Web app showcasing the Align AI Decision Maker library, designed to make human-value attribute aligned decisions in scenarios that consist of more than one correct choice.
Users select the ADM type, LLM backbone, alignment targets, and scenario. Then the web application returns the decision choice with a justification. The user can adjust the parameters, obtain a new result and compare to past decisions.
- Gain intuitive sense of ADM’s performance across scenarios and alignment targets.
- Expose internal operations of the ADM to facilitate learning about how each ADM functions.
- Battle test ALIGN System’s use as a Python library.
pip install poetry
git clone https://github.com/ITM-Kitware/align-app.git
cd align-app
poetry installMany of the LLM Backbones used in the app require you agree to some terms. Example Mistral-AI's
- Agree to the terms on the HuggingFace website for the models you use.
- Set an environment variable with your HuggingFace user access token.
export HF_TOKEN=<your token obtained from Hugging Face website>poetry run align-appThen visit http://localhost:8080
The first time you run a model, it will take some time for the HuggingFace transformers library to download the model.
The web server is from Trame. To configure the port, use the --port arg
poetry run align-app --port 8081To expose the server to the network run with the --host arg
poetry run align-app --host 0.0.0.0pip install poetry
git clone https://github.com/ITM-Kitware/align-app.git
cd align-app
poetry install --with dev
pre-commit installMerge a PR to main with semantic commit messages.