updated embeddings

app.py

@@ -13,12 +13,7 @@ from langchain_community.vectorstores.faiss import FAISS
 import time
 from PyPDF2 import PdfReader
 import tempfile
-from dotenv import load_dotenv
-load_dotenv()
 
-## Load the Groq API key
-# groq_api_key = os.getenv('GROQ_API_KEY')
-# google_api_key = os.getenv('GOOGLE_API_KEY')
 
 st.title("Ask your questions from pdf(s) or website")
 option = None
@@ -60,7 +55,7 @@ def llm_model():
         print("Response time :", time.process_time()-start)
         st.write(response['answer'])
 
-st.session_state.embeddings =GoogleGenerativeAIEmbeddings(model = 'models/embedding-001')
+st.session_state.embeddings = GoogleGenerativeAIEmbeddings(model = 'models/embedding-001')
 st.session_state.text_splitter = RecursiveCharacterTextSplitter(chunk_size =1000, chunk_overlap= 200)
 
 if option: