Automatic code generation and programming
TEXT_INPUT:Enter the programming requirements and specifications;;CHATGPT:Prompt ChatGPT to generate code based on the given requirements and specifications;;DISPLAY_OUTPUT:Display the generated code to the user
Generative AI models like LLM and image generators provide effective tools for automatic code generation and programming. For instance, OpenAI's GPT-3, with its language pattern recognition capacity, can generate Python code snippets from human-written requirements. By inputting a simple command like 'Generate a function that sorts a list in descending order,' GPT-3 can interpret your request and output the corresponding Python code.
Image generators are another effective tool in the realm of auto codes. For instance, by using Sketch2Code, it's possible to convert hand-drawn designs into HTML or CSS code. Simply upload an image of your UI sketch and the AI will generate the corresponding front-end code.
Overall, these AI tools aid in effortless code generation and programming, transforming hassle-filled tasks into convenient activities.
How to build with Clevis
This is an overview of an example application titled 'Automatic Code Generation App' that you can build using Clevis. This insightful tool allows the development of similar applications within the same sphere.
The initial process starts when the application prompts the user to input their programming requirements and specifications using Text Input module. This tool digitizes and prepares the specifications in a format that can easily be interpreted by Machine Learning algorithms.
The data is then sent to OpenAI's ChatGPT. ChatGPT is a conversational AI model leveraged in the next step called ChatGPT. The given prompts are processed by the model to autogenerate the code that fulfils the input requirements. The use of ChatGPT ensures the creation of efficient, effective, and accurate codes.
After the code is created, it's displayed to the user in the form of an output, under the step named Display Output. This output presents the autogenerated code, allowing the users not only to save time in creating codes from scratch but also to validate the generated code with the initial requirements.
So, this application provides an automated, productive and high-level approach to code generation, demonstrating the capabilities of AI in programming tasks.