Update app.py

app.py

@@ -27,9 +27,9 @@ if uploaded_file:
 # Initialize the CSVLoader to load the uploaded CSV file
     loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8", csv_args={'delimiter': ','})
     data = loader.load()
+    embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2',model_kwargs={'device': 'cpu'})
     db.save_local(DB_FAISS_PATH)
     llm = load_llm()
-
     chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db.as_retriever())
 
 
@@ -90,11 +90,6 @@ if uploaded_file:
 text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=20)
 text_chunks = text_splitter.split_documents(data)
 
-print(len(text_chunks))
-
-# Download Sentence Transformers Embedding From Hugging Face
-embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2',
-                                       model_kwargs={'device': 'cpu'})
 
 # COnverting the text Chunks into embeddings and saving the embeddings into FAISS Knowledge Base
 docsearch = FAISS.from_documents(text_chunks, embeddings)