#python #agent #agentic_ai #grpo #kimi_ai #llms #lora #qwen #qwen3 #reinforcement_learning #rl
ART is a tool that helps you train smart agents for real-world tasks using reinforcement learning, especially with the GRPO method. The standout feature is RULER, which lets you skip the hard work of designing reward functions by using a large language model to automatically score how well your agent is doing—just describe your task, and RULER takes care of the rest. This makes building and improving agents much faster and easier, works for any task, and often performs as well as or better than hand-crafted rewards. You can install ART with a simple command and start training agents right away, even on your own computer or with cloud resources.
https://github.com/OpenPipe/ART
ART is a tool that helps you train smart agents for real-world tasks using reinforcement learning, especially with the GRPO method. The standout feature is RULER, which lets you skip the hard work of designing reward functions by using a large language model to automatically score how well your agent is doing—just describe your task, and RULER takes care of the rest. This makes building and improving agents much faster and easier, works for any task, and often performs as well as or better than hand-crafted rewards. You can install ART with a simple command and start training agents right away, even on your own computer or with cloud resources.
https://github.com/OpenPipe/ART
GitHub
GitHub - OpenPipe/ART: Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on…
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, and more! - OpenPipe/ART
#typescript #agentic_ai #ai #flow_based_programming #visual_ai #visual_programming #visual_programming_editor #visual_programming_language #vscode #vscode_extension
Flyde is a free, open-source tool that lets you build and manage AI workflows visually inside your existing TypeScript codebase using VS Code. It helps you create, test, and improve complex backend AI logic like AI agents and prompt chains with a clear visual interface, making it easier for both developers and non-developers to collaborate. Flyde integrates directly with your code and tools, so you keep full control while simplifying development and debugging. This saves time, reduces errors, and improves teamwork on AI-powered backend projects.
https://github.com/flydelabs/flyde
Flyde is a free, open-source tool that lets you build and manage AI workflows visually inside your existing TypeScript codebase using VS Code. It helps you create, test, and improve complex backend AI logic like AI agents and prompt chains with a clear visual interface, making it easier for both developers and non-developers to collaborate. Flyde integrates directly with your code and tools, so you keep full control while simplifying development and debugging. This saves time, reduces errors, and improves teamwork on AI-powered backend projects.
https://github.com/flydelabs/flyde
GitHub
GitHub - flydelabs/flyde: Open-source Visual programming for backend logic that integrates with existing codebases. Flyde bridges…
Open-source Visual programming for backend logic that integrates with existing codebases. Flyde bridges the gap between technical and non-technical team members. Product managers, designers, and ba...
#python #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
The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects.
https://github.com/google/adk-python
The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects.
https://github.com/google/adk-python
GitHub
GitHub - google/adk-python: An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI…
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-python
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#typescript #agentic_ai #agents #ai #claude #copilot #cursor #git #llm #mcp
GitMCP is a free, open-source service that connects AI assistants to any GitHub project’s latest documentation and code using the Model Context Protocol (MCP). This means your AI can access up-to-date, accurate information directly from the source, reducing mistakes and hallucinations when coding or asking questions about libraries, even new or niche ones. You just add a GitMCP URL for your chosen GitHub repo to your AI tool, and it fetches relevant docs and code smartly without setup hassle. This helps you get reliable code examples and API usage instantly, improving your coding efficiency and accuracy. It’s private, easy to use, and works with many AI assistants.
https://github.com/idosal/git-mcp
GitMCP is a free, open-source service that connects AI assistants to any GitHub project’s latest documentation and code using the Model Context Protocol (MCP). This means your AI can access up-to-date, accurate information directly from the source, reducing mistakes and hallucinations when coding or asking questions about libraries, even new or niche ones. You just add a GitMCP URL for your chosen GitHub repo to your AI tool, and it fetches relevant docs and code smartly without setup hassle. This helps you get reliable code examples and API usage instantly, improving your coding efficiency and accuracy. It’s private, easy to use, and works with many AI assistants.
https://github.com/idosal/git-mcp
GitHub
GitHub - idosal/git-mcp: Put an end to code hallucinations! GitMCP is a free, open-source, remote MCP server for any GitHub project
Put an end to code hallucinations! GitMCP is a free, open-source, remote MCP server for any GitHub project - idosal/git-mcp
#typescript #agent #agentic_ai #agents #ai #ai_agents #ai_tools #anthropic #automation #bytebot #computer_use #computer_use_agent #cua #desktop #desktop_automation #docker #gemini #llm #mcp #openai
Bytebot is an open-source AI desktop agent that acts like a virtual employee with its own computer, able to use real applications, browse websites, handle passwords, and process documents automatically. You just describe tasks in plain English, and Bytebot completes them by clicking, typing, downloading files, organizing data, and running complex workflows across multiple programs. It runs locally on your own infrastructure, ensuring privacy and full control, and supports many AI models. This helps you save time by automating repetitive or complex tasks without scripting, improving efficiency and accuracy in business, research, or development work.
