OAPEN Suggestion Service

Description

The OAPEN Suggestion Service uses natural-language processing to suggest books based on their content similarities. To protect user privacy, we utilize text analysis rather than usage data to provide recommendations. This service is built on the proof-of-concept and paper by Ronald Snijder from the OAPEN Foundation, and you can read the paper here.

Table of Contents

• Installation (Server)
  • DigitalOcean Droplet
  • DigitalOcean Managed Database
  • Setup Users & Install Requirements
  • Clone & Configure the Project
  • SSL Certificate
• Running
• Endpoints
  • /api
  • /api/ngrams
  • /api/{handle}
  • /api/{handle}/ngrams
• Logging
• Service Components
  • Suggestion Engine
  • API
  • Embed Script
  • Web Demo
• Updates
• Local Installation (No Server)

Installation (Server)

DigitalOcean Droplet

1. Log in to your DigitalOcean account.
2. Create a new Droplet.
3. Under "Choose an image" select "Marketplace" and search for "Docker". Select "Docker 20.10.21 on Ubuntu 22.04".
4. Choose any size, but the cheapest option will work fine.
5. If you do not have an ssh key, generate one with:

   ssh-keygen -t rsa -b 4096
   

   And copy the public key to your clipboard. If you have a key on your computer already, you can use that.
6. Under "Choose Authentication Method" choose "SSH Key" and click "New SSH Key", and in the popup window paste the public key you copied to your clipboard. Make sure it is selected.
7. Give the Droplet a name and click "Create".
8. Open the firewall ports
   • https://cloud.digitalocean.com/networking/firewalls

DigitalOcean Managed Database

1. From the DigitalOcean dashboard, click "Databases" > "Create Database".
2. Ideally, select the same region & datacenter as the Droplet you just created, so they can be part of the same VPC network.
3. Choose "PostgreSQL v15".
4. Select any sizing plan, but the cheapest one will suffice.
5. Give the database a name, and click "Create Database Cluster".
6. Once the database is done creating (this can take a few minutes), find the "Connection details" section on the new database's page, you will need them later.

Setup Users & Install Requirements

1. Log in to the droplet over SSH:

   ssh root@<your-droplet-ip>
   

2. Create a new user oapen and set a password, adding them to the sudo and docker groups, then login as the new user:

   useradd -m -G sudo,docker oapen
   passwd oapen
   su -l -s /bin/bash oapen
   

3. Install the docker compose command:

   sudo apt-get update
   sudo apt-get install docker-compose-plugin
   

4. Change the SSH configuration file to disallow root login:

   sudo sed -i 's/PermitRootLogin yes/PermitRootLogin no/' /etc/ssh/sshd_config
   

5. Allow SSH login with non-root user with the same SSH keys you uploaded to DigitalOcean:

   mkdir -p ~/.ssh
   sudo cp /root/.ssh/authorized_keys ~/.ssh/
   sudo chown -R oapen:oapen ~/.ssh
   sudo chmod 700 ~/.ssh
   sudo chmod 600 ~/.ssh/authorized_keys
   sudo systemctl restart ssh
   

6. Create a swapfile to avoid issues with high memory usage:

   sudo fallocate -l 1G /swapfile
   sudo chmod 600 /swapfile
   sudo mkswap /swapfile
   sudo swapon /swapfile
   echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab
   

   Feel free to replace 1G in the first command with 4G. Although the service should never use this much memory, extra swap never hurts if you have the disk space to spare. More on swap here.

7. Restart the droplet to persist all of the changes. From now on, login to the droplet with:

   ssh oapen@<your-droplet-ip>
   

Clone & Configure the Project

1. Clone the repository and cd into the directory it creates:

   git clone https://github.com/EbookFoundation/oapen-suggestion-service.git
   cd oapen-suggestion-service
   

   You can clone this anywhere but in the home directory is easiest.

2. Copy the .env.template file to .env:

   cp .env.template .env
   

3. Using a text editor like vim or nano configure all of the options in .env:

   API_PORT=<Port to serve API on>
   POSTGRES_HOST=<Hostname of postgres server>
   POSTGRES_PORT=<Port postgres is running on>
   POSTGRES_DB_NAME=<Name of the postgres database>
   POSTGRES_USERNAME=<Username of the postgres user>
   POSTGRES_PASSWORD=<Password of the postgres user>
   POSTGRES_SSLMODE=<'require' when using a managed database>
   

   Postgres credentials can be found in the "Connection details" section of the managed database

SSL Certificate

TODO: add documentation

Running

You can start the services by running the following command in the directory where you cloned the repo:

docker compose up -d

The API will be running on https://<your-ip>:<API_PORT>.

NOTE: The -d flag runs the services in the background, so you can safely exit the session and the services will continue to run. The --build flag ensures any changes to the code are reflected in the containers.

You can stop the services with:

docker compose down

You can view the logs with:

docker compose logs -f

You can dump them with docker compose logs > some_file.txt

To view the logs for just a specific service component - for example the mining enginge - use:

docker logs -f oapen-suggestion-service-oapen-engine-1

NOTE: oapen-suggestion-service-oapen-engine-1 is the name of the docker container running the service component.

If you make local changes to the source code, you should re-build the images before running with:

docker compose build

or by adding the --build flag when running:

docker compose up -d --build

Endpoints

The API provides access to the following endpoints:

GET /api

Returns an array of suggestions for each book as an array.

The array of books is ordered by the date they were added (most recent first).

