Update src/app.py

src/app.py

@@ -2,6 +2,7 @@ import streamlit as st
 import pandas as pd
 import numpy as np
 import re
+import os
 
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sentence_transformers import SentenceTransformer
@@ -17,7 +18,7 @@ nltk.download('wordnet', quiet=True)
 from nltk.corpus import wordnet
 
 # ==============================
-# AUTHENTICATION
+# AUTHENTICATION (HF FIXED)
 # ==============================
 def login():
     st.title("🔐 Login Required")
@@ -26,19 +27,27 @@ def login():
     password = st.text_input("Password", type="password")
 
     if st.button("Login"):
-        if (
-            username == st.secrets["USERNAME"] and
-            password == st.secrets["PASSWORD"]
-        ):
+
+        # ✅ HuggingFace secrets via environment
+        hf_user = os.environ.get("USERNAME", "admin")
+        hf_pass = os.environ.get("PASSWORD", "admin123")
+
+        if username == hf_user and password == hf_pass:
             st.session_state["authenticated"] = True
             st.session_state["user"] = username
             st.session_state["login_time"] = pd.Timestamp.now()
+
+            log_activity(username, "Login Success", "-", "-")
+
             st.success("✅ Login successful")
             st.rerun()
         else:
+            log_activity(username, "Login Failed", "-", "-")
             st.error("❌ Invalid credentials")
 
-# Session control
+# ==============================
+# SESSION CONTROL
+# ==============================
 if "authenticated" not in st.session_state:
     st.session_state["authenticated"] = False
 
@@ -56,6 +65,12 @@ st.title("🔍 Advanced Multi-Search Product Engine")
 st.sidebar.success(f"👤 User: {st.session_state['user']}")
 st.sidebar.info(f"🕒 Login: {st.session_state['login_time']}")
 
+# Logout button
+if st.sidebar.button("🚪 Logout"):
+    log_activity(st.session_state["user"], "Logout", "-", "-")
+    st.session_state.clear()
+    st.rerun()
+
 # ==============================
 # LOAD MODEL
 # ==============================
@@ -66,10 +81,30 @@ def load_model():
 model = load_model()
 
 # ==============================
-# INIT ACTIVITY LOG
+# LOGGING FUNCTION (CSV SAVE)
 # ==============================
-if "activity_log" not in st.session_state:
-    st.session_state["activity_log"] = []
+LOG_FILE = "user_activity_log.csv"
+
+def log_activity(user, action, query, search_type):
+    log_entry = {
+        "User": user,
+        "Action": action,
+        "Query": query,
+        "Search_Type": search_type,
+        "Time": str(pd.Timestamp.now())
+    }
+
+    try:
+        if os.path.exists(LOG_FILE):
+            df_log = pd.read_csv(LOG_FILE)
+            df_log = pd.concat([df_log, pd.DataFrame([log_entry])], ignore_index=True)
+        else:
+            df_log = pd.DataFrame([log_entry])
+
+        df_log.to_csv(LOG_FILE, index=False)
+
+    except Exception as e:
+        st.warning(f"Logging failed: {e}")
 
 # ==============================
 # SEARCH INFO
@@ -102,10 +137,6 @@ except Exception as e:
     st.error(f"❌ Error loading file: {e}")
     st.stop()
 
-if df.empty:
-    st.error("Dataset is empty!")
-    st.stop()
-
 # ==============================
 # DATA PREVIEW
 # ==============================
@@ -158,7 +189,7 @@ def get_synonyms(word):
     return synonyms
 
 # ==============================
-# SEARCH FUNCTIONS
+# SEARCH FUNCTIONS (UNCHANGED)
 # ==============================
 def keyword_search(q):
     return [(i, 1) for i, p in enumerate(products) if q.lower() in p.lower()]
@@ -292,13 +323,8 @@ if st.button("Search"):
         results = func_map[search_type](query)
         results = sorted(results, key=lambda x: x[1], reverse=True)[:top_k]
 
-        # ✅ LOG USER ACTIVITY
-        st.session_state["activity_log"].append({
-            "User": st.session_state["user"],
-            "Query": query,
-            "Search Type": search_type,
-            "Time": str(pd.Timestamp.now())
-        })
+        # ✅ LOG SEARCH
+        log_activity(st.session_state["user"], "Search", query, search_type)
 
         indices = [i for i, _ in results]
         result_df = df.iloc[indices].copy()
@@ -308,12 +334,12 @@ if st.button("Search"):
         st.dataframe(result_df)
 
 # ==============================
-# SHOW ACTIVITY LOG
+# SHOW LOGS
 # ==============================
 st.sidebar.subheader("📊 Activity Log")
 
-if st.session_state["activity_log"]:
-    log_df = pd.DataFrame(st.session_state["activity_log"])
+if os.path.exists(LOG_FILE):
+    log_df = pd.read_csv(LOG_FILE)
     st.sidebar.dataframe(log_df.tail(10))
 else:
     st.sidebar.write("No activity yet")