Build An Autogpt Code Writing Ai Tool With Rust And Gpt-4

Learn Rust Whilst Taking ChatGPT to the Extreme In Creating an Automated GPT that Builds and Tests Code for You

What you'll learn

Master the Rust programming language from zero to hero

Understand how to leverage GPT-4 (ChatGPT) to build your own AutoGPT using Rust

Understand how to build AI functions for structuring exact desired responses from LLMs (large-language-models)

Build your first web server using the Actix Web framework in Rust

Build an AutoGPT that not only writes any code you like, but tests, improves and re-writes where necessary

Requirements

You must understand basic programming concepts and be able to program in another language

Basic programming concepts will not be covered in this course. You will need to know about for loops, if statements, functions etc

You must have access to OpenAI and the GPT-4 API (see inside course for how to get access)

Description

Develop a an automated ChatGPT agent which not only writes code, but tests and re-write code for you. In fact, you can request your agent to do just about anything.By going through this course, you will not only learn and master Rust from A-Z, but you will also have extensive knowledge in how to build your very own AutoGPT.The name of the AutoGPT we build together will be Auto-Gippity.Auto-Gippity will simply be given a task, which it will break down and delegate to other agents to complete. Each agent will be responsible for testing its own output.Our test piece will be to build an agent that writes a web server given a template. It will write the code in Rust. Not only that, but we will write the agent, that writes Rust code…in Rust. Fantastic. What a time to be a developer.AutoGPTs will only continue to become extremely relevant and highly sought after and combining these with the worlds favourite programming language, Rust, means that we can build an application which is blazingly fast, memory-safe, modern and robust.Right now, there is a window of opportunity to learn this fantastic and uncommon technology before it takes over in software engineering.Just think, you could build an AutoGPT that say, develops full stack SAAS websites end-to-end. With technologies like GPT-4 and soon beyond, such agents will only continue to improve in their performance.Companies are looking for developers who can build such tools and SAAS startups have a window to be first. If you are curious as to how you can connect new AI technologies to change the world then THIS is the course for you.You will learn:How to work with the Open AI API and the GPT-4 API using RustHow to master rust from A to Z, progressing from beginner, to intermediate, to advanced and beyondHow to build AI functions (special functions that extract a desired response from large-language-models)How to develop a web server template (including an introduction to web servers) using Actix WebHow to build an Automated GPT agent (Auto-Gippity) which writes code, that executes and tests code. If the code is wrong, it will simply re-write it and test againWe are truly excited to see what you develop, so make sure you share your application with the world.See you in class!Shaun

Overview

Section 1: Introduction

Lecture 1 What We Are Building

Lecture 2 Programming Experience Required

Lecture 3 About Your Instructor

Lecture 4 Discord and Q&A

Lecture 5 Getting Access to GPT-4

Lecture 6 AI Functions and LLM Limitations

Lecture 7 Course Structure Overview

Lecture 8 IMPORTANT: RESOURCES

Section 2: Rust Crash Course - Learning the Rust Environment

Lecture 9 Rust installation - Quick Walkthrough

Lecture 10 Rust Installation - Windows Docs

Lecture 11 About Rustup

Lecture 12 Rustup Tool Manager Docs

Lecture 13 Preparing Visual Studio Code

Lecture 14 Cargo New - Your First Rust Project

Lecture 15 Your First Rust Function

Lecture 16 A Brief Programming Language Comparison

Lecture 17 Structuring Project Modules - Brief Introduction

Lecture 18 Unit Testing with Cargo

Lecture 19 Create Docs with Cargo

Lecture 20 Creating a Rust Library

Lecture 21 Dead Code and Unused Variables

Section 3: Rust Crash Course - Types and Memory Management

Lecture 22 Must-Know Resources

Lecture 23 Rust vs Other Languages Revisited

Lecture 24 Integer Types

Lecture 25 Data Type Cheatsheet

Lecture 26 Stack vs Heap Intro

Lecture 27 Stack Deep Dive

Lecture 28 Stack vs Heap Walkthrough

Lecture 29 String Literals and Static (Read-Only) Memory

Lecture 30 Ownership and Borrowing - Immutable References

Lecture 31 Ownership and Borrowing - Mutable References

Lecture 32 Ownership and Borrowing - Dereferencing

Lecture 33 About Scope

Section 4: Rust Crash Course - Basics

Lecture 34 Intro - Create Project

Lecture 35 Fixed Size Variables

Lecture 36 Dynamic Sized Variables

Lecture 37 Basic Collections

Lecture 38 Closures

Lecture 39 Number Literals and Raw Strings

Lecture 40 Working Low Level with Binary

Lecture 41 Rust Std Library

Section 5: Rust Crash Course - Intermediate

Lecture 42 Intro - Create Module

Lecture 43 Enums - Your First Enum

Lecture 44 Enums - Result Enum with Generics Introduction

Lecture 45 Enums - Option Enum with Some or None

Lecture 46 Rusts Result and Option

Lecture 47 Structs - Your First Struct

Lecture 48 Structs - Using Type Impl

Lecture 49 Traits Introduction

Lecture 50 Polymorphism with Traits and Generics

Lecture 51 Lifetimes - Introduction

Lecture 52 Lifetimes - Generics and Structs

Lecture 53 Pattern Matching - Integer, Option and Result

Lecture 54 Pattern Matching - Mixed Data Enum

Lecture 55 Pattern Matching - Match Guards and Structs

Lecture 56 Your First Async API Call

Lecture 57 Handling Errors

Lecture 58 Collections Revisited - HashMaps and HashSets

Lecture 59 Project Cleanup

Section 6: Rust Crash Course - Advanced

Lecture 60 Declarative Macros - Introduction

Lecture 61 Declarative Macros - With Repetitions

Lecture 62 Declarative Macros - Note on Module Exporting

Lecture 63 Procedural Macros (Theory) - Introduction to Derive

Lecture 64 Procedural Macros (Theory) - Function Like Macro

Lecture 65 Procedural Macros (Theory) - Attribute Like Macro

Lecture 66 Procedural Macros (Practice) - Building an AI Function

Lecture 67 Smart Pointers - Box

Lecture 68 Smart Pointers - Reference Counting with RefCell

Lecture 69 Smart Pointers - Reference Counting with Weak

Lecture 70 Rust Concurrency with Mutex and Arc

Lecture 71 Publish Packages to Crates

Section 7: Build Web Server Template - First Project

Lecture 72 Theory - Introduction to Web Servers and Actix Web

Lecture 73 Theory - Actix Web REST API Docs Walkthrough

Lecture 74 Project Setup

Lecture 75 Struct Definitions

Lecture 76 Database Implementation

Lecture 77 Creating AppState with Mutex Provided Safety

Lecture 78 Writing Our Initial Web Server

Lecture 79 Testing Create Task Rest API Endpoint With Postman

Lecture 80 Create and Test GET Task Request

Lecture 81 Complete Task CRUD

Lecture 82 User Registration and Login

Lecture 83 Mutation Adjustment

Lecture 84 Next Steps

Section 8: Auto GPT Project - Supporting Functions

Lecture 85 Supporting Functions - Section Introduction

Lecture 86 Project Setup

Lecture 87 User Interaction with Command Line

Lecture 88 Extract API Keys

Lecture 89 OpenAI Call - Key Provisions

Lecture 90 OpenAI Call - Create Client

Lecture 91 OpenAI Call - Test API Call

Lecture 92 OpenAI Call - Error Handling

Lecture 93 OpenAI Call - Completion

Lecture 94 Extract AI Functions

Lecture 95 Extend AI Function

Lecture 96 Print Agent Activity to Command Line

Lecture 97 AI Task Function

Lecture 98 AI Task Function Decoded

Lecture 99 API Endpoint Valid Check Function

Lecture 100 File Read and Write Functions

Section 9: Auto GPT Project - Create Agents

Lecture 101 Create Agents - Section Introduction

Lecture 102 Basic Agent - Create Basic Agent

Lecture 103 Managing Agent - FactSheet Struct

Lecture 104 Managing Agent - Special Functions Trait

Lecture 105 Solutions Architect - Call Project Scope

Lecture 106 Solutions Architect - Call External Urls

Lecture 107 Solutions Architect - Handle Discovery State

Lecture 108 Solutions Architect - Write Test for Checking Urls

Lecture 109 Solutions Agent - Full Agent Test

Lecture 110 Managing Agent - Create New

Lecture 111 Managing Agent - Execute Project Fn

Lecture 112 Managing Agent - Initial Agent Test

Lecture 113 Backend Developer - Write and Improve Code Fn

Lecture 114 Backend Developer - Fix Code Bugs Fn

Lecture 115 Backend Developer - Rest API Endpoints Fn

Lecture 116 Backend Developer - Discovery and Working States

Lecture 117 Backend Developer - Initial Agent Test

Lecture 118 Backend Developer - Ensure AI Safety Human Check

Lecture 119 Backend Developer - Write Automated Cargo Build

Lecture 120 Backend Developer - Write Automated Cargo Run

Lecture 121 Backend Developer - Write Automated Endpoint Testing

Lecture 122 Backend Developer - Unit Testing Agents Unit Tests

Lecture 123 Backend Developer - Testing Code Rewrites

Section 10: Auto GPT Project - Finalise Agent Gippity

Lecture 124 Performing First Complete Agent Test (External Url Based)

Lecture 125 Performing First Test - Human Review

Lecture 126 Performing Second Test (Tracking CRUD Based)

Lecture 127 Performing Third Test (Hangman Game Build)

Lecture 128 Performing Third Test - Human Review

Lecture 129 Paper - Large Language Models as Tool Makers (Optional)

Lecture 130 Further Reading (Optional)

Lecture 131 Considerations on Overcoming Limitations

Lecture 132 Next Steps

Enthusiastic or intermediate programmers who want to learn Rust,Programmers who want to build their own blazingly fast and memory-safe AutoGPT models,Startups who want to give their developers a blue print to building cutting-edge AI solutions