news

app.py

@@ -1,9 +1,9 @@
+from pathlib import Path
+
 import streamlit as st
 from googlesearch import search
 import pandas as pd
-from pathlib import Path
 import os
-from PIL import Image
 from rag_sec.document_search_system import DocumentSearchSystem
 from chainguard.blockchain_logger import BlockchainLogger
 
@@ -14,7 +14,6 @@ blockchain_logger = BlockchainLogger()
 @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",
@@ -23,82 +22,63 @@ def initialize_system():
     system.retriever.load_documents()
     return system
 
-# Initialize and load system
-st.write("Initializing the Document Search System...")
+# Initialize the 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 and Search with Blockchain & Neo4j")
-st.subheader("Securely upload, organize, and query your files")
+st.title("Memora: Advanced Search and News Insights")
+st.subheader("Personalized news and global updates at your fingertips")
 
-# Google Search Section
-st.subheader("Find User Information via Google Search")
-search_query = st.text_input("Enter a name or topic to search on Google")
-if st.button("Google Search"):
-    if search_query:
+# Google Search: User-Specific News
+st.subheader("1. Latest News About You")
+user_name = st.text_input("Enter your name or handle to search for recent news", value="Talex Maxim")
+
+if st.button("Search News About Me"):
+    if user_name:
+        st.write(f"Searching Google for news about **{user_name}**...")
         try:
-            results = list(search(search_query, num_results=5))  # Fetch top 5 results
+            results = list(search(user_name, num_results=5))
             if results:
-                st.success(f"Top {len(results)} results for '{search_query}':")
-                result_data = {"URL": results}
-                df = pd.DataFrame(result_data)
-                st.dataframe(df)
+                st.success(f"Top {len(results)} results for '{user_name}':")
+                user_news_data = {"URL": results}
+                df_user_news = pd.DataFrame(user_news_data)
+                st.dataframe(df_user_news)
             else:
-                st.warning("No results found for the search query.")
+                st.warning("No recent news found about you.")
         except Exception as e:
             st.error(f"An error occurred during the search: {str(e)}")
     else:
-        st.warning("Please enter a search query.")
-
-# 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:
-        # Save file locally
-        file_path = os.path.join(UPLOAD_DIR, uploaded_file.name)
-        with open(file_path, "wb") as f:
-            f.write(uploaded_file.getbuffer())
-        st.success(f"File saved locally: {file_path}")
-
-        # 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)
-
-        # Metadata Input
-        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 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 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
-if st.button("Validate Blockchain Integrity"):
-    is_valid = blockchain_logger.is_blockchain_valid()
-    st.write("Blockchain Integrity:", "Valid ✅" if is_valid else "Invalid ❌")
-
-# Document Search Section
-st.subheader("Search Documents")
-
-# Query Input
+        st.warning("Please enter your name or handle to search.")
+
+# Google Search: Global News Categories
+st.subheader("2. Global News Insights")
+categories = ["Technology", "Sports", "Politics", "Entertainment", "Science"]
+news_results = {}
+
+if st.button("Fetch Global News"):
+    try:
+        for category in categories:
+            st.write(f"Fetching news for **{category}**...")
+            try:
+                category_results = list(search(f"latest {category} news", num_results=3))
+                news_results[category] = category_results
+            except Exception as e:
+                news_results[category] = [f"Error fetching news: {str(e)}"]
+
+        # Display results
+        for category, articles in news_results.items():
+            st.write(f"### Top News in {category}:")
+            for idx, article in enumerate(articles, start=1):
+                st.write(f"{idx}. [Read here]({article})")
+    except Exception as e:
+        st.error(f"An error occurred while fetching global news: {str(e)}")
+
+# Document Search
+st.subheader("3. Search Documents")
 query = st.text_input("Enter your query (e.g., 'sports news', 'machine learning')")
 
-if st.button("Search"):
+if st.button("Search Documents"):
     if query:
-        # Process query through the DocumentSearchSystem
         result = system.process_query(query)
         if result["status"] == "success":
             st.success(f"Query processed successfully!")