mirror of
https://github.com/BerriAI/litellm.git
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c7b288ce30
* VoyageEmbeddingConfig * fix voyage logic to get params * add voyage embedding transformation * add get_provider_embedding_config * use BaseEmbeddingConfig * voyage clean up * use llm http handler for embedding transformations * test_voyage_ai_embedding_extra_params * add voyage async * test_voyage_ai_embedding_extra_params * add async for llm http handler * update BaseLLMEmbeddingTest * test_voyage_ai_embedding_extra_params * fix linting * fix get_provider_embedding_config * fix anthropic text test * update location of base/chat/transformation * fix import path * fix IBMWatsonXAIConfig
71 lines
2.1 KiB
Python
71 lines
2.1 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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get_optional_params_embeddings,
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)
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# test_example.py
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from abc import ABC, abstractmethod
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class BaseLLMEmbeddingTest(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_embedding_call_args(self) -> dict:
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"""Must return the base embedding 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_embedding(self, sync_mode):
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litellm.set_verbose = True
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embedding_call_args = self.get_base_embedding_call_args()
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if sync_mode is True:
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response = litellm.embedding(
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**embedding_call_args,
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input=["hello", "world"],
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)
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print("embedding response: ", response)
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else:
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response = await litellm.aembedding(
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**embedding_call_args,
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input=["hello", "world"],
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)
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print("async embedding response: ", response)
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from openai.types.create_embedding_response import CreateEmbeddingResponse
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CreateEmbeddingResponse.model_validate(response.model_dump())
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def test_embedding_optional_params_max_retries(self):
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embedding_call_args = self.get_base_embedding_call_args()
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optional_params = get_optional_params_embeddings(
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**embedding_call_args, max_retries=20
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)
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assert optional_params["max_retries"] == 20
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