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Mock Completion() Responses - Save Testing Costs 💰

For testing purposes, you can use completion() with mock_response to mock calling the completion endpoint.

This will return a response object with a default response (works for streaming as well), without calling the LLM APIs.

quick start

from litellm import completion 

model = "gpt-3.5-turbo"
messages = [{"role":"user", "content":"This is a test request"}]

completion(model=model, messages=messages, mock_response="It's simple to use and easy to get started")

streaming

from litellm import completion 
model = "gpt-3.5-turbo"
messages = [{"role": "user", "content": "Hey, I'm a mock request"}]
response = completion(model=model, messages=messages, stream=True, mock_response="It's simple to use and easy to get started")
for chunk in response:
print(chunk) # {'choices': [{'delta': {'role': 'assistant', 'content': 'Thi'}, 'finish_reason': None}]}
complete_response += chunk["choices"][0]["delta"]["content"]

(Non-streaming) Mock Response Object

{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "This is a mock request",
"role": "assistant",
"logprobs": null
}
}
],
"created": 1694459929.4496052,
"model": "MockResponse",
"usage": {
"prompt_tokens": null,
"completion_tokens": null,
"total_tokens": null
}
}

Building a pytest function using completion with mock_response

from litellm import completion
import pytest

def test_completion_openai():
try:
response = completion(
model="gpt-3.5-turbo",
messages=[{"role":"user", "content":"Why is LiteLLM amazing?"}],
mock_response="LiteLLM is awesome"
)
# Add any assertions here to check the response
print(response)
assert(response['choices'][0]['message']['content'] == "LiteLLM is awesome")
except Exception as e:
pytest.fail(f"Error occurred: {e}")