docarray/docarray

Health v2 · maintenance only

Adoption not part of the score

3124 stars · 243 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DocArray is a Python library for representing, transmitting, storing, and retrieving multimodal data such as text, images, audio, and video. Built on Pydantic, it integrates with NumPy, PyTorch, TensorFlow, and JAX, and supports vector databases like Weaviate, Qdrant, Elasticsearch, and Redis.

Use cases

• represent multimodal data for machine learning models
• store and search embeddings in a vector database
• build semantic search over images and text
• send documents as JSON over HTTP or Protobuf over gRPC
• structure training data for PyTorch or TensorFlow
• build multimodal AI applications with FastAPI

When to choose

• you need typed data structures for mixed media (text, image, audio) in ML pipelines
• you want a unified interface to multiple vector databases
• you need Pydantic/FastAPI-compatible document models for ML services

When to avoid

• you only need plain tabular data (use pandas)
• you need a full vector database rather than a client-side data structure
• you rely on DocArray <=0.21 APIs, which differ significantly from 0.30+

Facets

library · maturity active

serialization vector-database search-engine machine-learning rag machine-learning deep-learning data-science large-language-models python cross-platform multimodal-data data-structures pydantic nearest-neighbor-search embeddings protobuf doclist search retrieval-augmented-generation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="docarray/docarray")