update

app.py

@@ -1,14 +1,11 @@
+from pathlib import Path
+
 import streamlit as st
+from googlesearch import search
+import pandas as pd
 import os
-from pathlib import Path
-from PIL import Image
 from rag_sec.document_search_system import DocumentSearchSystem
 from chainguard.blockchain_logger import BlockchainLogger
-import requests
-import pandas as pd
-
-# SerpAPI Key (Replace with your SerpAPI key)
-SERPAPI_KEY = "your_serpapi_api_key"
 
 # Blockchain Logger
 blockchain_logger = BlockchainLogger()
@@ -17,7 +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",
@@ -29,116 +25,56 @@ def initialize_system():
 # Initialize the system
 system = initialize_system()
 
-# Function to Fetch News from SerpAPI
-def fetch_news(query, num_results=5):
-    """Fetch search results using SerpAPI."""
-    url = "https://serpapi.com/search"
-    params = {
-        "engine": "google",
-        "q": query,
-        "api_key": SERPAPI_KEY,
-        "num": num_results
-    }
-    try:
-        response = requests.get(url, params=params)
-        response.raise_for_status()
-        search_results = response.json().get("organic_results", [])
-        return [{"title": result["title"], "link": result["link"]} for result in search_results]
-    except Exception as e:
-        return [{"error": f"An error occurred: {str(e)}"}]
-
-# Mock User Information (Replace with actual Google Login integration if needed)
-def get_user_info():
-    """Fetch or mock user details."""
-    return {"name": "Talex Maxim", "email": "taimax13@gmail.com"}  # Replace with dynamic user info
-
-# Directory for storing uploaded files
-UPLOAD_DIR = "uploaded_files"
-os.makedirs(UPLOAD_DIR, exist_ok=True)
-
 # Streamlit Layout
-st.title("Memora: Advanced File Upload and News Insights")
-st.subheader("Securely upload, organize, and query your files while staying informed.")
-
-# User-Specific Information
-user_info = get_user_info()
-if user_info:
-    st.sidebar.write("### Logged in as:")
-    st.sidebar.write(f"**Name:** {user_info['name']}")
-    st.sidebar.write(f"**Email:** {user_info['email']}")
-else:
-    st.sidebar.write("### Not Logged In")
-    st.sidebar.write("We invite you on the journey! Please log in with your Google account.")
+st.title("Memora: Advanced Search and News Insights")
+st.subheader("Personalized news and global updates at your fingertips")
 
 # Google Search: User-Specific News
-if user_info:
-    st.subheader("1. Latest News About You")
-    user_name = user_info["name"]
-    st.write(f"Fetching latest news for **{user_name}**...")
-    user_news = fetch_news(user_name, num_results=5)
-
-    if user_news and "error" not in user_news[0]:
-        st.success(f"Top {len(user_news)} results for '{user_name}':")
-        user_news_df = pd.DataFrame(user_news)
-        st.dataframe(user_news_df)
+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(user_name, num_results=5))
+            if results:
+                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 recent news found about you.")
+        except Exception as e:
+            st.error(f"An error occurred during the search: {str(e)}")
     else:
-        st.error(user_news[0].get("error", "No news found."))
-else:
-    st.warning("Please log in with your Google account to fetch personalized news.")
+        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 = {}
 
-for category in categories:
-    st.write(f"Fetching news for **{category}**...")
-    category_results = fetch_news(f"latest {category} news", num_results=3)
-    if category_results and "error" not in category_results[0]:
-        st.success(f"Top {len(category_results)} results for '{category}':")
-        for idx, result in enumerate(category_results, start=1):
-            st.write(f"{idx}. [{result['title']}]({result['link']})")
-    else:
-        st.error(category_results[0].get("error", "No news found."))
-
-# File Upload Section
-st.subheader("3. Upload and Organize Files")
-
-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 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
-        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_relationships(uploaded_file.name, album, blockchain_hash, [])
-            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 ❌")
+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)}")
 
-# Query System
-st.subheader("4. Search Documents")
+# Document Search
+st.subheader("3. Search Documents")
 query = st.text_input("Enter your query (e.g., 'sports news', 'machine learning')")
 
 if st.button("Search Documents"):