Showing 13 open source projects for "define"

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  • 1
    OpenAI Agents (Python)

    OpenAI Agents (Python)

    A lightweight, powerful framework for multi-agent workflows

    openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling.
    Downloads: 1 This Week
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  • 2
    AgentForge

    AgentForge

    Extensible AGI Framework

    AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications.
    Downloads: 1 This Week
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  • 3
    LangGraph

    LangGraph

    Build resilient language agents as graphs

    LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features.
    Downloads: 5 This Week
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  • 4
    CrewAI

    CrewAI

    Framework for orchestrating role-playing, autonomous AI agents

    Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI...
    Downloads: 5 This Week
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  • Enterprise-grade ITSM, for every business Icon
    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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  • 5
    VoltAgent

    VoltAgent

    Open Source TypeScript AI Agent Framework

    An AI Agent Framework provides the foundational structure and tools needed to build applications powered by autonomous agents. These agents, often driven by Large Language Models (LLMs), can perceive their environment, make decisions, and take actions to achieve specific goals. Building such agents from scratch involves managing complex interactions with LLMs, handling state, connecting to external tools and data, and orchestrating workflows. VoltAgent is an open source TypeScript framework...
    Downloads: 1 This Week
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  • 6
    AgentField

    AgentField

    Build and run AI agents like microservices

    ...Instead of treating agents as isolated scripts or prototypes, the system elevates them to first-class infrastructure components that can be deployed, orchestrated, and managed at scale across distributed environments. 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. ...
    Downloads: 0 This Week
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  • 7
    OpenSage

    OpenSage

    An agent framework that enables AI to create their own agent

    OpenSage is an emerging open-source AI agent development framework designed to automate the creation, orchestration, and evolution of intelligent agents through a self-programming paradigm. Unlike traditional agent frameworks that require developers to manually define workflows, tools, and structures, OpenSage introduces a system where large language models can dynamically generate their own agent architectures, including sub-agents, toolchains, and execution strategies. The framework is built around the concept of an Agent Development Kit (ADK), providing structured components for memory, reasoning, and task decomposition while allowing agents to iteratively improve their own design. ...
    Downloads: 0 This Week
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  • 8
    GitAgent

    GitAgent

    A framework-agnostic, git-native standard for defining AI agents

    ...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. The repository typically includes a manifest file that describes the agent’s configuration, along with additional files that define behavior, skills, and integrations with external tools. This structure allows organizations to treat agents similarly to software projects, with version control, branching, auditing, and collaboration handled through Git.
    Downloads: 0 This Week
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  • 9
    rLLM

    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 support large-scale language models (including support for big models via integrated training backends), making it relevant for state-of-the-art research and production use. ...
    Downloads: 0 This Week
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    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

    Build, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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  • 10
    Habitat-Lab

    Habitat-Lab

    A modular high-level library to train embodied AI agents

    ...Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. Configuring and instantiating a diverse set of embodied agents, including commercial robots and humanoids, specifying their sensors and capabilities. Providing algorithms for single and multi-agent training (via imitation or reinforcement learning, or no learning at all as in SensePlanAct pipelines), as well as tools to benchmark their performance on the defined tasks using standard metrics.
    Downloads: 0 This Week
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  • 11
    Agent Payments Protocol (AP2)

    Agent Payments Protocol (AP2)

    Building a Secure and Interoperable Future for AI-Driven Payments

    AP2 is a project released by Google’s “Agentic Commerce” initiative, focusing on a protocol and reference implementation for agent-driven or AI-mediated payments. In effect, AP2 aims to define a secure, interoperable protocol that allows software agents to act on behalf of users—making payments or shopping decisions autonomously—while preserving necessary security, auditability, and trust. The repository contains sample scenarios (in Python, Android, etc.) that illustrate how agents, servers, and payments flows would work under the protocol. ...
    Downloads: 0 This Week
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  • 12

    superplan-plugin

    Superplan is a CLI-first execution system.

    ...Instead of vague plans, chat history, or TODO lists, Superplan forces work into clear, step-by-step tasks that agents can execute, track, and resume at any time. The CLI is designed for agents to follow, not for humans to run manually. You define the work; your agent executes it through Superplan's structured runtime.
    Downloads: 0 This Week
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  • 13
    ChatArena

    ChatArena

    ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments

    ChatArena is a library that provides multi-agent language game environments and facilitates research about autonomous LLM agents and their social interactions.
    Downloads: 1 This Week
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