Build Your Own AI-Driven Code Analysis Chatbot for Developers with the GenAI Stack
The topic of GenAI is everywhere now, but even with so much interest, many developers are still trying to understand what the real-world use cases are. Last year, Docker hosted an AI/ML Hackathon, and genuinely interesting projects were submitted.
In this AI/ML Hackathon post, we will dive into a winning submission, Code Explorer, in the hope that it sparks project ideas for you.
For developers, understanding and navigating codebases can be a constant challenge. Even popular AI assistant tools like ChatGPT can fail to understand the context of your projects through code access and struggle with complex logic or unique project requirements. Although large language models (LLMs) can be valuable companions during development, they may not always grasp the specific nuances of your codebase. This is where the need for a deeper understanding and additional resources comes in.
Imagine you’re working on a project that queries datasets for both cats and dogs. You already have functional code in DogQuery.py that retrieves dog data using pagination (a technique for fetching data in parts). Now, you want to update CatQuery.py to achieve the same functionality for cat data. Wouldn’t it be amazing if you could ask your AI assistant to reference the existing code in DogQuery.py and guide you through the modification process?
