Kronos: A Foundation Model for the Language of Financial Markets
⚚ The coding harness with Hermes Agent wired into IDE.
Python SDK and desktop/CLI product providing dual-system cognitive memory pipelines for self-evolving LLM agents across chat, working, and coding scenes.
Build AI text detectors whose decisions are mechanistically grounded and human-auditable (EMNLP 2026)
HelixHarness 提供完整的 AI Coding 工程化基础能力,还支持不同企业和团队结合自身的业务知识、工程规范和研发流程,持续构建和演进属于自己的专属 Harness
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory with small models for free
A 197 KB local semantic verifier for AI agent tool calls. Exit code 0 is not proof.
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.
Reliable AI Skill + MCP toolkit for agent-driven desktop CAD automation.
Official code for Xiaomi-SpatialEmbodied, a Qwen3-VL-based VLM with 3D geometric and embodied adapters for driving and robotics VQA.
Unofficial Python API and agentic skill for Google Gemini Notebook. Full programmatic access to Gemini Notebook's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.
Repository for Timestral, the time-series foundation model by Mistral AI
Official PyTorch implementation of VisionHOPE: Visual Backbones as Self-Modifying Learning Systems.
Official Inference Code of EAGLE-4
FastAPI framework, high performance, easy to learn, fast to code, ready for production
🤗 smolagents: a barebones library for agents that think in code.
Tamper-evident tracing, policy gates and cross-checks for AI agents: see what the agent did, and why.
We write your reusable computer vision tools. 💜
OPAL: a reactive optimizer. A coding agent rewrites the optimizer while your model trains.
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
Open-source skills that empower any AI agent (Claude, Cursor, Hermes, etc.) to generate end-to-end marketing campaigns - UGC videos, ad videos, product photography and more.
A next generation HTTP client for Python. 🦋
Building the self-learning layer next-gen agents will ship with, learning skills from real work.