ruT5 smart home function calling

Fine-tuned ai-forever/ruT5-base. Takes a Russian smart home command and returns a JSON list of function calls in Home Assistant style (HassTurnOn, HassTurnOff, HassLightSet, HassClimateSetTemperature and others).

Модель превращает русскую команду для умного дома в JSON со списком вызовов функций.

Usage

The tokenizer vocabulary lacks some characters ({ } Q Y Z & é →), so the model works with an escaped text format. inference.py in this repository handles it. Do not call generate directly without it.

from huggingface_hub import snapshot_download
import sys

path = snapshot_download("ilyali034/ruT5-base-smart-home")
sys.path.insert(0, path)
from inference import SmartHomeModel

model = SmartHomeModel(path)
print(model.predict("включи свет на кухне"))

Output example:

{"text": "[{\"name\": \"HassTurnOn\", \"arguments\": {\"name\": \"Kitchen Light\"}}]", "calls": [{"name": "HassTurnOn", "arguments": {"name": "Kitchen Light"}}]}

Training

• Base model: ai-forever/ruT5-base
• Data: RockMan256/needle-ru-opt, split 90/5/5 (train/val/test), seed 42
• 5 epochs, Adafactor, learning rate 3e-4, batch size 16, fp16
• The tools list is identical in every example of the dataset, so it is not given to the model: the input is query: <command>

Results (test, 1290 examples)

Limitations

• Almost all errors are in the name argument (device name). The model does not see the list of devices in the home, so when a command does not say which device is meant (for example, several thermostats), or a device has several valid English names, it picks one. Use it together with a list of real devices, or map its output to the closest known device name.
• Sometimes the model skips the last call in commands with several actions.
• Device names in the data are mostly English, commands are Russian.
• Trained on synthetic data. Quality on real user phrases may be lower.