Data & Research · GitHub ·9,075 ★

deeplake

Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

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Details

Author
activeloopai
Category
Data & Research
Platform
GitHub
Framework
custom
Language
c++
Stars
9,075
First indexed
2026-05-15
Last active
2026-02-16
Directory sync
2026-05-15
@activeloopai@activeloopaiactiveloop.ai

Overview

Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

Quick start

git

git clone https://github.com/activeloopai/deeplake

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What deeplake can do

llmragdata
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Data — Reads, transforms, and analyses structured data.

Frequently asked questions

What is deeplake?
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
How do I install deeplake?
Use git: `git clone https://github.com/activeloopai/deeplake`. Full setup details on the source page linked above.
Is deeplake open source?
deeplake is published on GitHub.
What are alternatives to deeplake?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for deeplake is sourced from GitHub, published by activeloopai.

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