aimingmed-ai/app/streamlit/app_test.py
2025-03-06 17:47:35 +08:00

62 lines
2.2 KiB
Python

import datetime
from unittest.mock import patch
from streamlit.testing.v1 import AppTest
from openai.types.chat import ChatCompletionMessage
from openai.types.chat.chat_completion import ChatCompletion, Choice
# See https://github.com/openai/openai-python/issues/715#issuecomment-1809203346
def create_chat_completion(response: str, role: str = "assistant") -> ChatCompletion:
return ChatCompletion(
id="foo",
model="gpt-3.5-turbo",
object="chat.completion",
choices=[
Choice(
finish_reason="stop",
index=0,
message=ChatCompletionMessage(
content=response,
role=role,
),
)
],
created=int(datetime.datetime.now().timestamp()),
)
# @patch("langchain_deepseek.ChatDeepSeek.__call__")
# @patch("langchain_google_genai.ChatGoogleGenerativeAI.invoke")
# @patch("langchain_community.llms.moonshot.Moonshot.__call__")
# def test_Chatbot(moonshot_llm, gemini_llm, deepseek_llm):
# at = AppTest.from_file("Chatbot.py").run()
# assert not at.exception
# QUERY = "What is the best treatment for hypertension?"
# RESPONSE = "The best treatment for hypertension is..."
# deepseek_llm.return_value.content = RESPONSE
# gemini_llm.return_value.content = RESPONSE
# moonshot_llm.return_value = RESPONSE
# at.chat_input[0].set_value(QUERY).run()
# assert any(mock.called for mock in [deepseek_llm, gemini_llm, moonshot_llm])
# assert at.chat_message[1].markdown[0].value == QUERY
# assert at.chat_message[2].markdown[0].value == RESPONSE
# assert at.chat_message[2].avatar == "assistant"
# assert not at.exception
@patch("langchain.llms.OpenAI.__call__")
def test_Langchain_Quickstart(langchain_llm):
at = AppTest.from_file("pages/3_Langchain_Quickstart.py").run()
assert at.info[0].value == "Please add your OpenAI API key to continue."
RESPONSE = "1. The best way to learn how to code is by practicing..."
langchain_llm.return_value = RESPONSE
at.sidebar.text_input[0].set_value("sk-...")
at.button[0].set_value(True).run()
print(at)
assert at.info[0].value == RESPONSE