The toshiba_air_cond project implements functions to decode Toshiba AB protocol from indoor units to wired controllers and provides a hardware design for communication. It is developed for ESP8266 using PlatformIO and Wemos D1 mini board. The project offers features such as WebServer, WebSockets communication, Home Assistant integration, OTA updates, file uploading, and WiFiManager. It has been tested with specific Toshiba units and provides a web interface for controlling functions like power ON/OFF, setting target temperature, changing modes, adjusting fan speed, setting timers, and displaying current temperature and system information.

This repository contains a custom component for Home Assistant that integrates various Xiaomi Mi Air Purifier and Xiaomi Mi Air Humidifier models. It provides detailed support for different devices, including power control, preset modes, child lock, LED control, favorite level adjustment, and various attributes monitoring. The custom component offers a more extensive range of supported devices compared to the official Home Assistant component, with additional features and device compatibility. Users can easily set up and configure their Xiaomi air purifiers and humidifiers within Home Assistant for enhanced control and monitoring.

ChatGLM.cpp is a C++ implementation of ChatGLM-6B, ChatGLM2-6B, ChatGLM3-6B and more LLMs for real-time chatting on your MacBook. It is based on ggml, working in the same way as llama.cpp. ChatGLM.cpp features accelerated memory-efficient CPU inference with int4/int8 quantization, optimized KV cache and parallel computing. It also supports P-Tuning v2 and LoRA finetuned models, streaming generation with typewriter effect, Python binding, web demo, api servers and more possibilities.

Gollama is a tool designed for managing Ollama models through a Text User Interface (TUI). Users can list, inspect, delete, copy, and push Ollama models, as well as link them to LM Studio. The application offers interactive model selection, sorting by various criteria, and actions using hotkeys. It provides features like sorting and filtering capabilities, displaying model metadata, model linking, copying, pushing, and more. Gollama aims to be user-friendly and useful for managing models, especially for cleaning up old models.

llm.nvim is a universal plugin for a large language model (LLM) designed to enable users to interact with LLM within neovim. Users can customize various LLMs such as gpt, glm, kimi, and local LLM. The plugin provides tools for optimizing code, comparing code, translating text, and more. It also supports integration with free models from Cloudflare, Github models, siliconflow, and others. Users can customize tools, chat with LLM, quickly translate text, and explain code snippets. The plugin offers a flexible window interface for easy interaction and customization.

FLUTE (Flexible Lookup Table Engine for LUT-quantized LLMs) is a tool designed for uniform quantization and lookup table quantization of weights in lower-precision intervals. It offers flexibility in mapping intervals to arbitrary values through a lookup table. FLUTE supports various quantization formats such as int4, int3, int2, fp4, fp3, fp2, nf4, nf3, nf2, and even custom tables. The tool also introduces new quantization algorithms like Learned Normal Float (NFL) for improved performance and calibration data learning. FLUTE provides benchmarks, model zoo, and integration with frameworks like vLLM and HuggingFace for easy deployment and usage.

Fitten Code AI Programming Assistant for Neovim provides fast completion using AI, asynchronous I/O, and support for various actions like document code, edit code, explain code, find bugs, generate unit test, implement features, optimize code, refactor code, start chat, and more. It offers features like accepting suggestions with Tab, accepting line with Ctrl + Down, accepting word with Ctrl + Right, undoing accepted text, automatic scrolling, and multiple HTTP/REST backends. It can run as a coc.nvim source or nvim-cmp source.

9Router is a free AI router tool designed to help developers maximize their AI subscriptions, auto-route to free and cheap AI models with smart fallback, and avoid hitting limits and wasting money. It offers features like real-time quota tracking, format translation between OpenAI, Claude, and Gemini, multi-account support, auto token refresh, custom model combinations, request logging, cloud sync, usage analytics, and flexible deployment options. The tool supports various providers like Claude Code, Codex, Gemini CLI, GitHub Copilot, GLM, MiniMax, iFlow, Qwen, and Kiro, and allows users to create combos for different scenarios. Users can connect to the tool via CLI tools like Cursor, Claude Code, Codex, OpenClaw, and Cline, and deploy it on VPS, Docker, or Cloudflare Workers.

This project provides a unified backend interface for open large language models (LLMs), offering a consistent experience with OpenAI's ChatGPT API. It supports various open-source LLMs, enabling developers to seamlessly integrate them into their applications. The interface features streaming responses, text embedding capabilities, and support for LangChain, a tool for developing LLM-based applications. By modifying environment variables, developers can easily use open-source models as alternatives to ChatGPT, providing a cost-effective and customizable solution for various use cases.

