Stop memorizing commands. Just say what you need.

NL2Shell turns plain English into terminal commands — instantly, locally, privately. No API keys. No cloud dependency. A fine-tuned 0.8B parameter model that runs on a Raspberry Pi.

$ nl2shell "find all Python files larger than 1MB modified this week"
> find . -name "*.py" -size +1M -mtime -7

Every developer has typed "how to tar.gz a folder" into a search engine. ChatGPT works but requires internet, costs money, and sends your workflow context to someone else's server. Shell commands have cryptic syntax that even experienced developers look up constantly.

We fine-tuned Qwen3.5-0.8B (a hybrid DeltaNet architecture) using QLoRA on 12,834 curated natural-language-to-bash pairs. The result is a model small enough for edge devices but accurate enough for daily use.

Key properties:

• Runs fully offline after a one-time 400MB download
• Sub-second inference on Apple Silicon, ~1s on Raspberry Pi 5
• Covers Linux, macOS, git, Docker, Kubernetes, cloud CLIs
• MIT licensed — use it however you want

                          You (plain English)
                               |
                    +----------+----------+
                    |          |          |
                  [web]      [vox]    [collab]
                  browser    voice    desktop
                    |          |          |
                    +-----+----+----------+
                          |
                   [nl2shell model]
                    local via Ollama
                          |
                   [sandbox-bash-mcp]
                    safe execution
                          |
                       terminal

nl2shell is the brain — the fine-tuned model that translates natural language to shell commands.

Three interfaces feed into it:

• nl2shell-web — browser-based, includes an MCP server so AI agents can call it programmatically
• vox — speak commands aloud, get shell output. Fully offline via Ollama
• collab — desktop app with infinite canvas for managing multiple terminal sessions visually

sandbox-bash-mcp provides safe execution — commands run in isolated Docker containers with session persistence, so generated commands can be tested before running on your real system.

Option 1: Try it in the browser Visit nl2shell.com

Option 2: Install the CLI (recommended)

curl -fsSL https://nl2shell.com/install.sh | sh
nl2shell "list all running docker containers sorted by memory"

Option 3: Run the model directly

ollama run hf.co/AryaYT/nl2shell-0.8b "show disk usage by directory"

Option 4: Voice mode

pip install vox-cli
vox "find large log files"

NL2Shell exposes three tools via the Model Context Protocol:

Point your MCP client at https://nl2shell.com/api/mcp to use them.

See agents.txt and llms.txt for full agent integration specs.

We welcome contributions across all repositories. Each repo has its own CONTRIBUTING.md with setup instructions.

Good first issues are labeled good first issue across the org.

Areas where help is most needed:

• Training data: domain-specific command pairs (Kubernetes, AWS, networking)
• Benchmarking: testing on different hardware (especially ARM, Windows WSL)
• Integrations: editor plugins, shell completions, IDE extensions

• Website: nl2shell.com
• Model: HuggingFace
• Dataset: HuggingFace
• Demo: HuggingFace Spaces
• Author: Arya Teja

Built by Arya Teja. Part of the LeSearch AI ecosystem.