Showing 8 open source projects for "structure"

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    AIBuildAI

    AIBuildAI

    An AI agent that automatically builds AI models

    AI-Build-AI is an open-source framework focused on enabling autonomous systems that can design, generate, and improve AI applications with minimal human intervention. The project explores recursive AI development, where models are used not only as tools but as builders capable of constructing other AI systems, workflows, or components. It provides a structured environment for orchestrating agents that can plan, execute, and refine tasks such as code generation, system design, and iterative...
    Downloads: 3 This Week
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    PixelRAG

    PixelRAG

    The beginning of scalable pixel-native search

    ...It renders web pages, PDFs, and images into screenshot tiles, then performs retrieval over those visual representations. This approach preserves layout, tables, charts, diagrams, infographics, and other visual structure that traditional HTML or text parsing can miss. The project includes tools for rendering, chunking, embedding, indexing, and serving visual search indexes. It also provides a hosted API with a prebuilt Wikipedia index, plus local pipelines for building indexes from custom documents. PixelRAG can be used with Claude through the pixelbrowse skill, giving agents the ability to inspect pages visually instead of relying only on raw markup.
    Downloads: 1 This Week
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  • 3
    Agent Skills

    Agent Skills

    Specification and documentation for Agent Skills

    agentskills is the specification and documentation repository for the Agent Skills open format, which defines a standardized way to package capabilities that AI agents can discover and use. A “skill” is treated as a foldered bundle containing instructions, optional scripts, and supporting resources, so agents can reliably apply a workflow or expertise area when it becomes relevant. The central goal is portability: you can write a skill once and reuse it across different agent runtimes and...
    Downloads: 2 This Week
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  • 4
    Agently

    Agently

    AI Agent Application Development Framework

    Build AI agent native application in very little code. Easy to interact with AI agents in code using structure data and chained-calls syntax. Enhance AI Agent using plugins instead of rebuilding a whole new agent. Agently is a development framework that helps developers build AI agent native applications really fast. You can use and build AI agents in your code in an extremely simple way.
    Downloads: 0 This Week
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  • 5
    Harmonist

    Harmonist

    Portable AI agent orchestration with mechanical protocol enforcement

    ...The project uses Python, has no runtime dependencies beyond the standard library, and is positioned as a drop-in agent coordination pack. Its purpose is to bring structure, review discipline, and repeatable process control to AI-assisted development.
    Downloads: 0 This Week
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  • 6
    Khazix Skills

    Khazix Skills

    Digital Life Kazik Open Source AI Skills Collection

    Khazix Skills project is an automation framework designed to transform GitHub repositories into structured, reusable AI agent skills. It acts as a pipeline that analyzes a repository’s metadata, extracts relevant information such as README content and commit hashes, and converts it into a standardized skill format that can be integrated into agent ecosystems. The system emphasizes lifecycle management by embedding versioning, traceability, and metadata directly into generated skill files,...
    Downloads: 0 This Week
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  • 7
    Dash Data Agent

    Dash Data Agent

    Self-learning data agent that grounds its answers in layers of content

    Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live runtime context — to generate SQL queries that are both technically correct and semantically meaningful. The system then executes those queries against a database and interprets the results, returning human-friendly insights not just raw rows, while learning from errors and successes to reduce repeated mistakes.
    Downloads: 0 This Week
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  • 8
    Multi-Agent Particle Envs

    Multi-Agent Particle Envs

    Code for a multi-agent particle environment used in a paper

    ...Scenarios are designed to model cooperative, competitive, and mixed interactions among agents, making it useful for testing algorithms in multi-agent settings. The project includes built-in scenarios such as navigation to landmarks, cooperative tasks, and adversarial setups. Although archived, its concepts and code structure remain foundational for more advanced libraries like PettingZoo, which extended and maintained this environment.
    Downloads: 1 This Week
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