Chatbots, AI and Docker!


I have started my learning journey about AI. With that I started reading Artificial Intelligence & Generative AI for Beginners. One of the use cases it went through for NLP (Natural Language Processing) was Chatbots.

To the internet I went – ready to go down a rabbit hole and came across a Python library called ChatterBox. I knew I did not want to bloat and taint my local environment so I started using a Docker instance in Podman.

Down the Rabbit Hole

I quickly realized the project has not been actively maintained in a number of years and had some specific and dated dependencies. For example, it seemed to do best with python 3.6 whereas the latest at the time if this writing is 3.12.

This is where Docker shines though. It is really easy to find older images and declare which versions you want. The syntax of Dockerfile is such that you can specify the image and layer the commands you want to run on it. It will work every time, no matter where it is deployed from there.

I eventually found a somewhat updated fork of it here which simplified things but it still had its nuances. chatterbox-corpus (the training data) required PyYaml 3.13 but to get this to work it needed 5.


FROM python:3.6-slim

WORKDIR /usr/src/app

#COPY requirements.txt ./
#RUN pip install --no-cache-dir -r requirements.txt
RUN pip install spacy==2.2.4
RUN pip install pytz pyyaml chatterbot_corpus
RUN python -m spacy download en

RUN pip install --no-cache-dir chatterbot==1.0.8

COPY ./ .

CMD [ "python", "./" ]

Here we can see, I needed a specific version of Python(3.6) whereas at the time of writing the latest is 3.12. It also required a specific spacy package version. With this I have a repeatable environment that I can reproduce and share (to peers or even to production!)


Just for grins, when I was able to use the updated fork it did not take much!

FROM python:3.12-slim

WORKDIR /usr/src/app

#COPY requirements.txt ./
#RUN pip install --no-cache-dir -r requirements.txt
RUN pip install spacy==3.7.4 --only-binary=:all:
RUN python -m spacy download en_core_web_sm

RUN apt-get update && apt-get install -y git
RUN pip install git+

RUN pip install chatterbot-corpus

RUN pip uninstall -y PyYaml
RUN pip install --upgrade PyYaml

COPY ./ .

CMD [ "python", "./" ]

Without Docker

Without Docker(podman) I would have tainted my local environment with many different dependencies. At the point of getting it all working, I couldn’t be sure it would work properly on another machine. Even if it did, was their environment tainted as well? With Docker, I knew I could easily repeat the process from a fresh image to validate.

Previous projects I worked on that were python related could have also tainted my local to cause unexpected results on other machines or excessive hours troubleshooting something unique to my machine. All of that avoided with a container image!

Declarative Version Management

When it becomes time to update to the next version of Python, it will be a really easy feat. Many tools will even parse these types of files and do dependency management like Dependabot or Snyk

Author: David Chapman

I started my IT career in the very late 1990's as a systems administrator for a benefits company. I have always enjoyed learning new technologies and helping people fix problems which has lead me through a few different positions over the past 20+ years.

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