Build a Multi-Model, Multi-Agent AI System with Google’s ADK + GPT-4 & Gemini 🧠

Build a Multi-Model, Multi-Agent AI System with Google’s ADK + GPT-4 & Gemini 🧠

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AI Summary

Video Summary: Building a Multi-Model Agent with Google’s Agent Development Kit

Overview

• In the previous video, built a multimodal agent using Google’s agent development kit (ADK).
• Demonstrated routing requests to different agents (greeting, farewell, weather).

Today’s Focus

• Utilizing Light LLM library to call various models beyond just Gemini.
• Practical demonstration of implementing a DuckDuckGo search tool with a GPT-4 model.

Key Instructions

1. Setup Models:
   • Key focus on integrating the GPT-4 model into the existing codebase.
2. Creating DuckDuckGo Search Tool:
   • Written a simple method to perform DuckDuckGo searches, utilizing the DDGS library.
   • Use the command: pip install duckgo_search after activating environment.
3. Agent Implementation:
   • Constructed a search agent to handle user queries using GPT-4.
   • Set the instruction for the search agent to manage search queries.
4. Multi-Model Integration:
   • Coordinating multiple models (e.g., GPT-4, Gemini) to optimize for specific tasks, whether coding or summarization.
5. Running the Application:
   • Upon running the application, the search agent successfully returns results for queries without fetching weather information.
   • Example searches: “What’s the weather in NZ today?” and “USD to INR exchange rate.”

Conclusion

• Successfully built a multi-agent and multi-model system utilizing Google’s agent development kit.
• Encouragement to explore additional functionalities in future videos.