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-0.7.5.dev1.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-0.7.5.dev1.tar.gz.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.7.5.dev1.tar.gz
Algorithm Hash digest
SHA256 aedcac1b54af9e18dfa6a4d7e1dea001aa7607a17f322da4764461a9416fcd00
MD5 3187b6507015fb4df6ff30d23397a3b9
BLAKE2b-256 09a76406f6a7e890678a1fedc43f416fbf1ae7a64826e533a40bbb809251ef74

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_doc2vec-0.7.5.dev1-py3-none-any.whl.

File metadata

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.7.5.dev1-py3-none-any.whl
Algorithm Hash digest
SHA256 32ccb3f4ed624b4ce86d1d9a130532a0f5ca7f1c96816e85abc8fbadcbaf3ded
MD5 5ce5b25cf477d50dcef14bb257f83e32
BLAKE2b-256 447bc3d99786564f87479ffd173e4b0eba5e5e80a0fe28ad86985e756bbeaa1c

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