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# project/test.py
import unittest
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import HumanMessage
from app_modules.llm_loader import LLMLoader
from timeit import default_timer as timer
USER_QUESTION = "What's the capital city of Malaysia?"
class MyCustomHandler(BaseCallbackHandler):
def __init__(self):
self.reset()
def reset(self):
self.texts = []
def get_standalone_question(self) -> str:
return self.texts[0].strip() if len(self.texts) > 0 else None
def on_llm_end(self, response, **kwargs) -> None:
"""Run when chain ends running."""
print("\non_llm_end - response:")
print(response)
self.texts.append(response.generations[0][0].text)
class TestLLMLoader(unittest.TestCase):
def run_test_case(self, llm_model_type, query):
llm_loader = LLMLoader(llm_model_type)
start = timer()
llm_loader.init(n_threds=8, hf_pipeline_device_type="cpu")
end = timer()
print(f"Model loaded in {end - start:.3f}s")
result = llm_loader.llm(
[HumanMessage(content=query)] if llm_model_type == "openai" else query
)
end2 = timer()
print(f"Inference completed in {end2 - end:.3f}s")
print(result)
def xtest_openai(self):
self.run_test_case("openai", USER_QUESTION)
def xtest_llamacpp(self):
self.run_test_case("llamacpp", USER_QUESTION)
def xtest_gpt4all_j(self):
self.run_test_case("gpt4all-j", USER_QUESTION)
def test_huggingface(self):
self.run_test_case("huggingface", USER_QUESTION)
if __name__ == "__main__":
unittest.main()
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