Update app.py

app.py

@@ -4,11 +4,6 @@ from docx import Document
 from sentence_transformers import SentenceTransformer
 from langchain_community.vectorstores import FAISS
 from langchain_community.embeddings import HuggingFaceEmbeddings
-from langchain.docstores import InMemoryDocstore
-from langchain.docstores.base import Docstore
-from langchain.vectorstores.faiss import FAISS
-from langchain.vectorstores.faiss import FAISSIndex
-from langchain.vectorstores.faiss import IndexToDocstoreID
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 from nltk.tokenize import sent_tokenize
 import torch
@@ -55,11 +50,7 @@ if os.path.exists(index_path):
         faiss_index = pickle.load(f)
         print("Loaded FAISS index from faiss_index.pkl")
 else:
-    index = FAISSIndex(d=hf_embeddings.model.get_sentence_embedding_dimension())
-    docstore = InMemoryDocstore({})
-    index_to_docstore_id = IndexToDocstoreID({})
-    faiss_index = FAISS(embedding_function=hf_embeddings, index=index, docstore=docstore, index_to_docstore_id=index_to_docstore_id)
-    print("Created new FAISS index")
+    faiss_index = FAISS(embedding_function=hf_embeddings)
 
 def preprocess_text(text):
     sentences = sent_tokenize(text)
@@ -81,7 +72,8 @@ def upload_files(files):
 
             # Encode sentences and add to FAISS index
             embeddings = embedding_model.encode(sentences)
-            faiss_index.add_texts(sentences)
+            for sentence, embedding in zip(sentences, embeddings):
+                faiss_index.add_sentence(sentence, embedding)
 
         # Save the updated index
         with open(index_path, "wb") as f:
@@ -137,3 +129,5 @@ with gr.Blocks() as demo:
         query_button.click(fn=process_and_query, inputs=[query], outputs=query_output)
 
 demo.launch()
+
+