Paper Scoring Pipeline
Cross-platform composition layer for Paper Scoring. It combines the core, connectors, and reporting distributions without introducing Git or local-path dependencies.
Configuration is injected at process start. The package never automatically
loads .env during import.
pip install paper-scoring-pipeline==0.1.1
paper-scoring-pipeline --env-file .env score-json paper.json --output score.json
Public Python API
Applications that compose the pipeline can import runtime configuration and service construction directly from the package root:
from paper_scoring_pipeline import (
PipelineSettings,
apply_env_file,
build_scoring_service,
)
apply_env_file(".env")
settings = PipelineSettings.from_environment()
service = build_scoring_service(settings)
apply_env_file loads only the explicitly supplied file and preserves values
already present in the process environment. Passing None performs no action.
Importing paper_scoring_pipeline never loads an environment file.
Score a local PDF:
paper-scoring-pipeline --env-file .env score-pdf paper.pdf --author "Example Researcher"
Run the arXiv workflow without shell-specific date commands:
paper-scoring-pipeline --env-file .env arxiv --category cs.AI --days-ago 2 --max-results 10
The same command works in Ubuntu shells, Windows PowerShell, and the provided Docker image.
All inter-repository dependencies resolve from PyPI. uv.lock records hashes
for development and CI, and the container installs its locked runtime set with
hash verification before installing the local pipeline wheel.
Configuration is read only from the process environment and an explicitly
selected --env-file; importing the package never reads .env. Errors in a
provider, source, report, or SMTP operation are returned as bounded structured
failure metadata. Exception messages and tracebacks are not written to the JSON
output.
The image runs as UID/GID 65532. Compose also drops all capabilities, enables a read-only root filesystem, and prevents privilege escalation. To verify an offline command with networking disabled:
docker run --rm --network none --read-only --cap-drop ALL \
paper-scoring-pipeline:0.1.1 --help
The pipeline needs network access for arXiv, OpenAI, OpenAlex, Ollama, or SMTP.
For an entirely offline invocation, set
PAPER_SCORING_NETWORK_MODE=none when using Docker Compose.
Metadata
Release files for paper-scoring-pipeline 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| paper_scoring_pipeline-0.1.1.tar.gz | 129.8 kB | Without provenance | Details for paper_scoring_pipeline-0.1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| paper_scoring_pipeline-0.1.1-py3-none-any.whl | Python 3 | none | any | Details for paper_scoring_pipeline-0.1.1-py3-none-any.whl |
Total release size: 142.3 kB
Release files / paper_scoring_pipeline-0.1.1.tar.gz
| Download URL | paper_scoring_pipeline-0.1.1.tar.gz |
|---|---|
| Size | 129.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
|
Release files / paper_scoring_pipeline-0.1.1-py3-none-any.whl
| Download URL | paper_scoring_pipeline-0.1.1-py3-none-any.whl |
|---|---|
| Size | 12.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
091d31e57b4eff4b98c5c3512bbf0d24df1847294a7ecf9d87bcf7a04942a5d1
|
|
BLAKE2b-256 checksum How to use checksums |
4cbb0990977a80c8bbce73fce9caed99aca91a9596dcfd40fbe73f839cfb968b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
|
Security for paper-scoring-pipeline 0.1.1
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None of the files in this release were uploaded with provenance metadata.
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