Repository History
138 repositories tagged with LLM
Agent-Memory: Persistent Memory for AI Coding Agents
Agent-Memory provides persistent memory for AI coding agents, ensuring they remember past interactions and learned patterns across sessions. Built on the iii engine, it eliminates the need for re-explaining context, significantly improving agent efficiency and reducing token usage. This solution integrates seamlessly with various agents, offering a robust memory management system.
gh-aw-firewall: Secure Your Agentic Workflows with a Network Firewall
gh-aw-firewall is a robust network firewall designed specifically for agentic workflows, restricting outbound HTTP/HTTPS traffic to an allowlist of domains. It operates by running commands within a Docker sandbox, leveraging a Squid proxy for traffic filtering and an optional API proxy sidecar to securely manage LLM API keys. This project is a crucial component of GitHub's ongoing exploration into Agentic Workflows, enhancing their security and control.
code-session-memory: Automatic Vector Memory for AI Coding Sessions
code-session-memory provides automatic vector memory for various AI coding tools like OpenCode, Claude Code, Cursor, VS Code, Codex, and Gemini CLI. It indexes new messages into a vector database after each AI agent turn, enabling semantic search across all your past coding sessions. This tool ensures memory is shared across different platforms, enhancing developer productivity.
Cortex-Mem: A Production-Ready Memory Framework for Autonomous AI Systems
Cortex-Mem is a production-ready, AI-native memory framework built in Rust, providing intelligent long-term memory for autonomous systems. It features a hierarchical three-tier memory architecture for efficient information management, from extraction and search to automated optimization. This framework empowers AI agents to remember, learn, and personalize interactions across sessions, transforming stateless AI into context-aware partners.
AWESOME-OCR-LLM: Curated Reading List for OCR in the LLM Era
AWESOME-OCR-LLM is a continuously updated reading list focusing on Optical Character Recognition (OCR) in the era of large language models (LLMs). It covers key areas like document parsing, understanding, visual text generation, and benchmarks, highlighting research from the past five years. This resource is invaluable for anyone tracking the rapid advancements in multimodal document AI.
SkillOpt: Optimizing Self-Evolving Agent Skills for LLMs
SkillOpt is an innovative text-space optimizer from Microsoft that enables the training of reusable natural-language skills for frozen LLM agents. It approaches skill development with the rigor of deep-learning optimization, using trajectory-driven edits and validation-gated updates. This results in deployable `best_skill.md` artifacts that significantly boost agent performance across various benchmarks and models without modifying model weights.
Pi Agent Harness: An AI Agent Toolkit for LLMs and Coding
Pi Agent Harness is a comprehensive AI agent toolkit designed for building and deploying intelligent agents. It features a unified API for various Large Language Models, a robust agent runtime with tool calling, and an interactive coding agent CLI. This project provides a modular and extensible foundation for developing advanced AI applications.
LobeHub: Your Chief Agent Operator for AI Team Orchestration
LobeHub acts as a Chief Agent Operator, streamlining the management of your AI team. It enables hiring, scheduling, and reporting on agents for 24/7 operations, allowing users to maintain control without constant online presence. This platform transforms individual AI tools into a cohesive, productive team.
DeepTutor: Lifelong Personalized Tutoring with AI Agents
DeepTutor is an advanced AI-powered platform designed for lifelong personalized tutoring, integrating various learning modes into a single, extensible system. It leverages large language models and multi-agent systems to offer features like interactive chat, quiz generation, and skill development. This project provides a comprehensive environment for learners and educators seeking intelligent, adaptive educational tools.
Memori: Agent-Native Memory Infrastructure for LLM Production Systems
Memori provides agent-native memory infrastructure, offering an LLM-agnostic layer that transforms agent execution and conversations into structured, persistent state. Designed for enterprise use, it seamlessly integrates with existing data infrastructure and supports various deployment environments, ensuring robust memory management for AI agents.
awesome-agentic-ai: Your Comprehensive Hub for Agentic AI Resources
awesome-agentic-ai is a curated list of resources for learning, building, and mastering Agentic AI systems. This repository serves as a complete hub, offering a learning roadmap, top frameworks, tools, and real-world examples. It's designed for both beginners and experts looking to explore autonomous AI agents.
Colibri: Run 744B GLM-5.2 MoE on Consumer Machines with Pure C
Colibri is an innovative project that enables running the massive 744B-parameter GLM-5.2 Mixture-of-Experts (MoE) model on consumer-grade machines with as little as 25GB of RAM. It achieves this remarkable feat through a pure C engine with zero dependencies, streaming model experts from disk on demand. This allows users to interact with a frontier-class LLM without requiring expensive GPU hardware.