Showing 13 open source projects for "patterns"

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  • 1
    GenericAgent

    GenericAgent

    Self-evolving autonomous agent framework

    ...The project also focuses on extensibility, allowing developers to plug in custom tools or APIs and tailor agent behavior to specific use cases. By abstracting common agent patterns, it reduces the overhead of building agent systems from scratch. Overall, GenericAgent provides a foundation for scalable and reusable AI agent development.
    Downloads: 2 This Week
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  • 2
    Agent Skills for Context Engineering

    Agent Skills for Context Engineering

    A comprehensive collection of Agent Skills for context engineering

    ...The repository emphasizes context engineering as a discipline, covering why agents fail when context gets too large, too noisy, or poorly structured, and how to mitigate those failure modes with repeatable patterns. It is designed to be used across modern agent environments that support skill folders and structured instructions, so teams can standardize how agents operate instead of relying on ad-hoc prompting.
    Downloads: 1 This Week
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  • 3
    AI Agent Deep Dive

    AI Agent Deep Dive

    AI Agent Source Code Deep Research Report

    AI Agent Deep Dive is a comprehensive educational repository designed to provide a deep and structured understanding of how modern AI agents work, focusing on architecture, workflows, and real-world implementation patterns. It breaks down complex concepts such as planning, tool usage, memory management, and multi-step reasoning into digestible explanations and practical examples. The project is organized as a learning resource rather than a standalone framework, making it particularly useful for developers who want to move beyond surface-level prompt engineering into full agent system design. ...
    Downloads: 0 This Week
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  • 4
    Dash Data Agent

    Dash Data Agent

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

    ...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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  • 5
    ex-skill

    ex-skill

    Distill your ex into an AI Skill

    ex-skill is an experimental AI tooling project that allows users to transform personal memories, particularly past relationships, into interactive AI “skills” that replicate the communication style, personality, and behavioral patterns of a specific individual. The system works by ingesting various forms of personal data such as chat logs, social media content, photos, and user-provided descriptions, then structuring this information into a layered representation that combines memory and persona modeling. It is designed to run within Claude Code environments, where users can generate, manage, and interact with these personalized AI entities through command-based interfaces. ...
    Downloads: 5 This Week
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  • 6
    Scientific Agent Skills

    Scientific Agent Skills

    A set of ready to use Agent Skills for research, science, engineering

    Scientific Agent Skills is an open-source collection of ready-to-use agent skills designed to turn AI coding assistants into stronger research, science, engineering, and analysis partners. It supports any AI agent compatible with the Agent Skills standard, including tools such as Cursor, Claude Code, Codex, and Gemini CLI. The repository includes 135 skills across scientific domains such as genomics, cheminformatics, clinical research, medical imaging, machine learning, physics, materials...
    Downloads: 5 This Week
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  • 7
    Hello-Agents

    Hello-Agents

    Building an Intelligent Agent from Scratch

    ...The project focuses on guiding learners beyond superficial framework usage toward deeper comprehension of agent architecture, reasoning loops, and real-world implementation patterns. It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. ...
    Downloads: 2 This Week
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  • 8
    AutoCoder

    AutoCoder

    A long-running autonomous coding agent powered by the Claude Agent

    Autocoder is an experimental auto-generation engine that transforms high-level prompts or structured descriptions into functioning source code, models, or systems with minimal manual intervention. Rather than hand-writing boilerplate or repetitive patterns, users supply a specification—such as a description of a feature, a function prototype, or a module outline—and Autocoder fills in complete implementations that compile and run. It is built to support iterative refinement: after generating an initial draft, you can provide feedback or corrections, and the system will adjust the output to match evolving intentions. ...
    Downloads: 0 This Week
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  • 9
    Deep Search Agent

    Deep Search Agent

    Implement a concise and clear Deep Search Agent from 0

    ...The project is positioned primarily as a proof of concept for deep research agents rather than a production-ready system. Its architecture highlights agent loops, tool calling, and stepwise execution, which are increasingly important patterns in modern AI automation. Overall, the demo serves as a practical reference for developers exploring autonomous research agents and multi-tool LLM orchestration.
    Downloads: 0 This Week
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  • 10
    Agent Reinforcement Trainer

    Agent Reinforcement Trainer

    Train multi-step agents for real-world tasks using GRPO

    ...The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ART also supports scalable training patterns, observability tools, and integration with hosted platforms like Weights & Biases, and it provides notebooks that demonstrate training on standard benchmarks and tasks.
    Downloads: 0 This Week
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  • 11
    AI Agents Masterclass

    AI Agents Masterclass

    Follow along with my AI Agents Masterclass videos

    AI Agents Masterclass is an educational open-source repository designed to teach developers how to build, train, and deploy intelligent AI agents using modern tooling and workflow patterns. The project includes structured lessons, code examples, and practical exercises that cover foundational concepts like prompt engineering, chaining agents, tool usage, plan execution, evaluation, and safety considerations. It breaks down how autonomous agents interact with external systems, handle iterative reasoning, and integrate with third-party services or APIs to perform real tasks — for example, web search, browsing, scheduling, or coding assistance. ...
    Downloads: 0 This Week
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  • 12
    Live Agent Studio

    Live Agent Studio

    Open source AI Agents hosted on the oTTomator Live Agent Studio

    Live Agent Studio is a curated repository of open-source AI agents associated with the oTTomator Live Agent Studio platform, showcasing a variety of agent implementations that illustrate how autonomous and semi-autonomous tools can be constructed using modern AI frameworks. Each agent in the collection is designed for a specific use case — such as content summarization, task automation, travel planning, or RAG workflows — and is provided with the code or configuration needed to explore and...
    Downloads: 0 This Week
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  • 13
    Pal

    Pal

    A personal context-agent that learns how you work

    ...The agent can perform web research, summarize information, and store insights so that useful discoveries are not lost across conversations or sessions. Over time, the agent learns from interactions, remembers patterns that worked well, and applies those learnings to similar tasks in the future, allowing it to improve without requiring additional model training.
    Downloads: 0 This Week
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