Update app.py

app.py

@@ -4,18 +4,17 @@ import uuid
 import streamlit as st
 from dotenv import load_dotenv
 from qdrant_client import models
-from utils import setup_openai_embeddings, setup_qdrant_client, delete_collection, is_document_embedded
-from embed import embed_documents_into_qdrant
-from preprocess import split_documents, update_metadata, load_documents_OCR
-from retrieve import retrieve_documents_from_collection
-from summarize import summarize_documents
+
+from Lex.utils import setup_openai_embeddings, setup_qdrant_client, delete_collection, is_document_embedded
+from Lex.embed import embed_documents_into_qdrant
+from Lex.preprocess import split_documents, update_metadata, load_documents_OCR
+from Lex.retrieve import retrieve_documents, retrieve_documents_from_collection
+from Lex.summarize import summarize_documents
 
 # Load environment variables
 load_dotenv()
 
 
-
-
 def main():
     st.sidebar.title("PDF Management")
     uploaded_files = st.sidebar.file_uploader("Upload PDF files", type=["pdf"], accept_multiple_files=True)
@@ -42,7 +41,7 @@ def main():
 
     pages = {
         "Lex Document Summarization": page_summarization,
-        "Chat with RSCA": page_qna,
+        "Chat with Data Bank": page_qna,
         "Chat with Uploaded Docs": page_chat_with_uploaded_docs,
         "Chat with VOO": page_chat_with_voo
     }
@@ -91,7 +90,7 @@ def page_summarization(uploaded_files):
 
 def page_qna(uploaded_files):
     """Page for Q&A functionality."""
-    st.title("Chat with RSCA")
+    st.title("Chat with Data Bank")
     user_query = st.text_area("Enter your question here:", height=300)
     if st.button('Get Answer'):
         if user_query:
@@ -192,7 +191,7 @@ def add_docs_to_current_chat(files_info):
 def handle_query(query):
     """Retrieve answers based on the query."""
     try:
-        answer = retrieve_documents_from_collection(query, os.getenv('OPENAI_API_KEY'), os.getenv('QDRANT_URL'), os.getenv('QDRANT_API_KEY'),'Lex-v1')
+        answer = retrieve_documents(query, os.getenv('OPENAI_API_KEY'), os.getenv('QDRANT_URL'), os.getenv('QDRANT_API_KEY'))
         return answer or "No relevant answer found."
     except Exception as e:
         return f"Error processing the query: {str(e)}"