llm-chat/tests/test_cli.py

154 lines
4.5 KiB
Python

from io import StringIO
from pathlib import Path
from typing import Any, Type
from unittest.mock import MagicMock
import pytest
from pytest import MonkeyPatch
from rich.console import Console
from typer.testing import CliRunner
import llm_chat
from llm_chat.chat import ChatProtocol
from llm_chat.cli import app
from llm_chat.models import Conversation, Message, Role
from llm_chat.settings import Model, OpenAISettings
runner = CliRunner()
class ChatFake:
"""Fake chat class for testing."""
args: dict[str, Any]
conversation: Conversation
received_messages: list[str]
settings: OpenAISettings
def __init__(self, settings: OpenAISettings | None = None) -> None:
if settings is not None:
self.settings = settings
else:
self.settings = OpenAISettings()
self.args = {}
self.received_messages = []
def _set_args(self, **kwargs: Any) -> None:
self.args = kwargs
@property
def cost(self) -> float:
"""Get the cost of the conversation."""
return 0.0
@classmethod
def load(
cls, path: Path, api_key: str | None = None, history_dir: Path | None = None
) -> ChatProtocol:
"""Load a chat from a file."""
return cls()
def save(self) -> None:
"""Dummy save method."""
pass
def send_message(self, message: str) -> str:
"""Echo the received message."""
self.received_messages.append(message)
return message
def test_chat(monkeypatch: MonkeyPatch) -> None:
chat_fake = ChatFake()
output = StringIO()
console = Console(file=output)
def mock_get_chat(**_: Any) -> ChatProtocol:
return chat_fake
def mock_get_console() -> Console:
return console
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
result = runner.invoke(app, ["chat"])
assert result.exit_code == 0
assert chat_fake.received_messages == ["Hello"]
@pytest.mark.parametrize("argument", ["--context", "-c"], ids=["--context", "-c"])
def test_chat_with_context(
argument: str, monkeypatch: MonkeyPatch, tmp_path: Path
) -> None:
context = "Hello, world!"
tmp_file = tmp_path / "context.txt"
tmp_file.write_text(context)
chat_fake = ChatFake()
output = StringIO()
console = Console(file=output)
def mock_get_chat(**kwargs: Any) -> ChatProtocol:
chat_fake._set_args(**kwargs)
return chat_fake
def mock_get_console() -> Console:
return console
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
result = runner.invoke(app, ["chat", argument, str(tmp_file)])
assert result.exit_code == 0
assert chat_fake.received_messages == ["Hello"]
assert "context" in chat_fake.args
assert chat_fake.args["context"] == [Message(role=Role.SYSTEM, content=context)]
def test_load(monkeypatch: MonkeyPatch, tmp_path: Path) -> None:
# Create a conversation object to save
conversation = Conversation(
messages=[
Message(role=Role.SYSTEM, content="Hello!"),
Message(role=Role.USER, content="Hi!"),
Message(role=Role.ASSISTANT, content="How are you?"),
],
model=Model.GPT3,
temperature=0.5,
completion_tokens=10,
prompt_tokens=15,
cost=0.000043,
)
# Save the conversation to a file
file_path = tmp_path / "conversation.json"
with file_path.open("w") as f:
f.write(conversation.model_dump_json())
output = StringIO()
console = Console(file=output)
def mock_get_chat() -> Type[ChatFake]:
return ChatFake
def mock_get_console() -> Console:
return console
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat_class", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
# Load the conversation from the file
result = runner.invoke(app, ["load", str(file_path)])
assert result.exit_code == 0