BetterOCR is a tool that enhances text detection by combining multiple OCR engines with LLM (Language Model). It aims to improve OCR results, especially for languages with limited training data or noisy outputs. The tool combines results from EasyOCR, Tesseract, and Pororo engines, along with LLM support from OpenAI. Users can provide custom context for better accuracy, view performance examples by language, and upcoming features include box detection, improved interface, and async support. The package is under rapid development and contributions are welcomed.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.

Augustus is a Go-based LLM vulnerability scanner designed for security professionals to test large language models against a wide range of adversarial attacks. It integrates with 28 LLM providers, covers 210+ adversarial attacks including prompt injection, jailbreaks, encoding exploits, and data extraction, and produces actionable vulnerability reports. The tool is built for production security testing with features like concurrent scanning, rate limiting, retry logic, and timeout handling out of the box.

Autohand Code CLI is an autonomous coding agent in CLI form that uses the ReAct pattern to understand, plan, and execute code changes. It is designed for seamless coding experience without context switching or copy-pasting. The tool is fast, intuitive, and extensible with modular skills. It can be used to automate coding tasks, enforce code quality, and speed up development. Autohand can be integrated into team workflows and CI/CD pipelines to enhance productivity and efficiency.

AICommit2 is a Reactive CLI tool that streamlines interactions with various AI providers such as OpenAI, Anthropic Claude, Gemini, Mistral AI, Cohere, and unofficial providers like Huggingface and Clova X. Users can request multiple AI simultaneously to generate git commit messages without waiting for all AI responses. The tool runs 'git diff' to grab code changes, sends them to configured AI, and returns the AI-generated commit message. Users can set API keys or Cookies for different providers and configure options like locale, generate number of messages, commit type, proxy, timeout, max-length, and more. AICommit2 can be used both locally with Ollama and remotely with supported providers, offering flexibility and efficiency in generating commit messages.

LM Engine is a research-grade, production-ready library for training large language models at scale. It provides support for multiple accelerators including NVIDIA GPUs, Google TPUs, and AWS Trainiums. Key features include multi-accelerator support, advanced distributed training, flexible model architectures, HuggingFace integration, training modes like pretraining and finetuning, custom kernels for high performance, experiment tracking, and efficient checkpointing.

The toshiba_air_cond project implements functions to decode Toshiba AB protocol from indoor units to wired controllers and provides a hardware design for communication. It is developed for ESP8266 using PlatformIO and Wemos D1 mini board. The project offers features such as WebServer, WebSockets communication, Home Assistant integration, OTA updates, file uploading, and WiFiManager. It has been tested with specific Toshiba units and provides a web interface for controlling functions like power ON/OFF, setting target temperature, changing modes, adjusting fan speed, setting timers, and displaying current temperature and system information.

Frigate is a complete and local NVR designed for Home Assistant with AI object detection. It uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.

aiohomekit is a Python library that implements the HomeKit protocol for controlling HomeKit accessories using asyncio. It is primarily used with Home Assistant, targeting the same versions of Python and following their code standards. The library is still under development and does not offer API guarantees yet. It aims to match the behavior of real HAP controllers, even when not strictly specified, and works around issues like JSON formatting, boolean encoding, header sensitivity, and TCP packet splitting. aiohomekit is primarily tested with Phillips Hue and Eve Extend bridges via Home Assistant, but is known to work with many more devices. It does not support BLE accessories and is intended for client-side use only.

LLM Vision is a Home Assistant integration that allows users to analyze images, videos, and camera feeds using multimodal LLMs. It supports providers such as OpenAI, Anthropic, Google Gemini, LocalAI, and Ollama. Users can input images and videos from camera entities or local files, with the option to downscale images for faster processing. The tool provides detailed instructions on setting up LLM Vision and each supported provider, along with usage examples and service call parameters.

This GitHub project provides a simple way to use Xiaozhi-based devices with ESPHome, allowing them to serve as voice assistants integrated with Home Assistant. Users can follow a step-by-step installation guide to connect their devices, edit configurations, and set up the voice assistant. The project supports various devices such as Spotpear Ball, Muma Box, Puck, Guition Taichi pi, Xingzhi Cube, and more. Additionally, it offers links to purchase supported devices and accessories, including 3D files for holders and wireless chargers.

