Test chat bots, voice assistants, and IVR menus with pytest using a small Conversation object and a callable bot adapter. Use when the user wants to write rule-based assertions over multi-turn dialogue without bringing in an LLM dependency, when they have a chatbot reachable as a Python callable or HTTP webhook, when they need to keep per-conversation state across turns and assert on slot filling, when they want pytest-native fixtures and a printable transcript on failure, or when they mention voice-assistant testing, IVR menu testing, conversational AI testing, LLM bot testing (used as the target under test, not as the matcher), expect matchers for bot replies, or multi-turn dialogue tests.
99
100%
Does it follow best practices?
Impact
97%
1.56xAverage score across 3 eval scenarios
Passed
No known issues
"""Smoke tests for the public API."""
import re
from pytest_conversational import Conversation, Turn, __version__
def test_version_is_set():
# Version is read from package metadata via importlib.metadata.
# In a stale dev install it may lag pyproject.toml, so accept any
# non-empty PEP 440 style string.
assert isinstance(__version__, str)
assert __version__
assert re.match(r"^\d+\.\d+", __version__) or __version__.startswith("0.0.0+")
def test_empty_conversation_has_no_turns():
convo = Conversation()
assert convo.turns == []
assert convo.last is None
def test_add_user_appends_turn():
convo = Conversation()
turn = convo.add_user("hello")
assert turn.user == "hello"
assert turn.bot == ""
assert convo.last is turn
assert len(convo.turns) == 1
def test_turn_metadata_isolated_per_instance():
a = Turn(user="hi")
b = Turn(user="hi")
a.metadata["intent"] = "greet"
assert b.metadata == {}
def test_fixture_provides_empty_conversation(pytester):
pytester.makepyfile(
"""
def test_smoke(conversation):
assert conversation.turns == []
"""
)
result = pytester.runpytest()
result.assert_outcomes(passed=1).tessl-plugin
evals
src
pytest_conversational
tests