X-algorithm is a modular recommendation engine framework designed to orchestrate personalized content feeds. It functions as a machine learning ranking system that manages the end-to-end lifecycle of content delivery, from initial candidate retrieval to final display ordering.
The system distinguishes itself through a multi-stage pipeline that integrates vector-based similarity search with transformer-based engagement prediction. By mapping user history and content features into high-dimensional embeddings, it performs rapid approximate nearest neighbor searches to identify relevant items. These candidates are then processed through deep learning models that estimate the probability of multiple simultaneous user interactions, such as likes, replies, and reposts, in a single inference pass.
The framework supports complex workflow orchestration, including real-time data retrieval from in-memory stores and the application of multi-stage filtering to enforce safety policies and content relevance. It also provides capabilities for blending promotional content into feeds while maintaining sub-millisecond latency for candidate retrieval. The repository includes tools for managing these recommendation pipelines and performing semantic analysis on content to ensure compliance and quality.
