Awesome GitHub RepositoriesDocument Segmenters

DeepCode is an agentic development framework designed to orchestrate autonomous AI agents for software engineering tasks. It functions as a multi-agent workflow orchestrator that translates natural language requirements into functional codebases by coordinating specialized agents for architectural planning, intent analysis, and implementation. The platform integrates multiple language models to power these automated routines, providing a unified environment for complex development projects. The system distinguishes itself through its ability to transform academic research papers into executab

Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t

Easy-dataset is a comprehensive platform designed for the end-to-end management of machine learning datasets, specifically tailored for language and vision model fine-tuning. It functions as a centralized environment for the entire data lifecycle, encompassing the automated generation of synthetic training data, the structural organization of document collections, and the systematic annotation of individual data points. The platform distinguishes itself through its integrated evaluation and orchestration capabilities. It provides a dedicated suite for benchmarking models, featuring blind side

DataHub is a metadata management platform designed to unify technical, operational, and business context across diverse data ecosystems. By utilizing a graph-based metadata model and an event-driven ingestion architecture, it creates a centralized source of truth that maps complex data relationships, lineage, and ownership. This foundational framework enables organizations to maintain a synchronized view of their data landscape, supporting both human-led discovery and automated data operations. The platform distinguishes itself through its focus on grounding artificial intelligence and autono

Grobid es un sistema de aprendizaje automático diseñado para transformar publicaciones académicas y científicas en PDF a XML estructurado. Funciona como un analizador de PDF a XML y extractor de metadatos académicos, identificando y normalizando títulos, autores, afiliaciones y referencias bibliográficas de trabajos de investigación. El sistema utiliza un segmentador de documentos de aprendizaje profundo para dividir los PDF sin procesar en regiones funcionales y emplea un resolvedor de referencias bibliográficas para hacer coincidir las citas con registros externos para el enriquecimiento de metadatos y la resolución de DOI. Admite una canalización completa de entrenamiento de modelos de aprendizaje automático, lo que permite la generación de corpus de entrenamiento anotados, reentrenamiento de modelos y la exportación de binarios de modelos. El proyecto cubre una amplia gama de capacidades de extracción, incluyendo el análisis de encabezados de documentos, estructuración del cuerpo del texto completo y la identificación de entidades específicas del dominio como información de financiación y citas de patentes. También proporciona herramientas de análisis espacial para la extracción de cuadros delimitadores y mapeo de coordenadas para sincronizar etiquetas semánticas con el diseño original del PDF. La aplicación se puede desplegar a través de imágenes contenedorizadas e incluye utilidades de línea de comandos para el procesamiento por lotes multiproceso de grandes colecciones de documentos.

GPAC is an open-source multimedia framework built around a pluggable filter graph pipeline, where modular processing units called filters connect into a directed graph to handle media workflows. At its core, the framework centers all media packaging and manipulation on the ISO Base Media File Format (ISOBMFF), with specialized tools for reading, writing, fragmenting, and encrypting MP4 and related containers. It also provides a declarative scene graph composition system for describing interactive multimedia scenes using MPEG-4 BIFS, X3D, SVG, or VRML syntax, alongside a hardware-accelerated re