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Categorization Python Packages

Python packages with the GitHub topic categorization. Sorted by monthly downloads, with stars and forks.
rosette-api
rosette-api

Babel Street Analytics Client Library for Python

2K 38 37
jexp
watfile

Text/PDF - File categorization and sorting with Typesafe AI Jev or local calibrated decision model

2K 2 0
ediazpacheco
taxomesh

A multi-parent category graph with a Python stdlib-style interface — subscript, get, in, len, del — over YAML, JSON or Django storage.

1K 0 0
eddyluten
mkdocs-categories-plugin

An MkDocs plugin allowing for categorization of wiki pages

1K 16 1
chigwell
textcurator-llm-py

A new package would process user-provided text inputs, such as headlines or short descriptions, and generate structured summaries or categorizations using an LLM. It would be particularly useful for c

210 1 0
Kyle-Ross
glyphdeck

The glyphdeck library is a comprehensive toolkit designed to streamline & simplify various aspects of asynchronous LLM data processing workflows over high-volume, dense semantic data.

163 2 1
aau-network-security
richkit

Domain Enrichment Toolkit $ pip install richkit

125 11 3
artitw
text2class

Multi-class text categorization using state-of-the-art pre-trained contextualized language models, e.g. BERT

106 23 2
chigwell
ai-design-insights

A new package that helps extract and structure insights from discussions about AI system design challenges. Users can input text from forums, articles, or discussions, and the package will use llmatch

101 2 1
whois-api-llc
website-categorization

Website Categorization API client library for Python

51 1 0
chigwell
phenomenon-interpreter

phenomenon-interpreter analyzes textual descriptions of natural events to generate structured summaries or classifications automatically

50 1 0
chigwell
vpnfeedbacker

A new package that simplifies and structures user feedback or descriptions about VPN sign-up experiences. It takes text input from users describing their sign-up process with a VPN service, such as ea

38 1 0
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology