Update app.py

app.py

@@ -70,7 +70,7 @@ groq_client = Client(api_key=HUGGINGFACE_KEY)
 embedder = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
 
 # Define file path and vector store folder
-file_path = "Atomic habits ( PDFDrive ).pdf"  # File directly in the root directory of the app
+file_path = "The Rise of Agentic AI.pdf"  # File directly in the root directory of the app
 VECTORSTORE_FOLDER = "vectorstore"  # Folder where the FAISS index will be stored
 
 # Ensure the vector store folder exists
@@ -139,7 +139,7 @@ def process_and_store_document(file_path):
         st.error(f"Error saving the FAISS index: {e}")
 
 # User interface for Streamlit
-st.title("Atomic Habits RAG Application")
+st.title("The Rise of Agentic AI RAG Application")
 
 # Button to trigger document processing
 if st.button("Process PDF"):