GitHub Trends

#mdx#bilateral_teleoperation#force_feedback#genesis#gravity_compensation#humanoid_robot#imitation_learning#machine_learning#moveit2#mujoco#open_source#openarm#python#reinforcement_learning#robot#robot_arm#robotics#ros2#teleoperation OpenArm is a special robot arm that helps with physical AI research. It has 7 degrees of freedom, which means it can move like a human arm. This makes it good for tasks that involve touching or moving things safely around people. The robot is open-source, meaning anyone can build, modify, and use it. This is helpful because it makes advanced robotics available to more people, like researchers and students, without costing too much. A complete system with two arms costs about $6,500, which is much cheaper than similar robots. https://github.com/enactic/openarm

#python **What is nanoGPT?** nanoGPT is a simple and fast way to train medium-sized GPT models. It's based on minGPT but focuses more on speed and ease of use. You can easily train new models or fine-tune existing ones like GPT-2. The code is simple and easy to understand, making it great for developers who want to quickly work with GPT models. It uses popular libraries like PyTorch and Hugging Face's transformers, making it easy to customize and use on different devices, including GPUs and CPUs. **Benefits for Users** Simple code makes it easy to modify and train models. - **Fast Training** Allows users to train new models or fine-tune existing ones. https://github.com/karpathy/nanoGPT

#python#agent#context_engineering#electron#embedding_models#memory#proactive_ai#python#python3#rag#react#vector_database#vision_language_model MineContext is a special AI tool that helps you work more efficiently. It collects information from your computer screen and other sources, then uses this data to give you useful insights, summaries, and reminders. This helps you stay organized and focused on important tasks. MineContext is also very private because it stores all your data on your local device, not in the cloud. It's like having a personal assistant that helps you manage your digital life better. https://github.com/volcengine/MineContext

#python Using NVIDIA H100 GPUs for training large language models (LLMs) offers significant benefits. These GPUs are designed to speed up AI tasks, especially with their Transformer Engine and FP8 precision, which can train models like GPT-3 up to four times faster than previous generations[1][4]. The H100 GPUs are highly efficient and cost-effective, making them ideal for cloud-based environments[2][6]. They also support various AI frameworks, ensuring compatibility and ease of use for developers[7]. This setup allows for faster model convergence and reduced training time, making it a powerful tool for AI research and development. https://github.com/KellerJordan/modded-nanogpt

#python#agents#ai#ai_agents#api#developer_tools#discord#function_calling#integration#llm#mcp#mcp_client#mcp_server#oauth2#open_source Klavis AI helps developers connect AI tools to other services like GitHub, Gmail, and Slack easily. It offers hosted servers that handle authentication and client code automatically, making it simpler to integrate AI with various platforms. This saves time and effort by eliminating the need for custom authentication management and client library maintenance. Users can quickly set up and scale their AI applications without worrying about complex integrations, making it easier to deploy AI-powered workflows securely and efficiently. https://github.com/Klavis-AI/klavis

#python You can set up and run the Gemini 2.5 Computer Use model to automate browser tasks by cloning its repository, creating a Python virtual environment, installing dependencies, and configuring API keys for Gemini or Vertex AI. This model "sees" the browser screen via screenshots and performs actions like clicking or typing, mimicking human interaction. You run it using a command-line script where you give natural language instructions, and it executes them in a browser environment locally or via Browserbase. This helps automate repetitive tasks, testing, data collection, and more, saving time and reducing errors in web workflows. https://github.com/google/computer-use-preview

#python#agents#ai#framework#llm#openai#python The OpenAI Agents SDK is a Python framework that lets you easily build and connect AI agents—smart programs that can talk, use tools, and work together to solve tasks[2][3]. You can turn any Python function into a tool an agent can use, set up safety checks to control what agents do, and automatically pass tasks between different agents when needed[2][4]. The SDK manages conversation history for you, so agents remember past interactions, and it includes tools to track and debug how agents make decisions[2]. This makes it simple to create reliable, customizable AI helpers for things like customer support, research, or automation, with clear oversight and fast development. https://github.com/openai/openai-agents-python

#python Zen MCP Server lets you use your favorite command-line AI tools like Claude Code, Gemini CLI, or Codex CLI together with many AI models (Gemini, OpenAI, Anthropic, and more) in one smooth workflow. It connects these models so they can collaborate, share context, and specialize in tasks like code review, debugging, or planning, making your coding smarter and faster. You stay in control, choosing which AI to use and when, while Zen handles context continuity and model orchestration. This means better code quality, deeper insights, and efficient teamwork from multiple AI experts all within your CLI environment. https://github.com/BeehiveInnovations/zen-mcp-server

#python#security#security_tools#vulnerability#vulnerability_databases#vulnerability_management#vulnerability_scanners OSV is a free, open-source database and toolset that helps you find and manage security vulnerabilities in open source software you use. It collects vulnerability data from many sources, including official advisories and automated scans, and presents it in a clear, machine-readable format. You can use the OSV scanner tool to automatically check your software dependencies for known security issues, helping you fix them quickly. This improves your software’s security by focusing on real risks and making vulnerability management easier and more efficient. OSV also offers APIs and integrates with other tools for automation and alerts. https://github.com/google/osv.dev

#python#agent_framework#agentic_ai#agents#ai#dotnet#multi_agent#orchestration#python#sdk#workflows Microsoft Agent Framework is an open-source toolkit that helps you build and manage AI agents and multi-agent workflows using Python or .NET. It combines the best features of previous Microsoft AI projects to let you create simple chatbots or complex workflows where multiple agents work together. It supports many AI models, connects easily to external tools and APIs, and runs anywhere—on cloud or on-premises. The framework also includes features like human review, workflow checkpointing, and monitoring to make your AI applications reliable and adaptable. This means you can build powerful, flexible AI solutions faster and with less code. https://github.com/microsoft/agent-framework

#python This tool is a Chinese-enhanced AI system for financial trading decisions, supporting A-shares, Hong Kong, and US stock markets. It uses multiple smart agents to analyze fundamentals, technical data, news, and social media, then debates and makes investment suggestions with risk management. You get a fully Chinese interface, real-time progress tracking, and professional reports exportable in Word, PDF, or Markdown. It supports many AI models, including Chinese and global providers, with easy switching and persistent settings. Deployment is simple via Docker or local install. This helps you make smarter, data-driven investment decisions efficiently with AI tailored for Chinese markets. https://github.com/hsliuping/TradingAgents-CN

#python Tunix is an open-source library built on JAX that helps you easily improve large language models after their initial training. It supports fine-tuning with supervised learning, reinforcement learning, and knowledge distillation, making models more accurate and better aligned with user needs. Tunix works efficiently on TPUs and integrates well with JAX tools, allowing you to customize training and scale across devices. It simplifies complex steps like preference tuning by removing the need for separate reward models. Using Tunix, you can tailor AI models for specific tasks, improving their reasoning, accuracy, and response quality for practical applications in fields like healthcare and finance. https://github.com/google/tunix