zedd27/tagpredict repository overview

⁠Overview

TagPredict is an AI based application for predicting domain tags for research papers based on their title and description. This Docker image provides an easy way to deploy and run the TagPredict application in a containerized environment.

⁠Usage

⁠Step 1: Pull the Docker Image

Pull the TagPredict Docker image from Docker Hub using the following command:

docker pull zedd27/tagpredict:v1.0

⁠Step 2: Run the Docker Container

Run the TagPredict Docker container using the following command:

docker run -p 5000:5000 zedd27/tagpredict:v1.0

This command starts the TagPredict application inside a Docker container, and maps port 5000 on the host to port 5000 in the container.

⁠Step 3: Send Prediction Requests

You can send prediction requests to the TagPredict application using cURL or any HTTP client.

curl --location 'http://localhost:5000/predict' \
--header 'Content-Type: application/json' \
--data '{
    "title": "Title of Research Paper",
    "description": "Description of Research Paper"
}'

This cURL command sends a POST request to the /predict endpoint of the TagPredict application running on port 5000. It includes a JSON payload with the title and description of the research paper for prediction.

⁠Parameters

• title: The title of the research paper.
• description: The description or abstract of the research paper.

⁠Response

The TagPredict application returns a JSON response containing the predicted tags for the provided research paper.

⁠Example

Here's an example cURL command to send a prediction request:

curl --location 'http://localhost:5000/predict' \
--header 'Content-Type: application/json' \
--data '{
    "title": "Machine Learning in Healthcare",
    "description": "This paper discusses the applications of machine learning in the healthcare industry."
}'

Response:

{
    "predicted_tags": [
        "cs"
    ],
    "title": "Machine Learning in Healthcare"
}

This command predicts the domain tags for a research paper with the title "Machine Learning in Healthcare" and the provided description.

⁠Support

For any issues or questions regarding the TagPredict Docker image, please contact me here⁠.