Update app.py

app.py

@@ -11,77 +11,65 @@ import folium
 from streamlit_folium import st_folium
 from streamlit_geolocation import streamlit_geolocation
 
-# --- 1. CORE SYSTEM CONFIG ---
+# --- 1. CORE SYSTEM CONFIGURATION ---
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
 if not GROQ_API_KEY:
-    st.error("⚠️ API Key Missing! Please set it in your environment.")
+    st.error("⚠️ API Key Missing! Please set it in your environment secrets.")
     st.stop()
 
 st.set_page_config(page_title="IntelliCare Portal | Hassan Naseer", layout="wide", page_icon="🏥")
 
-# --- 2. PREMIUM CSS ENGINE (Beautiful Bubbles & Static Frame) ---
-def inject_premium_design():
-    st.markdown("""
-    <style>
-    @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;600&display=swap');
-    html, body, [class*="css"] { font-family: 'Poppins', sans-serif; }
-
-    /* 1. Dashboard Static Frame */
-    [data-testid="stSidebar"] {
-        background: linear-gradient(180deg, #0f172a 0%, #1e3a8a 100%);
-    }
-    
-    /* 2. Chat Board Styling */
-    .chat-container {
-        height: 60vh;
-        overflow-y: auto;
-        padding: 20px;
-        background: #f8fafc;
-        border-radius: 15px;
-        border: 1px solid #e2e8f0;
-        display: flex;
-        flex-direction: column;
-    }
-
-    /* 3. Beautiful Message Bubbles */
-    .user-bubble {
+# --- 2. BEAUTIFUL CHAT BUBBLE CSS (Simple Layout, Premium Chat) ---
+st.markdown("""
+<style>
+    /* User Message: Beautiful Blue Gradient */
+    .user-msg {
         background: linear-gradient(135deg, #3b82f6 0%, #2563eb 100%);
-        color: white; padding: 15px; border-radius: 20px 20px 0 20px;
-        align-self: flex-end; margin-bottom: 12px; max-width: 80%;
-        box-shadow: 0 4px 15px rgba(37,99,235,0.2);
-    }
-    .ai-bubble {
-        background: #ffffff; color: #1e293b; padding: 15px;
-        border-radius: 20px 20px 20px 0; align-self: flex-start;
-        margin-bottom: 12px; max-width: 80%; border: 1px solid #e2e8f0;
-        box-shadow: 0 4px 15px rgba(0,0,0,0.05);
+        color: white;
+        padding: 15px;
+        border-radius: 18px 18px 2px 18px;
+        margin-bottom: 15px;
+        margin-left: 20%;
+        box-shadow: 0 4px 10px rgba(37, 99, 235, 0.2);
     }
-
-    /* 4. Fixed Gemini Prompt Styling */
-    div[data-testid="stChatInput"] {
-        border-radius: 25px !important;
-        border: 2px solid #3b82f6 !important;
+    /* AI Message: Professional Soft Background */
+    .ai-msg {
+        background: #f1f5f9;
+        color: #1e293b;
+        padding: 15px;
+        border-radius: 18px 18px 18px 2px;
+        margin-bottom: 15px;
+        margin-right: 20%;
+        border: 1px solid #e2e8f0;
+        box-shadow: 0 2px 5px rgba(0,0,0,0.05);
     }
-    </style>
-    """, unsafe_allow_html=True)
+</style>
+""", unsafe_allow_html=True)
 
-inject_premium_design()
+# --- 3. DATA PERSISTENCE & UTILS ---
+USER_DB = "users_secure.csv"
+HISTORY_DB = "clinical_history.csv"
 
-# --- 3. DATA PERSISTENCE & SESSION ---
-USER_DB, HISTORY_DB = "users_secure.csv", "clinical_history.csv"
 def hash_pass(pwd): return hashlib.sha256(str.encode(pwd)).hexdigest()
+
 def load_db(file, cols):
     if os.path.exists(file): return pd.read_csv(file)
     return pd.DataFrame(columns=cols)
 
+def save_history(user, text, role):
+    df = load_db(HISTORY_DB, ["Time", "User", "Message", "Role"])
+    new_entry = pd.DataFrame([{"Time": datetime.now().strftime("%Y-%m-%d %H:%M"), "User": user, "Message": text, "Role": role}])
+    pd.concat([df, new_entry]).to_csv(HISTORY_DB, index=False)
+
+# Session State Initialization
 if "logged_in" not in st.session_state: st.session_state.logged_in = False
 if "msgs" not in st.session_state: st.session_state.msgs = []
 if "active_doc" not in st.session_state: st.session_state.active_doc = None
 if "last_voice_hash" not in st.session_state: st.session_state.last_voice_hash = None
 
