nicobot

A collection of 🤟 cool 🤟 chat bots :

• Transbot is a demo chatbot interface to IBM Watson™ Language Translator service
• Askbot is a one-shot chatbot that will throw a question and wait for an answer

My bots are cool, but they are absolutely EXPERIMENTAL use them at your own risk !

This project features :

• Participating in Signal conversations
• Using IBM Watson™ Language Translator cloud API

Requirements & installation

Classic installation

A classic (virtual) machine installation requires :

• Python 3 (>= 3.4.2)
• signal-cli for the Signal backend (see [Using the Signal backend] below for requirements)
• For transbot : an IBM Cloud account (free account ok)

Docker usage

There are several Docker images available, with the following tags :

• debian : if you have several images with the debian base, this may be the most efficient (as base layers will be shared with other images)
• debian-slim : if you want a smaller-sized image and you don't run other images based on debian (as it will not share as much layers as with the above debian tag)
• alpine : this is the smallest image (<100MB) but it may have more bugs than debian ones because it's more complex to maintain

Since those bots are probably not going be enterprise-level critical at any point, I suggest you use the alpine image and switch to debian or debian-slim if you encounter performance issues or other problems.

Those images should be able to run on all CPU architectures supported by the base images.

Sample command to run :

docker run --rm -it -v "myconfdir:/etc/nicobot" nicobot:alpine transbot -C /etc/nicobot

Installation from source

You can also install from source (you need python3 & pip) :

# Sample command to install python3 & pip3 on Debian ; update it according to your OS
sudo apt install python3 python3-pip
git clone https://github.com/nicolabs/nicobot.git
cd nicobot
pip3 install -r requirements-runtime.txt

Then simply follow the instructions below to configure & run it.

Transbot

Transbot is a demo chatbot interface to IBM Watson™ Language Translator service.

Again, this is NOT STABLE code, there is absolutely no warranty it will work or not harm butterflies on the other side of the world... Use it at your own risk !

The included sample configuration in tests/transbot-sample-conf, demoes how to make it translate any message like nicobot <message> in chinese or simply nicobot <message> (into the current language).

It can also automatically translate messages containing keywords into a random language. The sample configuration shows how to make it translate any message containing "Hello" or "Goodbye" in many languages.

Quick start

1. Install the package for systems this will look like :

   sudo apt install python3 python3-pip
   pip3 install nicobot
   

2. Create a Language Translator service instance on IBM Cloud and get the URL and API key from your console
3. Fill them into tests/transbot-sample-conf/config.yml (ibmcloud_url and ibmcloud_apikey)
4. Run transbot -C tests/transbot-sample-conf
5. Input Hello world in the console : the bot will print a random translation of "Hello World"
6. Input Bye nicobot : the bot will terminate

If you want to send & receive messages through Signal instead of reading from the keyboard & printing to the console :

1. Install and configure signal-cli (see below for details)
2. Run transbot -C tests/transbot-sample-conf -b signal -U '+33123456789' -r '+34987654321' with -U +33123456789 your Signal number and -r +33987654321 the one of the person you want to make the bot chat with

See dedicated chapters below for more options...

Main configuration options and files

Run transbot -h to get a description of all options.

Below are the most important configuration options for this bot (please also check the generic options below) :

• --keyword and --keywords-file will help you generate the list of keywords that will trigger the bot. To do this, run transbot --keyword <a_keyword> --keyword <another_keyword> ... a first time with : this will download all known translations for these keywords and save them into a keywords.json file. Next time you run the bot, don't use the --keyword option : it will reuse this saved keywords list. You can use --keywords-file to change the default name.
• --languages-file : The first time the bot runs, it will download the list of supported languages into languages.<locale>.json and reuse it afterwards but you can give it a specific file with the set of languages you want. You can use --locale to set the desired locale.
• --locale will select the locale to use for default translations (with no target language specified) and as the default parsing language for keywords.
• --ibmcloud-url and --ibmcloud-apikey can be obtained from your IBM Cloud account (create a Language Translator instance then go to the resource list)

The i18n.<locale>.yml file contains localization strings for your locale and fun :

• Transbot will say "Hello" when started and "Goodbye" before shutting down : you can configure those banners in this file.
• It also defines the pattern that terminates the bot.

A sample configuration is available in the tests/transbot-sample-conf/ directory.

Askbot

Askbot is a one-shot chatbot that will throw a question and wait for an answer.

Again, this is NOT STABLE code, there is absolutely no warranty it will work or not harm butterflies on the other side of the world... Use it at your own risk !

