DocArray

DocArray is an open-source Python framework designed for representing, processing, and transforming multimodal data for artificial intelligence and machine-learning applications. It provides a flexible data abstraction for developers, researchers, application teams, and organizations that need to work with structured and unstructured data such as text, images, documents, tensors, embeddings, and other AI-related objects.

The solution supports common AI and machine-learning workflows including preparing and processing documents, managing embeddings, handling multimodal data, performing similarity-based operations, preparing model inputs and outputs, and integrating structured data into AI and retrieval pipelines. DocArray is suitable for AI developers, machine-learning engineers, researchers, Python developers, and organizations that require a flexible self-hosted framework for data representation, document processing, embeddings, multimodal AI, and intelligent application development.

Features of DocArray:

• Open-source Python framework for representing and processing AI and machine-learning data.
• Provides structured representations for documents, text, images, tensors, and embeddings.
• Supports multimodal data processing for AI and machine-learning applications.
• Supports document and text processing workflows.
• Provides data structures for managing embedding and tensor-based information.
• Supports similarity-based data processing and retrieval workflows.
• Can be integrated with machine-learning and deep-learning models.
• Supports data preparation for AI and retrieval-augmented generation (RAG) pipelines.
• Can be integrated into Python applications and custom AI workflows.
• Suitable for development, research, experimentation, document processing, multimodal AI, and self-hosted machine-learning applications.

Usage instructions:

Activate Virtual Environment:
$ sudo su
$ cd /opt/docarray
$ source venv/bin/activate

# Check installed DocArray version: $ pip show docarray 

Disclaimer: DocArray is provided “as is” under its applicable open-source license. Functionality, performance, supported features, dependency requirements, resource consumption, and compatibility depend on the installed DocArray version, Python environment, integrated machine-learning frameworks, models, and system resources. Users are responsible for securing applications and services, managing dependencies, configuring access controls where required, and complying with applicable software licenses and data-protection requirements. This solution is suitable for self-hosted AI applications, multimodal data processing, embedding workflows, machine-learning development, research, experimentation, document processing, and production AI workflows.