Update app.py

app.py

@@ -6,66 +6,57 @@ import hashlib
 from datetime import datetime
 from groq import Groq
 import pdfplumber
+import plotly.graph_objects as go
 
-# --- 1. CONFIG ---
+# --- 1. CORE CONFIG ---
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
 if not GROQ_API_KEY:
-    st.error("⚠️ API Key Missing!")
+    st.error("⚠️ API Key Missing! Please set it in Space Secrets.")
     st.stop()
 
-st.set_page_config(page_title="IntelliCare Portal", layout="wide")
+st.set_page_config(page_title="IntelliCare Portal | Hassan Naseer", layout="wide", page_icon="🏥")
 
-# --- 2. ADVANCED CSS: THE WIDE GEMINI INPUT BAR & FIXED SCROLL ---
-def inject_gemini_v2():
+# --- 2. ADVANCED CSS: GEMINI UI + SCROLL LOCK ---
+def inject_full_design():
     st.markdown("""
     <style>
-    /* 1. LOCK MAIN FRAME */
-    .main { overflow: hidden; height: 100vh; }
-    
-    /* 2. GRADIENT SIDEBAR */
+    @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;600&display=swap');
+    html, body, [class*="css"] { font-family: 'Poppins', sans-serif; overflow: hidden; height: 100vh; }
+
+    /* Gradient Sidebar (Static) */
     [data-testid="stSidebar"] {
         background: linear-gradient(180deg, #0f172a 0%, #1e3a8a 100%);
     }
+    [data-testid="stSidebar"] * { color: white !important; }
 
-    /* 3. SCROLLABLE CHAT AREA */
-    .chat-scroll-area {
-        height: 70vh;
+    /* Scrollable Chat Area Only */
+    .chat-history-box {
+        height: 60vh;
         overflow-y: auto;
-        padding: 20px 5%;
+        padding: 20px 2%;
         display: flex;
         flex-direction: column;
     }
 
-    /* 4. LARGE UNIFIED INPUT BAR (FIXED BOTTOM) */
-    /* We style the container to hold the Plus, Input, and Mic */
-    .fixed-footer {
-        position: fixed;
-        bottom: 0;
-        left: 0;
-        width: 100%;
-        background: white;
-        padding: 20px 5%;
-        z-index: 1000;
-        border-top: 1px solid #e2e8f0;
+    /* Gemini Bubbles */
+    .user-msg {
+        background: #3b82f6; color: white; padding: 15px; border-radius: 20px 20px 0 20px;
+        align-self: flex-end; margin-bottom: 12px; max-width: 80%;
     }
-
-    /* Target Streamlit's internal input to make it wide and clean */
-    div[data-testid="stChatInput"] {
-        border-radius: 24px !important;
-        border: 1px solid #dfe1e5 !important;
-        box-shadow: 0 1px 6px rgba(32,33,36,0.28) !important;
+    .ai-msg {
+        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;
     }
 
-    /* 5. BUBBLES */
-    .user-msg {
-        background: #3b82f6; color: white; padding: 15px;
-        border-radius: 18px 18px 0 18px; align-self: flex-end;
-        margin-bottom: 15px; max-width: 80%;
+    /* Fixed Bottom Prompt Bar */
+    .fixed-input-bar {
+        position: fixed; bottom: 20px; left: 18%; width: 80%;
+        background: white; padding: 10px; z-index: 1000;
     }
-    .ai-msg {
-        background: #ffffff; color: #1e293b; padding: 15px;
-        border-radius: 18px 18px 18px 0; align-self: flex-start;
-        margin-bottom: 15px; max-width: 80%; border: 1px solid #e2e8f0;
+
+    /* Widening the Prompt Box */
+    div[data-testid="stChatInput"] {
+        border-radius: 25px !important; border: 1px solid #3b82f6 !important;
     }
     </style>
 
