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análisis de flujos de trabajo

  • An open-source Python library for structured logging of AI agent calls, prompts, responses, and metrics for debugging and audit.
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    What is Agent Logging?
    Agent Logging provides a unified logging framework for AI agent frameworks and custom workflows. It intercepts and records each stage of an agent’s execution—prompt generation, tool invocation, LLM response, and final output—along with timestamps and metadata. Logs can be exported in JSON, CSV, or sent to monitoring services. The library supports customizable log levels, hooks for integration with observability platforms, and visualization tools to trace decision paths. With Agent Logging, teams gain insights into agent behavior, spot performance bottlenecks, and maintain transparent records for auditing.
    Agent Logging Core Features
    • Structured capture of prompts, tool calls, and responses
    • Performance metrics and timestamps for each step
    • Multiple export formats: JSON, CSV, observability streams
    • Customizable log levels and metadata hooks
    • Integration with monitoring and visualization tools
  • Discover user interactions for improved productivity with IBM Task Mining.
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    What is IBM Task Mining?
    IBM Task Mining is a powerful tool designed to discover, monitor, and analyze user interactions on desktops. By capturing detailed frontend activities, it provides insights into workflows that help organizations identify inefficiencies and improve productivity. This tool plays a crucial role in the broader context of process mining, assisting users in understanding how tasks are performed, where they can be optimized, and ultimately driving automation efforts.
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