Skip to main content

Sublinear Python SDK

The official Python client for submitting robot videos and trajectories to Sublinear foundation reward models.

Installation

pip install sublinear

The PyPI distribution is named sublinear, while the Python import package is named sublinear:

from sublinear import Sublinear

Quick start

Create an API key from the Sublinear dashboard, then submit a local MP4 video:

import os
from sublinear import Sublinear
client = Sublinear(api_key=os.environ["SUBLINEAR_API_KEY"])
response = client.responses.create(model="sole-r1", task_description="Fold the clothing.", video_path="episode.mp4")
print(response.rewards)
print(response.success)

You can also provide RGB video frames directly as a list or NumPy array with shape (frames, height, width, 3):

import os
import numpy as np
from sublinear import Sublinear
client = Sublinear(api_key=os.environ["SUBLINEAR_API_KEY"])
video_frames = np.load("video_frames.npy")
response = client.responses.create(model="robometer", task_description="Fold the clothing.", video_frames=video_frames)
print(response.rewards)
print(response.success)

Multiple videos

Pass video_paths to process multiple videos. The SDK submits jobs concurrently, up to max_parallel_jobs at a time.

import os
from sublinear import Sublinear
client = Sublinear(api_key=os.environ["SUBLINEAR_API_KEY"], max_parallel_jobs=8)
response = client.responses.create(model="sole-r1", task_description="Pick up the cube.", video_paths=["episode_1.mp4", "episode_2.mp4"])
print(response.rewards)
print(response.success)

Available models

  • sole-r1 — reasoning-based robot trajectory evaluation
  • robometer — dense task-progress reward estimation
  • topreward — visual reward estimation across robot tasks
  • roboreward — general-purpose robot reward prediction

Documentation

Full documentation and additional input formats are available at sublinear.dev/docs.

Package layout

This project uses a src layout:

sublinear/
├── pyproject.toml
├── README.md
└── src/
    └── sublinear/
        ├── __init__.py
        └── core.py

Your src/sublinear/__init__.py should expose the public client:

from .core import Sublinear
__all__ = ["Sublinear"]

Development

Install the package locally in editable mode:

python -m pip install -e .

Build the source distribution and wheel:

python -m pip install --upgrade build
python -m build

Before publishing, verify the package metadata and archives:

python -m pip install --upgrade twine
python -m twine check dist/*

Publish to PyPI:

python -m twine upload dist/*

License

MIT

Metadata

Release files for sublinear 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sublinear 0.1.1
File Size Uploaded
sublinear-0.1.1.tar.gz 7.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for sublinear 0.1.1
File Interpreter ABI Platform
sublinear-0.1.1-py3-none-any.whl Python 3 none any Details

Total release size: 13.6 kB

Release files / sublinear-0.1.1.tar.gz

Download URL sublinear-0.1.1.tar.gz
Size 7.3 kB
Tags Source
SHA-256 checksum
How to use checksums
51ca506c6cc9bc801e1c2d335c8d5cb2e1d6e2773ce25123cff5196446ed119e
BLAKE2b-256 checksum
How to use checksums
2004e793ae4f1c63b3f856df0bb914b0ed36b4ae87bab11dbf5deda29c93105c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.15

Release files / sublinear-0.1.1-py3-none-any.whl

Download URL sublinear-0.1.1-py3-none-any.whl
Size 6.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
2e58b0788b9d6d1c24d95a30082a0ee0cd0ecb5375c9512e21ec9261e6a0d74a
BLAKE2b-256 checksum
How to use checksums
1c39cdf5e94176d1d1420cf0bb16bf4162baf6e318979e03baa3fa10c15cfa6e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.15

Release history Release notifications | RSS feed

0.2.2

2 release files

0.2.1

2 release files

0.2.0

2 release files

This release

0.1.1 This release

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page