Ruby wrapper for the Weaviate.io API.
Part of the Langchain.rb stack.
Install the gem and add to the application's Gemfile by executing:
$ bundle add weaviate-ruby
If bundler is not being used to manage dependencies, install the gem by executing:
$ gem install weaviate-ruby
require 'weaviate'
client = Weaviate::Client.new(
url: 'https://some-endpoint.weaviate.network', # Replace with your endpoint
api_key: '', # Weaviate API key
model_service: :openai, # Service that will be used to generate vectors. Possible values: :openai, :azure_openai, :cohere, :huggingface, :google_palm
model_service_api_key: 'xxxxxxx' # Either OpenAI, Azure OpenAI, Cohere, Hugging Face or Google PaLM api key
)# Creating a new data object class in the schema
client.schema.create(
class_name: 'Question',
description: 'Information from a Jeopardy! question',
properties: [
{
"dataType": ["text"],
"description": "The question",
"name": "question"
}, {
"dataType": ["text"],
"description": "The answer",
"name": "answer"
}, {
"dataType": ["text"],
"description": "The category",
"name": "category"
}
],
# Possible values: 'text2vec-cohere', 'text2vec-openai', 'text2vec-huggingface', 'text2vec-transformers', 'text2vec-contextionary', 'img2vec-neural', 'multi2vec-clip', 'ref2vec-centroid'
vectorizer: "text2vec-openai"
)
# Get a single class from the schema
client.schema.get(class_name: 'Question')
# Get the schema
client.schema.list()
# Remove a class (and all data in the instances) from the schema.
client.schema.delete(class_name: 'Question')
# Update settings of an existing schema class.
# Does not support modifying existing properties.
client.schema.update(
class_name: 'Question',
description: 'Information from a Wheel of Fortune question'
)
# Adding a new property
client.schema.add_property(
class_name: 'Question',
property: {
"dataType": ["boolean"],
"name": "homepage"
}
)
# Inspect the shards of a class
client.schema.shards(class_name: 'Question')# Create a new data object.
client.objects.create(
class_name: 'Question',
properties: {
answer: '42',
question: 'What is the meaning of life?',
category: 'philosophy'
}
)
# Lists all data objects in reverse order of creation.
client.objects.list()
# Get a single data object.
client.objects.get(
class_name: "Question",
id: "uuid"
)
# Check if a data object exists.
client.objects.exists?(
class_name: "Question",
id: "uuid"
)
# Delete a single data object from Weaviate.
client.objects.delete(
class_name: "Question",
id: "uuid"
)
# Update a single data object based on its uuid.
client.objects.update(
class_name: "Question",
id: "uuid",
properties: {
question: "What does 6 times 7 equal to?",
category: "math",
answer: "42"
}
)
# Batch create objects
client.objects.batch_create(objects: [
{
class: "Question",
properties: {
answer: "42",
question: "What is the meaning of life?",
category: "philosophy"
}
}, {
class: "Question",
properties: {
answer: "42",
question: "What does 6 times 7 equal to?",
category: "math"
}
}
])
# Batch delete objects
client.objects.batch_delete(
class_name: "Question",
where: {
valueString: "uuid",
operator: "Equal",
path: ["id"]
}
)near_text = '{ concepts: ["biology"] }'
near_vector = '{ vector: [0.1, 0.2, ...] }'
sort_obj = '{ path: ["category"], order: desc }'
where_obj = '{ path: ["id"], operator: Equal, valueString: "..." }'
with_hybrid = '{ query: "Sweets", alpha: 0.5 }'
client.query.get(
class_name: 'Question',
fields: "question answer category _additional { answer { result hasAnswer property startPosition endPosition } }",
limit: "1",
offset: "1",
after: "id",
sort: sort_obj,
where: where_obj,
# To use this parameter you must have created your schema by setting the `vectorizer:` property to
# either 'text2vec-transformers', 'text2vec-contextionary', 'text2vec-openai', 'multi2vec-clip', 'text2vec-huggingface' or 'text2vec-cohere'
near_text: near_text,
# To use this parameter you must have created your schema by setting the `vectorizer:` property to 'multi2vec-clip' or 'img2vec-neural'
near_image: near_image,
near_vector: near_vector,
with_hybrid: with_hybrid,
bm25: bm25,
near_object: near_object,
ask: '{ question: "your-question?" }'
)
# Example queries:
client.query.get class_name: 'Question', where: '{ operator: Like, valueText: "SCIENCE", path: ["category"] }', fields: 'answer question category', limit: "2"
client.query.get class_name: 'Question', fields: 'answer question category _additional { id }', after: "3c5f7039-37f3-4244-b3e2-8f4a083e448d", limit: "1"
client.query.aggs(
class_name: "Question",
fields: 'meta { count }',
group_by: ["category"],
object_limit: "10",
near_text: "{ concepts: [\"knowledge\"] }"
)client.query.explore(
fields: 'className',
near_text: "{ concepts: [\"science\"] }",
limit: "1"
)# Start a classification
client.classifications.create(
type: "zeroshot",
class_name: "Posts",
classify_properties: ["hasColor"],
based_on_properties: ["text"]
)
# Get the status, results and metadata of a previously created classification
client.classifications.get(
id: ""
)# Create backup
client.backups.create(
backend: "filesystem",
id: "my-first-backup",
include: ["Question"]
)
# Get the backup
client.backups.get(
backend: "filesystem",
id: "my-first-backup"
)
# Restore backup
client.backups.restore(
backend: "filesystem",
id: "my-first-backup"
)
# Check the backup restore status
client.backups.restore_status(
backend: "filesystem",
id: "my-first-backup"
)client.nodes# Live determines whether the application is alive. It can be used for Kubernetes liveness probe.
client.live?# Live determines whether the application is ready to receive traffic. It can be used for Kubernetes readiness probe.
client.ready?After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.
To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and the created tag, and push the .gem file to rubygems.org.
Bug reports and pull requests are welcome on GitHub at https://github.com/andreibondarev/weaviate.
The gem is available as open source under the terms of the MIT License.