fix: use query params bridge for menubar→backend communication

app.py

@@ -1,7 +1,11 @@
 """
-Aria — Premium Personal AI Assistant
-=====================================
-Premium UI inspired by top AI products
+Personal AI Assistant v3 — Smarter, More Personal, Human-like
+==============================================================
+- llama-3.3-70b (smarter model)
+- Personal profile (learns about you)
+- Full conversation history
+- Custom PA name and personality
+- Proactive suggestions
 Run with: streamlit run app.py
 """
 
@@ -10,6 +14,8 @@ import streamlit as st
 import numpy as np
 from duckduckgo_search import DDGS
 
+# ══════════════════════════════════════════════════════
+#  CONFIG
 # ══════════════════════════════════════════════════════
 LLM_MODEL            = "llama-3.3-70b-versatile"
 SIMILARITY_THRESHOLD = 0.78
@@ -18,509 +24,108 @@ WEB_MAX_RESULTS      = 4
 PINECONE_INDEX_NAME  = "pa-memory"
 NOTES_FILE           = "pa_notes.json"
 PROFILE_FILE         = "pa_profile.json"
-PA_NAME              = "Aria"
+PA_NAME              = "Aria"          # ← your PA's name
 PA_PERSONALITY       = (
     "You are Aria, a brilliant and warm personal AI assistant. "
     "You are proactive, thoughtful, and genuinely care about helping. "
     "You remember things about the user and reference them naturally. "
+    "You occasionally make helpful suggestions the user didn't ask for. "
     "You are concise but never cold. You feel like a real assistant, not a robot."
 )
 # ══════════════════════════════════════════════════════
 
-st.set_page_config(
-    page_title="Aria — Personal AI",
-    page_icon="✦",
-    layout="wide",
-    initial_sidebar_state="collapsed"
-)
+st.set_page_config(page_title=f"{PA_NAME} — Personal AI", page_icon="✨", layout="centered")
 
