Delete faiss_utils.py

faiss_utils.py

@@ -1,45 +0,0 @@
-import os
-from langchain_community.vectorstores import FAISS
-from langchain.embeddings import OpenAIEmbeddings
-
-
-def embed(input_strings):
-    vectorstore = FAISS.from_texts(texts=input_strings, embedding=OpenAIEmbeddings())
-    return vectorstore
-
-
-# Function to save a FAISS vectorstore to a specified path
-def save_local(vectorstore, path="safe/"):
-    if not os.path.exists(path):
-        os.makedirs(path)
-    file_path = os.path.join(path, "faiss_index.index")
-    vectorstore.save_local(file_path)
-    print(f"FAISS vectorstore saved to {file_path}")
-
-
-# Function to load a FAISS vectorstore from a specified path
-def load_vectorstore(path):
-    embeddings = OpenAIEmbeddings()  # Needed to initialize the FAISS properly
-    vectorstore = FAISS.load_local(path, embeddings, allow_dangerous_deserialization=True)
-    print(f"FAISS vectorstore loaded from {path}")
-    return vectorstore
-
-
-# Example usage
-if __name__ == "__main__":
-    # Embed a few words
-    words = ["hello", "world", "sample", "text"]
-    faiss_db1 = embed(words)
-
-    # Save the vectorstore
-    save_local(faiss_db1)
-
-    # Load the vectorstore
-    loaded_db1 = load_vectorstore("safe/faiss_index.index")
-
-    # Embed another set of words and create a second vectorstore
-    more_words = ["FAISS", "database", "information", "retrieval"]
-    faiss_db2 = embed(more_words)
-
-    loaded_db1.merge_from(faiss_db2)
-    print("Merged vectorstore with other vectorstore containing total vectors:", loaded_db1.index.ntotal)