litellm-mirror/litellm/tests/test_caching.py

import sys, os
import traceback
from dotenv import load_dotenv

load_dotenv()
import os

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

messages = [{"role": "user", "content": "who is ishaan Github?  "}]
# comment

# test if response cached
def test_caching():
    try:
        litellm.caching = True
        response1 = completion(model="gpt-3.5-turbo", messages=messages)
        response2 = completion(model="gpt-3.5-turbo", messages=messages)
        print(f"response1: {response1}")
        print(f"response2: {response2}")
        litellm.caching = False
        if response2 != response1:
            print(f"response1: {response1}")
            print(f"response2: {response2}")
            pytest.fail(f"Error occurred: {e}")
    except Exception as e:
        litellm.caching = False
        print(f"error occurred: {traceback.format_exc()}")
        pytest.fail(f"Error occurred: {e}")


def test_caching_with_models():
    litellm.caching_with_models = True
    response1 = completion(model="gpt-3.5-turbo", messages=messages)
    response2 = completion(model="gpt-3.5-turbo", messages=messages)
    response3 = completion(model="command-nightly", messages=messages)
    print(f"response2: {response2}")
    print(f"response3: {response3}")
    litellm.caching_with_models = False
    if response3 == response2:
        # if models are different, it should not return cached response
        print(f"response2: {response2}")
        print(f"response3: {response3}")
        pytest.fail(f"Error occurred:")
    if response1 != response2:
        print(f"response1: {response1}")
        print(f"response2: {response2}")
        pytest.fail(f"Error occurred:")


# test_caching_with_models()


def test_gpt_cache():
    # INIT GPT Cache #
    from gptcache import cache
    from litellm.cache import completion

    cache.init()
    cache.set_openai_key()

    messages = [{"role": "user", "content": "what is litellm YC 22?"}]
    response2 = completion(model="gpt-3.5-turbo", messages=messages)
    response3 = completion(model="command-nightly", messages=messages)
    print(f"response2: {response2}")
    print(f"response3: {response3}")

    if response3["choices"] != response2["choices"]:
        # if models are different, it should not return cached response
        print(f"response2: {response2}")
        print(f"response3: {response3}")
        pytest.fail(f"Error occurred:")


# test_gpt_cache()


####### Updated Caching as of Aug 28, 2023 ###################
messages = [{"role": "user", "content": "who is ishaan 5222"}]
def test_caching_v2():
    try:
        litellm.cache = Cache()
        response1 = completion(model="gpt-3.5-turbo", messages=messages)
        response2 = completion(model="gpt-3.5-turbo", messages=messages)
        print(f"response1: {response1}")
        print(f"response2: {response2}")
        litellm.cache = None # disable cache
        if response2 != response1:
            print(f"response1: {response1}")
            print(f"response2: {response2}")
            pytest.fail(f"Error occurred: {e}")
    except Exception as e:
        print(f"error occurred: {traceback.format_exc()}")
        pytest.fail(f"Error occurred: {e}")

# test_caching()


def test_caching_with_models_v2():
    messages = [{"role": "user", "content": "who is ishaan CTO of litellm from litellm 2023"}]
    litellm.cache = Cache()
    print("test2 for caching")
    response1 = completion(model="gpt-3.5-turbo", messages=messages)
    response2 = completion(model="gpt-3.5-turbo", messages=messages)
    response3 = completion(model="command-nightly", messages=messages)
    print(f"response1: {response1}")
    print(f"response2: {response2}")
    print(f"response3: {response3}")
    litellm.cache = None
    if response3 == response2:
        # if models are different, it should not return cached response
        print(f"response2: {response2}")
        print(f"response3: {response3}")
        pytest.fail(f"Error occurred:")
    if response1 != response2:
        print(f"response1: {response1}")
        print(f"response2: {response2}")
        pytest.fail(f"Error occurred:")


embedding_large_text = """
small text
""" * 5

# test_caching_with_models()
def test_embedding_caching():
    import time
    litellm.cache = Cache()
    text_to_embed = [embedding_large_text]
    start_time = time.time()
    embedding1 = embedding(model="text-embedding-ada-002", input=text_to_embed)
    end_time = time.time()
    print(f"Embedding 1 response time: {end_time - start_time} seconds")
    
    time.sleep(1)
    start_time = time.time()
    embedding2 = embedding(model="text-embedding-ada-002", input=text_to_embed)
    end_time = time.time()
    print(f"Embedding 2 response time: {end_time - start_time} seconds")
    
    litellm.cache = None
    if embedding2 != embedding1:
        print(f"embedding1: {embedding1}")
        print(f"embedding2: {embedding2}")
        pytest.fail("Error occurred: Embedding caching failed")

# test_embedding_caching()