comment-recommendation-framework 0.16.0

Framework to develop comment recommendation systems

Comment Recommendation Framework

The Comment Recommendation Framework is a modular approach to support scientists in the development of prototypes for comment recommendation systems that can be used in real-world scenarios. The advantage of such a system is that it relieves the scientist from the majority of the technical code and only prototype-specific components have to be developed. In this way, the researchers can invest more time in the development of recommendation models and less time has to be spent in the development of a prototype while at the same time getting prototypes that can be used in real-world settings.

Setup

Ensure that the following tools are installed:

• Docker
• Docker-Compose
• Pyhon >= 3.10

Documentation

Find the latest documentation here

Environment Variables

The framework need some environment variables to be set for running properly. Please ensure that you have an .env file with the following variables:

• NEO4J_PASSWORD
• NEO4J_BOLT_URL (Format: bolt://neo4j:<NEO4J_PASSWORD>@neo4j:7687)

Run the Comment Recommendation Framework

Install the package locally

To install the package locally, you have to build it first. For this, run in the folder with setup.py:

python3 -m build

This creates a dist folder at your current location with two files Comment-Recommendation-Framework-X.X.X.tar.gz and Comment_Recommendation_Framework-X.X.X-py3-none-any.whl. The tar.gz file is the source distribution and the .whl is the built distribution.

We recommend to create a virtual environment to isolate your project from the rest of your system to prevent import and version problems.

Then you run inside your virtual environment:

pip install <path_to_the_whl_file>

Create your project

To create the system template you run the following command in your virtual env after you have installed the package:

python3 -m comment_recommendation_framework

Then the package asks you different questions to determine which modules you need for your project. You can answer them with y for yes and n for no.

Run different moduls with docker-compose

We provide you with the following docker-compose files to run the different components of the recommendation framework.

• docker-compose.scraping.yml: Runs the news agency scraper to retrieve articles and comments from various news agencies.
• docker-compose.embed.yml: Starts the embedding process to compute the embeddings for the comments and articles. Should be run directly after docker-compose.scraping.yml.
• docker-compose.csv.yml: Imports comments and articles from a csv file into the database.
• docker-compose.test.yml: Runs the tests for the system.
• docker-compose.api.yml: Runs the comment-recommendation systems.

Maintainers:

• Anonymous

Contributors:

• Anonymous

License:

Copyright(c) 2022 - today Anonymous

Distributed under the MIT License