Weaviate Vector Store in Python

import weaviate
from weaviate.classes.config import Configure, Property, DataType
from weaviate.classes.query import MetadataQuery

client = weaviate.connect_to_local()

if not client.collections.exists('Article'):
    client.collections.create(
        'Article',
        vectorizer_config=Configure.Vectorizer.text2vec_openai(),
        properties=[Property(name='content', data_type=DataType.TEXT), Property(name='title', data_type=DataType.TEXT)],
    )

collection = client.collections.get('Article')
collection.data.insert_many([
    {'content': 'Python is great for AI.', 'title': 'Python AI'},
    {'content': 'LLMs power modern chatbots.', 'title': 'LLMs'},
])

results = collection.query.near_text(query='artificial intelligence', limit=2, return_metadata=MetadataQuery(distance=True))
for obj in results.objects:
    print(obj.properties, obj.metadata.distance)

client.close()