This project has moved to clara-pip.
Conversational UI? Digital companion? The clara system can act as a stand alone chitchat framework or can easily be used to augment an existing chatbot by handling general small talk or non-command based queries. Clara uses JSON conversation files containing possible inputs and corresponding responses to match the best response to the user's query using the Levenshtein distance so even if they make a typo or type a query not included, it will still deliver a proper response. The system also has a dynamic emotional state which can affect the responses the system gives if made use of.
This is an early version, and has only recently graduated from being a fun experiment. However, it has worked very well in my systems and tests, and could prove to be immensenly useful to chatbot developers or those trying to build their own artificial companion.
- Run
pip install clara
- Create a script containing the below code.
from clara import brain
brain.run()
- In the same directory, run
clara setup
.
- Run
git clone https://github.com/huberf/clara-bot
- Now
cd
into theclara-bot
directory. - Try running
python3 brain.py
. If you get requirement errors,pip3
them into your instance. - If the command didn't return an error, try typing
Hello!
into the input box that should be present on the command line. - All messages and accompanying responses are located in the
convos/
directory. You can easily add conversation scripts others made by simply copying them into this directory. On startup, the program will load all data from any JSON file in that directory. - Feel free to add new responses or entire new conversation sets.
Clara has a Flask webserver setup in the web.py
file, and can be immediately
deployed to Heroku.
- Enter the clara-bot directory.
- Run
heroku create
- Type
git push heroku master
- Profit!
You can also setup the server locally by running python3 web.py
.
Currently, I've built a fully functional React Native clara client that has only been tested on iOS. It can connect to any Clara instance, and currently doesn't save your messages. On launch, one simply enters the URL of any Clara instance, and it will properly work with it. Link to checkout the Clara Mobile client
All json files from the convos/
directory are automatically loaded at startup.
Therefore, you break your convo files into an infinite number of individual
convo files. All such files contain an array of objects with the following keys:
starters
- This is an array of possible things a user could say to initiate the responses mentioned directly below this.replies
- This is an array of possible replies which are selected at random based upon theweight
key for each reply value. Replies can also be reserved for only certain states such as a happiness level greater than 0. To use this functionality one need only include thequalifiers
key which is an array of objects with the keysname
and then either{"$lt": 0}
,{"$gt": 0}
, or{"$eq": 0}
except with 0 being whatever value you wish the response to activate at against the less than, greater than, or equal to operators. Here is an example JSON response file:
[
{
"starters": ["this is a test", "i am testing you"],
"replies": [
{"text": "Hello very happy world!", "weight": 1, "modifiers":
[
{"name": "happy_level", "$gt": 2}
]
},
{"text": "Hello world!", "weight": 1, "modifiers":
[
{"name": "happy_level", "$eq": 2},
{"name": "happy_level", "$lt": 2}
]
}
]
}
]
A new simplified format in development is signified with the .convo
suffix. It
uses newlines combined with a letter, colon and space to divide up the data.
Ex:
Q: Who are you?; What are you?; Tell me what you are.
R: I am an artificial intelligence bot.
Q: I enjoy programming.
R: Wow! I do too!; Programming is the best thing in the world.
It is much easier to add to than the JSON, but with a much more limited feature set and doesn't include the ability to add conditional responses requiring certain moods or modifying data inside the "brain". Therefore, this convo format is meant for quickly adding new conversation info that isn't expected to be commonly used. It is also planned to be used in future machine learning response generation, where Clara could consume and process the data from such a file and then generate brand new responses with what the system learned. Therefore, in the future, the interpreter will support including chunks of conversation that has a flow. For example:
X:
Q: Hello?
R: Hi! What are you up to?
Q: I am working on a coding project.
R: That is very neat. What language are you using?
Q: I am using JavaScript.
R: Very neat!
Q: I have to go now. Bye!
\X:
As this is still in development, the format will continue to update and morph, and the JSON is still planned to be the main format for scripted responses.
A privately hosted Clara instance can be talked to and its convo log can be expanded by chatting via FB Messenger at m.me/clarachatbot.
Feel free to open an issue if you have an idea or feature request. To contribute code or additional convos simply open a pull request.