https://github.com/bytebot-ai/bytebot
Bytebot is an open-source AI desktop agent that acts like a virtual employee with its own computer, able to use real applications, browse websites, handle passwords, and process documents automatically. You just describe tasks in plain English, and Bytebot completes them by clicking, typing, downloading files, organizing data, and running complex workflows across multiple programs. It runs locally on your own infrastructure, ensuring privacy and full control, and supports many AI models. This helps you save time by automating repetitive or complex tasks without scripting, improving efficiency and accuracy in business, research, or development work.
https://github.com/bytebot-ai/bytebot
GitHub
GitHub - bytebot-ai/bytebot: Bytebot is a self-hosted AI desktop agent that automates computer tasks through natural language commands…
Bytebot is a self-hosted AI desktop agent that automates computer tasks through natural language commands, operating within a containerized Linux desktop environment. - bytebot-ai/bytebot
#typescript #agentic_ai #agentic_workflow #agents #ai #approval_process #escalation_policy #function_calling #human_as_tool #human_in_the_loop #humanlayer #llm #llms
HumanLayer helps you safely use AI agents to automate important tasks by ensuring a human always reviews high-risk actions, like sending emails or changing private data. This is crucial because AI can make mistakes or create wrong outputs, and some tasks are too sensitive to trust AI alone. HumanLayer’s tools guarantee human oversight in these cases, so you get the benefits of AI automation without risking errors in critical work. This makes AI more reliable and useful for automating complex workflows while keeping control and safety in your hands.
https://github.com/humanlayer/humanlayer
HumanLayer helps you safely use AI agents to automate important tasks by ensuring a human always reviews high-risk actions, like sending emails or changing private data. This is crucial because AI can make mistakes or create wrong outputs, and some tasks are too sensitive to trust AI alone. HumanLayer’s tools guarantee human oversight in these cases, so you get the benefits of AI automation without risking errors in critical work. This makes AI more reliable and useful for automating complex workflows while keeping control and safety in your hands.
https://github.com/humanlayer/humanlayer
GitHub
GitHub - humanlayer/humanlayer: The best way to get AI coding agents to solve hard problems in complex codebases.
The best way to get AI coding agents to solve hard problems in complex codebases. - humanlayer/humanlayer
#kotlin #agentframework #agentic_ai #agents #ai #aiagentframework #android_ai #anthropic #generative_ai #java #jvm #kotlin #ktor #llm #mcp #ollama #openai #spring
Koog is a Kotlin-based open-source framework that helps you build AI agents fully in Kotlin, making it easy to create smart assistants that can use tools, manage complex tasks, and remember past interactions. It supports multiple AI models like OpenAI and Google, runs on many platforms (JVM, JavaScript, iOS), and offers features like real-time streaming, custom tools, and efficient memory use. Koog also provides debugging tools, flexible workflows, and scales from simple chatbots to enterprise systems. Using Koog lets you develop powerful, maintainable AI agents quickly and naturally within the Kotlin ecosystem, benefiting your projects with speed, flexibility, and strong integration options.
https://github.com/JetBrains/koog
Koog is a Kotlin-based open-source framework that helps you build AI agents fully in Kotlin, making it easy to create smart assistants that can use tools, manage complex tasks, and remember past interactions. It supports multiple AI models like OpenAI and Google, runs on many platforms (JVM, JavaScript, iOS), and offers features like real-time streaming, custom tools, and efficient memory use. Koog also provides debugging tools, flexible workflows, and scales from simple chatbots to enterprise systems. Using Koog lets you develop powerful, maintainable AI agents quickly and naturally within the Kotlin ecosystem, benefiting your projects with speed, flexibility, and strong integration options.
https://github.com/JetBrains/koog
GitHub
GitHub - JetBrains/koog: Koog is the official Kotlin framework for building predictable, fault-tolerant and enterprise-ready AI…
Koog is the official Kotlin framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-brows...
#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
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
GitHub
GitHub - microsoft/agent-framework: A framework for building, orchestrating and deploying AI agents and multi-agent workflows with…
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET. - microsoft/agent-framework
#python #agent #agentic_ai #llm #mlops #reinforcement_learning
Agent Lightning is a tool that helps improve AI agents using reinforcement learning. It allows you to train your agents without making big changes to their code, which is very convenient. You can use it with many different frameworks like LangChain or OpenAI Agent SDK. It also supports various training methods, including reinforcement learning and automatic prompt optimization. This means you can make your agents better at their tasks without a lot of extra work.
https://github.com/microsoft/agent-lightning
Agent Lightning is a tool that helps improve AI agents using reinforcement learning. It allows you to train your agents without making big changes to their code, which is very convenient. You can use it with many different frameworks like LangChain or OpenAI Agent SDK. It also supports various training methods, including reinforcement learning and automatic prompt optimization. This means you can make your agents better at their tasks without a lot of extra work.
https://github.com/microsoft/agent-lightning
GitHub
GitHub - microsoft/agent-lightning: The absolute trainer to light up AI agents.
The absolute trainer to light up AI agents. Contribute to microsoft/agent-lightning development by creating an account on GitHub.
#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
https://github.com/google/adk-js
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
GitHub
GitHub - google/adk-js
Contribute to google/adk-js development by creating an account on GitHub.