Metabob: Debug and Refactor with AI installs statistics

Metabob: Generative AI for debugging & refactoring code

Metabob is an AI-based code review tool that utilizes a combination of Graph Neural Networks (GNNs) and Generative AI (LLMs). Using the underlying techniques, Metabob can detect complex logical problems and vulnerabilities, as well as general opportunities for code quality improvements. Metabob explains its detections in natural language and can generate code recommendations to fix the detections using an integrated fine-tuned LLM. ​

Supported Languages

• Python
• JavaScript
• TypeScript
• C
• C++
• Java

AI Code Review

• Automatically detect problems, vulnerabilities, and code optimization opportunities
• View natural language explanations for the detected problems
• Generate code recommendations to fix the detected problems
• Give feedback on the detections to optimize model performance (discard, endorse)

Features

• Problem, vulnerability & code optimization detection
• Detection explanations
• LLM interaction: generate code recommendations ​​

Settings​

• To disable Metabob anlaysis from running every time code is saved, go to the extension settings and deselect the checkbox under the text "Metabob: Analyze Document On Save"
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• To change the backend LLM model Metabob uses to generate problem descriptions and code recommendations, select your preferred model from the "Metabob: Backend Selection" drop down menu ​
• If you prefer to use one of the openai models, you need to authenticate by inputting your openai API key into the text field under "Metabob: ChatGPT Token" text field on Metabob's extension settings

Usage​

1. Analyze code

2. View detected problems

3. Generate fixes for detected problems

Data Policy

​ Metabob deletes all data from it's problem detection model one hour after the user has made their last API call. However, as Metabob integrates with third party LLMs to generate problem descriptions and code recommendations to perform fixes, Metabob has to pass data to these models and cannot control how the data is used by the companies hosting these LLMs. ​ ​