Metadata-Version: 2.1
Name: wafl
Version: 0.0.81
Summary: A hybrid chatbot.
Home-page: http://github.com/fractalego/wafl
Author: Alberto Cetoli
Author-email: alberto@fractalego.io
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown

# WAFL 0.0.80 [![Tests](https://github.com/fractalego/wafl/actions/workflows/development-tests1.yml/badge.svg)](https://github.com/fractalego/wafl/actions/workflows/development-tests1.yml)[![Docs](https://readthedocs.org/projects/wafl/badge/?version=latest)](https://wafl.readthedocs.io/en/latest/)

Introduction
============

![Logo](images/logo.png)

WAFL is a framework for home assistants.
It is designed to combine Large Language Models and rules to create a predictable behavior.
Specifically, instead of organising the work of an LLM into a chain of thoughts,
WAFL intends to organise its behavior into inference trees.

WAFL is a work in progress.
The current version requires the user to specify the rules to follow.
While it is ready to play with, it might not ready for production depending on your use-case.

Installation
============

In this version, WAFL is a two-part system.
Both can be installed on the same machine.

![The two parts of WAFL](images/two-parts.png)


## Interface side


The first part is local to your machine and needs to have access to a microphone and speaker.
To install it, run the following commands:

```bash 
$ sudo apt-get install portaudio19-dev ffmpeg
$ pip install wafl
```

After installing the requirements, you can initialize the interface by running the following command:

```bash
$ wafl init
```

which creates a `config.json` file that you can edit to change the default settings.
A standard rule file is also created as `wafl.rules`.
Please see the examples in the following chapters.


## LLM side (needs a GPU)
The second part (LLM side) is a model server for the speech-to-text model, the LLM, the embedding system, and the text-to-speech model.
A docker image can be used to run it as in the following:

```bash
$ docker run -p8080:8080 --env NVIDIA_DISABLE_REQUIRE=1 --gpus all fractalego/wafl-llm:0.80
```

The interface side has a `config.json` file that needs to be filled with the IP address of the LLM side.
The default is localhost.
Alternatively, you can run the LLM side by cloning [this repository](https://github.com/fractalego/wafl-llm).


Running WAFL
============
This document contains a few examples of how to use the `wafl` CLI.
There are four modes in which to run the system

## $ wafl run-audio

This is the main mode of operation. It will run the system in a loop, waiting for the user to speak a command.
The activation word is the name defined in config.json.
The default name is "computer", but you can change it to whatever you want.


## $ wafl run-server

It runs a local web server that listens for HTTP requests on port 8889.
The server will act as a chatbot, executing commands and returning the result as defined in the rules.


## $ wafl run-cli

This command works as for the run-server command, but it will listen for commands on the command line.
It does not run a webserver and is useful for testing purposes.


## $ wafl run-tests

This command will run all the tests defined in the file testcases.txt.


Documentation
=============

The documentation can be found at [wafl.readthedocs.io](https://wafl.readthedocs.io).


<a rel="me" href="https://fractalego.social/@wafl">Mastodon</a>
