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-0.6.1.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.

swarmauri_vectorstore_doc2vec-0.6.1-py3-none-any.whl (7.8 kB view details)

Uploaded Python 3

File details

Details for the file swarmauri_vectorstore_doc2vec-0.6.1.tar.gz.

File metadata

  • Download URL: swarmauri_vectorstore_doc2vec-0.6.1.tar.gz
  • Upload date:
  • Size: 6.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.12.9 Linux/6.8.0-1021-azure

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.6.1.tar.gz
Algorithm Hash digest
SHA256 ac2ada0676c9a8a7150e6522f7029ac7924456fe536503d6f4fa2c9fe7896914
MD5 ffffaf04325a6fc07b74a466d3b20bf2
BLAKE2b-256 cd3532d2b33533c51914b62474255d898107e7be2d0b49b52a2d863594c4469e

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_doc2vec-0.6.1-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9590350a97c5452e22d3e4d7058085e50cd67811cc55ce659792dc77a6bd7164
MD5 3ef6a81a5e5492e666651fcea6a8c4a8
BLAKE2b-256 13159a88942bdf6cf641ea039dee7de1bc1b1f87b11b1d112cb7b0498cc9b02b

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