tabnine-vscode
TabNine
Our great sponsors
tabnine-vscode | TabNine | |
---|---|---|
1 | 7 | |
1,335 | 10,387 | |
1.1% | 1.2% | |
9.4 | 0.0 | |
9 days ago | about 20 hours ago | |
TypeScript | Shell | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tabnine-vscode
-
Understanding AI for coders: Tabnine (your alternative to GitHub Copilot)
Both are related to limitations of vscode completion engine, so Tabnine can't really blamed for them in any way.
1. Initially Tabnine's auto-completion was triggered on any character, which best leveraged Tabnine's power but also had inherent problem: when Tabnine was triggered on non-letter character it sometimes prevented Vscode from showing suggestions from other completion sources (LSPs, snippets). There is a discussion in https://github.com/codota/tabnine-vscode/issues/6 with me explaining that the only viable solution is to reduce set of trigger characters to letters only. In the end a fix was pushed that reduced the set of trigger characters, which made the problem less likely but still not solved. The are numerous duplicates of this issue on Github.
2. Another problem is when Vscode has auto-completion suggestions from Tabnine and other sources (LSP, snippets), it frequently puts Tabnine's at the top of list. This is a big no-go for me because most of the time just want to complete the identifier (class field, method etc.). Modifying just the extension code didn't help so in the end I had add a small patch to Vscode itself, which gives lowest score to Tabnine's candidates: https://github.com/sergei-dyshel/vscode/commit/ee73034b9ec6c....
I must admit that both problems can be practically solved by new "inline auto-completion" mechanism in vscode which looks very promising for AI-based completion in general. I'm looking forward to evaluate it.
TabNine
-
Tabnine ships new code-native AI models, passes 1 million developers using its AI code assistant
Other people complaining too: https://github.com/codota/TabNine/issues/179
- L'Italia è il primo paese dell'Unione Europea per percentuale di NEET (giovani che non studiano nè lavorano) - Cosa ne pensate?
-
The Complete API Security Checklist
As applications grow in value to the end user so do they grow in complexity. Developers are pressured to increase productivity. Startups like Tabnine and Raycast have had impressive funding rounds recently, indicating how important developer productivity has become. With this pressure to perform, developers don't have the time to test each API connection for vulnerabilities or perform periodical penetration testing to ensure that new attack surfaces are not being introduced.
- GitHub Copilot Beta – My Experience
- GitHub Copilot: your AI pair programmer
-
42 Companies using Rust in production
We also use rust to build Tabnine! (see https://tabnine.com)
-
Tabnine links
Tabnine backend: https://github.com/codota/TabNine
What are some alternatives?
vscode-plugin - Kite Autocomplete Plugin for Visual Studio Code
copilot-cli - The AWS Copilot CLI is a tool for developers to build, release and operate production ready containerized applications on AWS App Runner or Amazon ECS on AWS Fargate.
lsp-mode - Emacs client/library for the Language Server Protocol
Flowgorithm-macOS - Flowgorithm for Mac OS
cpk - Light and fast package manager on C/C++ for C/C++/Python/Rust/Js packages
githut - Github Language Statistics
useful-java-links - A list of useful Java frameworks, libraries, software and hello worlds examples
asciinema - Terminal session recorder 📹
vscode-plugin - VS Code plugin that suggests code blocks as you type and check for errors. Works for JavaScript, TypeScript, Python, Java, Scala, Ruby, PHP, Apex, Docker
pen.el - Pen.el stands for Prompt Engineering in emacs. It facilitates the creation, discovery and usage of prompts to language models. Pen supports OpenAI, EleutherAI, Aleph-Alpha, HuggingFace and others. It's the engine for the LookingGlass imaginary web browser.
arl - lists of most popular repositories for most favoured programming languages (according to StackOverflow)
stable-baselines3-contrib - Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code