Rasa X: Custom Pipline Element

[Deprecated] Rasa X Community Edition
1

Hi Rasa X Team,

I am using:

Rasa OSS: 1.10.0
Rasa X: 0.28.x
Deployment: Docker-Compose Manual

First of all: everything works as described and expected besides the following question. I am able to train, modify, connect to a remote Repository and all that stuff.

I am currently facing the issue that I want to use one single custom pipeline element in my config.yml that is not shipped with the default rasa image, e.g. like:

 - name: DIETClassifier
   random_seed: 42
   intent_classification: True
   entity_recognition: True
   use_masked_language_model: False
   epochs: 300
 - name: EntitySynonymMapper
 - name: "my_custom_component.CustomExtractorOfChoice"

Can someone describe the most convenient way to add this element to the image and make sure, that the folder lies in the PYTHONPATH environment variable?

Kind regards
Julian

2

I’m not in the Rasa X Team but I went through the same process as you are now ;). The Rasa blog on custom components describes the steps to take to add a component:

  • add it to the config.yml
  • add the component directory the PYTHONPATH

You need to convert those steps into a Dockerfile to build a custom container:

# Extend the official Rasa SDK image (change the version to whatever you need)
FROM rasa/rasa:1.8.2-full

# Switch to root user
USER root

# Add a folder to python path
ENV PYTHONPATH "${PYTHONPATH}:/app/my_custom_component"

# Do other stuff, e.g.: add python dependencies, etc.

# Switch back to a non-root user
USER 1001

Then:

  • Build the container: docker build . -t foobar:version
  • Copy the custom components to the rasa-x installation directory cp -r /code/dir/my_custom_component/* /etc/rasa/my_custom_component
  • Add a docker-compose.override.yml file to /etc/rasa and include the custom container (Note that the specific setup of the container depends on what you are trying to extend):

EDIT (fixed the docker-compose example):

services:
  rasa-worker:
    volumes:
      - ./directory/my_custom_component.py:/app/my_custom_component.py

docker-compose rasa-x, and you’re done!

3 Likes
4

Hey @flythe,

thanks - I will give that a try. As far as I have seen, it’s the Rasa image itsself that has to be extended, isnt it?

Kind regards
Julian

5

Hi everyone,

if you stumble upon this Issue, @flythe 's answer does the job. In specific, you need to modify:

  rasa-worker:
    <<: *default-rasa-service
    volumes:
       - ./custom_component:/app/custom_component
    environment:
      <<: *rasa-credentials
      PYTHONPATH: "${PYTHONPATH}:/app/custom_component"
      RASA_ENVIRONMENT: "worker"
      DB_DATABASE: "worker_tracker"
      RASA_MODEL_SERVER: "http://rasa-x:5002/api/projects/default/models/tags/production"

Make sure that the component of choice lies inside the mounted volume folder.

Kind regards
Julian

6

You are right I copied the wrong override example. This is the correct setup:

services:
  rasa-worker:
    volumes:
      - ./directory/my_custom_component.py:/app/my_custom_component.py

Preferably you don’t edit the docker-compose.yml file directly because it will get overwritten when it is changed in a rasa-x update. Just place a docker-compose.override.yml file in the same root directory and docker will sort out the overriden settings.

1 Like
7

Very Informative guys, good job.

8

This solution does not fit in the way rasa x uses version control. When you now change this custom component you need to make sure to also place it in the rasa x server… There needs to be a way of marking files that rasa x needs to place in worker containers.

But for now I think this is the best we’ve got…

9

Hey guys @flythe @JulianGerhard,
might you be able to take a look at the way I am trying to extend the image? Something is going wrong, as training and uploading models fails without an error log. \

This is my docker file:

# Extend the official Rasa SDK image
FROM rasa/rasa:latest-full

USER root

# Use subdirectory as working directory
WORKDIR /app


# add as environment variable
ENV PYTHONPATH=$PYTHONPATH:/app

# Copy any additional custom requirements, if necessary (uncomment next line)
COPY requirements.txt ./

# Install extra requirements for worker, if necessary (uncomment next line)
RUN pip install -r requirements.txt
RUN python -m nltk.downloader vader_lexicon
# Copy sentiment analyzer to working directory
COPY sentiment_analyzer.py /app

#
CMD ["start","--actions","actions"]

# By best practices, don't run the code with root user
USER 1001

This is my docker-compose.override.yml:

version: '3.4'
services:
  app:
    image: janfeldmann/customactionserver:e1.3
  rasa-production:
    image: janfeldmann/rasa_se:0.5
  rasa-worker:
    image: janfeldmann/rasa_se:0.5

Is there something I am doing wrong?

10

Hi @Taufred, you should probably check your docker-compose output. Are the containers actually running? In my solution I only need to create a custom image for the app service so it seems less complex than your application.

11

Hey @flythe thanks for the response. I already solved my problem, it had something to do with the cache location of the sentiment analyzer and the folder in which the vader lexicon was being stored.

12

@Taufred do you mind explaining how you fixed this? I am stuck on it currently, so any help would be nice! :slight_smile:

13

@fabrice-toussaint I did two things: added the line chache_dir: /tmp to the BERT transformer in the config file and this line RUN python -m nltk.downloader -d /usr/local/share/nltk_data vader_lexicon to the dockerfile.

14

Thanks! I got it working now :slight_smile:

15

Hey, I was following this to setup my customcomponent, but unfortunately am stuck with this. I am using an helm chart to deploy…

This is my custom component image

And this is my dockerfile used to extend the image, can you point me to what I am doing wrong? I am not get any error message in the pods but not getting any response either

FROM rasa/rasa:2.1.3-full

#USER root
#
#COPY ./customComp /customComp/
#ENV PYTHONPATH=$PYTHONPATH:/customComp/
#
#
#RUN pip install --trusted-host pypi.python.org fuzzywuzzy==0.18.0 rapidfuzz==0.13.4
#
## Switch back to non-root to run code
#USER 1001

#ENTRYPOINT rasa run

USER root

# Use subdirectory as working directory
WORKDIR /app


# add as environment variable
ENV PYTHONPATH=$PYTHONPATH:/app

# Install extra requirements for worker, if necessary (uncomment next line)
RUN pip install --trusted-host pypi.python.org fuzzywuzzy==0.18.0 rapidfuzz==0.13.4

# Copy sentiment analyzer to working directory
COPY ./customComp/DateParser.py /app

#
#CMD ["start","--actions","actions"]

# By best practices, don't run the code with root user
USER 1001