Ango Hub Python SDK

A comprehensive Python SDK to interface programmatically with Ango Hub, iMerit's data annotation and AI training platform.

Overview

The iMerit-Ango SDK provides a powerful Python interface for interacting with Ango Hub, enabling you to:

Manage Projects: Create, configure, and manage annotation projects
Upload Data: Import assets from local storage, cloud storage (AWS S3, GCP, Azure), or URLs
Handle Annotations: Import and export annotations in various formats (COCO, YOLO, KITTI, Ango native format)
Workflow Management: Manage labeling workflows, batches, and task assignments
Team Collaboration: Add team members, manage roles, and track performance
Integration: Connect with your existing ML pipelines and data infrastructure

Installation

Install the latest version from PyPI:

pip install imerit-ango

To upgrade to the latest version:

pip install -U imerit-ango

Quick Start

1. Get Your API Key

First, obtain your API key from your Ango Hub account page:

Navigate to your Account page in Ango Hub
Go to the API tab
Create a new API key or copy your existing key

2. Basic Usage

import os
from dotenv import load_dotenv
from imerit_ango.sdk import SDK

# Load environment variables
load_dotenv()

# Initialize SDK
sdk = SDK(api_key=os.getenv('API_KEY'))

# List your projects
projects = sdk.list_projects()
print(f"Found {len(projects)} projects")

# Get project details
project = sdk.get_project(project_id=os.getenv('PROJECT_ID'))
print(f"Project: {project['name']}")

SDK Functions Overview

Project-Level Functions

Project Management: create_project(), get_project(), list_projects(), clone_project()
Data Upload: upload_files(), upload_files_cloud(), upload_chat_assets()
Batch Management: create_batch(), assign_batches(), get_batches()
Task Management: get_tasks(), assign_task(), requeue_tasks()
Annotations: import_labels(), export(), exportV3()
Team: add_members_to_project()
Performance: get_metrics(), get_project_performance()

Organization-Level Functions

Storage: create_storage(), get_storages(), delete_storage()
LLM: create_llm(), get_llms(), delete_llm()
Members: invite_members_to_org(), get_organization_members()
Permissions: update_organization_members_role()
Notifications: send_notification()

Supported Asset Types

The SDK supports a wide variety of data types:

Images: PNG, JPEG, TIFF, BMP, WebP
Videos: MP4, AVI, MOV, WebM
Medical: DICOM, NRRD files
Documents: PDF, Markdown, HTML
Text: Plain text, NER datasets
3D Data: Point clouds, multi-sensor fusion
Audio: WAV, MP3, FLAC
LLM: Chat conversations and responses

Documentation

Comprehensive Documentation

Full SDK documentation is available at: https://docs.imerit.net/sdk/sdk-documentation

Key Resources

Examples

Upload and Create a Labeling Project

# Create a new project
project = sdk.create_project(
    organization_id=org_id,
    name="My Annotation Project",
    description="Object detection for autonomous vehicles"
)

# Upload images from local directory
sdk.upload_files(
    project_id=project['_id'],
    file_paths=['/path/to/images/*.jpg']
)

# Create batches for organized labeling
batch = sdk.create_batch(
    project_id=project['_id'],
    batch_name="Training Set Batch 1"
)

Clone a Project

Clone copies project settings into a new project named {name} copy in the same organization. Assets, tasks, labels, and annotations are not cloned.

# Copy all settings (schema, assignees, batches, workflow, plugin presets, general settings)
cloned = sdk.clone_project(project_id)

# Exclude some sections from the copy
cloned = sdk.clone_project(
    project_id,
    batches=False,
    plugin_presets=False,
)

Export Annotations

# Export annotations in COCO format
export_result = sdk.export(
    project_id=project_id,
    export_format='COCO'
)

# Download the export
import requests
response = requests.get(export_result['downloadUrl'])
with open('annotations.json', 'wb') as f:
    f.write(response.content)

Release Process

Releases are created from master only and are triggered by pushing a vX.Y.Z tag. Using an annotated tag is the recommended release command.

Update the shared package version in imerit_ango/version.py.
Merge that version change into master.
Create an annotated release tag:

git tag -a v1.4.1 -m "Release v1.4.1"

Push the tag to GitHub:

git push origin v1.4.1

When a vX.Y.Z tag is pushed, GitHub Actions verifies that the tagged commit is in master history and that the tag matches the shared version in imerit_ango/version.py. It then builds both Python packages, publishes them to PyPI, and creates GitHub Release notes.

Versioning

The canonical version lives in imerit_ango/version.py as __version__. Both setup_ango.py and setup_imerit_ango.py read from this file, so updating one place is enough. The tag version (without the leading v) must match __version__ exactly or the workflow will fail.

Deployment and Releasing

One-time setup

Before the first automated release you need to configure PyPI trusted publishing and the GitHub environment:

Create a pypi environment in GitHub. Go to the repository Settings > Environments and create an environment named pypi. This is required by the publish job for OIDC token generation.
Configure PyPI trusted publishing for ango. On pypi.org, go to the ango project settings (or create the project if it does not exist yet) and add a trusted publisher with:
- PyPI project name: ango
- Owner: imerit-io
- Repository name: ango-sdk
- Workflow filename: release.yml
- Environment name: pypi
Configure PyPI trusted publishing for imerit-ango. Repeat the same steps for the imerit-ango project on PyPI:
- PyPI project name: imerit-ango
- Owner: imerit-io
- Repository name: ango-sdk
- Workflow filename: release.yml
- Environment name: pypi

After this setup, pushing a vX.Y.Z tag to master will automatically publish both packages and create a GitHub Release.

Release checklist

Update imerit_ango/version.py with the new version number.
Merge the version change into master.

Create and push an annotated tag:

git tag -a v1.4.1 -m "Release v1.4.1"
git push origin v1.4.1

Monitor the GitHub Actions run. If the workflow fails on version mismatch or master-ancestry checks, delete the tag, fix the issue, and re-tag:

git push origin :refs/tags/v1.4.1   # delete the remote tag
git tag -d v1.4.1                    # delete the local tag

Once the workflow succeeds, both ango and imerit-ango will be live on PyPI and a GitHub Release will appear on the repository.

Support

Documentation: https://docs.imerit.net
Status Page: Ango Hub Status
Customer Support: Available through your Ango Hub account

License

This SDK is provided by iMerit Technology Services for use with Ango Hub platform.

For the latest updates and detailed API reference, visit our complete documentation.

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- Sigstore integration time: Sep 2, 2026
Source repository:
- Permalink: imerit-io/ango-sdk@154fbadd3dfc365bf219a4e7d666634ff5acfcb8
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- Owner: https://github.com/imerit-io
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