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Fully automatic censorship removal for language models
⌥ AI Coding agent for the terminal — hash-anchored edits, optimized tool harness, LSP, Python, browser, subagents, and more
AutoMem: Automated Learning of Memory as a Cognitive Skill
A Python port of Pi’s minimalist coding agent.
Companion repo to our livestream series Show Us Your (Agent) Skills
Long-term memory for AI assistants. Graph + vector store that recalls decisions, relationships, and context across sessions.
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
Bridging LLM and Recommender System.
Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks.
A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes…
An interface library for RL post training with environments.
Synthetic Data Generation Toolkit for LLMs
The absolute trainer to light up AI agents.
Ingest, parse, and optimize any data format ➡️ from documents to multimedia ➡️ for enhanced compatibility with GenAI frameworks
#1 Persistent memory for AI coding agents based on real-world benchmarks
On-device AI agent Chrome extension powered by Transformers.js and Gemma 4
SkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.
An Open-Source Large-Scale Reinforcement Learning Project for Search Agents
Harness engineering beginner tutorial, from 0 to 1
Browser Harness | Self-healing harness that enables LLMs to complete any task.
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
Algorithm powering the For You feed on X
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
Cuda kernels for leveraging LLM sparsity to improve throughput and decrease the memory requirements during inference and training.