Search Results for "agent"
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26 projects for "agent" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing agent activities. -
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AG2
Framework for building and orchestrating multi-agent AI systems
...It provides abstractions that allow developers to define agents with distinct roles, responsibilities, and communication patterns, enabling collaborative problem-solving workflows. AG2 focuses on making multi-agent systems more accessible by simplifying how agents are configured, connected, and executed. It includes mechanisms for agent-to-agent interaction, task delegation, and iterative reasoning, which are essential for building advanced AI-driven applications. AG2 is intended for developers experimenting with autonomous systems, research prototypes, or production-grade agent pipelines. ... -
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kagent
Kubernetes native framework for building AI agents
Kagent is a Kubernetes-native framework for building, deploying, and operating AI agents as first-class cloud-native workloads. It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. ... -
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OpenManus
Open-source AI agent framework
...OpenManus supports integration with external tools, APIs, and environments, making it suitable for real-world automation workflows. It is built to be flexible and extensible, enabling customization of agent behaviors, tools, and reasoning strategies. Overall, OpenManus provides a foundation for creating more capable, autonomous AI systems that can handle dynamic and goal-driven tasks. -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. -
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PilottAI
Python framework for building scalable multi-agent systems
pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers. -
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GitClaw
A universal git-native AI agent framework
GitClaw is an open-source framework for building AI agents whose entire identity, configuration, memory, and capabilities live inside a Git repository. Instead of storing agent state in databases or application code, the framework treats a repository itself as the agent’s environment, allowing developers to version, inspect, and collaborate on agents using standard Git workflows. The system defines structured files that represent the agent’s personality, rules, configuration, and operational logic, enabling transparent control over how the agent behaves. ... -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ... -
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eve
The Framework for Building Agents
eve is Vercel’s open-source framework for building, running, and scaling durable backend AI agents. It uses a filesystem-first model where an agent is defined as a directory of files, making the project structure itself the agent contract. The framework is designed to include production concerns from the start instead of leaving developers to assemble durability, sandboxing, approvals, and deployment separately. Eve supports durable execution, sandboxed compute, human-in-the-loop approvals, subagents, long-running work, and Vercel-native deployment. ... -
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SwarmZero
SwarmZero's SDK for building AI agents, swarms of agents and much more
SwarmZero is an open-source platform designed for deploying and managing autonomous robot swarms. It enables collective coordination, decentralized decision-making, and real-time collaboration among large groups of autonomous agents, focusing on multi-robot systems and research in swarm robotics. -
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AgentScope Java
Agent-Oriented Programming for Building LLM Applications
AgentScope Java is an agent-oriented programming framework that enables Java developers to build intelligent, LLM-powered applications using a dynamic reasoning-acting (ReAct) paradigm. It provides a comprehensive toolkit for creating autonomous agents that can plan, execute, and adjust complex workflows, making decisions about which tools to invoke and how to solve multi-step problems. -
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GitAgent
A framework-agnostic, git-native standard for defining AI agents
GitAgent is an open standard and toolkit for defining portable AI agents using Git repositories as their foundational structure. The core idea behind the project is that an AI agent can be fully described by a set of files stored in a repository, allowing developers to clone the repository and instantly obtain a runnable agent. Unlike many frameworks that tightly couple agents to specific ecosystems, GitAgent is designed to be framework-agnostic so that the same agent definition can operate across multiple platforms and AI tooling environments. ... -
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AutoGen
An Open-Source Programming Framework for Agentic AI
...AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides multi-agent conversation framework as a high-level abstraction. With this framework, one can conveniently build LLM workflows. AutoGen offers a collection of working systems spanning a wide range of applications from various domains and complexities. AutoGen supports enhanced LLM inference APIs, which can be used to improve inference performance and reduce cost. -
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VoltAgent
Open Source TypeScript AI Agent Framework
...VoltAgent is an open source TypeScript framework that acts as this essential toolkit. It simplifies the development of AI agent applications by providing modular building blocks, standardized patterns, and abstractions. Whether you're creating chatbots, virtual assistants, automated workflows, or complex multi-agent systems, VoltAgent handles the underlying complexity, allowing you to focus on defining your agents' capabilities and logic. -
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AgentField
Build and run AI agents like microservices
