Update app.py

app.py

@@ -11,123 +11,188 @@ import folium
 from streamlit_folium import st_folium
 from streamlit_geolocation import streamlit_geolocation
 
-# --- 1. SYSTEM CONFIG ---
+# --- 1. CORE SYSTEM 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 check your environment variables.")
     st.stop()
 
-st.set_page_config(page_title="IntelliCare | Hassan Naseer", layout="wide", page_icon="🏥")
+st.set_page_config(page_title="IntelliCare Portal | Hassan Naseer", layout="wide", page_icon="🏥")
 
-# --- 2. CSS ---
+# --- 2. PREMIUM CSS ---
 st.markdown("""
 <style>
     [data-testid="stSidebar"] { background: #1e3a8a !important; }
     [data-testid="stSidebar"] * { color: #ffffff !important; }
-    div.stButton > button { background-color: #1e3a8a !important; color: white !important; }
-    .user-msg { background: #3b82f6; color: white; padding: 12px; border-radius: 15px 15px 2px 15px; margin-bottom: 10px; margin-left: 25%; }
-    .ai-msg { background: #f1f5f9; color: #1e293b; padding: 12px; border-radius: 15px 15px 15px 2px; margin-bottom: 10px; margin-right: 25%; border: 1px solid #e2e8f0; }
+    div.stButton > button {
+        background-color: #1e3a8a !important; color: white !important;
+        border: 1px solid #3b82f6 !important; transition: none !important;
+    }
+    .user-msg {
+        background: linear-gradient(135deg, #3b82f6 0%, #2563eb 100%);
+        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);
+    }
+    .ai-msg {
+        background: #f1f5f9; color: #1e293b; padding: 15px; border-radius: 18px 18px 18px 2px;
+        margin-bottom: 15px; margin-right: 20%; border: 1px solid #e2e8f0;
+    }
 </style>
 """, unsafe_allow_html=True)
 
-# --- 3. CORE LOGIC ---
+# --- 3. DATA UTILS ---
 USER_DB, CALL_LOG_DB, CALL_SIGNAL_DB = "users_secure.csv", "call_history.csv", "active_calls.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)
 
+# 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 = ""
 if "last_voice_hash" not in st.session_state: st.session_state.last_voice_hash = None
+if "audio_key" not in st.session_state: st.session_state.audio_key = 0 # To reset Mic
 
 # --- 4. AUTHENTICATION ---
 if not st.session_state.logged_in:
-    st.markdown("<h1 style='text-align: center;'>🏥 IntelliCare Portal</h1>", unsafe_allow_html=True)
+    st.markdown("<h1 style='text-align: center; color: #1e3a8a;'>🏥 IntelliCare Portal</h1>", unsafe_allow_html=True)
     c2 = st.columns([1, 2, 1])[1]
     with c2:
-        t1, t2 = st.tabs(["🔐 Login", "📝 Register"])
-        with t1:
+        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"):
                 db = load_db(USER_DB, ["username", "password", "role"])
-                m = db[(db['username'] == u) & (db['password'] == hash_pass(p))]
-                if not m.empty:
-                    st.session_state.logged_in, st.session_state.username, st.session_state.role = True, u, m.iloc[0]['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()
-        with t2:
-            nu, np, nr = st.text_input("New ID"), st.text_input("New Pass", type="password"), st.selectbox("Role", ["Patient", "Doctor"])
-            if st.button("Create Account"):
+        with tab2:
+            nu, np = st.text_input("New ID"), st.text_input("New Pass", type="password")
+            nr = 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("Registered!")
+                pd.concat([df, pd.DataFrame([{"username": nu, "password": hash_pass(np), "role": nr}])]).to_csv(USER_DB, index=False)
+                st.success("Registered!")
     st.stop()
 
-# --- 5. SIDEBAR ---
+# --- 5. SIDEBAR NAVIGATION ---
 with st.sidebar:
     st.markdown(f"### 👤 {st.session_state.username}")
     lang = st.radio("🌐 Language", ["English", "Urdu"])
     
-    # PERMANENT DOWNLOAD BUTTON
-    chat_history_text = "\n".join([f"{m['role'].upper()}: {m['content']}" for m in st.session_state.msgs])
-    st.download_button(
-        label="📥 Download Full Chat PDF/Text",
-        data=chat_history_text,
-        file_name=f"IntelliCare_Chat_{datetime.now().strftime('%Y%m%d')}.txt",
-        mime="text/plain"
-    )
+    # PERMANENT DOWNLOAD
+    chat_txt = "\n".join([f"{m['role']}: {m['content']}" for m in st.session_state.msgs])
+    st.download_button("📥 Download History", data=chat_txt, file_name="chat.txt")
     
-    if st.button("🗑️ Clear Chat"):
+    if st.button("🗑️ Clear Chat"): 
         st.session_state.msgs, st.session_state.active_doc = [], ""
         st.rerun()
+    if st.button("🚪 Logout"): st.session_state.logged_in = False; st.rerun()
     st.divider()
-    nav = st.radio("Menu", ["💬 Chat", "🧪 Lab", "📍 Maps", "📞 Video"]) if st.session_state.role == "Patient" else st.radio("Menu", ["🖥️ Desk", "📜 Logs"])
+    
+    if st.session_state.role == "Patient":
+        nav = st.radio("Menu", ["💬 AI Chat", "🧪 Health Lab", "📍 Nearby Clinics", "📞 Video Consult", "📜 History"])
+    else:
+        nav = st.radio("Menu", ["🖥️ Consultation Desk", "📜 Call Logs"])
 
