Update app.py

app.py

@@ -11,189 +11,139 @@ import folium
 from streamlit_folium import st_folium
 from streamlit_geolocation import streamlit_geolocation
 
-# --- 1. CORE CONFIG ---
+# --- 1. CORE SYSTEM CONFIGURATION ---
 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 your environment secrets.")
     st.stop()
 
 st.set_page_config(page_title="IntelliCare Portal | Hassan Naseer", layout="wide", page_icon="🏥")
 
-# --- 2. THE STATIC FRAME ENGINE ---
-def inject_static_layout():
-    st.markdown("""
-    <style>
-    @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;600&display=swap');
-    
-    /* 1. LOCK THE VIEWPORT */
-    html, body, [data-testid="stAppViewContainer"] {
-        overflow: hidden !important;
-        height: 100vh;
-        font-family: 'Poppins', sans-serif;
-    }
-
-    /* 2. STATIC SIDEBAR */
-    [data-testid="stSidebar"] {
-        background: linear-gradient(180deg, #0f172a 0%, #1e3a8a 100%);
-        position: fixed;
-        height: 100vh;
-        z-index: 1000;
-    }
-    [data-testid="stSidebar"] * { color: #f8fafc !important; }
-
-    /* 3. SCROLLABLE CHAT BOARD */
-    .chat-board-container {
-        height: 58vh;
-        overflow-y: auto;
-        padding: 20px;
-        background: #ffffff;
-        border-radius: 15px;
-        border: 1px solid #e2e8f0;
-        display: flex;
-        flex-direction: column;
-        margin-top: 10px;
-    }
-
-    /* 4. STATIC PROMPT BAR (FIXED AT BOTTOM) */
-    div[data-testid="stChatInput"] {
-        position: fixed !important;
-        bottom: 40px !important;
-        left: 25% !important; /* Adjusted to make room for left icons */
-        width: 65% !important;
-        z-index: 999 !important;
-        border-radius: 30px !important;
-        border: 2px solid #3b82f6 !important;
-        background: white !important;
-    }
-
-    /* Professional 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%;
-    }
-    .ai-msg {
-        background: #f8fafc; color: #1e293b; padding: 15px;
-        border-radius: 20px 20px 20px 0; align-self: flex-start;
-        margin-bottom: 12px; max-width: 80%; border: 1px solid #e2e8f0;
-    }
-    .voice-btn { background: none; border: none; cursor: pointer; float: right; font-size: 1.1rem; }
-    </style>
-
-    <script>
-    function speak(text) {
-        window.speechSynthesis.cancel();
-        const msg = new SpeechSynthesisUtterance(text);
-        window.speechSynthesis.speak(msg);
-    }
-    </script>
-    """, unsafe_allow_html=True)
-
-inject_static_layout()
-
-# --- 3. SESSION & UTILS ---
+# --- 2. DATA PERSISTENCE & UTILS ---
 USER_DB = "users_secure.csv"
+HISTORY_DB = "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 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 ---
+# --- 3. AUTHENTICATION PORTAL (Account Creation & Login) ---
+
 if not st.session_state.logged_in:
-    st.markdown("<h1 style='text-align: center; color: #1e3a8a; padding-top: 50px;'>🏥 INTELLICARE PORTAL</h1>", unsafe_allow_html=True)
-    c2 = st.columns([1, 2, 1])[1]
+    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", "✨ Register"])
+        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"):
+            if st.button("Sign In"):
                 db = load_db(USER_DB, ["username", "password", "role"])
                 match = db[(db['username'] == u) & (db['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()
+                else:
+                    st.error("Invalid credentials.")
         with tab2:
-            nu, np, nr = st.text_input("New ID"), st.text_input("New Pass", type="password"), st.selectbox("I am a:", ["Patient", "Doctor"])
-            if st.button("REGISTER"):
+            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 not in df['username'].values:
+                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("Registered!")
+                    st.success("Account Registered! Please Login.")
     st.stop()
 
