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Installation

The base install is deliberately tiny — pyyaml + httpx. Optional detection layers are pulled in as extras.

pip install wardcat            # base: regex + Ollama/OpenAI-compatible LLM backend
pip install "wardcat[ner]"     # + SpaCy NER (PERSON, ORG, ADDRESS)
pip install "wardcat[phone]"   # + national phone formats (libphonenumber)
pip install "wardcat[all]"     # everything: SpaCy + Transformers

git clone https://github.com/oguzhantopcu0/wardcat.git
cd wardcat
uv sync                 # base: regex + Ollama/OpenAI-compatible LLM backend
uv sync --extra ner     # + SpaCy NER (PERSON, ORG, ADDRESS)
uv sync --extra all     # everything: SpaCy + Transformers

Extras

Extra Adds Layer
(base) regex detection + Ollama / OpenAI-compatible LLM backend regex, llm (HTTP)
ner SpaCy ner
transformers HuggingFace Transformers + torch llm (in-process)
all everything above all

SpaCy models (for the NER layer)

The NER layer needs a language model. The simplest path is to let wardcat resolve and download it via the language= builder:

from wardcat import Wardcat, Language

guard = Wardcat().with_ner(language=Language.EN)                   # → en_core_web_sm
guard = Wardcat().with_ner(language=Language.TR, spacy_size="md")  # → tr_core_news_md

Or download a model yourself:

uv run python -m spacy download en_core_web_sm
uv run python -m spacy download tr_core_news_md

Requirements

  • Python 3.11+