refactor

pages/Load_Documents.py

@@ -3,7 +3,6 @@ import openai
 from utils._admin_util import create_embeddings, create_vector_store, read_pdf_data, split_data
 import streamlit as st
 from dotenv import load_dotenv
-import requests
 
 def validate_api_key(api_key):
     """Test if the API key is valid"""
@@ -37,70 +36,51 @@ def main():
     # if not validate_api_key(api_key):
     #     st.stop()
     
-    print("API KEY :",api_key)
+    #print("API KEY :",api_key)
 
     st.set_page_config(page_title="Dump PDFs to QDrant - Vector Store")
     st.title("Please upload your files...📁 ")
+    try:
+        # Upload multiple PDF files
+        uploaded_files = st.file_uploader("Upload PDF files", type=["pdf"], accept_multiple_files=True)
 
-    # Upload multiple PDF files
-    uploaded_files = st.file_uploader("Upload PDF files", type=["pdf"], accept_multiple_files=True)
-
-    if uploaded_files:
-        try:
+        if uploaded_files:
+        
             with st.spinner('Processing PDF files...'):
                 all_chunks = []
                 
                 # Process each PDF file
                 for pdf in uploaded_files:
-                    try:
-                        st.write(f"Processing: {pdf.name}")
-                        
-                        # Extract text from PDF
-                        text = read_pdf_data(pdf)
-                        st.write(f"👉 Reading {pdf.name} done")
-
-                        # Create chunks for this PDF
-                        chunks = split_data(text)
-                        all_chunks.extend(chunks)
-                        st.write(f"👉 Splitting {pdf.name} into chunks done")
-                    except Exception as e:
-                        st.error(f"❌ Error processing {pdf.name}: {str(e)}")
-                        continue
+                  
+                    st.write(f"Processing: {pdf.name}")
+                    
+                    # Extract text from PDF
+                    text = read_pdf_data(pdf)
+                    st.write(f"👉 Reading {pdf.name} done")
 
+                    # Create chunks for this PDF
+                    chunks = split_data(text)
+                    all_chunks.extend(chunks)
+                    st.write(f"👉 Splitting {pdf.name} into chunks done")
+                    
                 if not all_chunks:
                     st.error("❌ No valid chunks were created from the PDFs")
                     st.stop()
 
-                # Create embeddings with progress tracking
-                try:
-                    st.write("Creating embeddings...")
-                    embeddings = create_embeddings()
-                    st.write("👉 Creating embeddings instance done")
-                except openai.RateLimitError:
-                    st.error("❌ Rate limit exceeded. Please try again later.")
-                    st.stop()
-                except Exception as e:
-                    st.error(f"❌ Error creating embeddings: {str(e)}")
-                    st.stop()
-
+                st.write("Creating embeddings...")
+                embeddings = create_embeddings()
+                st.write("👉 Creating embeddings instance done")
+        
                 # Create vector store with all chunks
-                try:
-                    vector_store = create_vector_store(embeddings, all_chunks)
-                    st.session_state.vector_store = vector_store
-                except Exception as e:
-                    st.error(f"❌ Error creating vector store: {str(e)}")
-                    st.stop()
-                
+                vector_store = create_vector_store(embeddings, all_chunks)
+                st.session_state.vector_store = vector_store
+            
                 st.success(f"✅ Successfully processed {len(uploaded_files)} files and pushed embeddings to Qdrant")
                 st.write(f"Total chunks created: {len(all_chunks)}")
 
-        except requests.exceptions.RequestException as e:
-            st.error(f"❌ Network error: {str(e)}")
-            st.error("Please check your internet connection and try again.")
-        except Exception as e:
+    except Exception as e:
             st.error(f"❌ An unexpected error occurred: {str(e)}")
-            st.error("Please check your API key and permissions.")
-            st.error("If the problem persists, please contact support.")
-
+            
+            
 if __name__ == '__main__':
     main()