Solution - Create Bad Word Filter Service¶

As a bookstore owner, you aim to receive instant notifications in a Slack channel whenever a customer submits a new negative review comment. By leveraging Knative Function, you can set up a serverless function that contains a simple bad word filter service to tell whether the text contains any hateful/insultive speech.

What Knative features will we learn about?¶

The easiness to use Knative Function to deploy your service, and make it be managed by Knative Serving, which give you the ability to auto-scale your service to zero, and scale up to handle the demand.

What does the final deliverable look like?¶

A running serverless Knative Function that contains a python application that receives the new review comments as CloudEvent and returns the result that tells your input text contains any inappropriate languages or not. The result is sent back as CloudEvent.

Info

We are using the profanity_check library to detect the bad words in the text. It is a open source library. Please see the disclaimer here. The result may not be 100% accurate.

The function's output will be only from:

good
bad

Implementation¶

The process is straightforward:

Begin by utilizing the func create command to generate your code template.
Next, incorporate your unique code into this template.
Finally, execute func deploy to deploy your application seamlessly to the Kubernetes cluster.

This workflow ensures a smooth transition from development to deployment within the Knative Functions ecosystem.

Troubleshooting

If you see command not found, you may need to add the func CLI to your PATH.)

Step 1: Create a Knative Function template¶

Create a new function using the func CLI:

func create -l <language> <function-name>

In this case, we are creating a python function, so the command will be:

func create -l python bad-word-filter

This command will create a new directory with the name bad-word-filter and a bunch of files in it. The func CLI will generate a basic function template for you to start with.

You can find all the supported language templates here.

Verify

The file tree will look like this:

/start/bad-word-filter
├── func.yaml
├── .funcignore
├── .gitignore
├── requirements.txt
├── app.sh
├── test_func.py
├── README.md
├── Procfile
└── func.py

Step 2: Replace the generated code with the bad word filter logic¶

bad-word-filter/func.py is the file that contains the code for the function. You can replace the generated code with the bad word filter logic. You can use the following code as a starting point:

bad-word-filter/func.py

from parliament import Context
from profanity_check import predict
from cloudevents.http import CloudEvent

# The function to convert the bad word filter result into a CloudEvent
def create_cloud_event(inputText, data):
    attributes = {
        "type": "new-review-comment",
        "source": "book-review-broker",
        "datacontenttype": "application/json",
        "badwordfilter": data,
    }

    # Put the bad word filter result into a dictionary
    data = {"reviewText": inputText, "badWordResult": data}

    # Create a CloudEvent object
    event = CloudEvent(attributes, data)
    return event

def inappropriate_language_filter(text):
    profanity_result = predict([text["reviewText"]])
    result = "good"
    if profanity_result[0] == 1:
        result = "bad"

    profanity_event = create_cloud_event(text["reviewText"], result)
    return profanity_event

def main(context: Context):
    """
    Function template
    The context parameter contains the Flask request object and any
    CloudEvent received with the request.
    """
    print("Received CloudEvent: ", context.cloud_event)

    # Add your business logic here
    return inappropriate_language_filter(context.cloud_event.data)

Step 3: Configure the dependencies¶

The bad-word-filter/requirements.txt file contains the dependencies for the function. You can add the following dependencies to the requirements.txt file:

bad-word-filter/requirements.txt

parliament-functions==0.1.0
alt-profanity-check==1.4.1.post1
cloudevents==1.10.1

Knative Function will automatically install the dependencies listed here when you build the function.

Step 4: Deploy the function to the cluster¶

Note

Please enter /bad-word-filter when you are executing the following commands.

After you have finished the code, you can deploy the function to the cluster using the following command:

func deploy -b=s2i -v

Verify

When the deployment is complete, you will see the following output:

Function deployed in namespace "default" and exposed at URL:
http://bad-word-filter.default.svc.cluster.local

Verify¶

After deployment, the func CLI provides a URL to access your function. You can verify the function's operation by sending a request with a sample review comment.

Simply use Knative Function's command func invoke to directly send a CloudEvent to the function on your cluster:

func invoke -f=cloudevent --data='{"reviewText":"I love Knative so much"}' -v

-f flag indicates the type of the data, is either HTTP or cloudevent
--data flag is the input text
You can use -t flag to specify the URI to the Knative Function.

Verify

If the function is running successfully, you will see the following output:

Context Attributes,
specversion: 1.0
type: new-review-comment
source: book-review-broker
id: ebbcd761-3a78-4c44-92e3-de575d1f2d38
time: 2024-05-27T04:44:07.549303Z
datacontenttype: application/json
Extensions,
badwordfilter: good
Data,
{
    "reviewText": "I love Knative so much",
    "badWordResult": "good"
}

Next Step¶

In this tutorial, you learned how to create a serverless function for a simple service that can detect the inappropriate languages in text with Knative.

Next, we'll be learning how to use Knative Sequence to connect the 2 ML workflow and make sure they are executed in the order you want.

Go to Create Knative Sequence