microsoft/RecAI

Bridging LLM and Recommender System.

55
/ 100
Established

RecAI helps e-commerce managers, content curators, and platform strategists build more intelligent and interactive recommendation systems. It takes various forms of data, like user interactions and item descriptions, and uses large language models to generate personalized product recommendations, content suggestions, or tailored user experiences. The output is a more sophisticated and explainable recommendation engine.

1,063 stars.

Use this if you are developing or managing a system that needs to offer highly personalized, interactive, and understandable recommendations to users, moving beyond traditional, less conversational methods.

Not ideal if your primary need is for a simple, traditional recommender system without the advanced interactivity, explainability, or language-based processing that LLMs provide.

e-commerce recommendations content discovery personalization engine customer engagement AI agent development
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 19 / 25

How are scores calculated?

Stars

1,063

Forks

114

Language

Jupyter Notebook

License

MIT

Last pushed

Jan 27, 2026

Commits (30d)

0

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