/sentiment_MS_app

An microservices app using RESTful API to predict the sentiment of a social media comment.

Primary LanguagePythonApache License 2.0Apache-2.0

sentiment_MS_app

An microservices app using RESTful API to predict the sentiment of a social media comment.

How to run the code

Execute the docker-compose.yaml file using command

If you are on mac silicon: DOCKER_DEFAULT_PLATFORM=linux/amd64 docker compose up If you are on linux: docker compose up

Once the docker file is up and running, you can utilize it as feddit api. The Feddit API is running at http://localhost:8080/docs.

To Run the flask server, go to terminal or command prompt in the root folder and run python app.py

The server is running at: http://127.0.0.1:5000/polarity/admin_1

User can utilize the api for 3 subfeddit categories i.e Admin_1, Admin_2,Admin_3

Querry parameters

The comment sentiment API has 3 querry parameters:

  1. sort: To sort comments based on polarity. User sort=Desc for desc order, sort=any value for asc value and 'sort=' for the original order.
  2. limit: parameter to limit the no of comments.
  3. date_range: parameter to filter the comments between the given date range. Format is YYYYMMDD.

An example url with all parameters: http://127.0.0.1:5000/polarity/admin_1?sort=&limit=100&date_range=20240101,20240401

Output

Output is a JSON object with the format:

{ "UID_comment": 1, "date": "20240604", "polarity_score": 1.0, "sentiment_class": "Positive", "text_comment": "It looks great!" }