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Serverless function for sentiment analysis of GitHub issues that adds positive/negative labels

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github-issue-bot

This is a Serverless function that tracks new GitHib issues, processes them with sentiment analysis and applies positive and review labels.

Deploy Sentiment Analysis function

In order to use this issue-bot function, you will need to deploy the Sentiment Analysis function first. This is a python function that provides a rating on sentiment positive/negative (polarity -1.0-1.0) and subjectivity provided to each of the sentences sent in via the TextBlob project.

You can checkout the function from faas/sample-functions.

Update image with your Docker ID

You need to update image value in filter.yml and replace docwareiy with your Docker ID. You can check your images in Docker Hub.

Create Github Auth token

Go to your GitHub profile -> Settings/Developer settings/Personal access tokens and generate new token.

Copy the contents of env.example.yml to env.yml and update auth_token value with the new generated token.

Update repo in env.yml with the repository you'd like to use the function for.

Create GitHub repo Webhook

Go to your github repo -> Settings/Webhooks and create a new Webhook.

Update Payload URL to be your OpenFaaS host and the function extension, e.g. http://localhost:8080/function/issue-bot.

Choose application/json for a Content Type.

Select Let me select individual events and then Issues and Issue comment.

Select Active and press Update webhook.

Build and Deploy:

Use the CLI to build and deploy the function:

faas build -f issue.yml & faas push -f issue-bot.yml & faas deploy -f issue-bot.yml

View the logs by executing docker service logs -f issue-bot on the Docker instance.

You can now test the function by creating new issues in your repo.

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Serverless function for sentiment analysis of GitHub issues that adds positive/negative labels

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