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Comprehensive flujos de trabajo asincrónicos Tools for Every Need

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flujos de trabajo asincrónicos

  • AI-Agents

    A modular Python framework to build autonomous AI agents with LLM-driven planning, memory management, and tool integration.
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    What is AI-Agents?
    AI-Agents provides a flexible agent architecture that orchestrates language model planners, persistent memory modules, and pluggable toolkits. Developers define tools for HTTP requests, file operations, and custom logic, then configure an LLM planner to decide which tool to invoke. Memory stores context and conversation history. The framework handles asynchronous execution, error recovery, and logging, enabling rapid prototyping of intelligent assistants, data analyzers, or automation bots without reinventing core orchestration logic.
    AI-Agents Core Features
    • Modular planner‐executor architecture
    • LLM-driven decision planning
    • Persistent conversation memory
    • Pluggable custom tool integration
    • Asynchronous task orchestration
    • Error handling and retry logic
    • Detailed execution logging

  • Pydantic AI

    Pydantic AI offers a Python framework to declaratively define, validate, and orchestrate AI agents’ inputs, prompts, and outputs.
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    What is Pydantic AI?
    Pydantic AI uses Pydantic models to encapsulate AI agent definitions, enforcing type-safe inputs and outputs. Developers declare prompt templates as model fields, automatically validating user data and agent responses. The framework offers built-in error handling, retry logic, and function‐calling support. It integrates with popular LLMs (OpenAI, Azure, Anthropic, etc.), supports asynchronous workflows, and enables modular agent composition. With clear schemas and validation layers, Pydantic AI reduces runtime errors, simplifies prompt management, and accelerates the creation of robust, maintainable AI agents.
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