Multi-Agent Farm Advisor with Amazon Bedrock
Learn to build a smart farming system using Amazon Bedrock's multi-agent collaboration. Coordinate AI agents to optimize agricultural decisions.
Nitin Eusebius
Amazon Employee
Published Jan 8, 2025
Amazon Bedrock's new multi-agent collaboration enables specialized AI agents to work together on complex tasks. This feature lets developers create and coordinate agents with distinct roles, improving accuracy and scalability across diverse business applications.
Agricultural operations involve complex decision-making that requires expertise across multiple domains - from crop science to meteorology to resource management. In this post, we'll demonstrate how to build a smart farming advisory system using Amazon Bedrock's new multi-agent collaboration capability. We'll create a system that helps farmers make informed decisions by coordinating between specialized AI agents for crop planning, weather monitoring, and resource management.
The demo solution uses Amazon Bedrock's multi-agent collaboration to create a farm management system with four key components:
- A supervisor agent that coordinates overall farm management
- A crop planning specialist agent for variety selection and planting guidance
- A weather monitoring agent for climate-related recommendations
- A resource planning agent for equipment and irrigation management
To follow along with this tutorial, you'll need:
- An AWS account with access to Amazon Bedrock
- Basic familiarity with the Amazon Bedrock console
- The sample knowledge base documents we'll provide
- Agents creation and getting started
For the demo, we will first create four demo knowledge base documents that provide our agents with foundational agricultural information. These documents contain sample generic guidelines and best practices for demonstration purposes only. For production you will have your own set of knowledge documents or repo.
This demo uses knowledge bases, but yo can also use action groups to define actions for your agent to perform
The Crop Planning knowledge base includes:
- Variety selection criteria
- Population guidelines
- Basic fertility requirements
The Weather Analysis knowledge base contains:
- Growth stage weather requirements
- Risk assessment guidelines
- Weather impact thresholds
The Resource Planning knowledge base covers:
- Irrigation scheduling
- Equipment utilization
- Labor planning
The Supervisor Integration guide provides:
- Seasonal planning frameworks
- Decision-making protocols
- Emergency response procedures
You can refer to steps to get started with agents here and how to use multi-agent collaboration with Amazon Bedrock Agents
Note : When you create your respective agent, keep following in mind
- Prepare the agent and alias as you would needing when you configure the multi-agent configurations. More details here
- For role creations, keep default service role creation.
- This demo uses knowledge bases, but yo can also use action groups to define actions for your agent to perform
Basic Setup:
Agent Instructions:
Knowledge Base:
Point to the knowledge base you created before and in the instructions tag key concepts like varieties, populations, fertility
Basic Setup:
Agent Instructions:
Knowledge Base:
Point to the knowledge base you created before and in the instructions tag key concepts like temperature, moisture, risks
Basic Setup:
Agent Instructions:
Knowledge Base:
Point to the knowledge base you created before and in the instructions tag key concepts like irrigation, equipment, labor
Basic Configuration:
Supervisor Instructions:
Knowledge Base:
Point to the knowledge base you created before
For crop-planner:
For weather-monitor:
For resource-planner:
Let's test our system with a realistic farming scenario:
The system processes this request through the following steps:
- Supervisor analyzes general request
- Crop planner provides variety guidelines
- Weather monitor assesses typical timing
- Resource planner suggests general equipment needs
Now lets run another example
The system processes this request through the following steps:
- Weather monitor assesses temperature impact
- Crop planner provides growth stage needs
- Resource planner calculates irrigation requirements
- Supervisor creates integrated plan
The multi-agent collaboration trace feature allows us to monitor the interaction between agents. Access this by selecting "Show trace" after each interaction to see:
- Order of agent consultations
- Information flow between agents
- Decision-making process
- Response compilation
Amazon Bedrock's multi-agent collaboration capability enables us to create sophisticated agricultural advisory systems that coordinate between specialized agents. This demo shows how we can build a practical system that helps farmers make better decisions by integrating expertise across multiple domains.
The solution can be extended by:
- Adding more specialist agents (e.g., marketing, finance)
- Integrating with real-time weather data
- Connecting to farm management software
- Incorporating precision agriculture data
Happy Building !
Resources :
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.