-# --- 5. STATIC SIDEBAR ---
+# --- 4. SIDEBAR NAVIGATION ---
 with st.sidebar:
-    st.markdown(f"### 👤 {st.session_state.username}\n**{st.session_state.role} Dashboard**")
-    if st.button("🚪 Logout"): st.session_state.logged_in = False; st.rerun()
+    st.markdown(f"### 👤 {st.session_state.username} ({st.session_state.role})")
+    if st.button("Logout Session"): st.session_state.logged_in = False; st.rerun()
     st.divider()
-    nav = st.radio("Navigation", ["💬 AI Chat Board", "🧪 Health Lab", "📍 Nearby Clinics", "📞 Video Consult"])
-
-# --- 6. AI CHAT BOARD (MIC & PLUS ON LEFT) ---
-if nav == "💬 AI Chat Board":
-    st.markdown("### 💬 Clinical Intelligence Assistant")
-    
-    # Scrollable Box
-    st.markdown('<div class="chat-board-container">', unsafe_allow_html=True)
+    if st.session_state.role == "Patient":
+        nav = st.radio("Menu", ["💬 AI Chat", "🧪 Health Lab", "📍 Nearby Clinics", "📞 Video Consult", "📜 My History"])
+    else:
+        nav = st.radio("Menu", ["🖥️ Consultation Desk", "📋 Patient Archive", "📜 Session Logs"])
+
+# --- 5. PATIENT PORTAL MODULES ---
+if nav == "💬 AI Chat":
+    st.markdown("### 💬 Clinical AI Assistant")
     for m in st.session_state.msgs:
-        bubble = "user-msg" if m["role"] == "user" else "ai-msg"
-        icon = f'<button class="voice-btn" 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)
+        role_label = "🧑‍💻 Patient" if m["role"] == "user" else "🤖 AI Assistant"
+        st.write(f"**{role_label}:** {m['content']}")
 
-    # UNIFIED INPUT: Mic and Plus on the LEFT
     st.divider()
-    col_mic, col_plus, col_text = st.columns([0.8, 0.8, 10])
-    
-    with col_mic:
-        v = st.audio_input("🎤", label_visibility="collapsed")
-        
-    with col_plus:
+    # MIC AND PLUS ON LEFT OF PROMPT
+    col_v, col_up, col_q = st.columns([1, 1, 8])
+    with col_v: v = st.audio_input("🎤", label_visibility="collapsed")
+    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])
-                    st.success("PDF Analyzed")
-                    
-    with col_text:
-        q = st.chat_input("Enter clinical query...")
+                    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 clinical query...")
 
-    # AI LOGIC
+    # Unified Processing Logic with Voice-Lock
     final_q = None
-    if q:
-        final_q = q
+    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 retry.")
 
     if final_q:
         st.session_state.msgs.append({"role": "user", "content": final_q})
-        sys_p = "Medical Assistant. Use PDF data if present. Answer medical queries only."
-        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
-        )
+        save_history(st.session_state.username, final_q, "Patient")
+        sys_p = "Medical Assistant. Use PDF data if present. Provide professional clinical advice."
+        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. OTHER TOOLS (REMAINS STATIC) ---
-elif nav == "🧪 Health Lab":
-    st.markdown("### 🧪 Diagnostics")
-    tool = st.selectbox("Tool", ["BMI Analyzer", "Glucose Tracker"])
-    if tool == "BMI Analyzer":
-        
-        w, h = st.number_input("Weight (kg)", 70), st.number_input("Height (cm)", 175)
-        bmi = round(w / ((h/100)**2), 1)
-        st.metric("BMI", bmi)
+elif nav == "📞 Video Consult":
+    st.markdown("### 📞 Specialist Live Call")
+    db = load_db(USER_DB, ["username", "role"])
+    doctors = db[db['role'] == 'Doctor']['username'].tolist() # Patient sees registered Doctors
+    sel_doc = st.selectbox("Select Available Specialist", doctors)
+    if st.button("Initialize Meeting"):
+        st.session_state.call_room = f"IntelliCare-{st.session_state.username}-{sel_doc}"
+    if "call_room" in st.session_state:
+        st.components.v1.html(f'<iframe src="https://meet.jit.si/{st.session_state.call_room}" width="100%" height="600px"></iframe>', height=650)
+
+# --- 6. DOCTOR PORTAL MODULES ---
+elif nav == "🖥️ Consultation Desk":
+    st.markdown("### 🖥️ Doctor Consultation Desk")
+    room_id = st.text_input("Enter Meeting ID (Provided by Patient)")
+    if st.button("JOIN SESSION"):
+        st.components.v1.html(f'<iframe src="https://meet.jit.si/{room_id}" width="100%" height="600px"></iframe>', height=650)
+
+elif nav == "📋 Patient Archive":
+    st.markdown("### 📋 Clinical Records Archive")
+    st.dataframe(load_db(HISTORY_DB, ["Time", "User", "Message", "Role"]), use_container_width=True)
+
+# --- 7. SHARED HISTORY LOGS ---
+elif nav in ["📜 My History", "📜 Session Logs"]:
+    st.markdown("### 📜 Session History Logs")
+    history = load_db(HISTORY_DB, ["Time", "User", "Message", "Role"])
+    if st.session_state.role == "Patient":
+        st.dataframe(history[history['User'] == st.session_state.username]) # Patients see only their own history
+    else:
+        st.dataframe(history) # Doctors can view all clinical history