paperus-ml
Machine learning service of paperus: text embeddings for search by meaning, with ONNX Runtime on the CPU. Models are downloaded from Hugging Face on first use and unloaded when idle.
pip install paperus-ml
PAPERUS_ML_TOKEN=… paperus-ml --host 0.0.0.0 # port 3003
Settings are environment variables:
| Variable | Default | Meaning |
|---|---|---|
PAPERUS_ML_TOKEN |
none | Shared secret; requests need Authorization: Bearer <token> |
PAPERUS_ML_CACHE_PATH |
~/.cache/paperus-ml |
Downloaded models |
PAPERUS_ML_PRELOAD |
[] |
Models to load at start and keep, e.g. ["arctic-embed-m-v2"] (paperus then sends the one in use) |
PAPERUS_ML_MODEL_TTL |
300 |
Unload other models after this many idle seconds (0: never) |
PAPERUS_ML_INTRA_OP_THREADS |
0 |
CPU cores per model at start (0: all it sees); paperus' administration sets it afterwards |
PAPERUS_ML_MAX_BATCH_TEXTS / _TOKENS |
32 / 16384 |
Batch size (memory grows with both) |
paperus sends its settings with PUT /config (cores, models to keep
loaded). One batch runs at a time per model, using all its cores; simultaneous
requests take turns batch by batch.
Most installations use the paperus-ml container image instead. Status:
early version (0.0.x); expect breaking changes.
Metadata
Release files for paperus-ml 0.0.8
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| paperus_ml-0.0.8.tar.gz | 13.4 kB | With provenance | Details for paperus_ml-0.0.8.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| paperus_ml-0.0.8-py3-none-any.whl | Python 3 | none | any | Details for paperus_ml-0.0.8-py3-none-any.whl |
Total release size: 29.5 kB
Release files / paperus_ml-0.0.8.tar.gz
| Download URL | paperus_ml-0.0.8.tar.gz |
|---|---|
| Size | 13.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / paperus_ml-0.0.8-py3-none-any.whl
| Download URL | paperus_ml-0.0.8-py3-none-any.whl |
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| Size | 16.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
7a8a5c4041311d67483886b8a587ab2f938860299d1fc6f5e9c062af41b73765
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
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Signed by GitHub Actions, verified by PyPI on Nov 5, 2026.
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