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(test) caching - get cache key for embedding

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ishaan-jaff 2023-12-14 14:08:58 +05:30
parent 80fc8050eb
commit ee6b936377
1 changed files with 44 additions and 1 deletions
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45
litellm/tests/test_caching.py
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@ -398,15 +398,58 @@ def test_custom_redis_cache_params():
def test_get_cache_key():
from litellm.caching import Cache
try:
print("Testing get_cache_key")
cache_instance = Cache()
cache_key = cache_instance.get_cache_key(**{'model': 'gpt-3.5-turbo', 'messages': [{'role': 'user', 'content': 'write a one sentence poem about: 7510'}], 'max_tokens': 40, 'temperature': 0.2, 'stream': True, 'litellm_call_id': 'ffe75e7e-8a07-431f-9a74-71a5b9f35f0b', 'litellm_logging_obj': {}}
)
cache_key_2 = cache_instance.get_cache_key(**{'model': 'gpt-3.5-turbo', 'messages': [{'role': 'user', 'content': 'write a one sentence poem about: 7510'}], 'max_tokens': 40, 'temperature': 0.2, 'stream': True, 'litellm_call_id': 'ffe75e7e-8a07-431f-9a74-71a5b9f35f0b', 'litellm_logging_obj': {}}
)
assert cache_key == "model: gpt-3.5-turbomessages: [{'role': 'user', 'content': 'write a one sentence poem about: 7510'}]temperature: 0.2max_tokens: 40"
assert cache_key == cache_key_2, f"{cache_key} != {cache_key_2}. The same kwargs should have the same cache key across runs"
embedding_cache_key = cache_instance.get_cache_key(
**{'model': 'azure/azure-embedding-model', 'api_base': 'https://openai-gpt-4-test-v-1.openai.azure.com/',
'api_key': '', 'api_version': '2023-07-01-preview',
'timeout': None, 'max_retries': 0, 'input': ['hi who is ishaan'],
'caching': True,
'client': "<openai.lib.azure.AsyncAzureOpenAI object at 0x12b6a1060>"
}
)
print(embedding_cache_key)
assert embedding_cache_key == "model: azure/azure-embedding-modelinput: ['hi who is ishaan']", f"{embedding_cache_key} != 'model: azure/azure-embedding-modelinput: ['hi who is ishaan']'. The same kwargs should have the same cache key across runs"
# Proxy - embedding cache, test if embedding key, gets model_group and not model
embedding_cache_key_2 = cache_instance.get_cache_key(
**{'model': 'azure/azure-embedding-model', 'api_base': 'https://openai-gpt-4-test-v-1.openai.azure.com/',
'api_key': '', 'api_version': '2023-07-01-preview',
'timeout': None, 'max_retries': 0, 'input': ['hi who is ishaan'],
'caching': True,
'client': "<openai.lib.azure.AsyncAzureOpenAI object at 0x12b6a1060>",
'proxy_server_request': {'url': 'http://0.0.0.0:8000/embeddings',
'method': 'POST',
'headers':
{'host': '0.0.0.0:8000', 'user-agent': 'curl/7.88.1', 'accept': '*/*', 'content-type': 'application/json',
'content-length': '80'},
'body': {'model': 'azure-embedding-model', 'input': ['hi who is ishaan']}},
'user': None,
'metadata': {'user_api_key': None,
'headers': {'host': '0.0.0.0:8000', 'user-agent': 'curl/7.88.1', 'accept': '*/*', 'content-type': 'application/json', 'content-length': '80'},
'model_group': 'EMBEDDING_MODEL_GROUP',
'deployment': 'azure/azure-embedding-model-ModelID-azure/azure-embedding-modelhttps://openai-gpt-4-test-v-1.openai.azure.com/2023-07-01-preview'},
'model_info': {'mode': 'embedding', 'base_model': 'text-embedding-ada-002', 'id': '20b2b515-f151-4dd5-a74f-2231e2f54e29'},
'litellm_call_id': '2642e009-b3cd-443d-b5dd-bb7d56123b0e', 'litellm_logging_obj': '<litellm.utils.Logging object at 0x12f1bddb0>'}
)
print(embedding_cache_key_2)
assert embedding_cache_key_2 == "model: EMBEDDING_MODEL_GROUPinput: ['hi who is ishaan']"
print("passed!")
except Exception as e:
traceback.print_exc()
pytest.fail(f"Error occurred:", e)
# test_get_cache_key()
test_get_cache_key()
# test_custom_redis_cache_params()