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(
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response=response, custom_llm_provider=custom_llm_provider.value
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)
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else:
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response = await litellm.arerank(
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**rerank_call_args,
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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(
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response=response, custom_llm_provider=custom_llm_provider.value
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)
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