GitHub Trends

#python#ai#bug_detection#code_audit#code_quality#code_review#developer_tools#devsecops#google_gemini#llm#react#sast#security_scanner#supabase#typescript#vite#vulnerability_scanner#xai **DeepAudit** is an AI-powered code audit tool using multi-agent collaboration to deeply scan projects for vulnerabilities like SQL injection, XSS, and path traversal. Import code from GitHub/GitLab or paste snippets; agents plan, analyze with RAG knowledge, and verify issues via secure Docker sandbox PoCs, generating PDF reports with fix suggestions. Deploy easily with one Docker command, supports local Ollama models for privacy, and cuts traditional tools' high false positives. **You benefit** by automating secure audits like a pro hacker—saving time, reducing errors, ensuring real exploits are caught, and speeding safe releases without manual hassle. https://github.com/lintsinghua/DeepAudit

#go#gemma3#go#gpt_oss#granite4#llama#llama3#llm#on_device_ai#phi3#qwen3#qwen3vl#sdk#stable_diffusion#vlm NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience. https://github.com/NexaAI/nexa-sdk

#typescript#documentation_generator#nuxt#nuxt_theme Docus is a CLI tool that quickly scaffolds a complete, modern documentation site using Markdown and Vue (Nuxt 4), with responsive design, dark mode, i18n, full-text search, enhanced Markdown components, TypeScript support, and built-in AI/LLM integration via llms.txt and a native MCP server for editor/IDE tools like Cursor and VS Code, letting you start a docs site with npx create-docus and npm run dev so it runs locally instantly. Benefit: you get a production-ready, customizable docs site fast—saving setup time and giving built-in search, localization, performance, and AI tooling to improve authoring and user experience. https://github.com/nuxt-content/docus

#python Mini-SGLang is a compact, easy-to-read inference framework (~5,000 Python lines) that runs and serves large language models with high speed using optimizations like radix cache, chunked prefill, overlap scheduling, tensor parallelism, and FlashAttention/FlashInfer kernels. It’s CUDA-dependent, quick to install from source, and can launch an OpenAI-compatible API or interactive shell for single- or multi‑GPU serving, letting you test or deploy models (e.g., Qwen, Llama) with low latency and scalable throughput. Benefit: you get a transparent, modifiable engine to deploy fast, efficient LLM inference for development, benchmarking, or production use. https://github.com/sgl-project/mini-sglang

#typescript#agent#agentic#agentic_ai#agents#agents_sdk#ai#ai_agents#aiagentframework#genai#genai_chatbot#llm#llms#multi_agent#multi_agent_systems#multi_agents#multi_agents_collaboration Agent Development Kit (ADK) for TypeScript is an open-source toolkit to build, test, and deploy advanced AI agents with full control in code. Key features include rich tools like Google Search, custom functions, and multi-agent hierarchies for scalable apps, plus a dev UI for easy debugging. Install via npm install @google/adk. You benefit by creating flexible, versioned AI agents that integrate tightly with Google Cloud, run anywhere from laptop to cloud, and speed up development like regular software. https://github.com/google/adk-js

#python#large_language_models#llm#penetration_testing#python PentestGPT is a free, open-source AI tool that automates penetration testing like solving CTF challenges in web, crypto, and more. Install easily with Docker, add your API key (Anthropic, OpenAI, or local LLMs), then run pentestgpt --target [IP] for interactive guidance on scans, exploits, and reports. New v1.0 adds autonomous agents and session saving. It boosts your speed and accuracy in ethical hacking, helping beginners learn steps fast and pros tackle complex targets efficiently. https://github.com/GreyDGL/PentestGPT

#rich_text_format#lcd_display#python#serial_communication#smart_display#smart_screen#system_monitor#system_monitoring#turing_smart_screen#xuanfang **turing-smart-screen-python** is free open-source Python software (3.9+) for small USB-C IPS smart screens like Turing 3.5"/5", XuanFang, and others on Windows, Linux, Raspberry Pi, or macOS. Use it as a standalone system monitor showing CPU/GPU usage, temps, memory, and custom data via easy themes (with editor and community shares), or integrate into your Python projects to display text, images, progress bars, brightness, rotation, and RGB LEDs. It auto-detects ports with a simple GUI wizard—no coding needed. You benefit by turning your screen into a customizable HW dashboard or app display affordably, cross-platform, without vendor limits. https://github.com/mathoudebine/turing-smart-screen-python

#python **ty** is a super-fast Python type checker and language server built in Rust by Astral (makers of uv and Ruff). It's 10-100x faster than mypy or Pyright, with rich error messages, IDE features like auto-complete and hover help, and support for big projects or partial typing. Try it via `uvx ty check`. This helps you catch bugs early, code faster with real-time feedback, and boost productivity in editors like VS Code. https://github.com/astral-sh/ty

#c_lang#driver#flash#jedec#jedec_sfdp#qspi#sfdp#sfdp_flash#spi_flash#universal_driver **SFUD** is an open-source library that drives many SPI/QSPI Flash chips from brands like Winbond and Macronix. It auto-detects chip specs via the **SFDP** standard or a built-in table, letting you read, write, erase, and init with simple APIs after easy config. This helps you avoid risks from Flash shortages or upgrades, boosts software reuse across projects, cuts dev time, and enables tools like programmers—saving effort on varied hardware. https://github.com/armink/SFUD

#python#gym#gym_environment#reinforcement_learning#reinforcement_learning_agent#reinforcement_learning_environments#rl_environment#rl_training NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior. https://github.com/NVIDIA-NeMo/Gym

#python#help_wanted#looking_for_contributors This M3U playlist gives you a single, regularly updated file of free, legal TV channels worldwide (grouped by country and marked for HD, geo-blocking, or YouTube live) so you can add it to an IPTV player and watch many working streams without hunting links; it focuses on quality (only free, mainstream channels, one URL per channel) and lets you contribute fixes or channel changes via GitHub pull requests, which helps you get reliable channels and keeps the list current for smoother viewing. https://github.com/Free-TV/IPTV

#typescript Zerobyte is a simple web app that automates encrypted, compressed backups (using Restic) from local folders or remote shares to many storage types—including S3, GCS, Azure, rclone remotes, NFS, SMB and WebDAV—letting you schedule jobs, set retention rules, monitor progress, and restore files through a dashboard (it’s early-stage and may change). Installing requires Docker Compose and optional FUSE/SYS_ADMIN for remote mounts; rclone support lets you use 40+ cloud providers. Benefit: you get automatic, space-efficient, end-to-end encrypted backups with easy scheduling and restores, reducing manual work and risk of data loss. https://github.com/nicotsx/zerobyte