Skip to main content

Swarmauri Persistent Qdrant Vector Store

Project description

Swarmauri Logo

PyPI - Downloads PyPI - Python Version PyPI - License PyPI - Version


Swarmauri Qdrant Vector Store

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-0.7.0.dev6.tar.gz (8.5 kB view details)

Uploaded Source

Built Distribution

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

File details

Details for the file swarmauri_vectorstore_qdrant-0.7.0.dev6.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_qdrant-0.7.0.dev6.tar.gz
Algorithm Hash digest
SHA256 1270e77707a6c3f62f48dd6fe503bd4d103b371f5913daa12f781793fb9a518f
MD5 d62968daef40a3702bd7bd0f269422c4
BLAKE2b-256 0731c9ac813015f93547ccde393c3f14fcd7a083e6a4bee8b29ca72ec5e102b7

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_qdrant-0.7.0.dev6-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_qdrant-0.7.0.dev6-py3-none-any.whl
Algorithm Hash digest
SHA256 b3d37bade1d986c74148868bd8345f484f1c1350802db017eb5ce16bee3b2712
MD5 1dcf6dc051c395bf23c6f4c2136dafb4
BLAKE2b-256 7ada9c25f25e8904242edded1583d57a6765bbc559987b7f359fb4b7ad66ff23

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