intextum-worker
The Intextum processing worker: an HTTP-polling worker that pulls tasks from an Intextum API instance and runs the Docling / FFmpeg document, image and audio pipeline (OCR, ASR, chunking, classification, content enrichment, embeddings).
The worker is always-remote: it downloads source files from and uploads results to the API over HTTP, so it does not need a shared volume and can run anywhere — including on a host with a GPU while the rest of the stack runs in Docker.
Install
Pick the bundle that matches your accelerator. The macOS (Apple MPS) wheels are on PyPI, so it installs with no extra flags:
pip install 'intextum-worker[mps]'
Linux CPU and NVIDIA CUDA pull their Torch build from the PyTorch index, so add
the matching --extra-index-url:
# Linux, CPU only
pip install 'intextum-worker[cpu]' --extra-index-url https://download.pytorch.org/whl/cpu
# Linux, NVIDIA CUDA 12.6
pip install 'intextum-worker[cuda]' --extra-index-url https://download.pytorch.org/whl/cu126
Available extras: mps, cpu, cuda, cpu-document (document/image only), plus
the granular document, asr, enrichment stacks.
Run
export API_URL="https://your-intextum-host" # the API to poll
export WORKER_TOKEN="<token from the Add Worker dialog>"
intextum-worker --capabilities document,video,image
intextum-worker --help lists all flags. Every flag also has an environment
variable (API_URL, WORKER_TOKEN, WORK_DIR, CAPABILITIES, POLL_INTERVAL,
CLASSIFICATION_DEVICE, DOCLING_OCR_ENGINE, …); CLI flags take precedence.
Development
This package uses a src/ layout. The repo-root VERSION file is the single
source of truth for the version; it is staged into worker/VERSION at build time
(worker/VERSION is gitignored).
cp ../VERSION VERSION # stage the version for an editable install
pip install -e '.[mps,test]' # or [cpu,test] / [cuda,test]
pytest
export API_URL="http://localhost:8000"
export WORKER_TOKEN="<token from the Add Worker dialog>"
export CLASSIFICATION_DEVICE="mps" # macOS Apple Silicon; use cpu/cuda elsewhere
intextum-worker --capabilities document,video,image,training
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