-# --- 4. AUTHENTICATION (Login & Account Creation) ---
+# --- 4. AUTHENTICATION (Account Creation & Login) ---
 if not st.session_state.logged_in:
-    st.markdown("<h1 style='text-align: center; color: #1e3a8a;'>🏥 INTELLICARE PORTAL</h1>", unsafe_allow_html=True)
+    st.markdown("<h1 style='text-align: center;'>🏥 IntelliCare Portal</h1>", unsafe_allow_html=True)
     c1, c2, c3 = st.columns([1, 2, 1])
     with c2:
         tab1, tab2 = st.tabs(["🔐 Login", "📝 Create Account"])
@@ -94,88 +82,111 @@ if not st.session_state.logged_in:
                     st.session_state.logged_in, st.session_state.username = True, u
                     st.session_state.role = match.iloc[0]['role']
                     st.rerun()
+                else:
+                    st.error("Invalid credentials.")
         with tab2:
             nu, np, nr = st.text_input("New ID"), st.text_input("New Pass", type="password"), st.selectbox("Role", ["Patient", "Doctor"])
             if st.button("Register Account"):
                 df = load_db(USER_DB, ["username", "password", "role"])
-                if nu in df['username'].values: st.warning("User exists.")
+                if nu in df['username'].values: st.warning("User already exists.")
                 else:
                     pd.concat([df, pd.DataFrame([{"username": nu, "password": hash_pass(np), "role": nr}])]).to_csv(USER_DB, index=False)
-                    st.success("Account Created! Please Login.")
+                    st.success("Account Registered! Please Login.") #
     st.stop()
 
 # --- 5. SIDEBAR NAVIGATION ---
 with st.sidebar:
     st.markdown(f"### 👤 {st.session_state.username} ({st.session_state.role})")
-    if st.button("Logout Session"): st.session_state.logged_in = False; st.rerun()
+    if st.button("Logout"): st.session_state.logged_in = False; st.rerun()
     st.divider()
     if st.session_state.role == "Patient":
-        nav = st.radio("Menu", ["💬 AI Chat", "🧪 Health Lab", "📍 Nearby Clinics", "📞 Video Consult", "📜 History"])
+        nav = st.radio("Menu", ["💬 AI Chat", "🧪 Health Lab", "📍 Nearby Clinics", "📞 Video Consult", "📜 My History"])
     else:
-        nav = st.radio("Menu", ["🖥️ Consultation Desk", "📋 Patient Records"])
+        nav = st.radio("Menu", ["🖥️ Consultation Desk", "📋 Patient Archive", "📜 Session Logs"])
 
-# --- 6. AI CHAT MODULE (PREMIUM DESIGN) ---
+# --- 6. AI CHAT MODULE (BEAUTIFUL BACKGROUNDS & LEFT ICONS) ---
 if nav == "💬 AI Chat":
-    st.markdown("### 💬 Clinical Intelligence Assistant")
+    st.markdown("### 💬 Clinical AI Assistant")
     
-    # Beautiful Chat History Dashboard
-    st.markdown('<div class="chat-container">', unsafe_allow_html=True)
+    # Render Beautiful Chat
     for m in st.session_state.msgs:
-        bubble_type = "user-bubble" if m["role"] == "user" else "ai-bubble"
-        st.markdown(f'<div class="{bubble_type}">{m["content"]}</div>', unsafe_allow_html=True)
-    st.markdown('</div>', unsafe_allow_html=True)
+        div_class = "user-msg" if m["role"] == "user" else "ai-msg"
+        st.markdown(f'<div class="{div_class}">{m["content"]}</div>', unsafe_allow_html=True)
 
-    # UNIFIED INPUT: Mic & Plus on Left
     st.divider()
-    col_v, col_up, col_q = st.columns([1, 1, 8])
-    with col_v: v = st.audio_input("🎤", label_visibility="collapsed")
+    # MIC AND PLUS ON LEFT OF PROMPT
+    col_v, col_up, col_q = st.columns([0.6, 0.6, 8.8])
+    with col_v: 
+        v = st.audio_input("🎤", label_visibility="collapsed", key=f"mic_{len(st.session_state.msgs)}")
     with col_up:
         with st.popover("➕"):
-            up = st.file_uploader("Upload PDF", type=['pdf'])
+            up = st.file_uploader("Upload Medical PDF", type=['pdf'])
             if up:
                 with pdfplumber.open(up) as f:
                     st.session_state.active_doc = " ".join([p.extract_text() for p in f.pages if p.extract_text()])
-                    st.success("PDF Context Loaded.")
-    with col_q: q = st.chat_input("Ask a medical question...")
-
-    # Stable Logic
-    final_q = q if q else None
-    if v and not final_q:
+                    st.success("PDF Context Extracted!") #
+    with col_q: 
+        q = st.chat_input("Enter clinical query...")
+
+    # Stable Processing Logic
+    final_q = None
+    if q: final_q = q
+    elif v:
         v_hash = hashlib.md5(v.getvalue()).hexdigest()
         if v_hash != st.session_state.last_voice_hash:
-            final_q = Groq(api_key=GROQ_API_KEY).audio.transcriptions.create(file=("a.wav", v.getvalue()), model="whisper-large-v3", response_format="text")
-            st.session_state.last_voice_hash = v_hash
+            try:
+                final_q = Groq(api_key=GROQ_API_KEY).audio.transcriptions.create(file=("a.wav", v.getvalue()), model="whisper-large-v3", response_format="text")
+                st.session_state.last_voice_hash = v_hash
+            except: st.error("Mic error. Please try again.")
 