When run, it will send a message (if provided) and wait for an answer, in different ways (see options below). Once the conditions are met, the bot will terminate and print the result in JSON format. This JSON structure will have to be parsed in order to retrieve the answer and determine what were the exit(s) condition(s).

Main configuration options

Run askbot -h to get a description of all options.

Below are the most important configuration options for this bot (please also check the generic options below) :

• --max-count will define how many messages to read at maximum before exiting. This allows the recipient to send several messages in answer. However currently all of those messages are returned at once after they all have been read by the bot so they cannot be parsed on the fly. To give x tries to the recipient, run x times this bot instead.
• --pattern defines a pattern that will end the bot when matched. It takes 2 arguments : a symbolic name and a regular expression pattern that will be tested against each message. It can be passed several times in the same command line, hence the <name> argument, which will allow identifying which pattern(s) matched.

Sample configuration can be found in tests/askbot-sample-conf.

Example

The following command will :

• Send the message "Do you like me" to +34987654321 on Signal

• Wait for a maximum of 3 messages in answer and return

• Or return immediately if one message matches one of the given patterns labeled 'yes', 'no' or 'cancel'

  askbot -m "Do you like me ?" -p yes '(?i)\b(yes|ok)\b' -p no '(?i)\bno\b' -p cancel '(?i)\b(cancel|abort)\b' --max-count 3 -b signal -U '+33123456789' --recipient '+34987654321'

If the user +34987654321 would reply "I don't know" then "Ok then : NO !", the output would be :

{
    "max_responses": false,
    "messages": [{
        "message": "I don't know...",
        "patterns": [{
            "name": "yes",
            "pattern": "(?i)\\b(yes|ok)\\b",
            "matched": false
        }, {
            "name": "no",
            "pattern": "(?i)\\bno\\b",
            "matched": false
        }, {
            "name": "cancel",
            "pattern": "(?i)\\b(cancel|abort)\\b",
            "matched": false
        }]
    }, {
        "message": "Ok then : NO !",
        "patterns": [{
            "name": "yes",
            "pattern": "(?i)\\b(yes|ok)\\b",
            "matched": true
        }, {
            "name": "no",
            "pattern": "(?i)\\bno\\b",
            "matched": true
        }, {
            "name": "cancel",
            "pattern": "(?i)\\b(cancel|abort)\\b",
            "matched": false
        }]
    }]
}

A few notes about the example : in -p yes '(?i)\b(yes|ok)\b' :

• (?i) enables case-insensitive match
• \b means "edge of a word" ; it is used to make sure the wanted text will not be part of another word (e.g. tik tok would match ok otherwise)
• Note that a search is done on the messages (not a match) so it is not required to specify a full expression with ^ and $ (though you may if you want). This makes the pattern more readable.
• The pattern is labeled 'yes' so it can easily be identified in the JSON output and checked for a positive match

Also you can notice the importance to define patterns that don't overlap (here the message matched both 'yes' and 'no') or to handle unknow states.

You could parse the output with a script, or with a command-line client like jq. For instance, to get the name of the matched patterns in Python :

output = json.loads('{ "max_responses": false, "messages": [...] }')
matched = [ p['name'] for p in output['messages'][-1]['patterns'] if p['matched'] ]

It will return the list of the names of the patterns that matched the last message ; e.g. ['yes','no'] in our above example.

Generic instructions

Main generic options

The following options are common to both bots :

• --config-file and --config-dir let you change the default configuration directory and file. All configuration files will be looked up from this directory ; --config-file allows overriding the location of config.yml.
• --backend selects the chatter system to use : it currently supports "console" and "signal" (see below)
• --stealth will make the bot connect and listen to messages but print any answer instead of sending it ; useful to observe the bot's behavior in a real chatroom...

Config.yml configuration file

Options can also be taken from a configuration file : by default it reads the config.yml file in the current directory but can be changed with the --config-file and --config-dir options. This file is in YAML format with all options at root level. Keys have the same name as command line options, with middle dashes - replaced with underscores _ and a s appended for lists (options --ibmcloud-url https://api... will become ibmcloud_url: https://api... and --keywords-file 1.json --keywords-file 2.json will become :

keywords_files:
    - 1.json
    - 2.json

See also sample configurations in the tests/ directory.

Please first review YAML syntax if you don't know about YAML.

Using the Jabber/XMPP backend

By using --backend jabber you can make the bot chat with XMPP (a.k.a. Jabber) users.

Jabber-specific options

• --jabber-username and --jabber-password are the JabberID (e.g. myusername@myserver.im) and password of the bot's account used to send and read messages. If --jabber-username missing, --username will be used.
• --jabber-recipient is the JabberID of the person to send the message to. If missing, --recipient will be used.

