Release Note

This release contains 1 new feature, 3 bug fixes and 2 documentation improvements.

🆕 Features

Add Epsilla connector (#1835)

We have integrated Epsilla into DocArray.

Here's a simple example of how to use it:

import numpy as np
from docarray import BaseDoc
from docarray.index import EpsillaDocumentIndex
from docarray.typing import NdArray
from pydantic import Field


class MyDoc(BaseDoc):
    text: str
    embedding: NdArray[10] = Field(is_embedding=True)

docs = [MyDoc(text=f'text {i}', embedding=np.random.rand(10)) for i in range(10)]
query = np.random.rand(10)
db = EpsillaDocumentIndex[MyDoc]()
db.index(docs)
results = db.find(query, limit=10)

In this example, we create a document class with both textual and numeric data. Then, we initialize an Epsilla-backed document index and use it to index our documents. Finally, we perform a search query.

🐞 Bug Fixes

Fixed type hints error in Python 3.12 (#1840)

DocArray type-hinting is now available for Python 3.12.

Fix issue serializing and deserializing complex schemas (#1836)

There was an issue when serializing and deserializing protobuf documents with nested documents in dictionaries and other complex structures.

Fix storage issue in TorchTensor class (#1833)

There was a bug when deep-copying a TorchTensor object its dtype was not float32. This has now been fixed.

📗 Documentation Improvements

• Add Epsilla integration guide (docs(epsilla): add epsilla integration guide #1838)
• Fix sign commit command in docs (docs: fix sign commit commad in docs #1834)

🤟 Contributors

We would like to thank all contributors to this release:

• Tony Yang (@tonyyanga )
• Naymul Islam (@ai-naymul )
• Ben Shaver (@bpshaver )
• Joan Fontanals (@@JoanFM)
• 954 (@954-Ivory )