Recommender systems are a very active area of research in academia, though few of the generated systems make it out of the lab. Here are a few I have found that did:

1. Duine Framework a Java based recommendation system that has been abandoned
2. MyMediaLite C# based in-memory recommender system that has been abandoned
3. Bonus: List of Recommender System Dissertations, a useful list to keep up with the current state of recommendations systems in academia
4. LibRec A Java based Recommendations engine with loads of implemented algorithms (suggested by Saúl Vargas)
5. RankSys Java Recommendation system for novelty and diversity created by Saúl Vargas)
6. LIBMF A Matrix-factorization Library for Recommender Systems
7. proNet-core A general-purpose network embedding framework which provides several factorization-based models for recommender systems
8. Devooght A repository containing collaborative-filtering algorithms based on sequences.
9. Cornac A Python based comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data (developed by Preferred.AI).