https://github.com/intellabs/convassist
https://github.com/intellabs/convassist
Last synced: 4 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/intellabs/convassist
- Owner: IntelLabs
- License: gpl-3.0
- Created: 2023-12-20T20:42:09.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-27T15:14:59.000Z (over 1 year ago)
- Last Synced: 2025-02-27T21:51:04.196Z (over 1 year ago)
- Language: Python
- Size: 94.9 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
Awesome Lists containing this project
README
# ConvAssist
[](https://scorecard.dev/viewer/?uri=github.com/IntelLabs/ConvAssist)
[](https://github.com/IntelLabs/ConvAssist/actions/workflows/run_unittests.yaml)
[](https://pytorch.org/get-started/locally/)
[](https://deepwiki.com/IntelLabs/ConvAssist)
ConvAssist is a library intended to enable and empower users with disabilities to communicate using the latest language modeling technologies, via Intel's Assistive Context Aware Toolkit, ACAT. ConvAssist can quickly suggest utterances/sentences that the user can use to have a social conversation or communicate with their caregiver in near real time.
ConvAssist is built on [Pressagio](https://github.com/Poio-NLP/pressagio), that is a library that predicts text based on n-gram models. Pressagio is a pure Python port of the [presage library](https://presage.sourceforge.io) and is part of the [Poio project](https://www.poio.eu).
ConvAssist contains language models based on specific Assistive and Augmentative Communication (AAC) datasets, and dialog datasets, tailored for day-to-day communication in our assistive usecase. These language models support both next word prediction and sentence completion for enabling near-real time communication with least amount of user effort and intervention.
## Predictor Classes
### Sentence Completion Predictor
```SentenceCompletionPredictor``` is a class that provides sentence completion predictions using a combination of n-gram models and GPT-2.
### Spell Correct Predictor
```SpellCorrectPredictor``` is a class that extends the Predictor class to provide spell correction functionality. It uses a spell checker to generate suggestions for the last token in the context.
### Canned Phrases Predictor
```CannedPhrasesPredictor``` is a class that searches a database of canned phrases to find matching next words and sentences based on a given context.
### Canned Word Predictor
```CannedWordPredictor``` is a specialized predictor that extends the SmoothedNgramPredictor. It is designed to handle canned responses using natural language processing (NLP) techniques.
### Smoothed NGram Predictor
```SmoothedNgramPredictor``` is a class that extends the Predictor class to provide functionality for predicting the next word(s) in a sequence using smoothed n-grams.
### General Word Predictor
```GeneralWordPredictor``` is a class that extends SmoothedNgramPredictor to provide word predictions based on a precomputed set of most frequent starting words from an AAC dataset.
## Installation and use
ConvAssist works with Python 3.12.x or greater. Create a virtual environment and install the required packages. We provide a pyproject.toml file to assist, and use Poetry for package management.
#### Create a Virtual Environment with Poetry
1. **Clone the Repository**:
```sh
git clone https://github.com/IntelLabs/ConvAssist.git
cd ConvAssist
```
2. **Install Poetry**:
If you don't have Poetry installed, you can install it by following the instructions on the [Poetry website](https://python-poetry.org/docs/#installation).
3. **Install Dependencies and Create Virtual Environment**:
```sh
poetry install
```
This command will create a virtual environment, install the dependencies specified in the `pyproject.toml` file, and set up the environment for you.
4. **Activate the Virtual Environment**:
```sh
poetry shell
```
This command activates the virtual environment created by Poetry.
## Installation and use
ConvAssist works with Python 3.12.x or greater. Create a virtual environment and install the required packages. We provide a pyproject.toml file to assist, and use Poetry for package management.
#### Create a Virtual Environment with Poetry
1. **Clone the Repository**:
```sh
git clone https://github.com/IntelLabs/ConvAssist.git
cd ConvAssist
```
2. **Install Poetry**:
If you don't have Poetry installed, you can install it by following the instructions on the [Poetry website](https://python-poetry.org/docs/#installation).
3. **Install Dependencies and Create Virtual Environment**:
```sh
poetry install
```
This command will create a virtual environment, install the dependencies specified in the `pyproject.toml` file, and set up the environment for you.
4. **Activate the Virtual Environment**:
```sh
poetry shell
```
This command activates the virtual environment created by Poetry.
### Run
We provide several demonstration apps to showcase how to use ConvAssist
#### DEMO - Continuous Predict
``` sh
cd interfaces/Demos/continuous_predict
python pyprompter.py
```
The `continuous_prediction.ini` file defines which predictors are enable. See documentation for continuous_predict for details on how to use the configuration file.
## License
ConvAssist source code is distributed under the GPL-3.0 or later license.