Back

Interacting with Injective in Natural Language: An AI-powered on-chain Trading Experience

In this course, you'll learn how to build an AI Agent application powered by the Injective blockchain. You'll explore how to interact with the Injective network using natural language commands by integrating the OpenAI API with the Injective SDK. By the end of the course, you will have built a smart agent capable of handling tasks like chat-based interaction, checking wallet balances, and performing token transfers. Along the way, you'll gain hands-on experience with essential components such as project architecture design, configuration management, and client-side command execution. Ultimately, you’ll create an AI-driven on-chain interaction experience that bridges user-friendly dialogue with blockchain functionality.

Language

Python

Total Length

1.7h

Part of Learning Track

Build on Injective + 1

What You’ll Learn

AI-driven Blockchain Interaction:Learn how to build an AI Agent that combines natural language processing with blockchain operations

Wallet Balance Query Implementation:Step-by-step breakdown of how user input is processed into a blockchain query

JSON Schema & Function Calling:Design LLM-friendly function formats using JSON Schema

Blockchain Interaction Architecture:Learn efficient patterns for communicating with the Injective network

Testing & Debugging:Understand multi-layered testing strategies and how to troubleshoot common blockchain development issues

Working with the OpenAI API and function calling system

Using core components of the Injective SDK

Syllabus

Unit 1 – Project Overview and Architecture Design

In this unit, you'll explore the overall architecture of the Injective iAgent project, including its core technical stack and how to set up the development environment.4o

Unit 2 - Detailed Server-Side Implementation

This unit will provide an in-depth explanation of the server-side implementation of the Injective AI interaction system. It covers the core module structure, request processing flow, and the integration mechanisms with the Injective network and OpenAI API. This will help you gain a comprehensive understanding of the backend logic and lay a solid foundation for future feature expansion.

Unit 3 - Configuration File Explained

In building a fully functional AI dialogue system, the design and management of configuration files play a crucial role. This unit will delve into the key configuration files in the system, helping you understand their structure, purpose, and how they can be extended.

Unit 4 – Detailed Explanation of Client Implementation

This unit will provide an in-depth introduction to the client-side implementation of iAgent, covering the command-line interface architecture, core class implementations, command parsing mechanisms, error handling strategies, and the communication mechanisms between the client and server. You will learn how to build a fully functional and user-friendly blockchain interaction tool.

Unit 5 - Mastering Dependency Management

In this unit, we’ll take a closer look at how the iAgent project manages its dependencies. You'll learn how the system ensures consistent behavior across different environments and guarantees that all essential features work reliably.

Unit 6 - In-Depth Guide to Balance Query Functionality

In this unit, we take a deep dive into the implementation of the balance query feature in the iAgent project. Through four detailed lessons, we explore how natural language understanding is integrated with blockchain interaction to create a user-friendly balance-checking experience.

Unit 7 – Implementation of the Transfer Function

This unit provides a detailed introduction to the design and implementation of the transfer function within an AI-driven blockchain interaction system. Through four comprehensive lessons, you will gain a full understanding of how to design, implement, and test a secure and reliable transfer system.

Unit 8 – Overview of Market Data and Trading Functions

In this unit, we will dive into the implementation of market data queries and trading functions within the iAgent system. These features empower users to access market data on the Injective blockchain and execute trading operations — all through natural language interaction.