-# ── Premium CSS ───────────────────────────────────────
 st.markdown("""
 <style>
-@import url('https://fonts.googleapis.com/css2?family=Instrument+Serif:ital@0;1&family=Geist:wght@300;400;500;600&display=swap');
-
-/* Reset & Base */
-*, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
-
-:root {
-    --bg:        #0c0c0e;
-    --surface:   #141416;
-    --border:    #222226;
-    --border2:   #2a2a2f;
-    --text:      #f0f0f2;
-    --muted:     #666670;
-    --accent:    #7c6fcd;
-    --accent2:   #5bc4a0;
-    --glow:      rgba(124, 111, 205, 0.15);
-    --radius:    16px;
-}
-
-/* Hide Streamlit chrome */
-#MainMenu, footer, header, .stDeployButton,
-[data-testid="stToolbar"], [data-testid="stDecoration"],
-[data-testid="stStatusWidget"] { display: none !important; }
-
-/* Hide sidebar toggle */
-[data-testid="collapsedControl"] { display: none !important; }
-
-/* App background */
-.stApp {
-    background: var(--bg) !important;
-    font-family: 'Geist', sans-serif !important;
-}
-
-/* Grain overlay */
-.stApp::before {
-    content: '';
-    position: fixed;
-    inset: 0;
-    background-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 256 256' xmlns='http://www.w3.org/2000/svg'%3E%3Cfilter id='noise'%3E%3CfeTurbulence type='fractalNoise' baseFrequency='0.9' numOctaves='4' stitchTiles='stitch'/%3E%3C/filter%3E%3Crect width='100%25' height='100%25' filter='url(%23noise)' opacity='0.03'/%3E%3C/svg%3E");
-    pointer-events: none;
-    z-index: 0;
-    opacity: 0.4;
-}
-
-/* Ambient glow */
-.stApp::after {
-    content: '';
-    position: fixed;
-    top: -200px;
-    left: 50%;
-    transform: translateX(-50%);
-    width: 600px;
-    height: 400px;
-    background: radial-gradient(ellipse, rgba(124,111,205,0.06) 0%, transparent 70%);
-    pointer-events: none;
-    z-index: 0;
-}
-
-/* Main container */
-.main .block-container {
-    max-width: 780px !important;
-    margin: 0 auto !important;
-    padding: 0 24px 120px !important;
-}
-
-/* Header */
-.aria-header {
-    display: flex;
-    align-items: center;
-    gap: 12px;
-    padding: 32px 0 8px;
-    margin-bottom: 8px;
-}
-
-.aria-logo {
-    width: 36px;
-    height: 36px;
-    background: linear-gradient(135deg, #7c6fcd, #5bc4a0);
-    border-radius: 10px;
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    font-size: 16px;
-    flex-shrink: 0;
-}
-
-.aria-title {
-    font-family: 'Instrument Serif', serif !important;
-    font-size: 22px !important;
-    color: var(--text) !important;
-    font-weight: 400 !important;
-    letter-spacing: -0.3px;
-}
-
-.aria-subtitle {
-    font-size: 12px;
-    color: var(--muted);
-    letter-spacing: 0.05em;
-}
-
-/* Chat messages */
-[data-testid="stChatMessage"] {
-    background: transparent !important;
-    border: none !important;
-    padding: 4px 0 !important;
-    gap: 14px !important;
-}
-
-/* User messages */
-[data-testid="stChatMessage"][data-testid*="user"],
-[data-testid="stChatMessage"]:has([data-testid="chatAvatarIcon-user"]) {
-    flex-direction: row-reverse !important;
-}
-
-[data-testid="stChatMessage"]:has([data-testid="chatAvatarIcon-user"]) .stMarkdown {
-    background: #1e1e28 !important;
-    border: 1px solid var(--border2) !important;
-    border-radius: 18px 4px 18px 18px !important;
-    padding: 12px 16px !important;
-    max-width: 80% !important;
-    margin-left: auto !important;
-    font-size: 15px !important;
-    color: var(--text) !important;
-    line-height: 1.6 !important;
-}
-
-/* Assistant messages */
-[data-testid="stChatMessage"]:has([data-testid="chatAvatarIcon-assistant"]) .stMarkdown {
-    background: transparent !important;
-    border: none !important;
-    padding: 4px 0 !important;
-    font-size: 15px !important;
-    color: #d8d8e0 !important;
-    line-height: 1.75 !important;
-    max-width: 100% !important;
-}
-
-/* Avatar icons */
-[data-testid="chatAvatarIcon-user"] {
-    background: linear-gradient(135deg, #2a2a35, #333340) !important;
-    border: 1px solid var(--border2) !important;
-    border-radius: 50% !important;
-    color: var(--muted) !important;
-    font-size: 13px !important;
-    width: 32px !important;
-    height: 32px !important;
-    flex-shrink: 0 !important;
-}
-
-[data-testid="chatAvatarIcon-assistant"] {
-    background: linear-gradient(135deg, #7c6fcd, #5bc4a0) !important;
-    border: none !important;
-    border-radius: 10px !important;
-    color: white !important;
-    font-size: 13px !important;
-    width: 32px !important;
-    height: 32px !important;
-    flex-shrink: 0 !important;
-}
-
-/* Chat input */
-[data-testid="stChatInput"] {
-    position: fixed !important;
-    bottom: 0 !important;
-    left: 50% !important;
-    transform: translateX(-50%) !important;
-    width: 100% !important;
-    max-width: 780px !important;
-    padding: 16px 24px 24px !important;
-    background: linear-gradient(to top, var(--bg) 70%, transparent) !important;
-    z-index: 100 !important;
-}
-
-[data-testid="stChatInput"] textarea {
-    background: var(--surface) !important;
-    border: 1px solid var(--border2) !important;
-    border-radius: 14px !important;
-    color: var(--text) !important;
-    font-family: 'Geist', sans-serif !important;
-    font-size: 15px !important;
-    padding: 14px 18px !important;
-    resize: none !important;
-    transition: border-color 0.2s !important;
-    box-shadow: 0 0 0 0 transparent !important;
-}
-
-[data-testid="stChatInput"] textarea:focus {
-    border-color: var(--accent) !important;
-    box-shadow: 0 0 0 3px var(--glow) !important;
-    outline: none !important;
-}
-
-[data-testid="stChatInput"] textarea::placeholder {
-    color: var(--muted) !important;
-}
-
-/* Send button */
-[data-testid="stChatInput"] button {
-    background: linear-gradient(135deg, #7c6fcd, #6a5fc0) !important;
-    border: none !important;
-    border-radius: 10px !important;
-    color: white !important;
-    transition: all 0.2s !important;
-}
-
-[data-testid="stChatInput"] button:hover {
-    background: linear-gradient(135deg, #8d81d8, #7c6fcd) !important;
-    transform: scale(1.05) !important;
-}
-
-/* Sidebar */
-[data-testid="stSidebar"] {
-    background: var(--surface) !important;
-    border-right: 1px solid var(--border) !important;
-}
-
-[data-testid="stSidebar"] * {
-    font-family: 'Geist', sans-serif !important;
-    color: var(--text) !important;
-}
-
-/* Buttons */
-.stButton button {
-    background: var(--surface) !important;
-    border: 1px solid var(--border2) !important;
-    border-radius: 10px !important;
-    color: var(--text) !important;
-    font-family: 'Geist', sans-serif !important;
-    font-size: 13px !important;
-    padding: 8px 16px !important;
-    transition: all 0.2s !important;
-    width: 100% !important;
-}
-
-.stButton button:hover {
-    border-color: var(--accent) !important;
-    background: var(--glow) !important;
-}
-
-/* Text inputs */
-.stTextInput input, .stTextArea textarea {
-    background: #0f0f12 !important;
-    border: 1px solid var(--border2) !important;
-    border-radius: 10px !important;
-    color: var(--text) !important;
-    font-family: 'Geist', sans-serif !important;
-    font-size: 14px !important;
-}
-
-.stTextInput input:focus, .stTextArea textarea:focus {
-    border-color: var(--accent) !important;
-    box-shadow: 0 0 0 2px var(--glow) !important;
-}
-
-/* Labels */
-.stTextInput label, .stTextArea label {
-    color: var(--muted) !important;
-    font-size: 12px !important;
-    letter-spacing: 0.06em !important;
-    text-transform: uppercase !important;
-    font-weight: 500 !important;
-}
-
-/* Caption / info */
-.stCaption, [data-testid="stCaptionContainer"] {
-    color: var(--muted) !important;
-    font-size: 12px !important;
-}
-
-/* Spinner */
-.stSpinner > div {
-    border-color: var(--accent) transparent transparent transparent !important;
-}
-
-/* Success / info */
-.stSuccess, .stInfo {
-    background: rgba(91,196,160,0.08) !important;
-    border: 1px solid rgba(91,196,160,0.2) !important;
-    border-radius: 10px !important;
-    color: #5bc4a0 !important;
-    font-size: 13px !important;
-}
-
-/* Divider */
-hr { border-color: var(--border) !important; }
-
-/* Scrollbar */
-::-webkit-scrollbar { width: 4px; }
-::-webkit-scrollbar-track { background: transparent; }
-::-webkit-scrollbar-thumb { background: var(--border2); border-radius: 4px; }
-
-/* Suggestion chips */
-.chip-row {
-    display: flex;
-    flex-wrap: wrap;
-    gap: 8px;
-    margin: 24px 0 16px;
-}
-.chip {
-    background: var(--surface);
-    border: 1px solid var(--border2);
-    border-radius: 100px;
-    padding: 8px 16px;
-    font-size: 13px;
-    color: var(--muted);
-    cursor: pointer;
-    transition: all 0.2s;
-    font-family: 'Geist', sans-serif;
-    white-space: nowrap;
-}
-.chip:hover {
-    border-color: var(--accent);
-    color: var(--text);
-    background: var(--glow);
-}
-
-/* Tool badge */
-.tool-pill {
-    display: inline-flex;
-    align-items: center;
-    gap: 6px;
-    background: rgba(124,111,205,0.1);
-    border: 1px solid rgba(124,111,205,0.2);
-    border-radius: 100px;
-    padding: 4px 12px;
-    font-size: 12px;
-    color: #a99ee0;
-    margin-bottom: 8px;
-    font-family: 'Geist', sans-serif;
-}
-
-/* Memory badge */
-.memory-pill {
-    display: inline-flex;
-    align-items: center;
-    gap: 6px;
-    background: rgba(91,196,160,0.08);
-    border: 1px solid rgba(91,196,160,0.2);
-    border-radius: 100px;
-    padding: 4px 12px;
-    font-size: 12px;
-    color: #5bc4a0;
-    margin-bottom: 8px;
-}
-
-/* Metric */
-[data-testid="stMetric"] {
-    background: var(--surface) !important;
-    border: 1px solid var(--border) !important;
-    border-radius: 10px !important;
-    padding: 12px !important;
-}
+    .stApp { background-color: #0a0a0f; color: #e2e8f0; }
+    .stChatMessage { background: #12121a; border: 1px solid #1e1e2e; border-radius: 12px; }
+    .stSidebar { background-color: #12121a; }
+    h1 { background: linear-gradient(135deg, #fff 0%, #7c3aed 60%, #06b6d4 100%);
+         -webkit-background-clip: text; -webkit-text-fill-color: transparent; }
+    .profile-box { background: rgba(124,58,237,0.08); border: 1px solid rgba(124,58,237,0.2);
+                   border-radius: 10px; padding: 12px; margin: 8px 0; font-size: 13px; }
 </style>
 """, unsafe_allow_html=True)
 
