adjustments

app.py

@@ -4,34 +4,40 @@ from pathlib import Path
 from PIL import Image
 from rag_sec.document_search_system import DocumentSearchSystem
 from chainguard.blockchain_logger import BlockchainLogger
-from rag_sec.document_search_system import main
-import streamlit as st
-from rag_sec.document_retriver import DocumentRetriever
 
 # Blockchain Logger
 blockchain_logger = BlockchainLogger()
 
 # Initialize DocumentSearchSystem
-home_dir = Path(os.getenv("HOME", "/"))
-data_dir = home_dir / "data-sets/aclImdb/train"
-system = DocumentSearchSystem(
-    neo4j_uri="neo4j+s://0ca71b10.databases.neo4j.io",
-    neo4j_user="neo4j",
-    neo4j_password="HwGDOxyGS1-79nLeTiX5bx5ohoFSpvHCmTv8IRgt-lY"
-)
-
-system.retriever.load_documents()
+@st.cache_resource
+def initialize_system():
+    """Initialize the DocumentSearchSystem and load documents."""
+    home_dir = Path(os.getenv("HOME", "/"))
+    system = DocumentSearchSystem(
+        neo4j_uri="neo4j+s://0ca71b10.databases.neo4j.io",
+        neo4j_user="neo4j",
+        neo4j_password="HwGDOxyGS1-79nLeTiX5bx5ohoFSpvHCmTv8IRgt-lY"
+    )
+    system.retriever.load_documents()
+    return system
+
+# Initialize and load system
+st.write("Initializing the Document Search System...")
+system = initialize_system()
+st.success("System initialized and documents loaded!")
 
 # Directory for storing uploaded files
 UPLOAD_DIR = "uploaded_files"
 os.makedirs(UPLOAD_DIR, exist_ok=True)
 
 # Streamlit Layout
-st.title("Memora: Secure File Upload with Blockchain & Neo4j")
+st.title("Memora: Secure File Upload and Search with Blockchain & Neo4j")
 st.subheader("Securely upload, organize, and query your files")
 
-# File Upload
-uploaded_files = st.file_uploader("Upload your files", accept_multiple_files=True, type=['jpg', 'jpeg', 'png', 'mp4', 'avi'])
+# File Upload Section
+uploaded_files = st.file_uploader(
+    "Upload your files", accept_multiple_files=True, type=['jpg', 'jpeg', 'png', 'mp4', 'avi']
+)
 
 if uploaded_files:
     for uploaded_file in uploaded_files:
@@ -41,7 +47,7 @@ if uploaded_files:
             f.write(uploaded_file.getbuffer())
         st.success(f"File saved locally: {file_path}")
 
-        # Display file details
+        # Display uploaded file details
         if uploaded_file.type.startswith('image'):
             image = Image.open(uploaded_file)
             st.image(image, caption=uploaded_file.name, use_column_width=True)
@@ -50,14 +56,14 @@ if uploaded_files:
         album = st.text_input(f"Album for {uploaded_file.name}", "Default Album")
         tags = st.text_input(f"Tags for {uploaded_file.name} (comma-separated)", "")
 
-        # Log Metadata
+        # Log Metadata and Transaction
         if st.button(f"Log Metadata for {uploaded_file.name}"):
             metadata = {"file_name": uploaded_file.name, "tags": tags.split(','), "album": album}
             blockchain_details = blockchain_logger.log_data(metadata)
             blockchain_hash = blockchain_details.get("block_hash", "N/A")
 
-            # Use Neo4jHandler from DocumentSearchSystem to log transaction
-            system.neo4j_handler.log_transaction(uploaded_file.name, file_path, blockchain_hash)
+            # Use Neo4jHandler from DocumentSearchSystem to log the transaction
+            system.neo4j_handler.log_relationships(uploaded_file.name, tags, blockchain_hash, [album])
             st.write(f"Metadata logged successfully! Blockchain Details: {blockchain_details}")
 
 # Blockchain Integrity Validation
@@ -65,45 +71,33 @@ if st.button("Validate Blockchain Integrity"):
     is_valid = blockchain_logger.is_blockchain_valid()
     st.write("Blockchain Integrity:", "Valid ✅" if is_valid else "Invalid ❌")
 
-# Query System
-st.subheader("Query Files")
-
-# Initialize DocumentRetriever
-retriever = DocumentRetriever()
-
-@st.cache_resource
-def load_retriever():
-    """Load documents into the retriever."""
-    retriever.load_documents()
-    return retriever
-# Load the retriever and documents
-st.write("Loading documents...")
-retriever = load_retriever()
-st.write("Documents successfully loaded!")
-
-# Streamlit UI
-st.title("Document Search App")
-st.subheader("Enter a query to search for related documents")
+# Document Search Section
+st.subheader("Search Documents")
 
 # Query Input
 query = st.text_input("Enter your query (e.g., 'sports news', 'machine learning')")
 
 if st.button("Search"):
     if query:
-        # Retrieve documents
-        results = retriever.retrieve(query)
-        if results == ["Document retrieval is not initialized."]:
-            st.error("Document retrieval is not initialized. Please reload the app.")
-        elif not results:
+        # Process query through the DocumentSearchSystem
+        result = system.process_query(query)
+        if result["status"] == "success":
+            st.success(f"Query processed successfully!")
+            st.write("### Query Response:")
+            st.write(result["response"])
+            st.write("### Retrieved Documents:")
+            for idx, doc in enumerate(result["retrieved_documents"], start=1):
+                st.write(f"**Document {idx}:**")
+                st.write(doc[:500])  # Display the first 500 characters
+            st.write("### Blockchain Details:")
+            st.json(result["blockchain_details"])
+        elif result["status"] == "no_results":
             st.warning("No relevant documents found for your query.")
-        else:
-            st.success(f"Found {len(results)} relevant document(s).")
-            for idx, doc in enumerate(results, start=1):
-                st.write(f"### Document {idx}")
-                st.write(doc[:500])  # Display first 500 characters of each document
+        elif result["status"] == "rejected":
+            st.error(result["message"])
     else:
         st.warning("Please enter a query to search.")
 
 # Debugging Section
 if st.checkbox("Show Debug Information"):
-    st.write(f"Total documents loaded: {len(retriever.documents)}")
+    st.write(f"Total documents loaded: {len(system.retriever.documents)}")