bob_vector_db.qdrant_embedder
=============================

.. py:module:: bob_vector_db.qdrant_embedder


Classes
-------

.. autoapisummary::

   bob_vector_db.qdrant_embedder.QdrantEmbedder


Module Contents
---------------

.. py:class:: QdrantEmbedder(model: str, **kwargs)

   Bases: :py:obj:`json_embedder.JsonEmbedder`


   Qdrant JSON embedding interface.

   The __call__ function expects a string with a JSON dict containing the following attributes:
     collection: to be used collection name. 
     documents: list with document content, if also images are provided this should be the caption. 
     metadatas: list of metadata dictionaries used as payload. 
     images: optional list of image file names to embed along with the documents. 
     ids: optional list of id strings, if not provided automatically uuid4 are created. 


   .. py:attribute:: model


   .. py:attribute:: text_model
      :value: None



   .. py:attribute:: image_model
      :value: None



   .. py:method:: __call__(j: str, media: list = None) -> None

      Performs the embedding into the Vector DB

      :param j: Parsable JSON string with embedding information 
      :type j: str



   .. py:method:: embed_images(data: dict, media: list = None)

      Embed dictionary with embedding information.

      :param data: Dictionary with embedding information
      :type data: dict