-# ── Header ────────────────────────────────────────────
-st.markdown(f"""
-<div class="aria-header">
-    <div class="aria-logo">✦</div>
-    <div>
-        <div class="aria-title">{PA_NAME}</div>
-        <div class="aria-subtitle">Personal AI Assistant</div>
-    </div>
-</div>
-""", unsafe_allow_html=True)
-
-# ── Persistent key storage (survives page refresh via session + file) ─────────
-KEYS_FILE = ".cbae_keys.json"
-
-def load_saved_keys():
-    if os.path.exists(KEYS_FILE):
-        try: return json.load(open(KEYS_FILE))
-        except: pass
-    return {}
-
-def save_keys(groq, pinecone, name):
-    json.dump({"groq_key": groq, "pinecone_key": pinecone, "your_name": name},
-              open(KEYS_FILE, "w"))
+st.title(f"✨ {PA_NAME}")
+st.caption("Your Personal AI Assistant")
+
+# ── Profile ───────────────────────────────────────────
+def load_profile():
+    if os.path.exists(PROFILE_FILE):
+        return json.load(open(PROFILE_FILE))
+    return {"name": "", "about": "", "preferences": [], "facts": []}
+
+def save_profile(profile):
+    json.dump(profile, open(PROFILE_FILE, "w"), indent=2)
+
+def update_profile_from_chat(question, answer):
+    """Extract and save personal facts mentioned in conversation."""
+    profile = load_profile()
+    keywords = ["i am", "i'm", "my name is", "i work", "i like", "i love",
+                "i hate", "i live", "i study", "i'm from", "my job", "my hobby"]
+    q_lower = question.lower()
+    if any(kw in q_lower for kw in keywords):
+        fact = question[:150]
+        if fact not in profile["facts"]:
+            profile["facts"].append(fact)
+            if len(profile["facts"]) > 20:
+                profile["facts"] = profile["facts"][-20:]
+            save_profile(profile)
 