AIO Homematic (hahomematic) is a lightweight Python 3 library for controlling and monitoring HomeMatic and HomematicIP devices, with support for third-party devices/gateways. It automatically creates entities for device parameters, offers custom entity classes for complex behavior, and includes features like caching paramsets for faster restarts. Designed to integrate with Home Assistant, it requires specific firmware versions for HomematicIP devices. The public API is defined in modules like central, client, model, exceptions, and const, with example usage provided. Useful links include changelog, data point definitions, troubleshooting, and developer resources for architecture, data flow, model extension, and Home Assistant lifecycle.

ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. Key value propositions of ExecuTorch are: * **Portability:** Compatibility with a wide variety of computing platforms, from high-end mobile phones to highly constrained embedded systems and microcontrollers. * **Productivity:** Enabling developers to use the same toolchains and SDK from PyTorch model authoring and conversion, to debugging and deployment to a wide variety of platforms. * **Performance:** Providing end users with a seamless and high-performance experience due to a lightweight runtime and utilizing full hardware capabilities such as CPUs, NPUs, and DSPs.

The Holoscan SDK is part of NVIDIA Holoscan, the AI sensor processing platform that combines hardware systems for low-latency sensor and network connectivity, optimized libraries for data processing and AI, and core microservices to run streaming, imaging, and other applications, from embedded to edge to cloud. It can be used to build streaming AI pipelines for a variety of domains, including Medical Devices, High Performance Computing at the Edge, Industrial Inspection and more.

Panda is a car interface tool that speaks CAN and CAN FD, running on STM32F413 and STM32H725. It provides safety modes and controls_allowed feature for message handling. The tool ensures code rigor through CI regression tests, including static code analysis, MISRA C:2012 violations check, unit tests, and hardware-in-the-loop tests. The software interface supports Python library, C++ library, and socketcan in kernel. Panda is licensed under the MIT license.

aiocoap is a Python library that implements the Constrained Application Protocol (CoAP) using native asyncio methods in Python 3. It supports various CoAP standards such as RFC7252, RFC7641, RFC7959, RFC8323, RFC7967, RFC8132, RFC9176, RFC8613, and draft-ietf-core-oscore-groupcomm-17. The library provides features for clients and servers, including multicast support, blockwise transfer, CoAP over TCP, TLS, and WebSockets, No-Response, PATCH/FETCH, OSCORE, and Group OSCORE. It offers an easy-to-use interface for concurrent operations and is suitable for IoT applications.

CPP-Notes is a comprehensive repository providing detailed insights into the history, evolution, and modern development of the C++ programming language. It covers the foundational concepts of C++ and its transition from C, highlighting key features such as object-oriented programming, generic programming, and modern enhancements introduced in C++11/14/17. The repository delves into the significance of C++ in system programming, library development, and its role as a versatile and efficient language. It explores the historical milestones of C++ development, from its inception in 1979 by Bjarne Stroustrup to the latest C++20 standard, showcasing major advancements like Concepts, Ranges library, Coroutines, Modules, and enhanced concurrency features.

AI-on-the-edge-device is a project that enables users to digitize analog water, gas, power, and other meters using an ESP32 board with a supported camera. It integrates Tensorflow Lite for AI processing, offers a small and affordable device with integrated camera and illumination, provides a web interface for administration and control, supports Homeassistant, Influx DB, MQTT, and REST API. The device captures meter images, extracts Regions of Interest (ROIs), runs them through AI for digitization, and allows users to send data to MQTT, InfluxDb, or access it via REST API. The project also includes 3D-printable housing options and tools for logfile management.

RKLLM software stack is a toolkit designed to help users quickly deploy AI models to Rockchip chips. It consists of RKLLM-Toolkit for model conversion and quantization, RKLLM Runtime for deploying models on Rockchip NPU platform, and RKNPU kernel driver for hardware interaction. The toolkit supports RK3588 and RK3576 series chips and various models like TinyLLAMA, Qwen, Phi, ChatGLM3, Gemma, InternLM2, and MiniCPM. Users can download packages, docker images, examples, and docs from RKLLM_SDK. Additionally, RKNN-Toolkit2 SDK is available for deploying additional AI models.

RK3588 is a flagship 8K SoC chip by Rockchip, integrating Cortex-A76 and Cortex-A55 cores with NEON coprocessor for 8K video codec. This repository curates resources for developing with RK3588, including official resources, RKNN models, projects, development boards, documentation, tools, and sample code.