deeplake-skills

Deeplake Managed Service SDK

Agent-friendly SDK for ingesting data into Deeplake managed tables. Use this skill when users want to store, ingest, or query data in Deeplake. Available in both Python and Node.js/TypeScript.

Quick Reference

Python

pip install deeplake # uv add deeplake 

Python import (primary):

from deeplake import Client

# Async variant (requires aiohttp: pip install aiohttp):
from deeplake.managed import AsyncClient

from deeplake import Client

# Initialize -- token from DEEPLAKE_API_KEY env var, workspace defaults to "default"
client = Client()
client = Client(token="dl_xxx", workspace_id="my-workspace")

# Ingest files (FILE schema)
client.ingest("videos", {"path": ["video1.mp4", "video2.mp4"]}, schema={"path": "FILE"})

# Ingest structured data with indexes for search
client.ingest("embeddings", {
    "text": ["doc1", "doc2", "doc3"],
    "embedding": [[0.1, 0.2, ...], [0.3, 0.4, ...], [0.5, 0.6, ...]],
}, index=["embedding", "text"])

# Ingest from HuggingFace
client.ingest("cifar", {"_huggingface": "cifar10"})