PyMongo-VoyageAI-Multimodal
===========================


Quickstart
----------

First, install PyMongo-VoyageAI-MultiModal:

.. code-block:: bash

    $ pip install pymongo-voyageai-multimodal

Then, perform the multi-modal embedding:

.. code-block:: python

    from pymongo_voyageai_multimodal import PyMongoVoyageAI

    # Create our client.
    client = PyMongoVoyageAI(
        voyageai_api_key=os.environ["VOYAGE_API_KEY"],
        mongo_connection_string=os.environ["MONGODB_URI"],
        s3_bucket_name="<my-bucket-name>",
        collection_name="test",
        database_name="tests",
    )

    # Load data from a pdf url.
    url = "https://www.fdrlibrary.org/documents/356632/390886/readingcopy.pdf"
    images = client.url_to_images(url)
    resp = client.add_documents(images)

    # Wait for the vector search index to update.
    client.wait_for_indexing()

    # Query the embeddings, extracting the images.
    query = "The consequences of a dictator's peace"
    data = client.similarity_search(query, extract_images=True)

    # Display the best image match.
    data[0]["inputs"][0].image.show()

    # Clean up and close the client.
    client.delete_many({})
    client.close()


.. toctree::
 :maxdepth: 3

 api
 examples