-def clear_keys():
-    if os.path.exists(KEYS_FILE): os.remove(KEYS_FILE)
-
-# Load from file on first run
-saved = load_saved_keys()
-if "groq_key"     not in st.session_state: st.session_state.groq_key     = saved.get("groq_key", "")
-if "pinecone_key" not in st.session_state: st.session_state.pinecone_key = saved.get("pinecone_key", "")
-if "your_name"    not in st.session_state: st.session_state.your_name    = saved.get("your_name", "Sterlin")
-
-groq_key     = st.session_state.groq_key
-pinecone_key = st.session_state.pinecone_key
-your_name    = st.session_state.your_name
+def get_profile_context():
+    profile = load_profile()
+    parts = []
+    if profile.get("name"):       parts.append(f"User's name: {profile['name']}")
+    if profile.get("about"):      parts.append(f"About user: {profile['about']}")
+    if profile.get("facts"):      parts.append("Things I know about user:\n" + "\n".join(f"- {f}" for f in profile["facts"][-10:]))
+    return "\n".join(parts) if parts else ""
 
 # ── Sidebar ───────────────────────────────────────────
 with st.sidebar:
-    st.markdown("### ⚙️ Settings")
-
-    # Show locked state if keys already saved
-    if groq_key and pinecone_key:
-        st.success("🔐 Keys saved & active")
-        st.caption(f"Groq: gsk_••••••{groq_key[-4:]}")
-        st.caption(f"Pinecone: ••••••{pinecone_key[-4:]}")
-        st.caption(f"Name: {your_name}")
-        if st.button("🔓 Logout / Change Keys"):
-            st.session_state.groq_key     = ""
-            st.session_state.pinecone_key = ""
-            st.session_state.your_name    = "Sterlin"
-            clear_keys()
-            st.rerun()
-    else:
-        new_groq     = st.text_input("Groq API Key",     type="password", placeholder="gsk_...")
-        new_pinecone = st.text_input("Pinecone API Key", type="password", placeholder="xxxxxxxx-xxxx...")
-        new_name     = st.text_input("Your Name", value="Sterlin")
-        if st.button("💾 Save & Connect"):
-            if new_groq and new_pinecone:
-                save_keys(new_groq, new_pinecone, new_name)
-                st.session_state.groq_key     = new_groq
-                st.session_state.pinecone_key = new_pinecone
-                st.session_state.your_name    = new_name
-                groq_key     = new_groq
-                pinecone_key = new_pinecone
-                your_name    = new_name
-                st.success("✅ Keys saved! You won't need to enter them again.")
-                st.rerun()
-            else:
-                st.error("Please enter both API keys.")
+    st.header(f"✨ {PA_NAME} Settings")
+    groq_key     = st.text_input("Groq API Key",     type="password", placeholder="gsk_...")
+    pinecone_key = st.text_input("Pinecone API Key", type="password", placeholder="xxxxxxxx...")
+    your_name    = st.text_input("Your Name", value="Sterlin")
 
     st.markdown("---")
-    st.markdown("### 👤 Your Profile")
-
-    def load_profile():
-        if os.path.exists(PROFILE_FILE):
-            return json.load(open(PROFILE_FILE))
-        return {"name":"","about":"","facts":[]}
-
-    def save_profile(p):
-        json.dump(p, open(PROFILE_FILE,"w"), indent=2)
-
-    profile   = load_profile()
-    about_you = st.text_area("About you", value=profile.get("about",""),
-                              placeholder="I'm a developer from Chennai...", height=80)
+    st.markdown("**👤 Your Profile**")
+    profile = load_profile()
+    about_you = st.text_area("Tell me about yourself", value=profile.get("about",""),
+                              placeholder="e.g. I'm a developer from Chennai who loves AI...",
+                              height=80)
     if st.button("💾 Save Profile"):
         profile["name"]  = your_name
         profile["about"] = about_you
         save_profile(profile)
-        st.success("Profile saved!")
+        st.success(f"Profile saved! {PA_NAME} now knows you better.")
 
