deeplake
Deeplake is a data runtime designed for AI agents, offering a serverless multimodal data lake.
- Type
- Agent Skill
- Open source
- Yes
- GitHub Stars
- ★ 9.2k
- Source
- skill-github
- Repository
- github.com/activeloopai/deeplake
Overview
Deeplake is a data runtime specifically designed for AI agents, providing serverless PostgreSQL and multimodal data lakes, supporting scalable data retrieval and training. It simplifies the deployment of enterprise-grade LLM products, supports various data types (embeddings, audio, text, video, images, etc.), and integrates with tools like LangChain and LlamaIndex. Suitable for scenarios such as storing and searching data, managing datasets for deep learning models, and more.
Capabilities
- ▪Serverless PostgreSQL support
- ▪Multimodal data lake
- ▪Data retrieval and training
- ▪Support for multiple data types
- ▪Integration with LangChain and LlamaIndex
Use cases
Setup
pip install deeplake
This information was compiled by AI from public sources and may contain inaccuracies — please refer to the source.
FAQ
Which cloud storage does Deeplake support?
Supports S3, GCP, Azure, and Activeloop cloud.
Is Deeplake open source?
Yes, Deeplake is an open-source project.
Related skills
OpenMetadata
OpenMetadata is an open data context layer that provides trustworthy data context and business semantics for AI.
XHS-Downloader
A link extraction and content collection tool for Xiaohongshu, supporting multiple download and information extraction features.
radiology-skills
A full-stack skill package for medical imaging research, covering the entire process from topic selection to grant application.
dbx
Lightweight cross-platform database management tool supporting over 70 databases.
nihaixia
A Chinese medicine AI capability developed based on Dr. Ni Haixia's teaching materials, covering Six-Channel Differentiation and classic formula selection.
powerbi-modeling-mcp
Power BI Modeling MCP Server provides AI agents with Power BI semantic modeling capabilities.