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nnnn / litellm /tests /test_embedding.py

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	import sys, os
	import traceback
	import pytest
	from dotenv import load_dotenv
	import openai

	load_dotenv()

	sys.path.insert(
	0, os.path.abspath("../..")
	) # Adds the parent directory to the system path
	import litellm
	from litellm import embedding, completion

	litellm.set_verbose = False

	def test_openai_embedding():
	try:
	litellm.set_verbose=True
	response = embedding(
	model="text-embedding-ada-002",
	input=["good morning from litellm", "this is another item"],
	metadata = {"anything": "good day"}
	)
	litellm_response = dict(response)
	litellm_response_keys = set(litellm_response.keys())
	litellm_response_keys.discard('_response_ms')

	print(litellm_response_keys)
	print("LiteLLM Response\n")
	# print(litellm_response)

	# same request with OpenAI 1.0+
	import openai
	client = openai.OpenAI(api_key=os.environ['OPENAI_API_KEY'])
	response = client.embeddings.create(
	model="text-embedding-ada-002", input=["good morning from litellm", "this is another item"]
	)

	response = dict(response)
	openai_response_keys = set(response.keys())
	print(openai_response_keys)
	assert litellm_response_keys == openai_response_keys # ENSURE the Keys in litellm response is exactly what the openai package returns
	assert len(litellm_response["data"]) == 2 # expect two embedding responses from litellm_response since input had two
	print(openai_response_keys)
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")
	# test_openai_embedding()

	def test_openai_azure_embedding_simple():
	try:
	response = embedding(
	model="azure/azure-embedding-model",
	input=["good morning from litellm"],
	)
	print(response)
	response_keys = set(dict(response).keys())
	response_keys.discard('_response_ms')
	assert set(["usage", "model", "object", "data"]) == set(response_keys) #assert litellm response has expected keys from OpenAI embedding response

	except Exception as e:
	pytest.fail(f"Error occurred: {e}")

	# test_openai_azure_embedding_simple()


	def test_openai_azure_embedding_timeouts():
	try:
	response = embedding(
	model="azure/azure-embedding-model",
	input=["good morning from litellm"],
	timeout=0.00001
	)
	print(response)
	except openai.APITimeoutError:
	print("Good job got timeout error!")
	pass
	except Exception as e:
	pytest.fail(f"Expected timeout error, did not get the correct error. Instead got {e}")

	# test_openai_azure_embedding_timeouts()

	def test_openai_embedding_timeouts():
	try:
	response = embedding(
	model="text-embedding-ada-002",
	input=["good morning from litellm"],
	timeout=0.00001
	)
	print(response)
	except openai.APITimeoutError:
	print("Good job got OpenAI timeout error!")
	pass
	except Exception as e:
	pytest.fail(f"Expected timeout error, did not get the correct error. Instead got {e}")
	# test_openai_embedding_timeouts()

	def test_openai_azure_embedding():
	try:
	api_key = os.environ['AZURE_API_KEY']
	api_base = os.environ['AZURE_API_BASE']
	api_version = os.environ['AZURE_API_VERSION']

	os.environ['AZURE_API_VERSION'] = ""
	os.environ['AZURE_API_BASE'] = ""
	os.environ['AZURE_API_KEY'] = ""

	response = embedding(
	model="azure/azure-embedding-model",
	input=["good morning from litellm", "this is another item"],
	api_key=api_key,
	api_base=api_base,
	api_version=api_version,
	)
	print(response)


	os.environ['AZURE_API_VERSION'] = api_version
	os.environ['AZURE_API_BASE'] = api_base
	os.environ['AZURE_API_KEY'] = api_key

	except Exception as e:
	pytest.fail(f"Error occurred: {e}")

	# test_openai_azure_embedding()

	# test_openai_embedding()

	def test_cohere_embedding():
	try:
	# litellm.set_verbose=True
	response = embedding(
	model="embed-english-v2.0", input=["good morning from litellm", "this is another item"]
	)
	print(f"response:", response)
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")

	# test_cohere_embedding()

	def test_cohere_embedding3():
	try:
	litellm.set_verbose=True
	response = embedding(
	model="embed-english-v3.0",
	input=["good morning from litellm", "this is another item"],
	)
	print(f"response:", response)
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")

	# test_cohere_embedding3()

	def test_bedrock_embedding():
	try:
	response = embedding(
	model="amazon.titan-embed-text-v1", input=["good morning from litellm, attempting to embed data",
	"lets test a second string for good measure"]
	)
	print(f"response:", response)
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")
	# test_bedrock_embedding()

	# comment out hf tests - since hf endpoints are unstable
	def test_hf_embedding():
	try:
	# huggingface/microsoft/codebert-base
	# huggingface/facebook/bart-large
	response = embedding(
	model="huggingface/sentence-transformers/all-MiniLM-L6-v2", input=["good morning from litellm", "this is another item"]
	)
	print(f"response:", response)
	except Exception as e:
	# Note: Huggingface inference API is unstable and fails with "model loading errors all the time"
	pass
	# test_hf_embedding()

	# test async embeddings
	def test_aembedding():
	try:
	import asyncio
	async def embedding_call():
	try:
	response = await litellm.aembedding(
	model="text-embedding-ada-002",
	input=["good morning from litellm", "this is another item"]
	)
	print(response)
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")
	asyncio.run(embedding_call())
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")

	# test_aembedding()


	def test_aembedding_azure():
	try:
	import asyncio
	async def embedding_call():
	try:
	response = await litellm.aembedding(
	model="azure/azure-embedding-model",
	input=["good morning from litellm", "this is another item"]
	)
	print(response)
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")
	asyncio.run(embedding_call())
	except Exception as e:
	pytest.fail(f"Error occurred: {e}")

	# test_aembedding_azure()

	# def test_custom_openai_embedding():
	# litellm.set_verbose=True
	# response = embedding(
	# model="openai/custom_embedding",
	# input=["good morning from litellm"],
	# api_base="http://0.0.0.0:8000/"
	# )
	# print(response)
	# test_custom_openai_embedding()