genblaze-decart 0.3.0

Decart Lucy video/image provider adapter for genblaze

genblaze-decart

Decart Lucy video + image provider adapter for genblaze — text-to-video, image-to-video, and image generation/editing AI pipelines with SHA-256 provenance manifests.

genblaze-decart wraps Decart's Lucy family of models as genblaze providers — DecartVideoProvider for text-to-video and image-to-video, DecartImageProvider for text-to-image and image-to-image editing. Compose them into multi-step AI pipelines, persist outputs to Backblaze B2 or any S3-compatible store, and emit a tamper-evident provenance manifest for every run.

Why genblaze-decart

• Lucy Pro video + image + edits — text-to-video, image-to-video, text-to-image, image-to-image, all under one pipeline API.
• Chain Lucy I2V after Lucy T2I — single pipeline, image→video with linked provenance.
• Provenance by default — SHA-256-verified manifest on every output.
• Production-ready — timeouts, retries, progress streaming, step caching.
• Durable storage — plug genblaze-s3 in for Backblaze B2 / AWS S3 / R2 / MinIO persistence.

Providers + models

Provider class	Modality	Models
DecartVideoProvider	video	lucy-pro-t2v (text-to-video), lucy-pro-i2v / lucy-dev-i2v (image-to-video)
DecartImageProvider	image	lucy-pro-t2i (text-to-image), lucy-pro-i2i (image-to-image editing)

Registered via entry points as decart and decart-image.

Install

pip install genblaze-decart

Quickstart — Lucy text-to-video

pip install genblaze-core genblaze-decart
export DECART_API_KEY="..."

from genblaze_core import Modality, Pipeline
from genblaze_decart import DecartVideoProvider

run, manifest = (
    Pipeline("decart-demo")
    .step(DecartVideoProvider(output_dir="output/video"),
          model="lucy-pro-t2v",
          prompt="A serene ocean with dolphins jumping at sunset, cinematic lighting",
          modality=Modality.VIDEO, resolution="720p")
    .run(timeout=300)
)
print(run.steps[0].assets[0].url, manifest.canonical_hash)

Quickstart — Lucy image-to-video chain

from genblaze_core import Modality, Pipeline
from genblaze_decart import DecartImageProvider, DecartVideoProvider

run, manifest = (
    Pipeline("image-to-video", chain=True)
    .step(DecartImageProvider(), model="lucy-pro-t2i",
          prompt="cyberpunk cityscape, neon reflections", modality=Modality.IMAGE)
    .step(DecartVideoProvider(), model="lucy-pro-i2v",
          prompt="camera slowly pans right", modality=Modality.VIDEO)
    .run(timeout=600)
)

Persist to Backblaze B2

from genblaze_core import KeyStrategy, ObjectStorageSink
from genblaze_s3 import S3StorageBackend

storage = ObjectStorageSink(
    S3StorageBackend.for_backblaze("my-bucket"),
    key_strategy=KeyStrategy.HIERARCHICAL,
)
# pass sink=storage to .run(…)

Backblaze B2 is the recommended default sink for large AI-generated video and image assets.

Credentials

Env var	Where to get it
DECART_API_KEY	https://platform.decart.ai/

Documentation

• Main repo: https://github.com/backblaze-labs/genblaze
• Example: decart_video_pipeline.py

Related packages

• genblaze-core — the pipeline SDK
• genblaze-s3 — durable storage on Backblaze B2 and other S3-compatible backends
• Other video providers: genblaze-openai (Sora) · genblaze-google (Veo) · genblaze-runway (Gen-4) · genblaze-luma (Dream Machine)

License

MIT