phoenix/litellm
1
0
Fork 0
forked from phoenix/litellm-mirror
Code Pull requests Activity

update model load testing

Browse source
This commit is contained in:
Krrish Dholakia 2023-08-16 12:28:47 -07:00
parent c58c52db04
commit f263e223b8
2 changed files with 10 additions and 10 deletions
Download patch file Download diff file Expand all files Collapse all files

18
litellm/testing.py
View file

@ -19,7 +19,8 @@ def testing_batch_completion(*args, **kwargs):
args_modified[0] = model["model"]
else:
kwargs_modified["model"] = model["model"] if isinstance(model, dict) and "model" in model else model # if model is a dictionary get it's value else assume it's a string
kwargs_modified["custom_llm_provider"] = model["custom_llm_provider"] if isinstance(model, dict) and "model" in model else None
kwargs_modified["custom_llm_provider"] = model["custom_llm_provider"] if isinstance(model, dict) and "custom_llm_provider" in model else None
kwargs_modified["custom_api_base"] = model["custom_api_base"] if isinstance(model, dict) and "custom_api_base" in model else None
for message_list in batch_messages:
if len(args) > 1:
args_modified[1] = message_list
@ -70,22 +71,21 @@ def duration_test_model(original_function):
return wrapper_function
@duration_test_model
def load_test_model(model: str, custom_llm_provider: str = None, custom_api_base: str = None, prompt: str = None, num_calls: int = None, request_timeout: int = None):
test_prompt = "Hey, how's it going"
def load_test_model(models: list, prompt: str = None, num_calls: int = None):
test_calls = 100
if prompt:
test_prompt = prompt
if num_calls:
test_calls = num_calls
messages = [[{"role": "user", "content": test_prompt}] for _ in range(test_calls)]
input_prompt = prompt if prompt else "Hey, how's it going?"
messages = [{"role": "user", "content": prompt}] if prompt else [{"role": "user", "content": input_prompt}]
full_message_list = [messages for _ in range(test_calls)] # call it as many times as set by user to load test models
start_time = time.time()
try:
results = testing_batch_completion(models=[model], messages=messages, custom_llm_provider=custom_llm_provider, custom_api_base = custom_api_base, force_timeout=request_timeout)
results = testing_batch_completion(models=models, messages=full_message_list)
end_time = time.time()
response_time = end_time - start_time
return {"total_response_time": response_time, "calls_made": test_calls, "prompt": test_prompt, "results": results}
return {"total_response_time": response_time, "calls_made": test_calls, "prompt": input_prompt, "results": results}
except Exception as e:
traceback.print_exc()
end_time = time.time()
response_time = end_time - start_time
return {"total_response_time": response_time, "calls_made": test_calls, "prompt": test_prompt, "exception": e}
return {"total_response_time": response_time, "calls_made": test_calls, "prompt": input_prompt, "exception": e}

2
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm"
version = "0.1.403"
version = "0.1.404"
description = "Library to easily interface with LLM API providers"
authors = ["BerriAI"]
license = "MIT License"