@@ -75,65 +66,121 @@ def inject_gemini_v2():
         const msg = new SpeechSynthesisUtterance(text);
         window.speechSynthesis.speak(msg);
     }
-    const area = document.querySelector('.chat-scroll-area');
-    if(area) { area.scrollTop = area.scrollHeight; }
     </script>
     """, unsafe_allow_html=True)
 
-inject_gemini_v2()
+inject_full_design()
 
-# --- 3. SESSION STATE ---
+# --- 3. DATABASE & 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)
+
+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
 
-# --- 4. SIDEBAR (NAVIGATION ONLY) ---
+# --- 4. AUTHENTICATION PORTAL (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)
+    c1, c2, c3 = st.columns([1, 2, 1])
+    with c2:
+        tab1, tab2 = st.tabs(["🔐 Login", "✨ Create Account"])
+        with tab1:
+            u, p = st.text_input("Username"), st.text_input("Password", type="password")
+            if st.button("SIGN IN"):
+                users = load_db(USER_DB, ["username", "password", "role"])
+                match = users[(users['username'] == u) & (users['password'] == hash_pass(p))]
+                if not match.empty:
+                    st.session_state.logged_in, st.session_state.username = True, u
+                    st.session_state.role = match.iloc[0]['role']
+                    st.rerun()
+        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"):
+                df = load_db(USER_DB, ["username", "password", "role"])
+                if nu not in df['username'].values:
+                    pd.concat([df, pd.DataFrame([{"username": nu, "password": hash_pass(np), "role": nr}])]).to_csv(USER_DB, index=False)
+                    st.success("Account Created!")
+    st.stop()
+
+# --- 5. DUAL-PORTAL NAVIGATION ---
 with st.sidebar:
-    st.markdown("### 👤 Patient Portal")
-    nav = st.radio("Go to", ["💬 AI Chat", "🧪 Health Lab", "📍 Clinics"])
-    if st.button("🚪 Logout"): st.rerun()
-
-# --- 5. CHAT HISTORY (SCROLLABLE) ---
-st.markdown('<div class="chat-scroll-area">', unsafe_allow_html=True)
-for m in st.session_state.msgs:
-    bubble = "user-msg" if m["role"] == "user" else "ai-msg"
-    icon = f'<button style="border:none; background:none; cursor:pointer; float:right;" onclick="speak(\'{m["content"].replace("'", "")}\')">🔊</button>' if m["role"] == "assistant" else ""
-    st.markdown(f'<div class="{bubble}">{icon}{m["content"]}</div>', unsafe_allow_html=True)
-st.markdown('</div>', unsafe_allow_html=True)
-
-# --- 6. THE GEMINI INPUT SUITE (Plus + Text + Mic) ---
-# We use columns to arrange them perfectly at the bottom
-st.divider()
-c1, c2, c3 = st.columns([1, 8, 1])
-
-with c1:
-    with st.popover("➕"):
-        up_pdf = st.file_uploader("Document", type=['pdf'])
-        if up_pdf:
-            with pdfplumber.open(up_pdf) as f:
-                st.session_state.active_doc = " ".join([p.extract_text() for p in f.pages if p.extract_text()])
-                st.success("PDF Loaded")
-
-with c2:
-    q = st.chat_input("Ask a medical question...")
-
-with c3:
-    v = st.audio_input("🎤", label_visibility="collapsed")
-
-# --- 7. AI ENGINE ---
-final_q = q if q else (v if v else None)
-
-if final_q:
-    if hasattr(final_q, 'getvalue'):
-        final_q = Groq(api_key=GROQ_API_KEY).audio.transcriptions.create(file=("a.wav", final_q.getvalue()), model="whisper-large-v3", response_format="text")
-    
-    st.session_state.msgs.append({"role": "user", "content": final_q})
-    
-    sys_p = "You are a Medical Assistant. Be concise. If a PDF is uploaded, analyze it. Refuse non-medical queries."
-    ctx = f"PDF_DATA: {st.session_state.active_doc}"
-    
-    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": ctx}] + st.session_state.msgs
-    )
