ravestate 0.6.0

Ravestate is a reactive library for real-time natural language dialog systems.

About

   ____                          __      __        _____       _____   
  / _  \____  __  ______  ______/ /_____/ /___    /_   _\     /_   _\  
 / /_/ / __ \/ / / / __ \/ ___\, / __ \, / __ \    0>  0>     <0  <0   
/ ,\ ,/ /_/ /\ \/ / /_/ /\__, / / /_/ / / /_/ /   \__⊽__/     \__⊽__/  
\/  \/\__/\/  \__/ ,___/\____/\/\__/\/\/ ,___/       ⋂  - Hey!   ⋂     
                 \____/                \____/             Olà! -       

Ravestate is a reactive library for real-time natural language dialog systems. It combines elements from event-based and reactive programming into an API, where application states are defined as functions that are run when a certain boolean set of criteria (signals) in the current application context is satisfied. It is the first reactive API to allow for boolean combinations of events. You may find a short introductory video here.

Reactive Hello World

import ravestate as rs

# We want to write some text output, so we
# need the raw:out context property from ravestate_rawio.
import ravestate_rawio as rawio

# Make sure that we use some i/o implementation,
# so we can actually see stuff that is written to rawio:out.
import ravestate_conio

# Ravestate applications should always be wrapped in a Module.
# This allows easier scoping, and enables separation of concerns
# beyond states.
with rs.Module(name="hi!"):

    # Create an application state which reacts to the `:startup` signal,
    # and writes a string to raw:out. Note: State functions are
    # always run asynchronously!
    @rs.state(cond=rs.sig_startup, write=rawio.prop_out)
    def hello_world(context):
        context[rawio.prop_out] = "Waddup waddup waddup!"

# Run context with console input/output and our 'hi!' module.
rs.Context("conio", "hi!").run()

Visualization

Ravestate has a d3.js-based visualization. When using ravestate_ui.UIContext instead of Context, or python3 -m ravestate_ui instead of python3 -m ravestate, a real-time visualization of all states/properties/signals in the state machine will be hosted on port 5001. Here is the view of http://localhost:5001 after launching python3 ravestate_ui -f generic.yml:

Installation

Via PIP

The easiest way to install ravestate is through pip:

pip install ravestate

Note: Ravestate requires Python 3.6 or higher. It is tested on Ubuntu 16.04 and 18.04, as well as macOS > High Sierra. It is currently not tested on Windows.

For reliability, we recommend using an environment virtualization tool, like virtualenv or conda.

For developers

Initial configuration and setup

Clone the repository and install dependencies:

# Create a virtual python environment to not pollute the global setup
python3 -m virtualenv python-ravestate

# Source the virtual environment
. python-ravestate/bin/activate

# Clone the repo
git clone [e-mail]:roboy/ravestate && cd ravestate

# Install normal requirements
pip install -r requirements.txt

# To run tests & build docs, install pytest, mocking, fixtures, pydoc, ...
pip install -r requirements-dev.txt

# Link your local ravestate clone into your virtualenv
pip install -e .

Now, launch a Neo4j docker instance to serve Scientio, so the dialog system has a memory:

docker run \
    --publish=7474:7474 --publish=7687:7687 \
    --volume=$HOME/neo4j/data:/data \
    --volume=$HOME/neo4j/logs:/logs \
    neo4j:latest

# Open the address localhost:7474 in a browser, and enter the
# credentials `neo4j`/`neo4j`. You will then be prompted to enter
# your own password. Remember this password.

In the config folder, create a file called keys.yml. It should have the following content:

module: telegramio
config:
  telegram-token: <sexycactus>  # This is where your own telegram bot token
                                # will go later
---
module: ontology
config:
  neo4j_address: bolt://localhost:7687  # Your neo4j server uri here
  neo4j_username: neo4j                 # Your neo4j user here
  neo4j_pw: test                        # Your neo4j pw here

You may now conduct your first conversation with ravestate:

python3 -m ravestate -f config/generic.yml -f config/keys.yml

After the conversation, check the Neo4j interface under localhost:7474. It should now contain some nodes!

Reminder: Whenever you use ravestate from the command line, activate the virtual environment first!

Setting up PyCharm

1. Open your local ravestate clone as a project in pycharm.
2. Mark the modules folder as sources root via the right-click context menu.
3. Create a run config alà the "Edit configurations menu":
   • Create a new Python configuration.
   • Set modules/ravestate/__main__.py as the script to execute
   • Set the working directory to the git clone directory.
   • Set parameters to -f config/generic.yml -f config/keys.yml.
   
