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 0.2.1

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 0.2.1
File Size Uploaded
sublinear-0.2.1.tar.gz 9.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for sublinear 0.2.1
File Interpreter ABI Platform
sublinear-0.2.1-py3-none-any.whl Python 3 none any Details

Total release size: 18.6 kB

Release files / sublinear-0.2.1.tar.gz

Download URL sublinear-0.2.1.tar.gz
Size 9.9 kB
Tags Source
SHA-256 checksum
How to use checksums
9efaa4c2761abbc472cbfbad2203f44c775dda86bfd567a8da4a4612a951f7ff
BLAKE2b-256 checksum
How to use checksums
36ea476dca52447aebe07df780231d87023dc5abb54312ad5150c80933ff62bc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.15

Release files / sublinear-0.2.1-py3-none-any.whl

Download URL sublinear-0.2.1-py3-none-any.whl
Size 8.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f6b21e0437b2ac633690d1f58d8de8474ea5ee7ca14712bd5f7da83c582b182e
BLAKE2b-256 checksum
How to use checksums
ed9be6a819f11382bd128a3f1ac22e6a535c5290140275775925668815bdbc04
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

This release

0.2.1 This release

2 release files

0.2.0

2 release files

0.1.1

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