Transforming R Code to Golang and ReactJS Using LLMs
Working with AI (Part 2): Code Conversion 🔗
Mantle faced the challenge of converting a prototype project written in R to their standard production stack using Golang and ReactJS. By utilizing a large language model (LLM), they managed to reduce the conversion scope significantly and save considerable developer time. The approach involved injecting existing code, defining context with libraries and architecture, and generating files in a structured manner. The team emphasized the importance of context to guide the LLM in producing compatible and efficient code, ultimately achieving 80% completion of boilerplate code to allow developers to focus on fine-tuning the remaining 20%. As LLMs evolve, the efficiency of this code conversion process is expected to improve further.
- Key Strategies Used:
- Leveraged LLM for code generation and context management.
- Focused on maintaining existing code patterns and libraries.
- Generated code incrementally, starting from backend to frontend.
What programming languages were involved in the project at Mantle?
The project involved converting code from R to Golang and ReactJS.
What was the primary goal of using the LLM in this context?
The primary goal was to reduce the time required for code conversion by generating boilerplate code, allowing engineers to concentrate on high-value details.
How did Mantle ensure the generated code was compatible with their existing codebase?
Mantle ensured compatibility by providing context such as existing code patterns, libraries, and database schemas to the LLM during the code generation process.