Skip to main content

A Doc2Vec based Vector Store and Doc2Vec Based Embedding Model.

Project description

Swamauri Logo

PyPI - Downloads Hits PyPI - Python Version PyPI - License PyPI - swarmauri_vectorstore_doc2vec


Swarmauri Vectorstore Doc2vec

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-0.9.0.dev4.tar.gz (6.9 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-0.9.0.dev4.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.9.0.dev4.tar.gz
Algorithm Hash digest
SHA256 8708566fbdb19fdb7853955a966f0e105b0f545c608d41d07ed081fd64cc85ba
MD5 c30ed62d7efbfd7987af5a92365fd3a7
BLAKE2b-256 dabcd18e3a45b2333e386c0c02c8c951dfe4bb064594a7031c24efe7e2ed03ff

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_doc2vec-0.9.0.dev4-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.9.0.dev4-py3-none-any.whl
Algorithm Hash digest
SHA256 3ea69365658945ce66c1595df3fdad1735a0907143e672fc8a47764a50210ba1
MD5 94c2b59117cf02e0e478e45f924a64f6
BLAKE2b-256 09e21d6ed3e6174ca8b3b619a08f3476ee24431ebf37bc811c4ba3f8f37335cb

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