twinnydotdev/twinny

The most no-nonsense, locally or API-hosted AI code completion plugin for Visual Studio Code - like GitHub Copilot but 100% free.

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Summary Information

Updated 29 minutes ago
Added to GitGenius on September 19th, 2026
Created on August 21st, 2023
Open Issues & Pull Requests: 49 (+0)
GitHub issues: Enabled
Number of forks: 229
Total Stargazers: 3,650 (+0)
Total Subscribers: 1 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 22.0 hours
Mean response time: 20.1 days
90th percentile: 48.4 days
Tracked items: 98

Most active contributors

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How this project is maintained

90% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Three people close 74% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 31
New in 7 days: 1
Closed in 7 days: 1
Avg open age: 617 days
Stale 30+ days: 30
Stale 90+ days: 30

Recent activity

Opened in 7 days: 1
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • help wanted (14)
  • enhancement (13)
  • good first issue (9)
  • bug (8)
  • question (4)
  • documentation (1)

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Detailed Description

Twinny is a Visual Studio Code extension that provides AI-powered code completion and chat features, available for free with support for both local and API-hosted models.

The tool addresses the cost barrier of commercial AI coding assistants by offering fill-in-the-middle code completion and conversational AI features without subscription fees. It works by connecting to either a locally-hosted model via Ollama or compatible APIs, or to external providers including OpenAI, Anthropic, Mistral, Groq, and others. The extension provides real-time inline suggestions as you type, alongside a sidebar chat interface for discussing code, requesting refactoring, generating tests, and creating commit messages. Workspace embeddings enable context-aware assistance by understanding your project structure.

Twinny suits developers who want AI coding assistance without ongoing costs or who require privacy-preserving local execution. It works well for teams through its gateway feature, which allows one model server to serve multiple developers with centralized configuration and usage tracking. The extension is particularly valuable for those already using Ollama or running local language models, as it integrates seamlessly with existing setups. Unlike commercial alternatives, it offers complete offline operation and customizable API endpoints, giving users control over which models and providers they use.

Development activity shows consistent engagement with the project. The maintainers actively solicit contributions through GitHub issues and social channels. The tool receives regular updates addressing functionality and user-reported issues. The project maintains documentation including setup guides and team deployment instructions, indicating sustained attention to user onboarding and feature explanation.