GitHub Trends

#python#agents#generative_ai_tools#llamacpp#llm#onnx#openvino#parsing#retrieval_augmented_generation#small_specialized_models llmware is a powerful, easy-to-use platform that helps you build AI applications using small, specialized language models designed for business tasks like question-answering, summarization, and data extraction. It supports private, secure deployment on your own machines without needing expensive GPUs, making it cost-effective and safe for enterprise use. You can organize and search your documents, run smart queries, and combine knowledge with AI to get accurate answers quickly. It also offers many ready-to-use models and examples, plus tools for building chatbots and agents that automate complex workflows. This helps you save time, improve accuracy, and securely leverage AI for your business needs[1][3][5]. https://github.com/llmware-ai/llmware

#python#isaac_sim#omniverse_kit_extension#robot_learning#robotics Isaac Lab is a free, open-source tool that helps you easily create and test robot learning projects using fast, realistic simulations powered by NVIDIA’s Isaac Sim. It supports many robot types and environments, with accurate sensors like cameras and LIDAR, and runs quickly on GPUs. You can train robots using popular AI methods like reinforcement learning, either on your computer or in the cloud. This saves you time and money by letting you develop and improve robot skills virtually before using real hardware. Isaac Lab also has detailed guides and a community to support your learning and projects. This makes robot research and development simpler and more efficient. https://github.com/isaac-sim/IsaacLab

#python#ernie#ernie_45#ernie_45_vl#erniekit#llm#vlm ERNIE 4.5 is a powerful AI model family that understands and generates text, images, and videos together, thanks to its special design that shares knowledge across these types without losing quality. It includes large models with billions of parameters and smaller efficient ones, all trained using the PaddlePaddle framework for fast and effective use. ERNIE 4.5 excels in tasks like language understanding, visual reasoning, and following instructions, often outperforming other top models. It also offers tools for easy training and deployment on various hardware. This means you can use ERNIE 4.5 for advanced AI applications involving text and visuals with high accuracy and efficiency, supported by open-source resources for customization and development[1][3][5]. https://github.com/PaddlePaddle/ERNIE

#python#ai#authentication#authorization#claude#cursor#fastapi#llm#mcp#mcp_server#mcp_servers#modelcontextprotocol#openapi#windsurf FastAPI-MCP is a tool that lets you easily turn your FastAPI web API endpoints into Model Context Protocol (MCP) tools, which AI agents can use directly. It requires almost no setup—just connect it to your FastAPI app, and it automatically preserves your request/response data models and documentation. It also includes built-in authentication using your existing FastAPI security methods. You can run the MCP server inside your app or separately, and it communicates efficiently using FastAPI’s ASGI interface. This makes it simple to integrate AI capabilities with your existing FastAPI services without rewriting code, saving you time and effort while keeping your API secure and well-documented[1][5]. https://github.com/tadata-org/fastapi_mcp

#python#copilot#csharp#dotnet#github#github_copilot#github_copilot_chat#github_copilot_for_azure#github_copilot_free#github_copilot_training#javascript#lab#labs#microsoft#python#sql#tutorial#tutorial_code#tutorial_exercises#visual_studio_code#vscode GitHub Copilot’s new Agent Mode is a powerful AI coding partner that goes beyond just suggesting code—it can independently write, debug, and improve your code, handle complex workflows, and even fix its own mistakes automatically. It works with multiple programming languages and integrates with popular development tools, helping you save time on repetitive tasks like testing, deployment, and refactoring. By using natural language prompts, you can guide it to complete multi-step projects, making coding faster and easier whether you’re a beginner or an expert. This course teaches you how to fully use these features, boosting your productivity and coding skills. https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming

#python MediaCrawler is a powerful tool that helps you collect public data from many popular social media platforms like Xiaohongshu, Douyin, Kuaishou, Bilibili, Weibo, Tieba, and Zhihu. It uses browser automation to log in and gather posts, comments, and user info without complex coding. You can search by keywords, get specific posts, and even analyze comments with word clouds. The Pro version adds features like resuming interrupted crawls, multi-account support, and easier setup without Playwright, making it great for learning and building large-scale data projects. This tool saves you time and effort in gathering social media data for research or analysis. https://github.com/NanmiCoder/MediaCrawler

