This is a chatbot developed to provide information about the covid-19 cases

In ubuntu 18.04, these are steps to be followed to setup the project env

Step 1: Create a Virtual Environment

python3 -m venv myenv

Step 2: Activate the virtual env

source myenv/bin/activate

Step 3: Deactivate the conda env if it exits

conda deactivate

Step 4: Install the requirements

pip3 install -r requirements.txt

or 

pip3 install rasa==1.9.6

Since the release of Rasa 1.0, the training of the NLU models became a lot easier with the new CLI. Train the model by running:

rasa train nlu

Once the model is trained, test the model:

rasa shell nlu

The biggest change in how Rasa Core model works is that custom action 'actions' now needs to run on a separate server. That server has to be configured in a 'endpoints.yml' file. This is how to train and run the dialogue management model:

1. Start the custom action server by running:

rasa run actions

2. Open a new terminal and train the Rasa Core model by running:

rasa train

3. Talk to the chatbot once it's loaded after running:

rasa shell

To run your assistant in a interactive learning session, run:

1. Make sure the custom actions server is running:

rasa run actions

2. Start the interactive training session by running:

rasa interactive

Run the below steps in different terminals

Step 1: Run the Flask server for getting covid data

python app.py

Step 2: Run the Actions Server

rasa run actions

Step 3: Run the Shell to interact with bot

rasa shell

Step 1: Run the Actions Server

rasa run actions

Step 2: Run the rasa model

python -m rasa run --m ./models --endpoints endpoints.yml --port 5005 --cors "*" -vv --enable-api

Step 3: Run the Flask Server for backend data

python app.py

Step 4: Run the HTTP server for running website for chatbot

The chatbot UI is provided in index.html forked from another repo is also placed for individual learnings into chatbot frontend.

python -m http.server 8008

Here 8008 is port number, u can change if needed

The chatbot is ready at http://localhost:8008

Note: Still the bot needs lot of training data. We can integrate RASA-X for this purpose which is not yet added into this project.

• Create the basic project
• Make NLU training data
• Make the dialogue management model
• Make a flask server to extract the covid data from https://api.covid19india.org/
• Create the more stories
• Handle the spelling mistakes by the users
• Handle the date format given by the users.
• Create a frontend application
• Connect the frontend with the rasa-chatbot
• Deploy the flask server.
• Deploy the chatbot app.

1. RasaMasterClass Official Youtube videos.

2. Thanks to https://github.com/JiteshGaikwad/Chatbot-Widget for frontend-ui code.

    Along with references, detailed blogs will be posted soon ...