Update app.py

app.py

@@ -4,7 +4,7 @@ import langchain
 from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.document_loaders import UnstructuredPDFLoader,UnstructuredWordDocumentLoader
 from langchain.indexes import VectorstoreIndexCreator
-from langchain_community.vectorstores import FAISS
+from langchain_community.vectorstores import LangChainFAISS
 from zipfile import ZipFile
 import gradio as gr
 import openpyxl
@@ -136,7 +136,7 @@ def merge_txt_to_db(filename,db,progress,progress_step=0.1):
   progress(progress_step,'txt unpacked')
   return merge_split_docs_to_db(split_docs,db,progress,progress_step)
 
-def unpack_zip_file(filename:str,db:FAISS,progress):
+def unpack_zip_file(filename:str,db:LangChainFAISS,progress):
     with ZipFile(filename, 'r') as zipObj:
         contents = zipObj.namelist()
         print(f"unpack zip: contents: {contents}")
@@ -144,7 +144,7 @@ def unpack_zip_file(filename:str,db:FAISS,progress):
         shutil.unpack_archive(filename, tmp_directory)
 
         if 'index.faiss' in [item.lower() for item in contents]:
-            db2 = FAISS.load_local(tmp_directory, embeddings, allow_dangerous_deserialization=True)
+            db2 = LangChainFAISS.load_local(tmp_directory, embeddings, allow_dangerous_deserialization=True)
             db.merge_from(db2)
             return db
         
@@ -179,11 +179,11 @@ def embed_files(files,ui_session_id,progress=gr.Progress(),progress_step=0.05):
     session_id = f"PDFAISS-{ui_session_id}"
 
     try:
-      db = FAISS.load_local(session_id,embeddings, allow_dangerous_deserialization=True)
+      db = LangChainFAISS.load_local(session_id,embeddings, allow_dangerous_deserialization=True)
     except:
       print(f"SESSION: {session_id} database does not exist, create a FAISS db")
       #db =  FAISS.from_documents([foo], embeddings)
-      db = FAISS.from_texts(["foo is fou!"],embeddings,[{"source":"foo source"}])
+      db = LangChainFAISS.from_texts(["foo is fou!"],embeddings,[{"source":"foo source"}])
       db.save_local(session_id)
       print(f"SESSION: {session_id} database created")
     
@@ -222,7 +222,7 @@ def embed_files(files,ui_session_id,progress=gr.Progress(),progress_step=0.05):
 
     ### load the updated db and zip it ###
     progress(progress_step, desc = 'loading db')
-    db = FAISS.load_local(session_id,embeddings, allow_dangerous_deserialization=True)
+    db = LangChainFAISS.load_local(session_id,embeddings, allow_dangerous_deserialization=True)
     print("EMBEDDED, after embeddeding: ",session_id,len(db.index_to_docstore_id))
     progress(progress_step, desc = 'zipping db for download')
     add_files_to_zip(session_id)
@@ -316,7 +316,7 @@ def ask_gpt(query, ui_session_id, history):
         return "Please Login", "", ""
     session_id = f"PDFAISS-{ui_session_id}"
     try:
-      db = FAISS.load_local(session_id,embeddings, allow_dangerous_deserialization=True)
+      db = LangChainFAISS.load_local(session_id,embeddings, allow_dangerous_deserialization=True)
       print("ASKGPT after loading",session_id,len(db.index_to_docstore_id))
     except:
       print(f"SESSION: {session_id} database does not exist")