Arun Shankar

About

Arun Shankar works in AI engineering and AI automation & agents, based in Dallas, TX (Google). Generative AI @ Google. Public projects on GitHub include Agentic-Workflow-Patterns (Repository demonstrating best practices and patterns for implementing agentic workflows in Python, featuring…), React From Scratch (This repo compiles a collection of examples that demonstrate the effective use of the ReAct pattern in LLM…) and AgenticSearch (AgenticSearch operates within an agentic workflow, utilizing Gemini 2.0 and an extensive tool registry to…), mostly written in Python and Jupyter.

Projects 6

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  Agentic-Workflow-Patterns

  Repository demonstrating best practices and patterns for implementing agentic workflows in Python, featuring modular, scalable, and reusable design patterns for intelligent automation.

  github.com
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  React From Scratch

  This repo compiles a collection of examples that demonstrate the effective use of the ReAct pattern in LLM prompting. It includes variations and implementations of agents that leverage the ReAct pattern, optimized for Gemini.

  github.com
• github.com

  AgenticSearch

  AgenticSearch operates within an agentic workflow, utilizing Gemini 2.0 and an extensive tool registry to handle complex questions. By integrating and synthesizing data from multiple APIs, it delivers cohesive and detailed answers, enabling a robust and intelligent search system.

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  Python-Design-Patterns-for-AI

  A repository showcasing Python design patterns specifically adapted for building robust and efficient AI workflows.

  github.com
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  VertexAI-Semantic-Caching

  Repository dedicated to enhancing data retrieval and processing efficiencies in Google Cloud's Vertex AI by implementing a semantic caching layer with MemoryStore, Vertex AI Vector Search, and Gemini, focusing on GenAI applications.

  github.com
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  VAIS-RAG-Patterns

  Architectural Blueprints for RAG Automation: Advanced Document Understanding using Vertex AI Search

  github.com