...Developers define agents as typed functions, and the platform automatically handles orchestration, communication, identity, and execution, allowing agents to behave like APIs within a broader system architecture. The framework includes built-in support for asynchronous execution, long-running processes, and multi-agent coordination, enabling complex workflows that go far beyond simple prompt-response interactions. It also introduces strong identity and governance mechanisms, such as cryptographic identities and policy enforcement, ensuring that agents can operate securely. -
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NVIDIA AgentIQ
The NVIDIA AgentIQ toolkit is an open-source library
NVIDIA AgentIQ is an open-source toolkit designed to efficiently connect, evaluate, and accelerate teams of AI agents. It provides a framework-agnostic platform that integrates seamlessly with various data sources and tools, enabling developers to build composable and reusable agentic workflows. By treating agents, tools, and workflows as simple function calls, AgentIQ facilitates rapid development and optimization of AI-driven applications, enhancing collaboration and efficiency in complex... -
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Mastra
The TypeScript AI agent framework
Mastra is a TypeScript-first framework for building AI-powered applications and agents, designed to take projects from prototype to production on a modern JavaScript/TypeScript stack. It integrates cleanly with React, Next.js, and Node-based backends, but can also run as a standalone server, giving teams flexibility in how they deploy their AI logic. At its core, Mastra provides abstractions for agents, workflows, tools, memory, retrieval, and model routing, so developers can focus on... -
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Agentic Commerce Protocol (ACP)
Interaction model for connecting buyers to complete purchases
...Merchants remain the merchant-of-record—orders, fraud controls, payment authorization/capture, refunds, and post-purchase communication all stay on their systems while the agent surfaces status to the buyer. -
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Alan AI
In-App assistant SDK to build a multimodal conversational UX websites
Quickly add voice to your app with the Alan Platform. Create an in-app voice assistant to enable human-like conversations and provide a personalized voice experience for every user. Alan is a conversational voice AI platform that lets you create an intelligent voice assistant for your app. It offers all the necessary tools to design, embed, and host your voice solutions. A powerful web-based IDE where you can write, test and debug dialog scenarios for your voice assistant or chatbot. Alan's... -
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UCP Python SDK
The official Python SDK for UCP
UCP Python SDK repository for the Universal Commerce Protocol (UCP) delivers an official Python client library that simplifies building UCP-compliant applications in Python. UCP itself is a modern, open-source standard that empowers seamless commerce interactions between platforms, AI agents, merchants, and payment providers without requiring bespoke integrations for every participant in the commerce ecosystem. This SDK provides Pydantic models for UCP schemas, making it easy for Python... -
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Universal Commerce Protocol (UCP)
The common language for platforms, agents and businesses.
Universal Commerce Protocol (UCP) is an open standard designed to unify how platforms, businesses, and payment providers interact across the modern commerce ecosystem. It provides a common language that eliminates fragmented, custom integrations and enables seamless interoperability between diverse commerce systems. Built for an increasingly agentic web, UCP supports AI-driven platforms that can discover products, manage carts, and complete transactions securely on a user’s behalf. Its... -
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rLLM
Democratizing Reinforcement Learning for LLMs
rLLM is an open-source framework for building and training post-training language agents via reinforcement learning — that is, using reinforcement signals to fine-tune or adapt language models (LLMs) into customizable agents for real-world tasks. With rLLM, developers can define custom “agents” and “environments,” and then train those agents via reinforcement learning workflows, possibly surpassing what vanilla fine-tuning or supervised learning might provide. The project is designed to... -
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OWL
Optimized Workforce Learning for General Multi-Agent Assistance
Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. OWL (Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation) is an advanced framework designed to enhance multi-agent collaboration, improving task automation across various domains. By utilizing dynamic agent interactions, OWL aims to streamline and optimize complex workflows, making AI collaboration more natural, efficient, and adaptable. ... -
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dlric
Fork of OpenClaw at 19/march/2026 to fix bugs and enhancements
Fork of OpenClaw at 19/march/2026 to fix bugs and enhancements This is our contribution to the project, but notice that I am new to typescript then take easy with me This is not available at github because as anyone knows my github account was blocked by Microsoft since 2021 (without reason...) Hope to release the first release in a few hours as soon I catchup with typescript My github account is maria901, if you can unlock it I say thanks Now back to the code -
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SuperAGI
A dev-first open source autonomous AI agent framework
...Agents typically learn and improve their performance over time with feedback loops. Run multiple agents simultaneously to improve efficiency and productivity. Connect to multiple Vector DBs to enhance your agent’s performance. Each agent is unique, use different models of your choice. Get insights into your agent’s performance and optimize accordingly. Control token usage to manage costs effectively. Enable your agents to learn and adapt by storing their memory. Get notified when agents get stuck in the loop, and provide proactive resolution. Read and store files generated by Agents.