-    st.session_state.msgs.append({"role": "assistant", "content": ans.choices[0].message.content})
-    st.rerun()
+    st.markdown(f"### 👤 {st.session_state.username}\n**{st.session_state.role} Portal**")
+    if st.button("🚪 Logout"): st.session_state.logged_in = False; st.rerun()
+    st.divider()
+    if st.session_state.role == "Patient":
+        nav = st.radio("Navigation", ["💬 Medical AI", "🧪 Health Lab", "📍 Clinics"])
+    else:
+        nav = st.radio("Navigation", ["🖥️ Consultation Desk", "📋 Patient Records"])
+
+# --- 6. PATIENT PORTAL ---
+if st.session_state.role == "Patient":
+    if nav == "💬 Medical AI":
+        st.markdown("### 💬 Clinical Intelligence")
+        if st.session_state.active_doc: st.info("📄 Document Context Loaded")
+
+        # SCROLLABLE CHAT AREA
+        st.markdown('<div class="chat-history-box">', unsafe_allow_html=True)
+        for m in st.session_state.msgs:
+            bubble = "user-msg" if m["role"] == "user" else "ai-msg"
+            icon = f'<button style="float:right; border:none; background:none; cursor:pointer;" onclick="speak(\'{m["content"].replace("'", "")}\')">🔊</button>' if m["role"] == "assistant" else ""
+            st.markdown(f'<div class="{bubble}">{icon}{m["content"]}</div>', unsafe_allow_html=True)
+        st.markdown('</div>', unsafe_allow_html=True)
+
+        # GEMINI UNIFIED INPUT (Bottom of screen)
+        st.divider()
+        prompt_col1, prompt_col2, prompt_col3 = st.columns([1, 8, 1])
+        with prompt_col1:
+            with st.popover("➕"):
+                up_pdf = st.file_uploader("PDF", type=['pdf'])
+                if up_pdf:
+                    with pdfplumber.open(up_pdf) as f:
+                        st.session_state.active_doc = " ".join([p.extract_text() for p in f.pages if p.extract_text()])
+                        st.success("Analyzed!")
+        with prompt_col2:
+            q = st.chat_input("Ask about symptoms or reports...")
+        with prompt_col3:
+            v = st.audio_input("🎤", label_visibility="collapsed")
+
+        # AI LOGIC
+        final_q = q if q else (v if v else None)
+        if final_q:
+            if hasattr(final_q, 'getvalue'):
+                final_q = Groq(api_key=GROQ_API_KEY).audio.transcriptions.create(file=("a.wav", final_q.getvalue()), model="whisper-large-v3", response_format="text")
+            st.session_state.msgs.append({"role": "user", "content": final_q})
+            sys_p = "You are a Medical AI. Strictly medical only. Analyze PDFs if present."
+            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})
+            st.rerun()
+
+    elif nav == "🧪 Health Lab":
+        st.markdown("### 🧪 Diagnostics Library")
+        tool = st.selectbox("Tool", ["BMI Analyzer", "Glucose Tracker", "Heart Rate"])
+        if tool == "BMI Analyzer":
+            
+            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.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 Rate":
+            
+            hr = st.slider("BPM", 40, 180, 72)
+            t = np.linspace(0, 2, 200); y = np.sin(2 * np.pi * (hr/60) * t)
+            st.plotly_chart(go.Figure(data=go.Scatter(y=y, mode='lines', line=dict(color='#ff4b4b'))))
+
+# --- 7. DOCTOR PORTAL ---
+elif st.session_state.role == "Doctor":
+    if nav == "🖥️ Consultation Desk":
+        st.markdown("### 🖥️ Active Consultations")
+        room_id = st.text_input("Enter Patient Room ID")
+        if st.button("JOIN CALL"):
+            st.components.v1.html(f'<iframe src="https://meet.jit.si/{room_id}" width="100%" height="600px"></iframe>', height=650)
+    elif nav == "📋 Patient Records":
+        st.markdown("### 📋 Records Archive")
+        st.dataframe(load_db(HISTORY_DB, ["Time", "Patient", "Status"]), use_container_width=True)