Update app.py

app.py

@@ -14,6 +14,7 @@ from langchain_community.document_loaders import PyPDFLoader
 # from dotenv import load_dotenv, find_dotenv
 import pickle
 import os
+from langchain_community.document_loaders import PyPDFDirectoryLoader
 
 
 ## loading the .env file
@@ -21,12 +22,6 @@ import os
 
 huggingfacehub_api_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
-
-loader = PyPDFLoader("stg.pdf")
-documents = loader.load_and_split()
-
-
-
 # Define model and vector store
 
 embeddings = "BAAI/bge-base-en"
@@ -36,15 +31,33 @@ model_norm = HuggingFaceBgeEmbeddings(
     model_kwargs={'device': 'cpu'},
     encode_kwargs=encode_kwargs
 )  
-vector_store = FAISS.from_documents(documents, model_norm)
-# job_done = object()  # signals the processing is done
 
-## saving the embeddings locally
-vector_store.save_local("cdssagent_database")
+
+try:
+    ##ltoading
+    vector_sore = FAISS.load_local("cdssagent_database", model_norm, allow_dangerous_deserialization=True)
+    job_done = object()
+except Exception as e:
+    loader = PyPDFLoader("stg.pdf")
+    documents = loader.load_and_split()
+
+    # loader = PyPDFDirectoryLoader("wolo/")
+    
+    # documents = loader.load_and_split()
+    vector_store = FAISS.from_documents(documents, model_norm)
+    # job_done = object()  # signals the processing is done
+    
+    ## saving the embeddings locally
+    vector_store.save_local("wolo_database")
+
+
+
+
+
 
 ##loading
-vector_store = FAISS.load_local("cdssagent_database", model_norm, allow_dangerous_deserialization=True)
-job_done = object()
+# vector_store = FAISS.load_local("cdssagent_database", model_norm, allow_dangerous_deserialization=True)
+# job_done = object()
 
 
 # Lets set up our streaming