GitLab Code Suggestions ✓
Accelerate coding with AI-assisted code suggestions.
Free + from $29/mo
Verdict
A quick read before you dig into the full page.
- Best if
- Accelerate coding with AI-assisted code suggestions
- Skip if
- Limited IDE support
- Pick this when
- Enhances coding productivity
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Overview
GitLab's AI-Assisted Code Suggestions is an innovative tool which aims to improve coding productivity by offering predictive completions for code blocks, defining function logic, generating tests, and suggesting common code like regex patterns, all within a familiar coding environment.
With the main focus on privacy, GitLab guarantees that non-public customer code doesn't serve as part of the training data for this feature. The tool also has multilingual support, offering AI-powered code suggestions in 14 languages, including C++, C#, Go, Google SQL, Java, JavaScript, Kotlin, PHP, Python, Ruby, Rust, Scala, Swift, and TypeScript.
The service also integrates well with different IDEs, as GitLab extensions can be found in popular IDE marketplaces. These include the GitLab Web IDE, VS Code, Visual Studio, Jetbrains-based IDEs, and NeoVIM.
Additionally, GitLab's Code Suggestions is available for self-managed GitLab instances via a secure connection to GitLab.com. The tool continually improves the quality of suggestions with new prompt engineering, intelligent model routing, and expanded contexts for inference windows.
Best for
Short scenarios where GitLab Code Suggestions tends to shine.
-
Accelerate coding with AI-assisted code suggestions.
Example outputs 1
Sample generations and before/after results for GitLab Code Suggestions.
Access & connections
Where you can use GitLab Code Suggestions, and what it plugs into.
Platforms
Capabilities
What this tool accepts, produces, and is strongest at.
Input
- Code
Output
- Code
Supported features
- Code Review
- Code Assistant
- Autocomplete
Pros & cons
Pros
- Enhances coding productivity
- Accelerates software development
- Completes lines with one keystroke
- Quickly starts functions
- Generates boilerplate code
- Generates tests
- Prioritizes data privacy
- Prioritizes data security
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- Keeps source code protected
- Doesn't use code as training data
- Uses open-source pre-trained models
- Models are continually fine-tuned
- Customized open-source dataset
- Supports multi-language coding
- Supports broad range IDEs
- Planning to extend capabilities
- Code suggestions for self-managed instances
- Vast language support
- Data privacy guarantee
- Coming support for additional IDEs
- Integrated IDE support
- Improving suggestion quality
- Expanded contexts for inference
- Interactive demo
- Ease of use
- Continual expansion plans
- Jetbrains support
- VS Code support
- Web IDE support
- Visual Studio support
- Ruby support
- Swift support
- Scala support
- Rust support
- Python support
- Kotlin support
- JavaScript support
- Java support
- Google SQL support
- Go support
- C# support
- C++ support
- TypeScript support
- NeoVIM support
Cons
- Supports only 13 languages
- Limited control over suggestions
- Limited to GitLab cloud infrastructure
- Static suggestion presentation
- Doesn't use customer's code for training
- Requires secure connection for self-managed instances
- Limited IDE support
- No retention of source code inference
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