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Choir Code

Choir Code

AGIChoir

|
11 installs
| (1) | Free
Free AI coding assistant powered by distributed inference
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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More Info

Choir Code | Local AI Coding Assistant

Offline-first AI for VS Code. Code completions, chat, and code actions. No API keys. No cloud required.


Features

Chat

Ask questions, generate code, debug errors. Streaming responses in a side panel.

Inline Completions

Type and get suggestions as you code. Accept with Tab.

Code Actions (Right-click)

  • Explain Selection — understand unfamiliar code
  • Fix Selection — get a corrected version with explanation

Multilingual

Responds in your language. Works in English, Portuguese, Spanish, and others.


Not a cloud AI

  • No OpenAI API
  • No remote code execution
  • No data sent to third-party servers
  • No account or login required

Runs locally by default. Network features are optional and never required.


Install

  1. Install "Choir Code" from the VS Code Marketplace
  2. Wait ~60 seconds (downloads runtime + model on first use)
  3. Start coding

No Ollama. No Docker. No config files.


Performance

Metric Value
First load ~30–60s (model download + warmup)
First response ~2–5s
Subsequent responses ~1–2s
RAM usage ~600MB during inference
Disk ~600MB (runtime + model)

Requirements

  • Any x86_64 CPU (Intel/AMD, 2011 or newer)
  • ~600MB free disk
  • ~600MB free RAM
  • Works fully offline

How it works

Choir runs a small AI model (0.5B parameters) directly on your machine. Your code never leaves your computer.

Optional network verification when other nodes are online improving confidence in responses. This is automatic and never required.


Settings

Setting Default Description
choir.endpoint http://localhost:5001 Local node address

Troubleshooting

Chat not responding after install?

  • Wait 60s (model is downloading on first use)
  • Check Output panel → "Choir" for errors

Slow first response?

  • Model loads into RAM on first request (~2-5s)
  • Subsequent responses are fast (~1-2s)

High memory usage?

  • The model uses ~600MB RAM while active
  • Closing VS Code frees the memory

Links

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  • Manifesto

"Every cycle of computation produces real intelligence. Nothing is wasted."

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