     if profile.get("facts"):
-        st.markdown("**What Aria knows:**")
-        for f in profile["facts"][-4:]:
-            st.caption(f"• {f}")
+        st.markdown("**🧠 What I know about you:**")
+        for fact in profile["facts"][-5:]:
+            st.markdown(f'<div class="profile-box">• {fact}</div>', unsafe_allow_html=True)
 
     st.markdown("---")
-    st.markdown("### 🛠 Tools")
-    tools_list = ["🌐 Web Search","📰 News","🧮 Calculator",
-                  "🌤 Weather","💱 Currency","📏 Units","📝 Notes","📧 Email"]
-    for t in tools_list:
-        st.caption(t)
+    st.markdown("**🛠 Tools**")
+    st.markdown("🌐 Web · 🧮 Math · 🌤 Weather")
+    st.markdown("📰 News · 📧 Email · 💱 Currency")
+    st.markdown("📏 Units · 📝 Notes")
 
     st.markdown("---")
-    col1, col2 = st.columns(2)
-    with col1:
-        if st.button("🗑 Clear Chat"):
-            st.session_state.messages = []
-            st.session_state.history  = []
-            st.rerun()
-    with col2:
-        if st.button("🧹 Reset All"):
-            st.session_state.messages = []
-            st.session_state.history  = []
-            for f in [NOTES_FILE, PROFILE_FILE]:
-                if os.path.exists(f): os.remove(f)
-            st.rerun()
+    if st.button("🗑️ Clear Chat"):
+        st.session_state.messages  = []
+        st.session_state.history   = []
+        st.rerun()
+    if st.button("🧹 Clear All Memory"):
+        st.session_state.messages  = []
+        st.session_state.history   = []
+        if os.path.exists(NOTES_FILE):   os.remove(NOTES_FILE)
+        if os.path.exists(PROFILE_FILE): os.remove(PROFILE_FILE)
+        st.success("All memory cleared!")
 
 if not groq_key or not pinecone_key:
-    st.markdown("""
-    <div class="chip-row">
-        <div class="chip">🌐 Search the web</div>
-        <div class="chip">📰 Get latest news</div>
-        <div class="chip">💱 Convert currency</div>
-        <div class="chip">🌤 Check weather</div>
-        <div class="chip">📝 Save notes</div>
-        <div class="chip">🧮 Do math</div>
-    </div>
-    """, unsafe_allow_html=True)
-    st.info("👈 Open the sidebar (top left ›) and enter your API keys to start chatting with Aria.")
+    st.info(f"👈 Enter your API keys in the sidebar to start chatting with {PA_NAME}.")
     st.stop()
 
 # ── Load embedder ─────────────────────────────────────
@@ -531,10 +136,13 @@ def load_embedder():
 
 embedder = load_embedder()
 
+# ── Init Pinecone ─────────────────────────────────────
 @st.cache_resource
 def init_pinecone(_key):
     from pinecone import Pinecone
-    return Pinecone(api_key=_key).Index(PINECONE_INDEX_NAME)
+    pc    = Pinecone(api_key=_key)
+    index = pc.Index(PINECONE_INDEX_NAME)
+    return index
 
 try:
     pc_index = init_pinecone(pinecone_key)
@@ -546,184 +154,192 @@ except Exception as e:
 if "messages" not in st.session_state: st.session_state.messages = []
 if "history"  not in st.session_state: st.session_state.history  = []
 
-# ── Helper functions ──────────────────────────────────
+# ── Notes ─────────────────────────────────────────────
 def load_notes():
     return json.load(open(NOTES_FILE)) if os.path.exists(NOTES_FILE) else {}
 
 def save_note(title, content):
-    notes = load_notes(); notes[title] = content
-    json.dump(notes, open(NOTES_FILE,"w"), indent=2)
+    notes = load_notes()
+    notes[title] = content
+    json.dump(notes, open(NOTES_FILE, "w"), indent=2)
     return f"✅ Note saved: **{title}**"
 
 def get_note(title):
     notes = load_notes()
     for k, v in notes.items():
-        if title.lower() in k.lower(): return f"📝 **{k}**: {v}"
+        if title.lower() in k.lower():
+            return f"📝 **{k}**: {v}"
     return f"No note found for '{title}'"
 
