sigllm 0.0.1

Signals plus LLMs

An open source project from Data to AI Lab at MIT.

sigllm

Signals plus LLMs

• Documentation: https://sintel-dev.github.io/sigllm
• Homepage: https://github.com/sintel-dev/sigllm

Overview

TODO: Provide a short overview of the project here.

Install

Requirements

sigllm has been developed and tested on Python 3.8, 3.9, 3.10 and 3.11

Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system in which sigllm is run.

These are the minimum commands needed to create a virtualenv using python3.8 for sigllm:

pip install virtualenv
virtualenv -p $(which python3.6) sigllm-venv

Afterwards, you have to execute this command to activate the virtualenv:

source sigllm-venv/bin/activate

Remember to execute it every time you start a new console to work on sigllm!

Install from source

With your virtualenv activated, you can clone the repository and install it from source by running make install on the stable branch:

git clone [e-mail]:sintel-dev/sigllm.git
cd sigllm
git checkout stable
make install

Install for Development

If you want to contribute to the project, a few more steps are required to make the project ready for development.

Please head to the Contributing Guide for more details about this process.

Quickstart

In this short tutorial we will guide you through a series of steps that will help you getting started with sigllm.

TODO: Create a step by step guide here.

What's next?

For more details about sigllm and all its possibilities and features, please check the documentation site.

History

0.0.1 - 2024-09-25

First sigllm release to PyPI: https://pypi.org/project/sigllm/

• Add README – Issue #17 by @sarahmish
• Create a SigLLM API – Issue #13 by @sarahmish
• Add a Quick Example – Issue #12 by @sarahmish
• Forecasting Pipeline – Issue #11 by @sarahmish
• Refactor Transformation Primitives – Issue #7 by @sarahmish
• Forecasting Module – Issue #2 by @sarahmish