     if final_q:
         st.session_state.msgs.append({"role": "user", "content": final_q})
-        sys_p = "Medical AI. Use PDF data if present. Provide clinical advice."
+        save_history(st.session_state.username, final_q, "Patient") #
+        sys_p = "You are a Medical AI. Answer clinical queries. Use PDF data if present. Refuse non-medical topics."
         ans = Groq(api_key=GROQ_API_KEY).chat.completions.create(model="llama-3.3-70b-versatile", messages=[{"role": "system", "content": sys_p}, {"role": "system", "content": f"CTX: {st.session_state.active_doc}"}] + st.session_state.msgs)
         st.session_state.msgs.append({"role": "assistant", "content": ans.choices[0].message.content})
+        save_history(st.session_state.username, ans.choices[0].message.content, "AI") #
         st.rerun()
 
 # --- 7. ADDITIONAL TOOLS ---
 elif nav == "🧪 Health Lab":
-    st.markdown("### 🧪 Health Tools")
-    tool = st.selectbox("Tool", ["BMI Analyzer", "Glucose Tracker"])
+    st.markdown("### 🧪 Health Diagnostics")
+    tool = st.selectbox("Select Tool", ["BMI Analyzer", "Glucose Tracker", "Heart Simulator"])
     if tool == "BMI Analyzer":
         
-        w, h = st.number_input("Weight (kg)", 70), st.number_input("Height (cm)", 175)
+        w, h = st.number_input("Weight (kg)", 30, 200, 70), st.number_input("Height (cm)", 100, 250, 175)
         bmi = round(w / ((h/100)**2), 1)
         st.metric("Your BMI", bmi)
         st.plotly_chart(go.Figure(go.Indicator(mode="gauge+number", value=bmi, gauge={'bar':{'color':"#10b981"}})))
     elif tool == "Glucose Tracker":
         
         st.area_chart(pd.DataFrame(np.random.randn(20, 1).cumsum() + 100))
+    elif tool == "Heart Simulator":
+        
+        hr = st.slider("BPM", 40, 180, 72)
+        y = np.sin(2 * np.pi * (hr/60) * np.linspace(0, 2, 200))
+        st.plotly_chart(go.Figure(data=go.Scatter(y=y, mode='lines', line=dict(color='#ff4b4b'))))
+
+elif nav == "📍 Nearby Clinics":
+    st.markdown("### 📍 Specialist Hospital Locator")
+    loc = streamlit_geolocation()
+    if loc.get("latitude"):
+        m = folium.Map(location=[loc["latitude"], loc["longitude"]], zoom_start=14)
+        st_folium(m, width=1000, height=500)
 
 elif nav == "📞 Video Consult":
-    st.markdown("### 📞 Specialist Call")
+    st.markdown("### 📞 Specialist Live Call")
     db = load_db(USER_DB, ["username", "role"])
-    docs = db[db['role'] == 'Doctor']['username'].tolist() # Patient sees registered doctors
-    sel_doc = st.selectbox("Select Doctor", docs)
+    doctors = db[db['role'] == 'Doctor']['username'].tolist() #
+    sel_doc = st.selectbox("Select Registered Specialist", doctors)
     if st.button("Start Meeting"):
-        st.components.v1.html(f'<iframe src="https://meet.jit.si/IntelliCare-{st.session_state.username}-{sel_doc}" width="100%" height="600px"></iframe>', height=650)
+        room = f"IntelliCare-{st.session_state.username}-{sel_doc}"
+        st.components.v1.html(f'<iframe src="https://meet.jit.si/{room}" width="100%" height="600px"></iframe>', height=650)
 
-elif nav == "📜 History":
-    st.markdown("### 📜 Session History")
+elif nav in ["📜 My History", "📜 Session Logs", "📋 Patient Archive"]:
+    st.markdown("### 📜 Clinical History Logs")
     history = load_db(HISTORY_DB, ["Time", "User", "Message", "Role"])
-    st.dataframe(history[history['User'] == st.session_state.username], use_container_width=True) #
+    if st.session_state.role == "Patient":
+        st.dataframe(history[history['User'] == st.session_state.username], use_container_width=True) #
+    else:
+        st.dataframe(history, use_container_width=True) #