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desarrollo de asistentes de IA

  • Astro Agents is an open-source framework enabling developers to build AI-powered agents with customizable tools, memory, and reasoning.
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    What is Astro Agents?
    Astro Agents provides a modular architecture for building AI agents in JavaScript and TypeScript. Developers can register custom tools for data lookup, integrate memory stores to preserve conversational context, and orchestrate multi-step reasoning workflows. It supports multiple LLM providers such as OpenAI and Hugging Face, and can be deployed as static sites or serverless functions. With built-in observability and extensible plugins, teams can prototype, test, and scale AI-driven assistants without heavy infrastructure overhead.
    Astro Agents Core Features
    • Custom tool registry
    • Modular memory modules
    • Multi-step reasoning workflows
    • LLM provider integrations
    • Conversation history management
    • Secure API handling
    • Plugin extensibility
    Astro Agents Pro & Cons

    The Cons

    Focused on a niche domain which may limit broader applicability
    No information on user interface or ease of use for non-experts
    No clear pricing model or commercial support details available
    Lack of mobile or app store presence limits accessibility options

    The Pros

    Enables collaborative multi-agent hypothesis generation and refinement
    Integrates advanced AI models for deep scientific data analysis
    Designed specifically for complex scientific domains like astrobiology
    Supports structured workflows with distinct agent roles for analysis, planning, and review
    Open source availability promotes transparency and customization
  • Wizard Language is a declarative TypeScript DSL to define multi-step AI agents with prompt orchestration and tool integration.
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    What is Wizard Language?
    Wizard Language is a declarative domain-specific language built on TypeScript for authoring AI assistants as wizards. Developers define intent-driven steps, prompts, tool invocations, memory stores, and branching logic in a concise DSL. Under the hood, Wizard Language compiles these definitions into orchestrated LLM calls, managing context, asynchronous flows, and error handling. It accelerates prototyping of chatbots, data retrieval assistants, and automated workflows by abstracting prompt engineering and state management into reusable components.
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