-def get_profile_context():
-    p = load_profile()
-    parts = []
-    if p.get("name"):  parts.append(f"User's name: {p['name']}")
-    if p.get("about"): parts.append(f"About: {p['about']}")
-    if p.get("facts"): parts.append("Known facts:\n" + "\n".join(f"- {f}" for f in p["facts"][-8:]))
-    return "\n".join(parts)
-
-def update_profile(question):
-    keywords = ["i am","i'm","my name","i work","i like","i love","i live","i study","i'm from"]
-    if any(kw in question.lower() for kw in keywords):
-        p = load_profile()
-        if question[:150] not in p["facts"]:
-            p["facts"].append(question[:150])
-            p["facts"] = p["facts"][-20:]
-            save_profile(p)
-
+# ── Memory ────────────────────────────────────────────
 def search_memory(question):
     try:
-        results = pc_index.query(vector=embedder.encode(question).tolist(), top_k=1, include_metadata=True)
+        q_emb   = embedder.encode(question).tolist()
+        results = pc_index.query(vector=q_emb, top_k=1, include_metadata=True)
         if results.matches and results.matches[0].score >= SIMILARITY_THRESHOLD:
-            return results.matches[0].score, results.matches[0].metadata.get("answer","")
+            score  = results.matches[0].score
+            answer = results.matches[0].metadata.get("answer", "")
+            st.caption(f"🧠 Memory Hit — {score:.0%} confident")
+            return answer
     except: pass
-    return None, None
+    return None
 
 def store_memory(question, answer):
     try:
-        pc_index.upsert(vectors=[{"id": str(uuid.uuid4()),
-            "values": embedder.encode(question).tolist(),
-            "metadata": {"question":question,"answer":answer,
-                         "timestamp":datetime.datetime.now().isoformat()}}])
+        pc_index.upsert(vectors=[{
+            "id":       str(uuid.uuid4()),
+            "values":   embedder.encode(question).tolist(),
+            "metadata": {"question": question, "answer": answer,
+                         "timestamp": datetime.datetime.now().isoformat()}
+        }])
     except: pass
 
 # ── Tools ─────────────────────────────────────────────
-def tool_web_search(q):
+def tool_web_search(query):
     try:
-        with DDGS() as d: results = list(d.text(q, max_results=WEB_MAX_RESULTS))
+        with DDGS() as ddgs:
+            results = list(ddgs.text(query, max_results=WEB_MAX_RESULTS))
         return "\n\n".join(f"[{r.get('title','')}]\n{r.get('body','')}" for r in results) or "No results."
-    except Exception as e: return f"Search failed: {e}"
+    except Exception as e: return f"Web search failed: {e}"
 
 def tool_news(topic):
     try:
-        with DDGS() as d: results = list(d.news(topic, max_results=5))
-        return "\n\n".join(f"📰 {r.get('title','')}\n{r.get('body','')}" for r in results) or "No news."
+        with DDGS() as ddgs:
+            results = list(ddgs.news(topic, max_results=5))
+        return "\n\n".join(f"📰 {r.get('title','')}\n{r.get('body','')}" for r in results) or "No news found."
     except Exception as e: return f"News failed: {e}"
 
 def tool_calculator(expr):
     try:
-        allowed = {k: getattr(math,k) for k in dir(math) if not k.startswith("_")}
-        return f"Result: {eval(expr, {'__builtins__':{}}, allowed)}"
+        allowed = {k: getattr(math, k) for k in dir(math) if not k.startswith("_")}
+        return f"Result: {eval(expr, {'__builtins__': {}}, allowed)}"
     except Exception as e: return f"Error: {e}"
 
-def tool_datetime(): return datetime.datetime.now().strftime("Today is %A, %B %d, %Y. Time: %I:%M %p")
+def tool_datetime():
+    return datetime.datetime.now().strftime("Today is %A, %B %d, %Y. Time: %I:%M %p")
 
 def tool_weather(city):
-    try: return requests.get(f"https://wttr.in/{city}?format=3", timeout=5).text.strip()
+    try:
+        return requests.get(f"https://wttr.in/{city}?format=3", timeout=5).text.strip()
     except Exception as e: return f"Weather failed: {e}"
 
-def tool_currency(amount, f, t):
+def tool_currency(amount, from_cur, to_cur):
     try:
-        data = requests.get(f"https://api.exchangerate-api.com/v4/latest/{f.upper()}", timeout=5).json()
-        rate = data["rates"].get(t.upper())
-        if not rate: return f"Rate not found"
-        return f"💱 {amount} {f.upper()} = **{float(amount)*rate:.2f} {t.upper()}**"
+        data = requests.get(f"https://api.exchangerate-api.com/v4/latest/{from_cur.upper()}", timeout=5).json()
+        rate = data["rates"].get(to_cur.upper())
+        if not rate: return f"Rate not found for {to_cur}"
+        return f"💱 {amount} {from_cur.upper()} = **{float(amount)*rate:.2f} {to_cur.upper()}**"
     except Exception as e: return f"Currency failed: {e}"
 
