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aws-samples/AI-Agents-for-Education

Bedrock Agents for EDU Use Cases

This repository showcases example Bedrock Agents created for educational use cases.

Repo Structure

  • Data: Sample data that connects to the agents.
  • Tools: Tools for agents to use.
  • Production: Web UI and Bedrock agent integration.

Agent Example 1: Course Recommendation Agent

  • Name: Course Recommendation Agent
  • Target Audience: Higher-Ed Student Advisors
  • Sample questions: how many credits student 1 has earned? What courses are offerred this semester (202408) that's relevant to this student's major? Does this course conflict with student's schedule? What course do you recommend for student 1 to take this semester (202408)

Architecture

Course Recommendation Agent Architecture

Deployment Instructions of Course Recommendation Agent

  1. Prepare Data:

1.1 Structured data: Run the data-prep-course-recommendation-agent-short.ipynb notebook Structured data preparation section to prepare the tables.

1.2 Unstructured data: Run the data-prep-course-recommendation-agent-short.ipynb notebook Unstructured data preparation section to set up knowledge base.

  1. Launch Agent: Run course-recommendation-agent.ipynb notebook to deploy the agent in your AWS account.

  2. Test Agent: Use the above sample questions to test agent.

Agent Example 2: Visual Math Agent

  • Description: Agent creating math questions with visual artifacts
  • Target Audience: Math curriculum designer, Math content creator, instructors
  • Sample questions: create a multiple-choice question testing 3rd grader's understanding of equivalent fraction. create a question asking the time of an analog clock.

Deployment Instructions of Visual Math Agent

Launch Agent: Run visual-math-agent.ipynb notebook to deploy the agent in your AWS account.

Agent Example 3: Course Assistant Agent (Coming soon)

  • Description: Agent navigating course content to answer questions and making study plans.
  • Target Audience: Students

Agent Example 4: Multi-agent system for course recommendation

This is a multi-agent collaboration architecture for Agent Example 1

Architecture

Course Recommendation Agent Architecture

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