Skip to main content

A Doc2Vec based Vector Store and Doc2Vec Based Embedding Model.

Project description

Swarmauri 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.dev33.tar.gz (7.0 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.dev33.tar.gz.

File metadata

  • Download URL: swarmauri_vectorstore_doc2vec-0.9.0.dev33.tar.gz
  • Upload date:
  • Size: 7.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.3 {"installer":{"name":"uv","version":"0.10.3","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.9.0.dev33.tar.gz
Algorithm Hash digest
SHA256 6122e5592d51d096b3fece4dd805a908adbc96d8852ae1b5ad1080369d21949e
MD5 9ef398ee365f427a91d07997d86d96c6
BLAKE2b-256 c05e37ea703bd852d4881ed84930b93a99d5168a83db4ba5fb9d3330d8339675

See more details on using hashes here.

File details

Details for the file swarmauri_vectorstore_doc2vec-0.9.0.dev33-py3-none-any.whl.

File metadata

  • Download URL: swarmauri_vectorstore_doc2vec-0.9.0.dev33-py3-none-any.whl
  • Upload date:
  • Size: 8.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.3 {"installer":{"name":"uv","version":"0.10.3","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for swarmauri_vectorstore_doc2vec-0.9.0.dev33-py3-none-any.whl
Algorithm Hash digest
SHA256 86c6ef1224693bbbf37367ca4bd42edce216cdc02322cab91fb106bce4ab7c38
MD5 d6a6dcce1d680b19e67b897103d5bb20
BLAKE2b-256 466445830c3bf45188402cf21a513c732a8662eec3f4c5c5eba673c39cc25c22

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