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Autonomous Red Team agent that plans and executes realistic attack chains (reconnaissance, exploitation, pivoting, C2) while producing Rules of Engagement and an OPPLAN and running actions inside a hardened sandbox; intended for authorized red-team engagements and defensive verification.
Extends RAG beyond text: parses PDFs and Office files containing images, tables, equations, and charts, then queries them through one multimodal knowledge graph. Built on LightRAG, it replaces separate parsing and retrieval tools.
Gives AI coding assistants a queryable index of n8n's 2,000+ workflow nodes — their real properties, operations, and 2,300+ templates — so generated workflow JSON validates instead of hallucinating node names and connections.
Turns commodity WiFi Channel State Information into spatial sensing: 17-keypoint pose estimation, presence detection, and contactless breathing/heart-rate monitoring through walls, with no camera. Runs on a mesh of ESP32-S3 nodes (~$9 each).
Reimplements the vLLM inference engine from scratch in ~1,200 lines of readable Python, matching its offline throughput on small models. Prefix caching, tensor parallelism, torch.compile, and CUDA graphs are all kept legible.
Run Claude as a programmatic agent in Python: one-shot query() calls or a stateful ClaudeSDKClient for multi-turn loops. Define in-process tools, lifecycle hooks, and per-tool permissions; it bundles the Claude Code CLI and exposes its full toolset.
Curated marketplace of community-contributed GitHub Copilot customizations — reusable agents, file-scoped instructions, skills, plugins, hooks, and agentic workflows — installable via the Copilot CLI and searchable on a companion site.
A toolkit and open-weights system for real-time streaming music generation — offers two model sizes (230M / 2.4B), a Python inference library (JAX/MLX), and a C++ engine optimized for Apple Silicon for embedding into DAWs and apps; real-time streaming requires M‑series chips.
GPU-accelerated, non-destructive RAW photo editor designed for fast, low-footprint desktop workflows (<20MB). Built with Rust/WGPU/Tauri, it offers real-time 32-bit GPU processing, AI-assisted masking and optional ComfyUI integration for generative edits, plus presets and batch export.
Orchestrates 10+ coding agents (Claude Code, Codex, Gemini CLI) from a kanban board: plan tasks as issues, then run each in an isolated workspace with its own branch, terminal, and dev server. Inline diff review and one-click PR creation.
A code-first collection of runnable tutorials for building production-ready generative-AI agents — step-by-step guides covering stateful workflows, vector memory, RAG, tool integrations, Docker/AWS/RunPod deployment, security guardrails, observability, and multi-agent patterns.
Trains and optimizes AI agents with reinforcement learning using almost zero code change. Works with any agent framework (LangChain, OpenAI Agents SDK, AutoGen, CrewAI) or none, and can selectively optimize a single agent inside a multi-agent system.