BennyBot

A chatbot built and trained using a feed forward neural net, implemented in PyTorch. Detects user intent based on input, and provides a response.

Click here to visit!

Try out the API!

GET https://chat-with-bennybot.herokuapp.com/chat

Accepts:

Content-Type: application/json

Request:

{
  "sentence": "hi how are you"
}

Response:

{
  "msg": "Hi there, nice to meet you!",
  "tag": "greeting"
}

Running the App

Clone or download the repo, then do either of the following:

Run python3 cli_chat.py to test the chatbot in the terminal.

Run flask run to start the web app and server. Open http://127.0.0.1:5000/ to see the app!

Training

Include a custom intents.json file in the following format:

{
  "intents": [
    {
     "tag": "bot",
      "patterns": [
        "Are you real",
        "Are you a bot",
        "Who are you?"
      ]
    },

    ...

  ]
}

Also include a responses.json file in the following format:

{
  "response_data": [
  {
      "tag": "bot",
      "responses": [
        "I am a bot created to let others get to know my creator better! Ask more questions, or visit the link to find out more :)"
      ],
      "link": "https://bennymai.me/"    // optional
    },

    ...

  ]
}

With Python 3.6+ installed, run the following commands in the root directory/envrionment:

pip3 install -r requirements.txt
python3 train.py

This model was trained using Python 3.9, PyTorch 1.7.1, and CUDA 11.0. If training is done on a supported GPU, Install the correct version of torch found here.

Or, find the download link for the correct .whl file from https://download.pytorch.org/whl/torch_stable.html

For example: cu110/torch-1.7.1%2Bcu110-cp39-cp39-linux_x86_64.whl is the correct file for Python 3.9, PyTorch 1.7.1, and CUDA 11.0, running on a Linux machine.

Development

Deployed on Heroku using a Flask backend.

UI developed using HTML/CSS/Bootstrap

Support for fetching responses from a MongoDB database is WIP.