This release is a pre-release and may not be stable for production use.
Padatious
Padatious is a neural network intent parser, implemented in pure numpy with a FANN-compatible model format. This repository packages it as an OpenVoiceOS (OVOS) pipeline plugin and bundles a maintained fork of the original padatious from Mycroft AI.
Features
- Intents are easy to create from a handful of example sentences.
- Each intent trains its own small network, independent of the others.
- Fast training on a small amount of data.
- Entity extraction from a matched sentence (for example,
Find the nearest {place}matches "Find the nearest gas station" and extractsplace: gas station).
Installing
Padatious is pure Python (numpy). It needs no native libraries or compilers.
Install from PyPI:
pip install ovos-padatious-pipeline-plugin
Direct Usage
from ovos_padatious import IntentContainer
container = IntentContainer('intent_cache')
container.add_intent('hello', ['Hi there!', 'Hello.'])
container.add_intent('goodbye', ['See you!', 'Goodbye!'])
container.add_intent('search', ['Search for {query} (using|on) {engine}.'])
container.train()
print(container.calc_intent('Hello there!'))
print(container.calc_intent('Search for cats on CatTube.'))
container.remove_intent('goodbye')
Inside OVOS, the plugin is discovered automatically through its opm.pipeline entry point. See docs/ for installation details, the intent file syntax, the full Python API, pipeline configuration, and the matching algorithm.
Related projects
- OpenVoiceOS/ovos-spec-tools: the reference implementation of the OVOS architecture specifications, used here for sentence-template expansion and language tag handling.
- OpenVoiceOS/architecture: the OpenVoiceOS architecture specifications.
- OpenVoiceOS/ovos-plugin-manager: the plugin and entry-point system that loads this pipeline into OVOS.
License
Licensed under the Apache 2.0 license.
1 maintainer
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