Showing 11 open source projects for "apache local server"

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  • 1
    Strands Agents

    Strands Agents

    A model-driven approach to building AI agents in just a few lines

    Strands Agents SDK is a model-driven approach to building and running AI agents. It enables the creation of simple conversational assistants to complex autonomous workflows, scaling from local development to production deployment. The SDK is designed to be simple yet powerful, catering to various AI agent development needs.
    Downloads: 1 This Week
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  • 2
    Agents-Flex

    Agents-Flex

    Agents-Flex is an elegant LLM Application Framework like LangChain

    Agents-Flex includes a variety of network protocols for connecting LLMs, such as HTTP, SSE and WS. Its simple and flexible design allows developers to easily connect to various LLMs, including OpenAI, LLama, and other AI. Agents-Flex provides a rich set of development templates and Prompt Frameworks, including FEW-SHOT, CRISPE, BROKE, and ICIO. Developers can also customize their own unique prompt templates. Agents-Flex has a very flexible Function Calling component. It supports local method...
    Downloads: 0 This Week
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  • 3
    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,...
    Downloads: 0 This Week
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  • 4
    Letta

    Letta

    Letta (formerly MemGPT) is a framework for creating LLM services

    Letta is an AI-powered task automation framework designed to handle workflow automation, natural language commands, and AI-driven decision-making.
    Downloads: 0 This Week
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  • 5
    Agent S

    Agent S

    Agent S: an open agentic framework that uses computers like a human

    Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines...
    Downloads: 7 This Week
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  • 6
    RAGapp

    RAGapp

    The easiest way to use Agentic RAG in any enterprise

    The easiest way to use Agentic RAG in any enterprise. As simple to configure as OpenAI's custom GPTs, but deployable in your own cloud infrastructure using Docker. Built using LlamaIndex. Just the RAGapp container doesn't come with any authentication layer by design. This is the task of an API Gateway routing the traffic to RAGapp. This step heavily depends on your cloud provider and the services you use. For a pure Docker Compose environment, you can look at our RAGapp with management UI...
    Downloads: 0 This Week
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  • 7
    Goose

    Goose

    AI coding agent that's more than suggestions - install, execute, edit+

    Goose is an open-source, extensible AI agent that enhances the software development process by going beyond traditional code suggestions. It allows developers to install, execute, edit, and test code with any large language model (LLM), facilitating a more efficient and streamlined workflow. Designed to operate locally within a developer's environment, Goose integrates seamlessly with various tools and platforms, providing a customizable and powerful assistant for coding tasks. Its...
    Downloads: 4 This Week
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  • 8
    Qwen-Agent

    Qwen-Agent

    Agent framework and applications built upon Qwen>=3.0

    Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. Agent workflow can maintain context / memory to perform multi-turn or more complex logic over time....
    Downloads: 3 This Week
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  • 9
    kagent

    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...
    Downloads: 3 This Week
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  • 10
    Agentic Commerce Protocol (ACP)

    Agentic Commerce Protocol (ACP)

    Interaction model for connecting buyers to complete purchases

    ACP is an open, draft specification for letting buyers, their AI agents, and businesses complete purchases through a standardized interaction model. It’s maintained by OpenAI and Stripe and licensed under Apache-2.0, with the goal of being easy to adopt alongside a merchant’s existing commerce stack rather than replacing it. The repository organizes the spec as human-readable RFCs plus machine-readable OpenAPI and JSON Schema definitions, along with worked examples and a changelog so...
    Downloads: 1 This Week
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  • 11
    Shinkai: Local AI Agents

    Shinkai: Local AI Agents

    Shinkai allows you to create advanced AI (local) agents effortlessly

    Shinkai is a free, open-source AI platform that lets anyone create powerful AI agents without coding. These agents can collaborate with each other, handle complex tasks, and operate in decentralized crypto environments. Key Features: - No-Code Agent Creation - Build specialized agents (trading bots, sentiment trackers, etc.) with simple descriptions - Multi-Agent Collaboration - Agents work together to solve complex problems - Crypto Integration - Built-in support for decentralized...
    Downloads: 0 This Week
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