-def tool_unit(value, f, t):
-    conv = {("km","miles"):0.621371,("miles","km"):1.60934,("kg","lbs"):2.20462,
-            ("lbs","kg"):0.453592,("cm","inches"):0.393701,("inches","cm"):2.54,
-            ("m","ft"):3.28084,("ft","m"):0.3048,("l","gallons"):0.264172,("gallons","l"):3.78541}
-    if (f,t)==("c","f"): return f"🌡 {value}°C = **{float(value)*9/5+32:.1f}°F**"
-    if (f,t)==("f","c"): return f"🌡 {value}°F = **{(float(value)-32)*5/9:.1f}°C**"
-    factor = conv.get((f,t))
-    return f"📏 {value} {f} = **{float(value)*factor:.3f} {t}**" if factor else f"Can't convert {f} to {t}"
-
+def tool_unit_converter(value, from_unit, to_unit):
+    conversions = {
+        ("km","miles"):0.621371, ("miles","km"):1.60934,
+        ("kg","lbs"):2.20462,   ("lbs","kg"):0.453592,
+        ("cm","inches"):0.393701,("inches","cm"):2.54,
+        ("m","ft"):3.28084,     ("ft","m"):0.3048,
+        ("l","gallons"):0.264172,("gallons","l"):3.78541,
+    }
+    f, t = from_unit.lower(), to_unit.lower()
+    if (f,t) == ("c","f"): return f"🌡 {value}°C = **{float(value)*9/5+32:.1f}°F**"
+    if (f,t) == ("f","c"): return f"🌡 {value}°F = **{(float(value)-32)*5/9:.1f}°C**"
+    factor = conversions.get((f,t))
+    if factor: return f"📏 {value} {from_unit} = **{float(value)*factor:.3f} {to_unit}**"
+    return f"Can't convert {from_unit} to {to_unit}"
+
+# ── Tool Decision ─────────────────────────────────────
 def decide_tool(question):
     try:
         from groq import Groq
-        c = Groq(api_key=groq_key)
-        prompt = f"""Pick ONE tool or none.
+        client = Groq(api_key=groq_key)
+        prompt = f"""Pick ONE tool or none for this question.
 Tools: web_search(query), news(topic), calculator(expr), datetime(), weather(city),
-       currency(amount,from,to), unit_convert(value,from,to), save_note(title,content), get_note(title), none
+       currency(amount,from,to), unit_convert(value,from,to),
+       save_note(title,content), get_note(title), none
 Question: "{question}"
 Reply ONLY with tool call or 'none':"""
-        resp = c.chat.completions.create(model="llama-3.1-8b-instant",
-            messages=[{"role":"user","content":prompt}], max_tokens=60, temperature=0)
+        resp = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=[{"role":"user","content":prompt}],
+            max_tokens=60, temperature=0,
+        )
         d = resp.choices[0].message.content.strip().lower()
-        if d.startswith("web_search("):   return "🌐 Searching the web",     tool_web_search(d[11:].rstrip(")").strip("'\""))
-        if d.startswith("news("):         return "📰 Getting latest news",   tool_news(d[5:].rstrip(")").strip("'\""))
-        if d.startswith("calculator("):   return "🧮 Calculating",           tool_calculator(d[11:].rstrip(")").strip("'\""))
-        if d.startswith("datetime"):      return "🕐 Checking time",         tool_datetime()
-        if d.startswith("weather("):      return "🌤 Checking weather",      tool_weather(d[8:].rstrip(")").strip("'\""))
+        if d.startswith("web_search("):   return "🌐 Searching...",    tool_web_search(d[11:].rstrip(")").strip("'\""))
+        if d.startswith("news("):         return "📰 Getting news...", tool_news(d[5:].rstrip(")").strip("'\""))
+        if d.startswith("calculator("):   return "🧮 Calculating...",  tool_calculator(d[11:].rstrip(")").strip("'\""))
+        if d.startswith("datetime"):      return "🕐 Checking time...",tool_datetime()
+        if d.startswith("weather("):      return "🌤 Weather...",      tool_weather(d[8:].rstrip(")").strip("'\""))
         if d.startswith("currency("):
             p = d[9:].rstrip(")").split(",")
-            if len(p)==3: return "💱 Converting currency", tool_currency(p[0].strip(),p[1].strip(),p[2].strip())
+            if len(p)==3: return "💱 Converting...", tool_currency(p[0].strip(),p[1].strip(),p[2].strip())
         if d.startswith("unit_convert("):
             p = d[13:].rstrip(")").split(",")
-            if len(p)==3: return "📏 Converting units", tool_unit(p[0].strip(),p[1].strip(),p[2].strip())
+            if len(p)==3: return "📏 Converting...", tool_unit_converter(p[0].strip(),p[1].strip(),p[2].strip())
         if d.startswith("save_note("):
             p = d[10:].rstrip(")").split(",",1)
-            if len(p)==2: return "📝 Saving note", save_note(p[0].strip(),p[1].strip())
-        if d.startswith("get_note("):     return "📝 Finding note",          get_note(d[9:].rstrip(")").strip("'\""))
+            if len(p)==2: return "📝 Saving note...", save_note(p[0].strip(),p[1].strip())
+        if d.startswith("get_note("):     return "📝 Finding note...", get_note(d[9:].rstrip(")").strip("'\""))
     except: pass
     return None, None
 
