A View of an AI Agent's Architecture by Layers

A view of an AI Agent's architecture by layers

Taken from Jiweil Liu's kaggle post on: Building GPU-Accelerated Data Science Agents

Credit:https://www.kaggle.com/writeups/jiweiliu/gpu-accelerated-data-science-agent?linkId=100000392125201

Additional comments:

Understanding the structural foundation of AI agents is essential for developers aiming to build high performance systems. This diagram illustrates a modular architecture where the central Agent acts as the orchestrator. The Agent interacts directly with an LLM API to process logic and utilizes specific Tools to execute external functions. Beneath this layer, the LLM Inference Server provides the necessary backend support. This server relies on a combination of a robust Runtime environment and model Weights to deliver accurate, GPU accelerated responses. By separating these concerns, developers can optimize each component individually for greater efficiency and scalability in data science workflows. Credit for this visualization goes to Jiweil Liu, whose work on GPU Accelerated Data Science Agents provides a clear roadmap for modern AI development.