Convert Text to Code Using AI: Tools You Can Use

Picture articulating what you need in a program or website in simple English, and in a matter of seconds, AI generates the code for you. Forget battling with syntax, endless debugging, or logical fallacies; AI tools that transform text into code do it all. These tools are revolutionizing the industry for both amateur and seasoned developers by making coding easier, more efficient, and quicker than ever.
In this post, we are going to discuss how AI-powered text-to-code tools function, highlight some of the popular options in the industry, and examine how these tools help save time, boost productivity, and simplify coding projects. Whether you are a novice, veteran developer, or someone interested in the relationship between AI and coding, there is something for everyone.  

What Is Text-to-Code and How Does It Work?  
Text-to-code refers to the feature of AI that allows the input of instructions or descriptions in casual language such as English that can be converted to code. AI tools of this nature are usually developed using NLP (Natural Language Processing) models and complex machine learning systems, which equip them with understanding your commands contextually and strategically.
Using large datasets and pre-trained models, these tools autonomously learn to produce code snippets, entire functions, or even complete software projects. This is a time efficient process, reducing much of the grunt work which accompanies coding.  

Why Use AI for Converting Text into Code?  
1. Time-efficient: Writing out code is a tedious task that takes a good chunk of time, especially when it comes to repetitive tasks. AI helps automate this process, leaving you to focus on complex coding or problem-solving tasks.  
2. Elimination of errors: Most of the AI Generated code does lack the basic syntax error and blunders, thanks to the training done on datasets of clean codes.  
3. Broadening of frontiers: Text-to-code tools break barriers making it possible for one to create code without the need of being an expert coder. Anyone with an idea who has little to no programming knowledge can harness such tools.   
4. Encouraging creativity and innovation: AI helps in generating outlines or structure of repetitive code which can be adjusted and modified to the desired outcome.  
Top AI Tools for Converting Text into Code  
Below is a compilation of some of the leading AI-powered tools you can use to bring your text descriptions of code to reality. These tools are at the forefront of making text-to-code reality.
1. GitHub Copilot - The AI Pair Programmer
GitHub Copilot is one of the AI tools that is used widely for text-to-code conversion. GitHub together with OpenAI has developed Copilot which makes use of AI model trained on several million lines of code to help developers write code faster. 

How It Works:
GitHub Copilot has an add-in feature for IDE (Integrated Development Environment) 
applications like Visula Studio Code, so it works directly with these applications. As you work on comments or talk to the program, you may describe what you want in natural speech and Copilot will provide suggestions for relevant code fragments that match your description. It caters to everything from simple algorithms to advanced ones. 
Use Case: You are writing a Python program which requires a function to sort a list. You can state a comment: “Create a function to sort a list in ascending order”. After stating the comment, Copilot will, in return, provide optimized Python code. 
Why It's Useful: It saves significant amounts of time by suggesting optimized and relevant code, allowing a developer to concentrate on critical assessment of their project instead of tedious programming tasks. 
2. OpenAI Codex- the engine behind GitHub copilot. 
Open AI has the model Codex, a powerful AI language model that runs GitHub Copilot, is capable of translating human instructions into code written in a variety of programming languages such as Python, JavaScript, and even SQL.
Codex is extremely versatile of a tool for developers due to being trained on large datasets which contain a myriad of programming languages and code examples. 
How It Works:
Irrespective of the user input, whether it is a simple statement like, “Write a function to calculate the Fibonacci sequence,” or more complex tasks like “Create a Django model to store blog posts,” Codex has the ability to translate them into code. 
Use Case: Imagine that you wish to create a web scraper in python. Just stating a simple command, “Write a web scraper to extract headlines from a news site,” will lead Codex to generate the suitable Python code employing BeautifulSoup and requests libraries.  
Why It’s Useful: Codex is useful in automating the process of coding which aids in crafting a refined, reusable, and modular code effortlessly without being overly dependent on manual coding.  
3. Tabnine - The AI Code Completion Tool  
In a similar manner to GitHub Copilot, Tabnine is an AI Code Completion tool that utilizes ML to suggest code snippets tailored to what you’re typing. Unlike GitHub Copilot, it offers more customization options and integrates with an array of IDEs such as VS Code, IntelliJ IDEA, and Atom.  
How It Works:  
Smart code completions are provided as you type. This is made possible through Tabnine using deep learning models.
It supports multiple languages like Python, Java, TypeScript and Go. It aims to 
reduce the manual completion of repetitive tasks and fasten the pace of coding. 
Use Case: While coding in Java, you begin typing a class definition, and Tabnine 
suggests full code of the class, including method templates and constructor details.  
Why Its Useful: Tabnine assists developers in quicker code writing by predicting the next 
part in the code and providing suggestions that match context. It is meritous for tedious 
labeling jobs and even more compelling for those exploring new frameworks and libraries. 
Replit – AI‐Augmented Collaborative Coding 
Replit is an AI‐enhanced online programming environment that lets you write and execute code continually with built-in seamless sharing all done directly on your browser. It features an integrated AI assistant that provides you with real-time coding help by suggesting, completing, and debugging your code. 
 
