Code Completion: Provides predictive and auto-completion suggestions for code blocks within the context of the code being written.
Function Logic Generation: Helps generate logic for function declarations, reducing manual coding effort.
Test Generation: Suggests code for generating test cases and test scenarios, improving code quality and reliability.
Regex Patterns: Offers common code patterns, including regular expressions, to simplify code writing.
Privacy-Focused: Respects data privacy by not using proprietary code stored in GitLab as training data.
Multilingual Support: Available in 14 languages, including C++, Java, Python, and more, catering to a wide range of developers.
IDE Integration: Seamlessly integrates with popular integrated development environments, including GitLab Web IDE, VS Code, Visual Studio, Jetbrains-based IDEs, and NeoVIM.
Self-Managed Instances: Accessible for self-managed GitLab instances, ensuring data security and control.
Use Cases of Gitlab Code Suggestions
Efficient Coding: Developers can accelerate their coding process by leveraging AI-powered code suggestions to save time and effort.
Code Quality: Code Suggestions enhances code quality by generating accurate and relevant code blocks, improving reliability.
Data Privacy: Ideal for organizations with data privacy concerns, as it doesn't use proprietary code as training data.
Multilingual Development: Suitable for developers working in various programming languages, accommodating their language preferences.
IDE Enhancements: Integrates with popular IDEs, making it accessible for developers in their preferred coding environments.
Self-Managed Environments: Valuable for organizations with self-managed GitLab instances, maintaining control and data security.
Continuous Improvement: Ongoing enhancements ensure that code suggestions become increasingly valuable and efficient for developers.
General Availability: As it progresses towards general availability, developers can expect even more stability and improved user experience.
