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Description

This Study Partner agent demonstrates how to create an AI-powered study partner that combines multiple information sources and tools to provide comprehensive learning support. The agent showcases several key capabilities: Multi-tool Integration: Combines Exa search tools for web research and YouTube tools for video content discovery, enabling the agent to access diverse learning resources. Personalized Learning Support: Creates customized study plans based on user constraints (time available, current knowledge level, daily study hours) and learning preferences. Resource Curation: Searches and recommends high-quality learning materials including documentation, tutorials, research papers, and community discussions from reliable sources. Interactive Learning: Provides step-by-step explanations, practical examples, and hands-on project suggestions to reinforce understanding. Progress Tracking: Designs structured study plans with clear milestones and deadlines to help users stay on track with their learning goals. Learning Strategy: Offers tips on effective study techniques, time management, and motivation maintenance for sustained learning success. This example is particularly useful for developers, students, or anyone looking to build AI agents that can assist with educational content discovery, personalized learning path creation, and comprehensive study support across various subjects and skill levels.

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Code

cookbook/examples/agents/study_partner.py
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.exa import ExaTools
from agno.tools.youtube import YouTubeTools

study_partner = Agent(
    name="StudyScout",  # Fixed typo in name
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[ExaTools(), YouTubeTools()],
    markdown=True,
    description="You are a study partner who assists users in finding resources, answering questions, and providing explanations on various topics.",
    instructions=[
        "Use Exa to search for relevant information on the given topic and verify information from multiple reliable sources.",
        "Break down complex topics into digestible chunks and provide step-by-step explanations with practical examples.",
        "Share curated learning resources including documentation, tutorials, articles, research papers, and community discussions.",
        "Recommend high-quality YouTube videos and online courses that match the user's learning style and proficiency level.",
        "Suggest hands-on projects and exercises to reinforce learning, ranging from beginner to advanced difficulty.",
        "Create personalized study plans with clear milestones, deadlines, and progress tracking.",
        "Provide tips for effective learning techniques, time management, and maintaining motivation.",
        "Recommend relevant communities, forums, and study groups for peer learning and networking.",
    ],
)
study_partner.print_response(
    "I want to learn about Postgres in depth. I know the basics, have 2 weeks to learn, and can spend 3 hours daily. Please share some resources and a study plan.",
    stream=True,
)

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Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Set your API key

export OPENAI_API_KEY=****
export EXA_API_KEY=****
3

Install libraries

pip install -U agno exa_py openai
4

Run Agent

python cookbook/examples/agents/study_partner.py