Using the Signal backend

By using --backend signal you can make the bot chat with Signal users.

Prerequistes

You must first install and configure signal-cli.

Then you must register or link the computer when the bot will run ; e.g. :

signal-cli link --name MyComputer

Please see the man page for more details.

Signal-specific options

• --signal-username selects the account to use to send and read message : it is a phone number in international format (e.g. +33123456789). In config.yml, make sure to put quotes around it to prevent YAML thinking it's an integer (because of the 'plus' sign). If missing, --username will be used.
• --signal-recipient and --signal-group select the recipient (only one of them should be given). Make sure --signal-recipient is in international phone number format and --signal-group is a base 64 group ID (e.g. --signal-group "mABCDNVoEFGz0YeZM1234Q=="). If --signal-recipient is missing, --recipient will be used. Once registered with Signal, you can list the IDs of the groups you are in with signal-cli -U +336123456789 listGroups

Sample command line to run the bot with Signal :

transbot -b signal -U +33612345678 -g "mABCDNVoEFGz0YeZM1234Q==" --ibmcloud-url https://api.eu-de.language-translator.watson.cloud.ibm.com/instances/a234567f-4321-abcd-efgh-1234abcd7890 --ibmcloud-apikey "f5sAznhrKQyvBFFaZbtF60m5tzLbqWhyALQawBg5TjRI"

Development

Install Python dependencies with :

pip3 install -r requirements-build.txt -r requirements-runtime.txt

To run unit tests :

python3 -m unittest discover -v -s tests

To run directly from source (without packaging, e.g. for development) :

python3 -m nicobot.askbot

To build locally (more at pypi.org) :

python3 setup.py sdist bdist_wheel

To upload to test.pypi.org :

# Defines username and password (or '__token__' and API key) ; alternatively CLI `-u` and `-p` options or user input may be used (or even certificates, see `python3 -m twine upload --help`)
TWINE_USERNAME=__token__
TWINE_PASSWORD=`pass pypi/test.pypi.org/api_token | head -1`
python3 -m twine upload --repository testpypi dist/*

To upload to PROD pypi.org :

Otherwise, it is automatically tested, built and uploaded to pypi.org using Travis CI on each push to GitHub.

Docker build

There are several Dockerfile, each made for specific use cases (see Docker-usage above) :

Dockerfile-debian and Dockerfile-debian-slim are quite straight and very similar.

Dockerfile-alpine is a multi-stage build because most of the Python dependencies need to be compiled first. The first stage builds the libraries and the second stage just imports them without all the build tools. The result is a far smaller image.

There is no special requirement to build those images ; sample build & run commands :

docker build -t nicobot:alpine -f Dockerfile-alpine .
docker run --rm -it -v "$(pwd)/tests:/etc/nicobot" nicobot:debian-slim askbot -c /etc/nicobot/askbot-sample-conf/config.yml

The multiarch compatibility is simply supported by the base images (no need to run docker buildx).

The images have all the bots inside, as they only differ from each other by one script. The entrypoint.sh script takes as arguments : first the name of the bot to invoke, then the bot's arguments.

Versioning

The command-line option to display the scripts' version relies on setuptools_scm, which extracts it from the underlying git metadata. This is convenient because one does not have to manually update the version (or forget to do it prior a release).

There are several options from which the following one has been retained :

• Running setup.py creates / updates the version inside the version.py file
• The scripts simply load this module at runtime

This requires setup.py to be run before the version can be extracted but :

• it does not require setuptools nor git at runtime
• it frees us from having the .git directory around at runtime ; this is especially useful to make the docker images smaller

Resources

IBM Cloud

• Language Translator service
• Language Translator API documentation

Signal

• Signal home
• signal-cli man page

Jabber

• Official XMPP libraries : https://xmpp.org/software/libraries.html
• OMEMO compatible clients : https://omemo.top/
• OMEMO official Python library : looks very immature
• Gaijim, a Windows/MacOS/Linux XMPP client with OMEMO support : gajim.org | dev.gajim.org/gajim
• Conversations, an Android XMPP client with OMEMO support and paid hosting : https://conversations.im

Python libraries :

• xmpppy : this library is very easy to use but it does allow easy access to thread or timestamp, and no OMEMO...
• github.com/horazont/aioxmpp : officially referenced library from xmpp.org, seems the most complete but misses practical introduction and does not provide OMEMO OOTB.
• slixmpp : seems like a cool library too and pretends to require minimal dependencies ; plus it supports OMEMO so it's the winner. API doc.