Query Parameters

• limit (optional): limits the number of results returned. Default is 25, maximum is 100.
• offset (optional): offset the list of results. Default is 0.
• threshold (optional): sets the minimum similarity score to receive suggestions for. Default is 0, returning all suggestions.

Examples

Any combination of the query parameters in any order are valid.

• /api?threshold=3

  Returns suggestions with a similarity score of 3 or more for the 25 most recently added books.

• /api?threshold=5&limit=100

  Returns suggestions with a similarity score of 3 or more for the 100 most recently added books.

• /api?limit=50&offset=1000

  Returns 50 books and all of their suggestions, skipping the 1000 most recent.

GET /api/ngrams

Returns an array of ngrams and their occurences for each book as an array.

The array of books is ordered by the date they were added (most recent first).

Query Parameters

• limit (optional): limits the number of results returned. Default is 25, maximum is 100.
• offset (optional): offset the list of results. Default is 0.

Examples

Any combination of the query parameters in any order are valid.

• /api?limit=100

  Returns ngrams for the 100 most recent books.

• /api?offset=1000

  Returns ngrams for 25 books, skipping the 1000 most recent.

GET /api/{handle}

Returns suggestions for the book with the specified handle.

Path Parameters

{handle} (required): the handle of the book to retrieve.

Query Parameters

threshold (optional): sets the minimum similarity score to receive suggestions for. Default is 0, returning all suggestions.

Examples

NOTE: You won't need to worry about the forward slash in handles causing problems, this is handled server-side.

• /api/20.400.12657/47581

Returns suggestions for the book with the handle 20.400.12657/47581.

• /api/20.400.12657/47581?threshold=3

Returns suggestions with a similarity score of 3 or more for the book with the handle 20.400.12657/47581.

GET /api/{handle}/ngrams

Returns the ngrams and their occurences for the book with the specified handle.

Path Parameters

{handle} (required): the handle of the book to retrieve.

Example

/api/20.400.12657/47581/ngrams

Returns ngrams and their occurences for the book with the handle 20.400.12657/47581.

Logging

Log files are automatically generated by Docker for each container. The log files can be found in /var/lib/docker/containers/<container-id>/*-json.log.

To find a container's id, run docker ps -a.

To view log files, run tail -f /var/lib/docker/containers/<container-id>/*-json.log.

After some time, log files may take up too much disk space. To clear all logs on the host machine, run truncate -s 0 /var/lib/docker/containers/*/*-json.log

To clear logs for a specific container, run truncate -s 0 /var/lib/docker/containers/<container-id>/*-json.log

Service Components

This project is a monorepo, with multiple services that work in tandem to provide suggestions:

• Database
• Suggestion Engine
• API
• Embed Script
• Web Demo

Suggestion Engine

This engine is written in Python, and generates the recommendation data for users. Our suggestion service is centered around the trigram semantic inferencing algorithm. This script should be run as a job on a cron schedule to periodically ingest new texts added to the OAPEN catalog through their API. It populates the database with pre-processed lists of suggestions for each entry in the catalog.

You can find the code for the suggestion engine in oapen-engine/, and read more about it in oapen-engine/README.md.

API

This API server serves book recommendations from the database over HTTP in a standard RESTful architecture.

You can find the code for the API in api/, and readmore about it in api/README.md.

Embed Script

The embed script is a drop-in snippet of HTML, CSS, and JavaScript that can be added to the library.oapen.org site, and adds book recommendation functionality to the sidebar of each book page.

You can find the code for the embed script in embed-script/, and read more about it in embed-script/README.md.

Web Demo

This is a web-app demo that can be used to query the API engine and see suggested books. This does not have to be maintained if the API is used on another site, but is useful for development and a tech demo.

You can find the code for the web demo in web/.

Configuration info for the web demo is in web/README.md.

Base dependencies:

• NodeJS 14.x+
• NPM package manager

Automatically-installed dependencies:

• next -- Framework for production-driven web apps
  • Maintained by Vercel and the open source community
• react -- Frontend design framework
  • Maintained by Meta.
  • Largest frontend web UI library.
  • (Alternative considered: Angular -- however, was recently deprecated by Google)
• pg -- basic PostgreSQL driver
  • Maintained on npm
• typescript -- Types for JavaScript
  • Maintained by Microsoft and the open source community.

Updates

TODO: add documentation

Local Installation (No Server)

1. Install Docker

   This project uses Docker. Instructions for installing Docker here. Note that if you do not install Docker with Docker Desktop (which is recommended) you will have to install Docker Compose separately Instructions for that here.

2. Install PostgreSQL

   You can find instructions for installing PostgreSQL on your machine here.

   Or you can create a PostgreSQL server with Docker:

   docker run -d --name postgres -p 5432:5432 -e POSTGRES_PASSWORD=postgrespw postgres
   

   The username and database name will both be postgres and the password will be postgrespw. You can connect via the hostname host.docker.internal over port 5432.

3. Clone and configure the project

   • Clone the repo and go into its directory:

     git clone https://github.com/EbookFoundation/oapen-suggestion-service.git
     cd oapen-suggestion-service
     

   • Copy the .env.template file to .env:

     cp .env.template .env
     

   • Using a text editor like vim or nano configure all of the options in .env:

     API_PORT=<Port to serve API on>
     POSTGRES_HOST=<Hostname of postgres server>
     POSTGRES_PORT=<Port postgres is running on>
     POSTGRES_DB_NAME=<Name of the postgres database>
     POSTGRES_USERNAME=<Username of the postgres user>
     POSTGRES_PASSWORD=<Password of the postgres user>
     POSTGRES_SSLMODE=<'allow' for a local installation>
     

4. See Running