+# ── Streaming ─────────────────────────────────────────
 def stream_response(question, context):
     from groq import Groq
-    c = Groq(api_key=groq_key)
+    client = Groq(api_key=groq_key)
+
+    # Build full system prompt with profile
     profile_ctx = get_profile_context()
     system = PA_PERSONALITY
-    if profile_ctx: system += f"\n\nUser profile:\n{profile_ctx}"
-    if your_name:   system += f"\n\nAddress the user as {your_name} occasionally."
-    msgs = [{"role":"system","content":system}]
-    for m in st.session_state.history[-6:]: msgs.append(m)
-    user_content = (f"Tool result:\n{context}\n\n" if context else "") + question
-    msgs.append({"role":"user","content":user_content})
-    stream = c.chat.completions.create(model=LLM_MODEL, messages=msgs,
-                                        stream=True, max_tokens=1024, temperature=0.7)
+    if profile_ctx:
+        system += f"\n\nWhat you know about the user:\n{profile_ctx}"
+    if your_name:
+        system += f"\n\nThe user's name is {your_name}. Address them by name occasionally."
+
+    # Build messages with conversation history
+    messages = [{"role": "system", "content": system}]
+    # Add last 6 messages for context
+    for msg in st.session_state.history[-6:]:
+        messages.append(msg)
+    # Add current question with tool context
+    user_content = (f"Context from tools:\n{context}\n\n" if context else "") + question
+    messages.append({"role": "user", "content": user_content})
+
+    stream = client.chat.completions.create(
+        model=LLM_MODEL,
+        messages=messages,
+        stream=True, max_tokens=1024, temperature=0.7,
+    )
     for chunk in stream:
         yield chunk.choices[0].delta.content or ""
 
-# ── Welcome message ───────────────────────────────────
+# ── Chat UI ───────────────────────────────────────────
+# Welcome message on first load
 if not st.session_state.messages:
-    welcome = f"Hi {your_name}! I'm **Aria**, your personal AI. I can search the web, check the weather, convert currencies, save notes, and much more. What's on your mind?"
-    st.session_state.messages.append({"role":"assistant","content":welcome})
-
-# ── Suggestion chips (only on first load) ─────────────
-if len(st.session_state.messages) == 1:
-    st.markdown("""
-    <div class="chip-row">
-        <div class="chip">🌤 Weather today</div>
-        <div class="chip">📰 Latest AI news</div>
-        <div class="chip">💱 100 USD to INR</div>
-        <div class="chip">📝 Save a note</div>
-    </div>
-    """, unsafe_allow_html=True)
-
-# ── Render messages ───────────────────────────────────
+    welcome = f"Hi {your_name}! 👋 I'm **{PA_NAME}**, your personal AI assistant. I can search the web, check weather, convert currencies, save notes, and much more. What can I help you with today?"
+    st.session_state.messages.append({"role": "assistant", "content": welcome})
+
 for msg in st.session_state.messages:
     with st.chat_message(msg["role"]):
         st.markdown(msg["content"])
 
-# ── Input ─────────────────────────────────────────────
-if prompt := st.chat_input(f"Message Aria..."):
-    st.session_state.messages.append({"role":"user","content":prompt})
-    st.session_state.history.append({"role":"user","content":prompt})
+if prompt := st.chat_input(f"Talk to {PA_NAME}..."):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    st.session_state.history.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
     with st.chat_message("assistant"):
-        score, cached = search_memory(prompt)
+        cached = search_memory(prompt)
         if cached:
-            st.markdown(f'<div class="memory-pill">🧠 From memory · {score:.0%} match</div>', unsafe_allow_html=True)
             st.markdown(cached)
-            st.session_state.messages.append({"role":"assistant","content":cached})
-            st.session_state.history.append({"role":"assistant","content":cached})
+            st.session_state.messages.append({"role": "assistant", "content": cached})
+            st.session_state.history.append({"role": "assistant", "content": cached})
         else:
-            with st.spinner(""):
+            with st.spinner(f"{PA_NAME} is thinking..."):
                 tool_label, context = decide_tool(prompt)
             if tool_label:
-                st.markdown(f'<div class="tool-pill">⚡ {tool_label}</div>', unsafe_allow_html=True)
+                st.caption(tool_label)
             response = st.write_stream(stream_response(prompt, context or ""))
             store_memory(prompt, response)
-            update_profile(prompt)
-            st.session_state.messages.append({"role":"assistant","content":response})
-            st.session_state.history.append({"role":"assistant","content":response})
+            update_profile_from_chat(prompt, response)
+            st.session_state.messages.append({"role": "assistant", "content": response})
+            st.session_state.history.append({"role": "assistant", "content": response})