The official SDK for the HIDDB vector database.
Use the package manager pip to install the SDK.
pip install hiddbCreate a collection within a database <your database_id>.
from hiddb.synchronous import HIDDB
hiddb = HIDDB("<key>", "<secret>")
# Create a collection named 'wordvectors'
hiddb.create_collection(database_id="<your database_id>", collection_id="wordvectors")Create an index within this collection:
# Create an index on field 'vector' within the collection and dimension 300
hiddb.create_index(
database_id="<your database_id>",
collection_name='wordvectors',
index_name="vector",
dimension=300
)Insert documents like that:
document = {
"vector": [0.0]*300,
"id": "my first document"
}
hiddb.insert_document(
database_id=database_id,
collection_name='wordvectors',
documents=[document]
)Search for nearest documents:
similar_words = hiddb.search_nearest_documents(
database_id="<your database_id>",
collection_name='wordvectors',
index_name="vector",
vectors=[[42.0]*300],
max_neighbors=10
)More examples and a more detailed documentation will follow soon 🚀
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.