Neon Minerva (Modular INtelligent Evaluation for a Reliable Voice Assistant) provides tools for testing skills.
Install the Minerva Python package with: pip install neon-minerva
The minerva
entrypoint is available to interact with a bus via CLI.
Help is available via minerva --help
.
If testing Padatious intents, the following system packages must be installed before installing this package:
sudo apt install swig libfann-dev
To install this package from PyPI, simply run:
pip install neon-minerva
If testing with Padatious, install with the padatious
extras:
pip install neon-minerva[padatious]
This package provides a CLI for local testing of skills. Skills installed with
pip
can be specified by entrypoint, or skills cloned locally can be specified
by root directory.
To test that skill resources are defined for all supported languages,
minerva test-resources <skill-entrypoint> <test-file>
- <skill-entrypoint> is the string entrypoint for the skill to test as specified in
setup.py
OR the path to the skill's root directory- <test-file> is a relative or absolute path to the resource test file, usually
test_resources.yaml
example test_resources.yaml
:
# Specify resources to test here.
# Specify languages to be tested
languages:
- "en-us"
- "uk-ua"
# vocab is lowercase .voc file basenames
vocab:
- ip
- public
- query
# dialog is .dialog file basenames (case-sensitive)
dialog:
- dot
- my address is
- my address on X is Y
- no network connection
- word_public
- word_local
# regex entities, not necessarily filenames
regex: []
intents:
# Padatious intents are the `.intent` file names
padatious: []
# Adapt intents are the name passed to the constructor
adapt:
- IPIntent
To test that skill intents match as expected for all supported languages,
minerva test-intents <skill-entrypoint> <test-file>
- <skill-entrypoint> is the string entrypoint for the skill to test as specified in
setup.py
OR the path to the skill's root directory- <test-file> is a relative or absolute path to the resource test file, usually
test_intents.yaml
- The
--padacioso
flag can be added to test with Padacioso instead of Padatious for relevant intents
example test_intents.yaml
:
en-us:
IPIntent:
- what is your ip address
- what is my ip address:
- IP
- what is my i.p. address
- What is your I.P. address?
- what is my public IP address?:
- public: public
uk-ua:
IPIntent:
- шо в мене за ай пі:
- IP
- покажи яка в мене за мережа:
- IP
- покажи яка в мене публічний ай пі адреса:
- public: публічний
The following top-level sections can be added to intent test configuration:
unmatched intents
: dict oflang
to list ofutterances
that should match no intents. Note that this does not test for CommonQuery or CommonPlay matches.common query
: dict oflang
to list ofutterances
OR dict ofutterances
to expected:callback_data
(list keys or dict data),min_confidence
, andmax_confidence
common play
: TBD
In addition to convenient CLI methods, this package also provides test cases that may be extended.
neon_minerva.tests.skill_unit_test_base
provides SkillTestCase
, a class
that supplies boilerplate setup/teardown/mocking for testing a skill. An example
skill test implementation could look like:
from os import environ
from neon_minerva.tests.skill_unit_test_base import SkillTestCase
environ['TEST_SKILL_ENTRYPOINT'] = "my_skill.test"
class MySkillTest(SkillTestCase):
def test_skill_init(self):
self.assertEqual(self.skill.skill_id, "my_skill.test")
...
Be sure to review the base class for mocked methods and test paths as these may change in the future.
neon_minerva.chatbots
contains mocked data for testing as well as some utility
methods. neon_minerva.tests.chatbot_v1_test_base
provides TestSubmind
which
may be extended to test a submind bot in a mocked v1 environment. For example:
from os import environ
from datetime import datetime
from chatbot_core.utils.enum import ConversationState
from neon_minerva.tests.chatbot_v1_test_base import TestSubmind
from neon_minerva.chatbots.test_constants import PROMPT, RESPONSES
environ["TEST_BOT_ENTRYPOINT"] = "tester"
class TestTester(TestSubmind):
def test_submind_chatbot(self):
self.submind.state = ConversationState.RESP
response = self.submind.ask_chatbot("testrunner", PROMPT,
datetime.now().strftime(
"%I:%M:%S %p"))
self.assertIsInstance(response, str)
self.assertIsNotNone(response)
Make sure to install the
chatbots
extra to use this test case