Skip to main content

Swarmauri Persistent Qdrant Vector Store

Project description

Swamauri Logo

PyPI - Downloads Hits PyPI - Python Version PyPI - License PyPI - swarmauri_vectorstore_qdrant


Swarmauri Vectorstore Qdrant

A vector store implementation using Qdrant as the backend, supporting both persistent local storage and cloud-based operations for document storage and retrieval.

Installation

pip install swarmauri_vectorstore_qdrant

Usage

from swarmauri.documents.Document import Document
from swarmauri.vectorstores.PersistentQdrantVectorStore import PersistentQdrantVectorStore
from swarmauri.vector_stores.CloudQdrantVectorStore import CloudQdrantVectorStore

# Local Persistent Storage
local_store = PersistentQdrantVectorStore(
    collection_name="my_collection",
    vector_size=100,
    path="http://localhost:6333"
)
local_store.connect()

# Cloud Storage
cloud_store = CloudQdrantVectorStore(
    api_key="your_api_key",
    collection_name="my_collection",
    vector_size=100,
    url="your_qdrant_cloud_url"
)
cloud_store.connect()

# Add documents
documents = [
    Document(content="sample text 1"),
    Document(content="sample text 2")
]
local_store.add_documents(documents)

# Retrieve similar documents
results = local_store.retrieve("sample query", top_k=5)

Want to help?

If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

swarmauri_vectorstore_qdrant-0.7.5.tar.gz (8.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

swarmauri_vectorstore_qdrant-0.7.5-py3-none-any.whl (11.8 kB view details)

Uploaded Python 3

File details

Details for the file swarmauri_vectorstore_qdrant-0.7.5.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_qdrant-0.7.5.tar.gz
Algorithm Hash digest
SHA256 d7af0b114e914feef72453f951f9568e335656412536e1783cb32578a7ca94d7
MD5 cb6be7d00235ace70e31a72419f821a3
BLAKE2b-256 302f55a601579dbc81b8cefbbc1d77d96a53817eac3a48d987d943568a746a1a

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_qdrant-0.7.5-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_qdrant-0.7.5-py3-none-any.whl
Algorithm Hash digest
SHA256 61b1faa8fb548789eb812f32f73417c87b8d3140add9788496e1661c8c87b637
MD5 fedf372e4fd9b2c95489b26f764dea1b
BLAKE2b-256 4a4bc843f21d5f8ebdd99cc3cbaaeaf844ab1170f097db3b7b85d1061f0c99e3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page