Skip to main content

Neon Minerva

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.

Installation

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]

Usage

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.

Resource Tests

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

Intent Tests

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

Test Configuration

The following top-level sections can be added to intent test configuration:

  • unmatched intents: dict of lang to list of utterances that should match no intents. Note that this does not test for CommonQuery or CommonPlay matches.
  • common query: dict of lang to list of utterances OR dict of utterances to expected: callback_data (list keys or dict data), min_confidence, and max_confidence
  • common play: TBD

Advanced Usage

In addition to convenient CLI methods, this package also provides test cases that may be extended.

Skill Unit Tests

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.

Chatbot Unit Tests

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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

neon_minerva-0.4.1.tar.gz (26.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

neon_minerva-0.4.1-py3-none-any.whl (44.6 kB view details)

Uploaded Python 3

File details

Details for the file neon_minerva-0.4.1.tar.gz.

File metadata

  • Download URL: neon_minerva-0.4.1.tar.gz
  • Upload date:
  • Size: 26.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for neon_minerva-0.4.1.tar.gz
Algorithm Hash digest
SHA256 281b8f86da61ff4bc1d262a25be6171f8625b9f1ffd449f67d8308518f4c8cda
MD5 04b69df695c1622b7cdc21535910457c
BLAKE2b-256 95a9d67750b6c4192e31b4f0e3b8b3ba4d4f0769bda1a987f7979eeade2dec86

See more details on using hashes here.

File details

Details for the file neon_minerva-0.4.1-py3-none-any.whl.

File metadata

  • Download URL: neon_minerva-0.4.1-py3-none-any.whl
  • Upload date:
  • Size: 44.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for neon_minerva-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 c4e99e5eb84bea52bab68a63fe762b09a6e04b4cab9f6387d843d979e197f1f6
MD5 73a58441560434e8b2474b5de964c0c3
BLAKE2b-256 5d1244207236e4aa3282e495689b2eb3364b8db7593e87ab9dfa518f29ec0071

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page