Skip to main content

A Doc2Vec based Vector Store and Doc2Vec Based Embedding Model.

Project description

Swarmauri Logo

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


Doc2Vec Vector Store

A vector store implementation using Doc2Vec for document embedding and similarity search.

Installation

pip install swarmauri_vectorstore_doc2vec

Usage

from swarmauri.vectorstores.Doc2VecVectorStore import Doc2VecVectorStore
from swarmauri.documents.Document import Document


# Initialize vector store
vector_store = Doc2VecVectorStore()

# Add documents
documents = [
    Document(content="This is the first document"),
    Document(content="Here is another document"),
    Document(content="And a third document")
]
vector_store.add_documents(documents)

# Retrieve similar documents
results = vector_store.retrieve(query="document", top_k=2)

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


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_doc2vec-0.7.0.dev6.tar.gz (6.7 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_doc2vec-0.7.0.dev6.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.7.0.dev6.tar.gz
Algorithm Hash digest
SHA256 49bf0e8919bc88d990310a5a9c1dfba8b50df0a9010ed55e1e0ff9dd0dc9983a
MD5 39a3e8be41cafa15d17de29e7e04a7a6
BLAKE2b-256 a1a8929bac496c890bc08b64e64a7098744670f669cb6ddb9baecb211ebbf94d

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_doc2vec-0.7.0.dev6-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.7.0.dev6-py3-none-any.whl
Algorithm Hash digest
SHA256 2d408cedc2eaf5d4cdfe94b4fcaaa940b7c76ada9e5687aeaa77c78408a6ea8f
MD5 d2d342b5017578b6c120b79cce74b0a6
BLAKE2b-256 24766bcd5d7784f96925fc75d94c60e4bce5510713c5b0c795f543869e5a3b70

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