This is a chatbot developed to provide information about the covid-19 cases
Checkout the Demo Video Link https://youtu.be/xJg1ObtUWWY
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:
- Start the custom action server by running:
rasa run actions
- Open a new terminal and train the Rasa Core model by running:
rasa train
- Talk to the chatbot once it's loaded after running:
rasa shell
To run your assistant in a interactive learning session, run:
- Make sure the custom actions server is running:
rasa run actions
- 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.
-
RasaMasterClass Official Youtube videos.
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Thanks to https://github.com/JiteshGaikwad/Chatbot-Widget for frontend-ui code.
Along with references, detailed blogs will be posted soon ...