OVOS Model2Vec Intent Pipeline

An intent matching pipeline for OpenVoiceOS (OVOS), powered by the Model2Vec model for intent classification.

This plugin uses a pretrained Model2Vec model to classify natural language utterances into intent labels registered with the system (Adapt, Padatious, and plugin-specific labels). It only considers intents from loaded skills and ignores any labels from unregistered intents. This pipeline is ideal for use cases where other deterministic engines fail to provide a high-confidence match.

✨ Features

• ✅ Powered by Model2Vec for high-quality intent classification
• ✅ Plug-and-play integration with OVOS pipelines
• ✅ Model2Vec trained on GitLocalize exports
• ✅ English models in various sizes, distilled from Potion
• ✅ Multilingual model, distilled from LaBSE
• ✅ Syncs Adapt and Padatious intents dynamically at runtime
• ✅ Only considers intents from loaded skills, ignoring unregistered labels

💡 english models size ranges from 8MB to 150MB, the multilingual model (default) is over 500MB

📦 Installation

You can install the plugin via pip:

pip install ovos-m2v-pipeline

⚙️ Configuration

In your mycroft.conf:

{
  "intents": {
    "ovos-m2v-pipeline": {
      "model": "Jarbas/ovos-model2vec-intents-LaBSE",
      "conf_high": 0.7,
      "conf_medium": 0.5,
      "conf_low": 0.15,
      "ignore_intents": []
    }
  }
}

• model: Path to your pretrained Model2Vec model or huggingface repo.
• conf_xxx: Minimum confidence threshold for intent matching.
• ignore_intents: List of intents to ignore during matching.
• prototype_strategy: Scoring strategy for prototype mode ("max_over_all" default — back-compatible). See docs/strategies.md.
• prototype_top_k: Top-k cosines averaged by the top_k_mean strategy (default 3).
• prototype_tau: Softmax temperature for the softmax_weighted strategy (default 0.1).

⚠️ The Model2Vec model is pretrained based on GitLocalize exports and cannot learn new skills dynamically.

🧠 Usage

The Model2VecIntentPipeline class integrates with the OVOS intent system. It:

1. Receives an utterance (text).
2. Predicts intent labels using the pretrained Model2Vec model.
3. Filters out intents that are not part of the loaded skills.
4. Returns a match for the highest-confidence intent from the list of valid intents.

🧪 Tips

• Tune min_conf to control the confidence threshold for intent matching.
• Use the ignore_intents list to filter out specific problematic intent from predictions.
• Syncing of Adapt and Padatious intents is done automatically at runtime via the OVOS message bus.

💡 pre-trained models available in this huggingface collection ovos-model2vec-intents

🛡 License

This project is licensed under the Apache 2.0 License.

Credits

The model2vec intent pipeline was first prototyped by TigreGótico under the ILENIA project for OpenVoiceOS and substantially extended — an embeddings-only mode and new models — through the NGI0 Commons Fund.

This project was funded by the Ministerio para la Transformación Digital y de la Función Pública and Plan de Recuperación, Transformación y Resiliencia - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337

This project was funded through the NGI0 Commons Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 101135429.