OmniBioAI SDK

OmniBioAI SDK is a lightweight Python client for interacting with the OmniBioAI platform APIs, including:

• Object Registry (datasets, studies, jobs, workflows)
• Development APIs (/api/dev/*)
• Jupyter-based interactive analysis workflows

The SDK is intentionally thin and explicit — it does not hide API behavior and is designed to evolve alongside the OmniBioAI platform.

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Features

• Simple Python client (OmniClient)
• Works with local OmniBioAI development servers
• No Docker required
• Designed for notebooks, scripts, and pipelines
• Explicit auth and base URL control
• Easy to extend with new API endpoints

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Installation

pip install omnibioai-sdk

Or during development:

pip install -e .

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Quick Start

from omnibioai_sdk import OmniClient

c = OmniClient(
    base_url="http://127.0.0.1:8001",
    token="dev"
)

objects = c.objects_list()
print(objects["count"])

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Authentication

The SDK uses header-based authentication.

For development:

Authorization: Bearer dev

You can pass credentials explicitly or via environment variables.

Environment Variables (recommended)

export OMNIBIOAI_BASE_URL=http://127.0.0.1:8001
export OMNIBIOAI_TOKEN=dev

Then simply:

c = OmniClient()

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Object Registry API

List objects

lst = c.objects_list()
lst["count"]
lst["items"][0]

Get a single object

obj = c.object_get("56d3fc3a-709b-4ed0-bf17-8cb73c6746b0")
print(obj["object_type"])
print(obj["metadata"])

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Notebook-Based Analysis

OmniBioAI supports launching object-aware Jupyter notebooks.

Typical flow:

1. User clicks “Analyze in Notebook” in the OmniBioAI UI
2. Django endpoint generates a notebook
3. JupyterLab opens with the object context preloaded

Inside the notebook:

import os
from omnibioai_sdk import OmniClient

OBJECT_ID = os.environ["OMNIBIOAI_OBJECT_ID"]

c = OmniClient()
obj = c.object_get(OBJECT_ID)

obj["object_type"], obj["metadata"]

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Running Jupyter for OmniBioAI

Recommended dev command:

jupyter lab \
  --port 8890 \
  --port-retries=0 \
  --no-browser \
  --notebook-dir . \
  --IdentityProvider.token=devtoken

And set:

export OMNIBIOAI_JUPYTER_BASE=http://127.0.0.1:8890
export OMNIBIOAI_JUPYTER_TOKEN=devtoken

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Project Structure

omnibioai_sdk/
├── omnibioai_sdk/
│   ├── __init__.py
│   └── client.py
├── pyproject.toml
├── README.md

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Design Philosophy

• No magic: SDK mirrors REST APIs closely
• Dev-first: optimized for local servers and notebooks
• Composable: meant to be imported into pipelines, workflows, and notebooks
• Extensible: new APIs = new methods, not rewrites

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Extending the SDK

Add new API calls by extending OmniClient:

def workflow_list(self):
    r = requests.get(
        f"{self.base_url}/api/dev/workflows/",
        headers=self.headers,
        timeout=self.timeout
    )
    r.raise_for_status()
    return r.json()

No regeneration or codegen required.

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Versioning

The SDK follows semantic versioning:

• 0.x → fast iteration
• 1.0+ → stable API surface

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License

Apache License 2.0

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Status

Active development Used internally by the OmniBioAI workbench and services.

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Opening objects in analysis environments

For opening objects in JupyterLab, VS Code, or RStudio, see the omnibioai-launcher repository. The launcher is a standalone React UI that accepts an object_id via URL parameter and handles environment dispatch.