pyorla

Python SDK for Orla.

Install

From PyPI:

pip install pyorla

With uv, either install into the active environment:

uv pip install pyorla

Or, if you are already in a uv project i.e a directory with a pyproject.toml, add it as a dependency:

uv add pyorla

pyorla talks to a running orla serve daemon over HTTP. Install the Orla binary separately (see the Quickstart for Homebrew, pyorla, and related setup).

Developing pyorla

From a clone of the Orla repo, in the pyorla directory:

uv sync

To run checks, use the following make targets from the repository root:

make pyorla-lint

and

make pyorla-test

Releasing to PyPI

1. Bump version in pyproject.toml.
2. Commit and push a tag: pyorla-vX.Y.Z (must match the version in pyproject.toml).
3. The pyorla-publish workflow builds and uploads to PyPI via trusted publishing.

Remote server

Point OrlaClient at a running daemon:

from pyorla import OrlaClient

client = OrlaClient("https://orla.example.com")
client.health()

Register backends and run workflows / Stage / ChatOrla as in the package examples.

Local server from Python

For development or notebooks, you can spawn orla serve on loopback and get a client back (requires the orla CLI on PATH or ORLA_BIN):

from pyorla import orla_runtime

with orla_runtime() as client:
    client.health()
    # register backends, run execute, etc.

This starts a subprocess (orla serve --listen-address 127.0.0.1:<ephemeral-port>), waits for /api/v1/health, then terminates the process when the block exits.

Colab and remote notebooks

Colab cannot see localhost on your laptop. Use either:

• An Orla daemon on a public URL (VM, Kubernetes, tunnel), and pass that URL to OrlaClient, or
• A tunnel (ngrok, Cloudflare Tunnel, etc.) from the machine where orla serve runs to a URL you paste into the notebook.