fix FAISS embedding code as it is failing with "FAISS.__init__() missing 4 required positional arguments"

[johnsirmon]

fix bug
line 21, in
faiss_store = FAISS()
^^^^^^^
TypeError: FAISS.init() missing 4 required positional arguments: 'embedding_function', 'index', 'docstore', and 'index_to_docstore_id'

I think I need to modify as follows
from langchain.vectorstores import FAISS

Example: Define embedding_function (modify this based on your actual embedding method)

def embedding_function(text):
return embeddings.encode(text)

Example: Initialize a FAISS index

FAISS index can be initialized in various ways depending on the type of data and required precision

import faiss
index = faiss.IndexFlatL2(768) # Example for a 768-dimensional L2 index, adjust dimensions as needed

Example: Define docstore and index_to_docstore_id (simplified for illustration)

You'll need to implement these according to your data structure

docstore = {} # Can be a dictionary, database, etc.
def index_to_docstore_id(index_id):
return docstore.get(index_id, None)

Initialize FAISS with the required arguments

faiss_store = FAISS(embedding_function, index, docstore, index_to_docstore_id)