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Unstructured Text Python Packages

Python packages with the GitHub topic unstructured-text. Sorted by monthly downloads, with stars and forks.
Clarifai
clarifai-datautils

Extract Transform and Load unstructured data into the Clarifai's AI platform

245 8 0
chigwell
cryptoschema-extractor

This system takes a textual synopsis of a cryptographic scheme and extracts a structured summary that highlights its key components, such as the types of finite fields used, the encryption process, ke

117 1 0
chigwell
auto-comsight

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

75 1 0
chigwell
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.

56 1 0
chigwell
perfbenchify

A new package that transforms unstructured text descriptions of software performance benchmarks into standardized, comparable metrics. Users input text descriptions of performance tests, and the packa

54 1 0
chigwell
heritage-insight

Generates structured summaries, timelines, and thematic insights from historical or cultural texts using pattern matching and language models.

53 1 0
chigwell
sport-evo-summary

A new package that transforms unstructured text about sports evolution into a structured summary. Users input text describing changes in a sport, and the package returns a standardized breakdown of ke

51 1 0
chigwell
rankextractplus

rankextractplus extracts and structures ranked info from text, organizing data for easier comparison and analysis.

51 1 0
chigwell
text-to-struct

text-to-struct converts unstructured text into standardized, structured output

49 1 0
chigwell
unistruct

unistruct extracts structured data from unstructured text, aiding project planning and management by converting free-form inputs into actionable details.

48 1 0
chigwell
release-extractor

Extracts key release details from unstructured text to create clear, structured summaries.

48 1 0
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology