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GenAI with Python: Coding Agents
Build a Data Scientist AI that can query db with SQL, analyze data with Python, write reports with HTML, and do Machine Learning (No GPU, No APIKEY)
(Unless otherwise noted, all images are by the author)
Intro
In Generative AI, Agents are AI systems designed to process sequential reasoning, with the option of executing external tools (i.e. database query, web search) in case the LLM’s general-purpose knowledge base isn’t enough. To put it simply, a normal AI Chatbot generates random text when it doesn’t know how to answer a question. On the other hand, an Agent would activate its tools to fill the gap and give a specific response.
More precisely, AI Agents are capable of autonomous decision-making and action-taking to achieve specific goals, within their environment. They differ from LLMs in their ability to interact and perform actual tasks, not just process text. LLMs excel in natural language understanding and generation, and don’t execute tasks autonomously outside of text-based responses. On the other hand, AI Agents can adapt, learn, and operate with a higher degree of independence, making them suitable for dynamic applications beyond text processing.
