Generative AI applications are rapidly moving beyond single-turn conversational chatbots toward Autonomous Multi-Tool AI Agents. Instead of just generating static text, modern agents evaluate user prompts, make routing decisions, select specialised external tools, and fetch dynamic real-time data before returning a grounded response.
In this article, we will break down the end-to-end architecture and implementation of an autonomous agent built using Vertex AI, Python, and Google Cloud infrastructure.
## High-Level System Architecture
The solution uses a three-tier agentic architecture designed for low latency, modularity, and strict session isolation:
User Interaction Layer: A frontend built with Streamlit and deployed on Cloud Run, managing contextual chat turns via st.session_state`.
