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This app is built using Python 3.9+, Flask 2.0+, and Pinecone. It performs a similarity search using the Pinecone SDK to find articles that are similar to ones you've read in the past.

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thawkin3/article-recommendation-service

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Article Recommendation Service

This app is built using Python 3.9+, Flask 2.0+, and Pinecone. It performs a similarity search using the Pinecone SDK to find articles that are similar to ones you've read in the past.

Demo

Running the app locally

Begin by cloning this git repo and navigating to the project directory.

Next, create a virtual environment and activate it:

python -m venv venv
. venv/bin/activate

Install dependencies by running:

python -m pip install -r requirements.txt

Create an .env file and add your Pinecone API key:

PINECONE_API_KEY=your-key-here

Finally, to run the app on your machine, simply run this command from the terminal:

flask run

Or, to run the app in debug mode, add the FLASK_ENV=development environment variable before the command:

FLASK_ENV=development flask run

The app should now be running on http://127.0.0.1:5000 in your browser.

Resources

Python, pyenv, and pip

Flask

Pinecone

Dataset

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This app is built using Python 3.9+, Flask 2.0+, and Pinecone. It performs a similarity search using the Pinecone SDK to find articles that are similar to ones you've read in the past.

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