Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

Superposition is a context-based configuration management system designed to facilitate safe and flexible rollout of config changes

🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, uses embeddings/LLMs, and provides accurate context via a tool call.

Structured Data Extractor for AI Agents. Search your documents or the web for specific data and get it back in JSON or Markdown in a single tool call.

Java-Based Context-aware Recommendation Library

Contextual AI models for single-cell protein biology

Multimodal Infinite Memory AI Agent

Context-sensitive ranking and choice in Python with PyTorch

A Stream-based LLM Agent Framework for Continuous Context Sensing and Sharing

DevContext is a cutting-edge Model Context Protocol (MCP) server designed to provide developers with continuous, project-centric context awareness. Unlike traditional context systems, DevContext continuously learns from and adapts to your development patterns and delivers highly relevant context providing a deeper understanding of your codebase.

AWARE Framework for iOS

The implementation of “A Context-Aware User-Item Representation Learning for Item Recommendation”, Libing Wu, Cong Quan, Chenliang Li, Qian Wang, Bolong Zheng, Xiangyang Luo, https://dl.acm.org/citation.cfm?id=3298988

Open source IoT middleware suite that makes the data from just about anything usable. We believe in an open Internet of Things.

Oh-My-Papers: a Hybrid Context-aware Paper Recommendation System

Interactive chat application leveraging OpenAI's GPT-4 for real-time conversation simulations. Built with Flask, this project showcases streaming LLM responses in a user-friendly web interface.

Semantic Labeling in VHR Images via A Self-Cascaded CNN (ISPRS JPRS, IF=6.942)

AWARE Client iOS (Version2)

Dynamic FastMCP extends the Model Context Protocol Python server with context-aware tools that adapt their behavior and descriptions based on user, tenant, and request context.

A Deep Learning Based Context-Aware Recommendation Library

Context-aware Biases for Length Extrapolation