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2 repositorios

Awesome GitHub RepositoriesDocument Intelligence Pipelines

Modular pipelines that automate the ingestion, parsing, and vectorization of files to enable intelligent data analysis.

Explore 2 awesome GitHub repositories matching data & databases · Document Intelligence Pipelines. Refine with filters or upvote what's useful.

Awesome Document Intelligence Pipelines GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • docling-project/doclingAvatar de docling-project

    docling-project/docling

    61,674Ver en GitHub↗

    Docling is a modular framework designed for document parsing, layout analysis, and structured data extraction. It transforms unstructured files and web content into a unified, hierarchical data model that preserves the spatial and semantic relationships between text, tables, images, and layout elements. By normalizing diverse input formats into a consistent internal representation, the library enables uniform processing across various document types. The project distinguishes itself through a schema-driven approach that maps document regions to strongly-typed objects, ensuring data accuracy t

    Automates the ingestion, parsing, and structuring of unstructured files through a modular pipeline for downstream data analysis.

    Pythonaiconvertdocument-parser
    Ver en GitHub↗61,674
  • zylon-ai/private-gptAvatar de zylon-ai

    zylon-ai/private-gpt

    57,278Ver en GitHub↗

    This project is a privacy-first backend service designed to facilitate retrieval-augmented generation by processing local documents into searchable vector representations. It provides a modular architecture that allows users to ingest diverse file formats, manage document metadata, and perform semantic searches to provide context-aware responses for chat and completion requests. The system distinguishes itself through a database-agnostic abstraction layer that supports various storage backends, ranging from local disk storage to enterprise-grade vector databases. It offers flexible deployment

    Standardizes the ingestion, parsing, and vectorization of files to facilitate semantic search across internal knowledge bases.

    Python
    Ver en GitHub↗57,278
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