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This video discusses creating AI agents for e-commerce using ADK and Vector Search to address challenges like keyword/multimodal searches and item recommendations. It highlights advanced Vector Search practices (multimodal, hybrid, task-type embedding) and demonstrates how AI agents with Vector Search improve “”generative”” recommendations, exemplified by a “”Shopper’s Concierge”” demo. This demo, using ADK, Google Search grounding, query generation, and multimodal item curation, finds relevant items based on user intent, moving beyond simple text similarity search.
Resources:
Vertex AI Vector Search →https://goo.gle/3T5xxK5
Agent Development Kit→https://goo.gle/3RGrB9T
Shopper’s Concierge demo video→https://goo.gle/4jRbMJb
Shopper’s Concierge sample notebook→https://goo.gle/4kMkxot
Chapters:
0:00 – Intro
0:43 – Introduction to Vector Search & Advanced Practices (Kaz Sato)
1:18 – Typical RAG Scenario for E-commerce
2:56 – Challenges with Basic RAG in E-commerce
8:08 – Vector Search Advanced Practices
15:08 – Building the Shopper’s Concierge AI Agent with ADK & Vector Search (Kaz Sato)
8:50 – Challenge: Smart Recommendations
9:50 – Solution: AI Agents + Vector Search
11:13 – Shopper’s Concierge Demo
14:58 – Code Implementation Walkthrough
15:02 – Q&A and Resources
15:48 – Why “”Agent as a Tool”” vs. Sub-agent?
16:48 – Getting Started Resources
Subscribe to Google for Developers → https://goo.gle/developers
Speakers: Sita Lakshmi, Kaz Sato
Products Mentioned: Agent Developer Kit (ADK) Read More Google for Developers
