cat-pol 0.1.0

Policy document classification powered by LLMs

cat-pol

Policy document classification powered by LLMs. A thin, policy-specific wrapper around cat-stack.

cat-pol adds policy-document-specific prompt framing ("The following is an excerpt from a policy document...") on top of the domain-agnostic cat-stack engine — giving LLMs the context that text comes from policy documents.

Installation

pip install cat-pol

With optional extras:

pip install "cat-pol[pdf]"         # PDF document processing
pip install "cat-pol[embeddings]"  # Embedding-based similarity scoring

Quick Start

Classify policy document excerpts

import cat_pol

results = cat_pol.classify(
    input_data=[
        "The committee voted to approve the rezoning request for parcel 42.",
        "Motion to table the budget amendment until the next session.",
    ],
    categories=["Approval", "Rejection", "Deferral", "Amendment"],
    document_context="City council meeting minutes from March 2026",
    api_key="sk-...",
)

Discover categories from policy text

result = cat_pol.extract(
    input_data=excerpts,
    api_key="sk-...",
    document_context="FOIA request responses regarding environmental compliance",
)
print(result["top_categories"])

Summarize policy documents

summaries = cat_pol.summarize(
    input_data=documents,
    api_key="sk-...",
    description="Legislative bill summaries from the 118th Congress",
)

How It Works

cat-pol is a thin wrapper that:

1. Takes your document_context parameter
2. Injects policy-specific framing: "The following is an excerpt from a policy document. Context: {document_context}."
3. Delegates to cat-stack for all LLM communication, classification logic, batch processing, and ensemble methods

All cat-stack parameters (multi-model ensemble, batch mode, chain-of-thought, etc.) are passed through via **kwargs.

API

Function	Description
classify()	Classify excerpts into predefined categories
extract()	Discover and normalize categories from document text
explore()	Raw category extraction (no deduplication)
summarize()	Summarize documents (pass-through to cat-stack)

Ecosystem

Package	Role
cat-stack	Domain-agnostic LLM classification engine
cat-survey	Survey response classification
cat-pol	Policy document classification (this package)
cat-cog	Cognitive assessment scoring (CERAD)

License

GPL-3.0-or-later