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https://github.com/BerriAI/litellm.git
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fix caching
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parent
28b32dbe8b
commit
d4fd0b2010
2 changed files with 16 additions and 10 deletions
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@ -14,7 +14,6 @@ from litellm import embedding, completion
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messages = [{"role": "user", "content": "who is ishaan Github? "}]
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# test if response cached
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def test_caching():
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try:
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@ -36,6 +35,7 @@ def test_caching():
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def test_caching_with_models():
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litellm.caching_with_models = True
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response1 = completion(model="gpt-3.5-turbo", messages=messages)
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response2 = completion(model="gpt-3.5-turbo", messages=messages)
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response3 = completion(model="command-nightly", messages=messages)
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print(f"response2: {response2}")
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@ -46,6 +46,12 @@ def test_caching_with_models():
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print(f"response2: {response2}")
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print(f"response3: {response3}")
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pytest.fail(f"Error occurred:")
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if response1 != response2:
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print(f"response1: {response1}")
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print(f"response2: {response2}")
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pytest.fail(f"Error occurred:")
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# test_caching_with_models()
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def test_gpt_cache():
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@ -410,19 +410,20 @@ def client(original_function):
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def check_cache(*args, **kwargs):
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try: # never block execution
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prompt = get_prompt(*args, **kwargs)
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if (prompt != None and prompt
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in local_cache): # check if messages / prompt exists
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if (prompt != None): # check if messages / prompt exists
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if litellm.caching_with_models:
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# if caching with model names is enabled, key is prompt + model name
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if ("model" in kwargs and kwargs["model"]
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in local_cache[prompt]["models"]):
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if ("model" in kwargs):
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cache_key = prompt + kwargs["model"]
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return local_cache[cache_key]
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if cache_key in local_cache:
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return local_cache[cache_key]
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else: # caching only with prompts
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result = local_cache[prompt]
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return result
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if prompt in local_cache:
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result = local_cache[prompt]
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return result
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else:
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return None
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return None # default to return None
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except:
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return None
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@ -430,8 +431,7 @@ def client(original_function):
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try: # never block execution
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prompt = get_prompt(*args, **kwargs)
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if litellm.caching_with_models: # caching with model + prompt
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if ("model" in kwargs
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and kwargs["model"] in local_cache[prompt]["models"]):
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if ("model" in kwargs):
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cache_key = prompt + kwargs["model"]
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local_cache[cache_key] = result
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else: # caching based only on prompts
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