Researchers Python Packages

patzilla

PatZilla is a modular patent information research platform and data integration toolkit with a modern user interface and access to multiple data sources.

vitae-parser

vitae-parser extracts and structures biographical details from unstructured text using pattern matching.

texttoknowledge

Convert unstructured text into structured, queryable knowledge with llmatch-messages. Extract and organize key details for fast, reliable access—ideal for teams and researchers.

auto-comsight

Auto-comsight extracts structured insights from text about autonomous systems, categorizing components, challenges, and optimizations.

chronicle-ai

Chronicle-ai extracts and summarizes historical queries into structured, formatted summaries using llmatch-messages for clarity.

hnbookextractor

A new package is designed to analyze user-submitted text about Hacker News discussions to identify and extract a structured list of books mentioned in 2025. It leverages language models to recognize b

eco-num-extract

eco-num-extract turns natural science text into structured numeric data using llmatch-guided outputs.

econ-legalizer

econ-legalizer is a package that extracts structured summaries and insights from text input on regional economic and legal issues.

pre-v7-unix-summarizer

A new package that processes text input related to early Unix history (pre-V7) and returns structured, verified summaries using pattern matching and LLM interactions. It takes user-provided text (e.g.

partnershipparser

partnershipparser extracts and structures key info from tech partnership news for easy analysis of companies, focus areas, and impacts

summaryxtract

A new package is designed to facilitate structured, reliable extraction of key insights from user-provided texts about cultural topics. It accepts a text input, such as an article or discussion prompt

mindflow-synth

mindflow-synth extracts and structures insights on deep focus and flow from text, providing consistent, actionable summaries.

undesirablereasons

A new package that helps users extract and organize key reasons from text inputs, specifically focusing on why certain actions or outcomes might be undesirable. For example, given a text input about t