How It Works: 
 
Just like Copilot in GitHub, Replit AI assistant offers code suggestions in form of type assistance. However, you can also interact with other developers in real-time, hence, it’s ideal when multiple people are collaborating on a project or if they want to learn programming and do so in a group setting. 
Use Case: You are part of a team working on a web application. Replit AI helps you and your teammates with the AI's assistance in realtime.
The assistant can not only suggest edits to the code, but also complete automated tasks such as form validation. 
Additionally, they help to debug problems scattered throughout the code.Why it's helpful: Replit doesn't simply turn prompts into functions, but transforms collaborative learning alongsideAI into a project-building endeavor. 
5. Peltarion - AI for Text Based Model Development
Peltarion is a platform that allows for the creation of deep learning models without going into depth with coding. 
While not a “text-to-code” tool, Peltarion does offer automation features enabling users to construct machine learning models using straightforward text phrases. This approach makes it feasible for those without comprehensive coding expertise to build AI models.
Explanation:
Peltarion’s platform provides an intuitive interface alongside AI guidance for model architecture development based on user prompts, streamlining the construction process of machine learning models.
Use Case: A data scientist planning to develop a customer churn prediction machine learning model has to craft countless code snippets. Instead, they can describe, “Build a
“Segment customer demographic and transaction data to build a model that predicts customer churn.” 
And Peltarion takes care of the rest.  
Why It’s Useful: Peltarion allows end-users to create advanced machine learning models with no or minimal coding experience, thus democratizing AI.  
6. CodeT5 – AI for Text-to-Code with NLP  
A model that converts natural language into code using natural language processing techniques is called CodeT5. It specializes in generating, completing and refactoring code. CodeT5 is part of a new wave of AI models designed to aid in coding using natural language input by interpretering the user's intention.  
How It Helps: 
CodeT5 being a context-aware text-generating model capable of performing a wide range of tasks from crafting a basic function to designing intricate algorithm scaffolds, can do so in multiple programming languages, including but not limited to Python, Java, C++, and more.  
Use Case: While working on a project, a software developer intends to implement a feature that sorts an array. By entering this straightforward command: "Sort an array in ascending order,” CodeT5 can produce the relevant sorting algorithm in Python, saving valuable time and effort.
Why It’s Useful: CodeT5 can perform amazing tasks with simple natural language instructions because it allows developers to efficiently convert ideas into working code rapidly.

Conclusion: The Outlook of Text-to-Code AI

The emergence of AI text-to-code tools is changing the landscape of software 
development. With the advent of these tools, developers can write, edit, and deploy code with 
ease and speed like never before. Whether you are a beginner trying to learn coding, or an 
experienced developer trying to pace up your workflow, AI text-to-code tools enable you to 
streamline the coding process and the productivity and quality of your work. 
Amidst growing advancements in AI technologies, possibilities will keep increasing offered by 
text-to-code tools, making them robust and flexible for use by developers from different fields."
So, whether you are simplifying monotonous work, developing sophisticated applications, or 
tinkering with ideas, AI text-to-code tools will drive a paradigm shift in programming.”