mirror of
https://github.com/acon96/home-llm.git
synced 2026-01-08 21:28:05 -05:00
90 lines
5.0 KiB
Markdown
90 lines
5.0 KiB
Markdown
---
|
|
license: mit
|
|
task_categories:
|
|
- question-answering
|
|
- text-generation
|
|
tags:
|
|
- automation
|
|
- home
|
|
- assistant
|
|
language:
|
|
- en
|
|
pretty_name: Home Assistant Requests V2
|
|
size_categories:
|
|
- 10K<n<100k
|
|
---
|
|
|
|
# Home Assistant Requests V2 Dataset
|
|
|
|
This dataset contains a list of requests and responses for a user interacting with a personal assistant that controls an instance of [Home Assistant](https://www.home-assistant.io/).
|
|
|
|
The updated V2 of the dataset is now multilingual, containing data in English, German, French, Spanish, and Polish. The dataset also contains multiple "personalities" for the assistant to respond in, such as a formal assistant, a sarcastic assistant, and a friendly assistant. Lastly, the dataset has been updated to fully support modern tool-calling formats.
|
|
|
|
## Assembling the dataset
|
|
|
|
> NOTE: If you are viewing this dataset on HuggingFace, you can download the "small" dataset variant directly from the "Files and versions" tab.
|
|
|
|
The dataset is generated from the different CSV "piles". The "piles" contain different chunks of requests that are assembled into a final context that is presented to the LLM. For example, `piles/<language>/pile_of_device_names.csv` contains only names of various devices to be used as part of context as well as inserted into `piles/<language>/pile_of_templated_actions.csv` and `piles/<language>/pile_of_status_requests.csv`. The logic for assembling the final dataset from the piles is contained in [generate_data.py](./generate_data.py).
|
|
|
|
### Prepare environment
|
|
|
|
Start by installing system dependencies:
|
|
`sudo apt-get install python3-dev`
|
|
|
|
Then create a Python virtual environment and install all necessary library:
|
|
```
|
|
python3 -m venv .generate_data
|
|
source .generate_data/bin/activate
|
|
pip3 install -r requirements.txt
|
|
```
|
|
|
|
### Generating the dataset from piles
|
|
|
|
`python3 generate_data.py --train --test --small --language english german french spanish polish`
|
|
|
|
Supported dataset splits are `--test`, `--train`, & `--sample`
|
|
Arguments to set the train dataset size are `--small`, `--medium`, `--large`, & `--xl`.
|
|
Languages can be enabled using `--language english german french spanish polish`
|
|
|
|
## Adding a new personality
|
|
In order to add a new personality, you need to define a new system prompt and new set of responses for the assistant. The system prompt is the description of the assistant's behavior that occurs at the start of the context. The responses are what is said back to the user when performing a task. The model should still respond with the correct service call no matter what the assistant's response is. The list of system prompts are stored in `pile_of_system_prompts.csv`, and the list of responses are stored in `pile_of_responses.csv`
|
|
|
|
There are 2 columns in `pile_of_system_prompts.csv`:
|
|
- `persona`: the name of the persona
|
|
- `prompt`: the system prompt to use for that persona. Recommended to put this in quotes in case the prompt also has commas in it
|
|
|
|
The response pile is a CSV with the following headers: `service,response,language,persona,short`
|
|
- `service`: the service name that we are responding to. Make sure you cover enough different services so that the model can learn how to respond in all situations.
|
|
- `response`: the text of the response. Recommended to put this in quotes in case the response also has commas in it
|
|
- `persona`: the name of the persona the response belongs to. Use the name of your persona here
|
|
- `short`: either 0 or 1. If it is 1 then the response is considered "short', and can be combined together with other "short" responses using "and". These are used for examples where there are multiple service calls
|
|
|
|
Generating the full dataset using the python script will print out a warning for any responses that are missing for a persona.
|
|
|
|
## Synthesizing new pile data
|
|
You can quickly append fresh examples to the CSV piles without editing them manually by running `synthesize.py`. The script talks to the configured LLM and writes the generated rows directly into the per-language pile files.
|
|
|
|
Examples:
|
|
|
|
```bash
|
|
# Append 25 failed tool-call recoveries and 25 refusals in Spanish
|
|
python3 synthesize.py --language spanish --model gpt-oss-120b --failed-tool-calls 25 --refusals 25 --concurrency 6
|
|
|
|
# Generate new actions plus matching refusal samples in German
|
|
python3 synthesize.py --language german --actions 100 --refusals 40 --model gpt-oss-120b
|
|
```
|
|
|
|
Useful flags:
|
|
- `--failed-tool-calls`: number of `pile_of_failed_tool_calls.csv` rows to synthesize.
|
|
- `--refusals`: number of `pile_of_refusals.csv` rows to synthesize.
|
|
- `--actions`, `--status`, `--devices`: existing knobs for the other piles.
|
|
|
|
The script automatically routes generations to the correct language-specific pile under `data/piles/<language>/`.
|
|
|
|
## Adding new Home Assistant functionality
|
|
TODO
|
|
<!-- In order to add new home assistant device types, you will need to add data to a handful of piles, as well as make small modifications to the `generate_data.py` script.
|
|
1. Add 15-30 new device names with the new type to the `pile_of_device_names.csv`. This should be an entity_id and a 'friendly name'
|
|
2. Add
|
|
-->
|