Add documentation for Elasticsearch vector DB integration

[ehofesmann]

Adds documentation for the new Elasticsearch similarity backend.

Example usage

Setup

Launch elasticsearch:

docker run -p 127.0.0.1:9200:9200 -d \
    --name elasticsearch \
    -e ELASTIC_PASSWORD=elastic \
    -e "discovery.type=single-node" \
    -e "xpack.security.http.ssl.enabled=false" \
    -e "xpack.license.self_generated.type=trial" \
    docker.elastic.co/elasticsearch/elasticsearch:8.15.0

In your fiftyone shell:

pip install elasticsearch

export FIFTYONE_BRAIN_SIMILARITY_ELASTICSEARCH_HOSTS=http://localhost:9200
export FIFTYONE_BRAIN_SIMILARITY_ELASTICSEARCH_USERNAME=elastic
export FIFTYONE_BRAIN_SIMILARITY_ELASTICSEARCH_PASSWORD=elastic

Usage

import fiftyone as fo
import fiftyone.brain as fob
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

# Image similarity

elasticsearch_index = fob.compute_similarity(
    dataset,
    model="clip-vit-base32-torch",
    brain_key="elasticsearch_index",
    backend="elasticsearch",
)

view = dataset.sort_by_similarity("kites high in the air", k=15)

session = fo.launch_app(view)

# Object similarity

fob.compute_similarity(
    dataset,
    patches_field="ground_truth",
    model="clip-vit-base32-torch",
    backend="elasticsearch",
    brain_key="elasticsearch_patches",
)

patches = dataset.to_patches("ground_truth")
view = patches.sort_by_similarity("cute puppies", k=15)

session.view = view

[coderabbitai[bot]]

Walkthrough

The recent changes introduce comprehensive documentation for integrating Elasticsearch with the FiftyOne framework. This enhancement allows users to manage and query computer vision datasets more effectively. Key updates include a detailed setup guide, instructions for utilizing vector search features, and added support for managing similarity indexes. The integration is highlighted across various documentation pages, ensuring users can easily find and utilize Elasticsearch's capabilities within FiftyOne.

Changes

Files	Change Summary
docs/source/integrations/elasticsearch.rst	Added comprehensive documentation detailing the integration of Elasticsearch, including setup, workflows, and management of similarity indexes.
docs/source/integrations/index.rst	Introduced a custom card for Elasticsearch integration, enhancing visibility and accessibility of its documentation.
docs/source/user_guide/brain.rst	Added a new entry for the Elasticsearch backend in the user guide, enriching the list of supported backends.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant FiftyOne
    participant Elasticsearch

    User->>FiftyOne: Connect to Elasticsearch server
    FiftyOne->>Elasticsearch: Establish connection
    User->>FiftyOne: Load dataset
    FiftyOne->>Elasticsearch: Upload vector embeddings
    User->>FiftyOne: Perform similarity query
    FiftyOne->>Elasticsearch: Execute search
    Elasticsearch-->>FiftyOne: Return results
    FiftyOne-->>User: Display results

🌼🐰 In the garden of data, oh what a sight,
Elasticsearch hops in, making queries so bright.
With embeddings and searches, our datasets soar,
FiftyOne and friends, now better than before!
Let's celebrate changes, both big and small,
For in this data dance, we share joy with all! 🌼🐰

[!WARNING]

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