AI Grocery Recommendation

AI-powered grocery optimization using 5 specialized Google ADK agents that collaborate to find the best stores, compare prices, and create optimal shopping routes with real-time cost analysis.

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Inspiration

Grocery shopping is often inefficient, time-consuming, and expensive. People waste money by not comparing prices across stores and lose time driving to multiple locations without optimal routes. Our Smart Grocery Assistant solves this using Google's Agent Development Kit to create a collaborative multi-agent system.

What it does

The system employs 5 specialized ADK agents working together:

  • Root Coordination Agent: Orchestrates the entire workflow
  • Store Finder Agent: Uses Google Places API to locate nearby stores
  • Price Optimizer Agent: Analyzes prices across different store chains
  • Route Optimizer Agent: Calculates optimal driving routes using Google Maps
  • Shopping Advisor Agent: Provides intelligent recommendations

The agents collaborate to deliver three shopping scenarios: algorithm-optimized, user preference suggestions, and strict store requirements.

How we built it

Built using Google ADK (Agent Development Kit) for multi-agent orchestration, integrated with Google Maps APIs for location services, and deployed on Streamlit Cloud. The system implements real agent-to-agent communication patterns and handles complex decision-making workflows.

Challenges we faced

  • Designing effective agent communication protocols
  • Implementing real-time cost-benefit analysis including gas costs and time value
  • Creating fallback mechanisms when agents fail
  • Optimizing for global functionality across 190+ countries

Accomplishments

  • Successfully implemented 5 autonomous agents with Google ADK
  • Created a production-ready application with professional UI
  • Achieved real-time optimization that can save users significant money and time
  • Built a globally scalable solution

What we learned

  • Advanced multi-agent design patterns using Google ADK
  • Effective agent coordination and workflow orchestration
  • Real-world application of AI agents in consumer scenarios

What's next

  • Adding more store chains and price data sources
  • Implementing machine learning for better price predictions
  • Expanding to include product availability and store hours
  • Integration with grocery delivery services

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