anonim-video-text-library 0.1.7

Library and CLI for text anonymization plus audio/video transcription with diarization

Anonim Video Text Library

Standalone project for two separate workflows:

• text anonymization for JSON/JSONL/CSV/Markdown/TXT with a persistent people.json dictionary
• audio/video transcription with diarization

Project layout

• src/anonim_video_text_library/ - importable Python package
• text_anonim/ - default runtime workspace for the anonymizer
• examples/Anonimizez_example/ - self-contained anonymizer example
• examples/Transcibator_example/ - self-contained transcription example
• main.py - local wrapper for the transcription CLI
• gpu_backends/ - helper scripts for GPU transcription backends
• whisper.cpp/ - local checkout of whisper.cpp

Installation

cd Anonim_video_text_Library
python3 -m venv .venv
source .venv/bin/activate
pip install -e .

This installs the dependencies for both workflows, including torch, transformers, faster-whisper, pyannote.audio, and imageio-ffmpeg.

Run the anonymizer separately

CLI entrypoints:

python3 -m anonim_video_text_library --help
python3 text_anonim/anonimizer.py --help

Self-contained example:

cd examples/Anonimizez_example
python3 run_anonymizer_example.py

What is inside examples/Anonimizez_example/:

• .env and .env.example for settings
• input/ for source json/jsonl/csv/md/txt files
• output/ for anonymized copies
• runtime_root/files/pii/ for people.json and blocklists
• run_anonymizer_example.py as the runner

The example writes output files to output/. It does not print anonymized content only to the terminal.

Run the transcriber separately

CLI entrypoints:

anonim-video-text-transcribe --help
python3 main.py --help

Self-contained example:

cd examples/Transcibator_example
python3 run_transcriber_example.py

What is inside examples/Transcibator_example/:

• .env and .env.example for settings
• input/ for media files
• output/ for generated transcripts
• run_transcriber_example.py as the runner

If you need diarization, set HF_TOKEN in .env or in your shell.

Generate runtime examples

To generate the same two example folders inside any runtime workspace:

python3 -m anonim_video_text_library \
  --runtime-root /path/to/runtime \
  --example

To rebuild the generated README and example folders:

python3 -m anonim_video_text_library \
  --runtime-root /path/to/runtime \
  --example \
  --force-example

The generated runtime examples live under:

• examples/Anonimizez_example/
• examples/Transcibator_example/

Each example is isolated. The demo scripts no longer create another nested examples/ tree inside their own runtime data.

Default runtime workspace

By default the anonymizer uses:

text_anonim

That workspace contains:

• files/pii/ for input files, people.json, and blocklists
• files/pii_anonymized/ for anonymized output
• README.md with generated workspace instructions
• examples/ with the two generated example folders

Python API

The main public API is TextAnonymizationSession.

from pathlib import Path
from anonim_video_text_library import TextAnonymizationSession

session = TextAnonymizationSession.from_defaults(
    runtime_root=Path("/path/to/runtime"),
    device="auto",
    ner_batch_size=16,
)

text, stats = session.anonymize_text(
    "Jordan Miller from Northwind Labs wrote to [e-mail]",
    file_id="demo.txt",
)
print(text)
print(stats)

payload, stats = session.anonymize_value(
    {
        "title": "Jordan Miller",
        "body": "Northwind Labs contact: [e-mail]",
    },
    file_id="demo.json",
)
print(payload)
print(stats)

directory_stats = session.anonymize_directory(
    input_root=Path("/path/to/input"),
    output_root=Path("/path/to/output"),
    skip_existing=True,
)
print(directory_stats)
print(session.people_file)

Related docs

• text_anonim/README.md
• gpu_backends/README.md
• whisper.cpp/README.md

Notes

• text_anonim/files may contain large working datasets
• whisper.cpp/models/*.bin are not copied automatically with the project
• fairseq_env was intentionally not moved with the standalone package; recreate a local environment if you still need it