Summary
The Aralia Data Ecosystem is formed by an unlimited number of decentralized Aralia Data Planets which are independent data objects across the web. Aralia Data Planets encapsulate diverse entities into individual data objects and form an open-ended ecosystem of interoperating planets to generate synergistic insights.
Aralia AI SDK is the core module within the Aralia Data Ecosystem that empowers smart and interactive applications anytime from anywhere.
Aralia AI leverages Large Language Models (LLMs) and a rule-based agent architecture to offer a semantic, conversational interface. This allows users without technical background to easily perform data exploration, Q&A, scenario analysis, and automated reasoning throughout the Data Ecosystem.
Aralia AI’s goal is to “let every dataset speak,” thereby improving the effectiveness of data insights and the efficiency of decision-making.
Learning Objectives
- Understand Aralia AI’s positioning and how it works
- Learn to interact with AI using natural language to quickly obtain insights
- Interact directly with the Aralia Data Ecosystem using Aralia MCP
- Complete a full Aralia AI Tools (SDK) workflow in a Google Colab environment
- Grasp the basic flow design of Aralia AI Tools (SDK) and LangGraph
- Build a foundation for advanced AI tool development and teaching applications
AI Agent Tutorial
Quick Start
System Overview & Core Concepts
Prerequisite
Using Aralia MCP
Experiment with Aralia SDK in Colab
Custom AI Workflow
🔌 DataPlanet API
After completing this tutorial, you will be able to
- Talk to AI to get data insights → Complete a semantic query and response, including source citations and limitations.
- Hands-on online lab → Run the full SDK workflow directly in Google Colab; adjust a few parameters and customize prompts to experience the results.
- Apply it in a Lesson Plan → Add problems to a sample question bank and re-run with one click, supporting repeatable lesson plan in course use.
- Begin your AI tool development journey → Start building your own agent services with Aralia AI tools.
Suitable Users for Aralia MCP
- Users who need to perform data search and analysis
- No programming experience required
- Have experience and permission to install software and edit configuration files
Suitable Users for Colab Implementation
- Users who need to perform data search and analysis
- Individuals with Python development experience
- Learners or team members interested in AI development
Who This Is Not For
- Those not yet familiar with digital data and basic data concepts
- Those who are still new to the Python programming language
- Those seeking to build LLM applications entirely from the ground up
Next: AI Agent Tutorial →