Researchers Python Packages

patzilla

PatZilla is a modular patent information research platform and data integration toolkit. It features 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.

mindflow-synth

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

partnershipparser

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

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.

econ-legalizer

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

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

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