- Rasa need specific python version, hence create a enviorment using the following command
conda create -n rasa-env python=3.8
- now actiavte the enviorment
conda activate rasa-env
- now install rasa
pip install rasa
- other requirements have been listed in requirements.txt. run
pip install -r requirements.txt
- a new project can be initiallized using the command
rasa init
,rasa train
to train the rasa bot,rasa train nlu
to only train nlu,rasa run actions
to start the actions server with is esential for database contectivity,rasa run
to run the bot andrasa shell
to open the interactive chatbot.rasa test
to test the bost in different case senerios.
NOTE: we have already added the trained model in the repo so to run the bot only enviornment set up is needed then user can do rasa run actions
followed by rasa shell
rasa run actions
rasa run --enable-api --cors "*"
: This command runs the Rasa server with API enabled and CORS (Cross-Origin Resource Sharing) allowed from all origins, which is necessary for Streamlit to communicate with Rasa.streamlit run app.py
: Run Streamlit app (Open the URL displayed in terminal to view the Streamlit application)
NOTE: we tried deploying the streamlit bot usingb streamlit sharing, however it was always giving some kind of error. you can check the deployement here https://university-chatbot.streamlit.app/ but it doesnt work. So we advise that the UI be run using the 3 commmand mentioned above.