Downloads

OpenJarvis runs entirely on your hardware. Choose the interface that fits your workflow.

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Desktop App

The desktop app is a native window for the OpenJarvis chat UI. All inference and backend processing happens on your local machine — the app connects to the backend you start locally.

Backend required

Start the backend before opening the desktop app. The quickstart script handles everything:

git clone https://github.com/open-jarvis/OpenJarvis.git && cd OpenJarvis
./scripts/quickstart.sh

Download

Platform	Download	Notes
macOS (Apple Silicon)	OpenJarvis.dmg	M1/M2/M3/M4 Macs
Windows (64-bit)	OpenJarvis-setup.exe	Windows 10+
Linux (DEB)	OpenJarvis.deb	Ubuntu, Debian
Linux (RPM)	OpenJarvis.rpm	Fedora, RHEL
Linux (AppImage)	OpenJarvis.AppImage	Any distro

All releases

Browse all versions on the GitHub Releases page.

macOS: "app is damaged" fix

macOS Gatekeeper quarantines apps downloaded from the internet that aren't notarized by Apple. If you see "OpenJarvis is damaged and can't be opened", run this in Terminal to clear the quarantine flag:

xattr -cr /Applications/OpenJarvis.app

Then open the app normally. If you installed from the DMG but haven't moved it to /Applications yet, point the command at wherever the .app bundle is:

xattr -cr ~/Downloads/OpenJarvis.app

Note

This is standard for open-source macOS apps distributed outside the App Store. The command removes the quarantine extended attribute — it does not modify the app.

What's included

The desktop app provides:

• Full chat UI — same interface as the browser app, in a native window
• Energy monitoring — real-time power consumption tracking
• Telemetry dashboard — token throughput, latency, and cost comparison vs. cloud models
• System tray — quick access without keeping a terminal open

The backend (Ollama, Python API server, inference) runs separately on your machine.

Build from source

git clone https://github.com/open-jarvis/OpenJarvis.git
cd OpenJarvis/desktop
npm install
npm run tauri build

The built installer will be in desktop/src-tauri/target/release/bundle/.

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Browser App

Run the full chat UI in your browser. Everything stays local — the backend runs on your machine and the frontend connects via localhost.

One-command setup

git clone https://github.com/open-jarvis/OpenJarvis.git
cd OpenJarvis
./scripts/quickstart.sh

The script handles everything:

1. Checks for Python 3.10+ and Node.js 18+
2. Installs Ollama if not present and pulls a starter model
3. Installs Python and frontend dependencies
4. Starts the backend API server and frontend dev server
5. Opens http://localhost:5173 in your browser

Manual setup

If you prefer to run each step yourself:

Step 1: Clone and installStep 2: Start OllamaStep 3: Start backendStep 4: Start frontend

git clone https://github.com/open-jarvis/OpenJarvis.git
cd OpenJarvis
uv sync --extra server
cd frontend && npm install && cd ..

# Install from https://ollama.com if not already installed
ollama serve &
ollama pull qwen3:0.6b

uv run jarvis serve --port 8000

cd frontend
npm run dev

Then open http://localhost:5173.

What you get

• Chat interface — markdown rendering, streaming responses, conversation history
• Tool use — calculator, web search, code interpreter, file I/O
• System panel — live telemetry, energy monitoring, cost comparison vs. cloud models
• Dashboard — energy graphs, trace debugging, cost breakdown
• Settings — model selection, agent configuration, theme toggle

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CLI

The command-line interface is the fastest way to interact with OpenJarvis programmatically. Every feature is accessible from the terminal.

Install

git clone https://github.com/open-jarvis/OpenJarvis.git
cd OpenJarvis
uv sync

Verify

jarvis --version
# jarvis, version 0.1.0

First commands

# Ask a question
jarvis ask "What is the capital of France?"

# Use an agent with tools
jarvis ask --agent orchestrator --tools calculator "What is 137 * 42?"

# Start the API server
jarvis serve --port 8000

# Run diagnostics
jarvis doctor

# List available models
jarvis model list

# Interactive chat
jarvis chat

Inference backend required

The CLI requires a running inference backend (e.g., Ollama). See the Installation guide for setup instructions.

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Python SDK

For programmatic access, the Jarvis class provides a high-level sync API.

Install

git clone https://github.com/open-jarvis/OpenJarvis.git
cd OpenJarvis
uv sync

Quick example

from openjarvis import Jarvis

j = Jarvis()
print(j.ask("Explain quicksort in two sentences."))
j.close()

With agents and tools

result = j.ask_full(
    "What is the square root of 144?",
    agent="orchestrator",
    tools=["calculator", "think"],
)
print(result["content"])       # "12"
print(result["tool_results"])  # tool invocations
print(result["turns"])         # number of agent turns

Composition layer

For full control, use the SystemBuilder:

from openjarvis import SystemBuilder

system = (
    SystemBuilder()
    .engine("ollama")
    .model("qwen3:8b")
    .agent("orchestrator")
    .tools(["calculator", "web_search", "file_read"])
    .enable_telemetry()
    .enable_traces()
    .build()
)

result = system.ask("Summarize the latest AI news.")
system.close()

See the Python SDK guide for the full API reference.