session-anonymizer

Therapy Anonymizer

Three-layer PII detection and anonymization for therapy session transcripts. Supports Russian and English. Fully local by default — no data leaves the machine.

Architecture

Three detection layers run in sequence, each catching what others miss:

| Layer | Tool | Catches | Size | Speed |

|-------|------|---------|------|-------|

| 1 | Natasha | Russian names, locations, organizations | 27 MB | instant |

| 2 | OpenAI Privacy Filter (opf) | Phones, accounts, addresses, emails | 2.8 GB | ~1.5s |

| 3 | Ollama LLM | Medications, dates, contextual IDs | 2.5-7 GB | ~10s |

Spans from all layers are merged, overlaps resolved, and a unified redacted output is produced.

Prerequisites

pip install natasha setuptools pymorphy2-dicts-ru
pip install 'opf @ git+https://github.com/openai/privacy-filter.git'
ollama pull qwen3:4b

Each layer is optional — the script gracefully skips unavailable layers and warns.

Usage

Single file

python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py session.txt

Stdin pipe

cat session.txt | python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py

Batch processing

python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py --batch ~/sessions/ -o ~/sessions_clean/

JSON report

python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py session.txt --json

Pseudonyms instead of tags

python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py session.txt --pseudonyms

Select layers / model

# Fast — Natasha only
python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py session.txt --layers natasha

# LLM only — maximum coverage
python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py session.txt --layers ollama --model gemma4:e2b

Encrypt output (AES-256)

python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py session.txt -o clean.txt --encrypt "password"

Invoking from Claude Code

To anonymize text already in context, pipe it through the script:

echo '<text>' | python3 ~/.claude/skills/therapy-anonymizer/scripts/anonymize.py --json

For files, pass the path directly. Always recommend manual review after automated anonymization.

Limitations

• Contextual identifiers ("the only red-haired architect in Kostroma") are NOT detected by any automated tool
• OPF is English-focused — Russian coverage is partial
• Medications detected only by Layer 3 (requires Ollama)
• Does not assess re-identification risk from combinations of non-PII fields

Guardrails

• NEVER send raw transcripts to cloud services
• Cloud verification only on already-anonymized text
• Always recommend manual review for therapy data
• Never log original PII values