rasa train --domain domain-grp/

rasa shell

rasa run -m models --enable-api --cors "*" 

If it gives error port 5005 already in use check with

1. docker ps

   if your conatiner is running if yes stop it and if no container is running and it is still saying the same.

2. rasa run -m models --enable-api --cors "*" -p [ port-number ]

   and also make sure that this port number is also present in IDP.html in socketUrl : [ ip-address ]: [ port-number ]

you can replace sahib-bot-idp with your bot name

docker build -t sahib-bot-idp . 

docker run -it  -p 5005:5005 sahib-bot-idp:latest

If it gives an error port 5005 already in use

1. docker run -it -p [ port-number]:5005 sahib-bot-idp:latest

This will map your localhost [ port-number ] to 5005 and that 5005 port is used by docker container But make sure that this port number is also present in IDP.html in socketUrl : [ localhost ]: [ port-number ]

docker run  -it --workdir /app sahib-bot-idp bash ./scripts/start_shell.sh

docker stop <container-id>

docker image rm -f sahib-bot-idp:latest

To connect rasa x to Github via UI RASA X expects files to be of same structure as we get after

rasa init

Prerequisites for making build-domain.py file

pip3 install HiYaPyCo

Means it does not support multiple domain files But What we have done is we have written a script build-domain.py and gave it path of all domain files so what it does is it takes all domain files combines them to make domain.yml so that we can connect RASA X to github via UI.

Now whenever we make multiple domain files before every re training run

python3 build-domain.py

rasa train

rasa train --domain domain-grp/

Use step 1,2,3,4 from below link

https://rasa.com/docs/rasa-x/installation-and-setup/install/docker-compose/

1. After connecting rasa x to github ( considering we have made file structure same as rasa init) because then only rasa x connects to github.

2. cd /etc/rasa/

3. sudo docker-compose down

4. Make changes to credentials.yml

5. sudo docker-compose up -d

6. Open the [ Ip-address ] your RASA x is working

1. Made an Folder in server

2. Installed rasa (rasa 2.6.0)

   pip3 install -U pip
   pip3 install rasa
   

3. git pull from repo to get the latest code

4. rasa train

5. Open html file where you embedded the script from here ( any html file that can be present locally can be used just make sure 1. In socketUrl : [ ip-address]:5005 of server )

6. Make sure the port you are mentioning is open ( from Server UI you can do this ) ( In our case we had to manually to open port 5005 from Azure server because rasa by default runs on port 5005 )

7. rasa run -m models --enable-api --cors "*" or

8. docker build -t sahib-bot-idp .

8.a docker run -it -p 5005:5005 sahib-bot-idp:latest

1. lsof -i:5005 ( to see which service is running on port 5005 and what is the PID)

2.  kill $(lsof -t -i:5005)
   
    or
   
    kill -9 $(lsof -t -i:5005)
   

1. cd /etc/rasa/

2. sudo docker-compose down

sudo apt-get update
sudo apt-get install software-properties-common
sudo add-apt-repository universe
sudo add-apt-repository ppa:certbot/certbot
sudo apt-get update
sudo apt-get install certbot

1. sudo certbot certonly -d [ domain name ].

   1.a Example --->

   sudo certbot certonly -d chatbot.idp.tatrasdata.com

2. cd /etc/letsencrypt/archive/<domain name>/

Copy the certificates files :- Example ( copying certificates from /etc to inside our chatbot)

3. cp /etc/letsencrypt/archive/chatbot.idp.tatrasdata.com/ /home/idp-chat/idp_chatbot/certs

4. Give Permissions to files ( Go to path where they are copied in chatbot)

   chmod +rwx cert1.pem fullchain1.pem privkey1.pem chain1.pem

5. Give access of running command to User

Example --->

sudo chown -R chatbotadmin . ( It means give running access to username =chatbotadmin)

Make changes to HTML we will run in Browser set it's socketurl with DOMAIN NAME you BOUGHT

socketUrl: "https://chatbot.idp.tatrasdata.com:5005",

6. Command to Run Chatbot having SSL

rasa run --ssl-certificate ./certs/chatbot.idp.tatrasdata.com/cert1.pem --ssl-keyfile ./certs/chatbot.idp.tatrasdata.com/privkey1.pem -m models --enable-api --cors "*"

1. sudo docker system prune --volumes -a

or

2. sudo docker system prune

1. Have to solve the issue of chatbot giving False Positives ( Menas correct answer for wrong answer)

2. Permission error ( How to save model after training from docker image itself --if possible )

1. cd /etc/rasa
2. sudo docker-compose down
3. sudo docker-compose up

If you see this https://forum.rasa.com/t/the-answers-of-bot-dont-appear-on-rasa-x/41000/8

1. sudo docker system prune --all
2. sudo docker system prune -a --volumes
3. sudo docker volume prune -f
4. sudo docker image prune -a

fo any help related to above commands

1. https://docs.docker.com/engine/reference/commandline/system_prune/
2. https://docs.docker.com/config/pruning/

CLear RAM

1. ``` sync; echo 3 | sudo tee /proc/sys/vm/drop_caches ```

2. sync; echo 2 | sudo tee /proc/sys/vm/drop_caches 

Now sudo docker-compose down

and then again sudo docker-compose up -d

1. You have added all response selectors
2. Made changes for those repsonse selectors in rules and config file
3. WHen we press rasa train make sure all retrieval intents are present

TO check which files are consuming how much space 
https://www.hostinger.in/tutorials/vps/how-to-check-and-manage-disk-space-via-terminal

Then you will have to give More space to you VM