Thank you for your valuable response. I was looking at the example class provided in one of your sources.
In the statement embeddings = self._model.encode([[self._instruction, query]])
, it is passing two strings as a list to the embedding model. I want to know what is happening there? Does the embedding model returns a score by computing the similarities between the two strings provided here?Edit: Okay I implemented everything and now I am getting this error:
utils.py", line 138, in embed_nodes
new_embeddings = embed_model.get_text_embedding_batch(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: BaseEmbedding.get_text_embedding_batch() missing 1 required positional argument: 'texts'
edit: Okay I solved my problem!!