Desktop App

Download and run PraisonAI as a native app on Mac, Windows, or Linux — no Python setup

Download the app, run it, and the Python engine sets itself up on first launch. That’s it.

Download

Grab the latest build from the Releases page, then pick the file for your platform:

Which download do I need?

Follow the branch for your machine.

Open it

The builds are unsigned, so each OS shows a warning the first time. Here’s the one-time click for yours.

xattr -dr com.apple.quarantine /Applications/PraisonAI.app

What happens the first time you open it

The app needs a Python environment to run its engine and offers to build one: it fetches uv, installs a pinned CPython, creates a virtual environment, and installs praisonaiagents into it. Nothing is installed system-wide, and nothing is written inside the app itself — everything lives in one folder.

The folder appears as soon as you open the app; the ≈500 MB environment lands inside it once you click Get started.

On later launches the app also checks the venv against the shipped requirement and re-runs the install once if it drifted (the system tray reads Engine: updating… while it runs). This is why a fix in praisonaiagents reaches you on the next launch instead of requiring you to delete the venv by hand.

To remove the app completely, uninstall it and delete that folder.

Video generation

The Video tab has a model picker. MiniMax video-01 (Replicate) is a preset, not the only option — SDK-capable providers (OpenAI Sora 2, Google Veo 3.1) become selectable once their key is set. Add the relevant key to the .env file inside the data folder above:

Models without a configured key appear disabled in the dropdown. See Video generation for the full walkthrough.

Which models work in the desktop app

The desktop app runs any plain OpenAI-compatible model id (a bare name, no provider/ prefix); to reach a different endpoint, keep the bare id and set a Base URL override in Settings.

What the rejection message means

Saving a slashed id in Settings → Model returns this:

The model id “…” needs the LiteLLM provider path, which this build does not include. Use a plain OpenAI-compatible model id without a provider prefix (for example gpt-4o-mini); to reach another endpoint, keep the bare id and set a Base URL override.

This build ships a lean Python engine without the LiteLLM provider extra. Slashed provider ids need that extra. The remedy is a bare id plus an optional Base URL — not a re-install, and not pip install in your own Python, since the app manages its own environment.

Reach Ollama or another local endpoint

1. Enter the bare model name

   In Settings → Model, type llama3.2 — not ollama/llama3.2.

2. Set the Base URL

   In the Base URL field, enter http://localhost:11434/v1 (Ollama’s OpenAI-compatible endpoint).

3. Save

   The picker accepts it, and turns route to your local server.

To reach Anthropic, Gemini, or others, use the same pattern: a bare model id plus a Base URL for any provider that exposes an OpenAI-compatible endpoint (or a proxy such as LiteLLM Proxy). See OpenAI-compatible endpoints and LiteLLM Proxy.

If it will not start

The window shows the reason and the engine log. Two common ones:

Signing status

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