#other#beginner#contribution#contributions_welcome#css#frontend#hacktoberfest#html#javascript#open_source#opensource#php#projects#python#react You can find a well-organized collection of coding project ideas divided into three skill levels: beginner, intermediate, and advanced. Each project includes clear goals, user stories, optional bonus features, and helpful resources, making it easier for you to build and extend your projects. This helps you improve coding skills, experiment with new technologies, and create impressive portfolio pieces to attract employers or clients. The list covers various technologies like JavaScript, Python, React, MERN stack, and blockchain, with tutorials and design resources included. You can also contribute ideas and examples to grow the collection and get community support. This resource saves you time and inspires your learning journey. https://github.com/The-Cool-Coders/Project-Ideas-And-Resources

#typescript#data_visualization#geospatial_analysis#javascript#maps#python#visualization#webgl deck.gl is a powerful tool that helps you create fast, interactive, and visually impressive maps and data visualizations using WebGL technology. It lets you turn large sets of data into layers like icons, polygons, and text, which you can view in different ways such as maps or 3D scenes. It works well with popular map providers like Google Maps and Mapbox, and supports easy interaction like clicking and filtering. You can use it simply by adding a script or installing it via npm or Python. This makes it easier for you to build custom, high-performance visualizations quickly and with less coding effort. https://github.com/visgl/deck.gl

#python#gemini#gemini_api#googlesearch#imagen_3#load_balancer#openai_api Gemini Balance is a Python-based tool that acts as a proxy and load balancer for the Google Gemini API, letting you manage multiple API keys efficiently by rotating them automatically to improve availability and concurrency. It supports both Gemini and OpenAI API formats, enabling chat, image generation, image editing, and web search features. You can monitor key status in real-time, configure settings visually without restarting, and use proxies for special network needs. It also supports Docker deployment for easy setup. This helps you reliably use Gemini API services with better performance, flexibility, and monitoring, saving you time and effort in managing API keys and requests. https://github.com/snailyp/gemini-balance

#python LMCache is a tool that makes large language models (LLMs) faster and more efficient by storing and reusing parts of their memory (KV caches) across different devices like GPUs, CPUs, and disks. This reduces the time it takes to get the first response and saves computing power, especially when handling long texts or repeated queries. When combined with vLLM, it can cut delays by 3 to 10 times, making multi-round question answering and retrieval-augmented generation much quicker. This means you get faster AI responses and lower costs, improving your experience with LLM-based applications. It’s easy to install and supported by detailed guides and a helpful community. https://github.com/LMCache/LMCache

#cplusplus#cpp#hacktoberfest#iot#iot_device#iot_edge#microcontroller#microsoft_for_beginners#python#raspberry_pi#rpi You can learn the basics of the Internet of Things (IoT) through a free 12-week course with 24 lessons that guide you step-by-step in building real projects like plant monitoring, vehicle tracking, and smart cooking timers. Each lesson includes quizzes, instructions, challenges, and solutions to help you understand sensors, cloud connections, security, and AI on devices. The course uses real hardware or virtual options, making it easy to practice hands-on skills. This project-based learning helps you gain practical IoT knowledge useful for many industries, improving your tech skills and job readiness. https://github.com/microsoft/IoT-For-Beginners

#python#bounty#bugbounty#bypass#cheatsheet#enumeration#hacking#hacktoberfest#methodology#payload#payloads#penetration_testing#pentest#privilege_escalation#redteam#security#vulnerability#web_application Payloads All The Things is a comprehensive collection of useful payloads and bypass techniques for web application security testing and penetration testing. It offers detailed documentation for each vulnerability, including how to exploit it and ready-to-use payloads, plus files for tools like Burp Intruder. You can contribute your own payloads or improvements, making it a collaborative resource. It also links to related projects for internal network and hardware pentesting, and provides learning resources like books and videos. Using this resource helps you efficiently find and test security weaknesses in web applications, improving your pentesting effectiveness and knowledge. https://github.com/swisskyrepo/PayloadsAllTheThings