4. You should now be able to run the generic ravestate config from pycharm.

Running Hello World

Ravestate applications are defined by a configuration, which specifies the ravestate modules that should be loaded.

To run the basic hello world application, run ravestate with a config file or command line arguments:

Running with command line spec

You can easily run a combination of ravestate modules in a shared context, by listing them as arguments to python3 -m ravestate:

python3 -m ravestate \
    ravestate_wildtalk \
    ravestate_conio \
    ravestate_hibye \
    ravestate_persqa

Run python3 -m ravestate -h to see more options!

Running with config file(s)

You may specify a series of config files to configure ravestate context, when specifying everything through the command line becomes too laborious:

# In file hello_world.yml
module: core
config:
  import:
    - ravestate_wildtalk
    - ravestate_conio
    - ravestate_hibye
    - ravestate_persqa

Then, run ravestate with this config file:

python3 -m ravestate -f hello_world.yml

Module overview

Ravestate offers a landscape of fine-grained modules for different aspects of dialog application tasks, which may be seen in the following dependency diagram. Broadly, the modules are categorized into Core (Blue), I/O (Yellow), External (Red) and Skills (Green):

Core Modules

Module name	Description
ravestate	Core ravestate library.
ravestate_rawio	Provides raw_in, raw_out, pic_in properties, which are served by the IO modules.
ravestate_ontology	Connects to scientio to serve a built-in ontology.
ravestate_interloc	Provides the all_interlocutors property, where present interlocutors are registered by the IO modules.
ravestate_idle	Provides bored and impatient signals, as specified here.
ravestate_verbaliser	Utilities for easy management of conversational text, documented here.
ravestate_nlp	Spacy-based NLP properties and signals, documented here.
ravestate_ros2	Provides specific Ros2PubProperty, Ros2SubProperty and Ros2CallProperty context props., which greatly simplify working with ROS2 in ravestate.

IO Modules

Module name	Description
ravestate_conio	Simple command-line based IO for development purposes.
ravestate_telegramio	Single- or Multi-process Telegram server module, documented here.
ravestate_roboyio	PyroBoy -based STT/TTS with ROS2.

Skill Modules

Module name	Description
ravestate_wildtalk	ParlAI -based generative conversational module.
ravestate_hibye	Simply voices Hi! (or the likes thereof) when an interlocutor is added, and Bye when one is removed.
ravestate_persqa	Conducts personalized smalltalk with interlocutors, interacts with Scientio to persist trivia.
ravestate_genqa	DrQA -based general question answering module.
ravestate_roboyqa	QA module which provides answers to questions about Roboy, such as Who is your dad?
ravestate_akinator	Enables dialog-based play of Akinator!
ravestate_sendpics	Uses face recognition to extract facial features and an assiciated Person with pic_in and ontology, which are then persisted in Redis and Scientio.
ravestate_stalker	Uses facial feature <-> person tuples generated by sendpics, to surprise people in front of a camera with knowledge of their names.

Running tests

If you have installed the dependencies from requirements-dev.txt you may run the ravestate test suite as follows:

./run_tests.sh

Docker for ROS and ROS2

There is a Dockerfile for ROS and ROS2 support which can be built with

docker build -t ravestate-ros2-image .

The image contains ROS, ROS2 and a ROS Bridge to connect ROS with ROS2. Furthermore the roboy_communication message and service types are installed.

A container can then be created with the docker-compose.yml:

docker-compose up --detach ravestate

The container is now running and a connection into the container can be established with:

docker exec -it ravestate-ros2-container bash

Inside the container, first source the ROS2 setups and then ravestate can be run with ROS2 and rclpy available.

source ~/ros2_ws/install/setup.sh
python3 -m ravestate [...]

Start ROS Bridge

In order to start ROS Bridge, the image and container have to be set up as above. After connecting into the container run from inside the container:

export ROS_IP=192.168.0.105
source ~/melodic_ws/devel/setup.sh
source ~/ros2_ws/install/setup.sh
source ~/ros1_bridge_ws/install/setup.sh
ros2 run ros1_bridge dynamic_bridge

Building/maintaining the docs

If you have installed the dependencies from requirements-dev.txt, generate the docs by running this command at project root:

export PYTHONPATH=$PYTHONPATH:$(pwd)/modules
git rm -rf docs
rm -rf _build docs
pydocmd build
mkdir -p docs/resources/docs && cp resources/docs/*.png docs/resources/docs && cp resources/docs/*.gif docs/resources/docs
git add docs/*
# For inspection: python3 -m http.server --directory docs

The structure and content of the docs are defined in the file pydocmd.yml.