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Source channel @githubtrending · Post #15038 · Aug 8

#python#agent#agentic#agentic_ai#agents#agents_sdk#ai#ai_agents#aiagentframework#genai#genai_chatbot#llm#llms#multi_agent#multi_agent_systems#multi_agents#multi_agents_collaboration The Agent Development Kit (ADK) is an open-source Python toolkit that helps you easily build, test, and deploy smart AI agents, from simple helpers to complex multi-agent systems. It lets you write agent logic in Python, use many built-in or custom tools, and organize multiple agents to work together. You can deploy agents anywhere, including Google Cloud, and evaluate their performance with built-in tools. ADK supports flexible workflows and works with various AI models, not just Google’s. This means you get full control and flexibility to create powerful AI applications that fit your needs, speeding up development and making it easier to manage AI projects. https://github.com/google/adk-python

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djangoproject

@djangoproject · Post #77 · 07/05/2016, 07:46 AM

https://docs.python.org/2/library/logging.html This module defines functions and classes which implement a flexible event logging system for applications and libraries. The key benefit of having the #logging_API provided by a standard library module is that all Python modules can participate in logging, so your application log can include your own messages integrated with messages from third-party modules. The module provides a lot of functionality and flexibility. If you are unfamiliar with #logging, the best way to get to grips with it is to see the tutorials (see the links on the right). The basic classes defined by the module, together with their functions, are listed below. #Loggers expose the interface that application code directly uses. Handlers send the log records (created by loggers) to the appropriate destination. Filters provide a finer grained facility for determining which log records to output. Formatters specify the layout of log records in the final output.