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динамические шаблоны

  • Llamator is an open-source JavaScript framework that builds modular autonomous AI agents with memory, tools, and dynamic prompts.
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    What is Llamator?
    Llamator is an open-source JavaScript library that enables developers to build autonomous AI agents by combining memory modules, tool integrations, and dynamic prompt templates in a unified pipeline. It orchestrates planning, action execution, and reflection loops to handle multi-step tasks, supports multiple LLM providers, and allows custom tool definitions for API calls or data processing. With Llamator, you can rapidly prototype chatbots, personal assistants, and automated workflows within web or Node.js applications, leveraging a modular architecture for easy extension and testing.
    Llamator Core Features
    • Modular agent pipeline (plan, act, reflect)
    • Memory management for context retention
    • Custom tool integration for API calls
    • Dynamic prompt templates
    • Multi-LLM provider support
    Llamator Pro & Cons

    The Cons

    No pricing information available indicating potential unclear commercial support.
    No native mobile or browser extensions available.
    May require advanced knowledge to fully utilize custom attacks and client configurations.

    The Pros

    Supports multiple clients including LangChain and OpenAI-like APIs.
    Allows custom attacks and datasets for comprehensive testing.
    Wide range of attacks on LLMs, RAGs, Agents, and VLMs in multiple languages.
    Provides detailed history and report generation in common formats.
    Aligns with OWASP vulnerability classifications ensuring security focus.
    Open source with active community on Telegram.
  • An open-source Python framework to build LLM-driven agents with memory, tool integration, and multi-step task planning.
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    What is LLM-Agent?
    LLM-Agent is a lightweight, extensible framework for building AI agents powered by large language models. It provides abstractions for conversation memory, dynamic prompt templates, and seamless integration of custom tools or APIs. Developers can orchestrate multi-step reasoning processes, maintain state across interactions, and automate complex tasks such as data retrieval, report generation, and decision support. By combining memory management with tool usage and planning, LLM-Agent streamlines the development of intelligent, task-oriented agents in Python.
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