Package profile

unstructured

3 known vulnerabilitiesLatest: GHSA-4mvj-m6j5-pmf7 — unstructured: Server-Side Request Forgery in the URL-based partitioning View all →

Unstructured has 49 dependencies, 25 of which optional.

doclingSDK and CLI for parsing PDF, DOCX, HTML, and more, to a unified document representation for powering downstream workflows such as gen AI applications.
coremltoolsCommunity Tools for Core ML
spark-nlpJohn Snow Labs Spark NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.
ml-collectionsML Collections is a library of Python collections designed for ML usecases.
mlflowMLflow is an open source platform for the complete machine learning lifecycle
mlflow-skinnyMLflow is an open source platform for the complete machine learning lifecycle
transformersTransformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

3 known vulnerabilitiesLatest: GHSA-4mvj-m6j5-pmf7 — unstructured: Server-Side Request Forgery in the URL-based partitioning View all →

Source: ClickPy

Unstructured has 49 dependencies, 25 of which optional.

doclingSDK and CLI for parsing PDF, DOCX, HTML, and more, to a unified document representation for powering downstream workflows such as gen AI applications.
coremltoolsCommunity Tools for Core ML
spark-nlpJohn Snow Labs Spark NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.
ml-collectionsML Collections is a library of Python collections designed for ML usecases.
mlflowMLflow is an open source platform for the complete machine learning lifecycle
mlflow-skinnyMLflow is an open source platform for the complete machine learning lifecycle
transformersTransformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.