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A harness is the system around a model that enables it to act as an agent: prompts, tools, memory, skills, orchestration, and more. Harnessing is the process of optimizing that system.

Local-first search engine and MCP server for AI agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search without grep, agent memory and RAG.

Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.

Ears for coding agents: let AI hear, review and make sound. CPU-only, open source.

Jasna restores mosaics in videos and images. It is free, has a simple app and a command line, and runs on your GPU.

Let AI assistants and test suites use real phones like a human.

One 8 KB skill file that does what REA does: no MCP server, no 207 tools, no setup.

5 GB of RAM. Weights stream from SSD; a trained router predicts loads a step ahead. Mac, iPhone, Android, Windows supported

You can. Models write decent HTML now. The problem is the bill you pay in output tokens: the model has to type every line of CSS, every wrapper div and every SVG coordinate.

Best headless browser for AI agents. Lite, Fast, High-Compatibility. Built in Rust

《深入理解 AI Agent：设计原理与工程实践》（李博杰 著）开源主仓库：全书正文、编译版 PDF 与按章配套代码

Want to see it in use? nanoterm is a terminal with a coding agent, and nanomon an activity monitor, both built on nanoui.

A fast, multi-threaded Redis® and Valkey alternative written in Rust: drop-in compatible, with full-text and vector search built in

8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. cpp and MLX.

12 · NVIDIA GPU with BF16 support and 24 GB VRAM. YuE2 produces 48 kHz stereo audio without quantization. Model files download from Hugging Face on first use.

Fully automatic censorship removal for language models

Hy Memory (Official Website) is a production-grade dual-system cognitive memory engine and Python SDK (hy-memory) for self-evolving LLM agents, providing specialized memory pipelines across three task scenes: hierarchical long-term cognitive memory for Chat, two-layer fact and…

[NeurIPS 2026] Safety failures in coding agents and frontier LLMs. Reproducible workspaces for studying when AI agents generate unsafe data during task completion.

Red-teaming and evaluation framework for AI agents, built around an OWASP-inspired ASI01–ASI10 taxonomy

0 with open-source drivers, cross-OS sandboxes, and benchmarks for training, evaluation, and data generation.

MemoryBear is a next-generation AI memory system developed by RedBear AI. Its core breakthrough lies in moving beyond the limitations of traditional "static knowledge storage".

AI API 中转站评测排行与切换工具：实测可用率、延迟与价格 · Open-source AI API relay benchmark, rankings & switcher for Claude Code / Codex

> Hi everyone! The original version of PaperBanana is already open-sourced under Google-Research as PaperVizAgent.

ASPIRE is a new type of continual learning: "training" is skill refinement instead of gradient descent.

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py starts the SGLang server automatically and sends concurrent requests for an image directory or PDF:

Are you frustrated with vector database retrieval accuracy for long and complex documents? Vector-based RAG retrieves by semantic similarity. But similarity ≠ relevance — what retrieval actually needs is relevance, and relevance requires reasoning.

As part of model development, we evaluate our models on open research problems. We expanded these evaluations after performance on our existing mathematical evaluations saturated. Some outputs build upon earlier results produced by the models.

Build your own AI SRE agents. The open source toolkit for the AI era.

pth） - 支持跨不同 GPU 数量恢复（自动调整 step） - 支持 wandb 训练记录连续性（自动恢复同一个 run）