-# --- 6. CHAT MODULE (FIXED INPUT BAR & PDF TEXT) ---
-if nav == "💬 Chat":
+# --- 6. AI CHAT MODULE (FIXED MIC & INPUT) ---
+if nav == "💬 AI Chat":
     st.markdown("### 💬 Clinical Intelligence Assistant")
-    
-    # 1. Permanent PDF Reader UI
-    with st.expander("📄 Upload Medical PDF / Prescription"):
-        up = st.file_uploader("Drop PDF here", type=['pdf'], label_visibility="collapsed")
+    with st.expander("📄 Upload Report/Prescription"):
+        up = st.file_uploader("Drop PDF", type=['pdf'], label_visibility="collapsed")
         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("✅ Prescription/Report Analyzed!")
+                st.success("✅ Analysis Ready!")
 
-    # 2. Display Chat
     for m in st.session_state.msgs:
-        st.markdown(f'<div class="{"user-msg" if m["role"] == "user" else "ai-msg"}">{m["content"]}</div>', unsafe_allow_html=True)
+        st.markdown(f'<div class="{"user-msg" if m["role"]=="user" else "ai-msg"}">{m["content"]}</div>', unsafe_allow_html=True)
     
-    # 3. FIXED INPUT BAR (Always visible)
     st.divider()
-    c_v, c_q = st.columns([1, 9])
-    with c_v: v = st.audio_input("🎤", key="permanent_mic", label_visibility="collapsed")
-    with c_q: q = st.chat_input("Ask about your report or prescription...")
+    col_v, col_q = st.columns([1, 9])
+    with col_v: # FIXED MIC RESET
+        v = st.audio_input("🎤", key=f"mic_{st.session_state.audio_key}", label_visibility="collapsed")
+    with col_q: q = st.chat_input("Ask about your health...")
 
     final_q = q if q else None
-    if v and not final_q: # Voice-to-Text Logic
+    if v and not final_q:
         vh = hashlib.md5(v.getvalue()).hexdigest()
         if vh != 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 = vh
+            st.session_state.audio_key += 1 # Forces Mic refresh
 
     if final_q:
         st.session_state.msgs.append({"role": "user", "content": final_q})
-        # AI Logic: PDF Text + Voice/Text
-        sys_p = f"Medical Assistant. Language: {lang}. If PDF exists, read and explain it like a human doctor. Focus on prescriptions and reports."
-        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"PDF_CONTENT: {st.session_state.active_doc}"}] + st.session_state.msgs)
+        sys_p = f"Professional Medical Assistant. Language: {lang}. Analyze the PDF text provided. Refuse non-medical tasks."
+        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"PDF: {st.session_state.active_doc}"}] + st.session_state.msgs)
         st.session_state.msgs.append({"role": "assistant", "content": ans.choices[0].message.content})
         st.rerun()
 
-# --- 7. OTHER FEATURES ---
-elif nav == "🧪 Lab":
-    st.plotly_chart(go.Figure(go.Indicator(mode="gauge+number", value=22, title={'text': "BMI Gauge"})))
-elif nav == "📍 Maps":
+# --- 7. DIAGNOSTIC TOOLS (3 TOOLS RESTORED) ---
+elif nav == "🧪 Health Lab":
+    st.markdown("### 🧪 Interactive Clinical Lab")
+    tool = st.selectbox("Select Diagnostic Tool", ["⚖️ BMI Analyzer", "🩸 Glucose Tracker", "🫀 Heart Rate Sim"])
+    
+    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.metric("Your BMI", bmi)
+        st.plotly_chart(go.Figure(go.Indicator(mode="gauge+number", value=bmi, gauge={'axis': {'range': [10, 40]}, 'bar': {'color': "#3b82f6"}})), use_container_width=True)
+
+    elif tool == "🩸 Glucose Tracker":
+        
+        st.write("Recent Blood Sugar Levels (mg/dL)")
+        df = pd.DataFrame({'Time': range(1, 11), 'Level': np.random.randint(80, 150, 10)})
+        st.plotly_chart(go.Figure(data=go.Scatter(x=df['Time'], y=df['Level'], mode='lines+markers', line=dict(color='#2563eb'))), use_container_width=True)
+
+    elif tool == "🫀 Heart Rate Sim":
+        
+        bpm = st.slider("Select Current BPM", 40, 180, 72)
+        st.metric("Heart Rate", f"{bpm} BPM")
+        t = np.linspace(0, 2, 1000)
+        heart_wave = np.sin(2 * np.pi * (bpm/60) * t) + 0.1 * np.random.normal(0, 1, 1000)
+        st.plotly_chart(go.Figure(data=go.Scatter(x=t, y=heart_wave, line=dict(color='#ef4444'))), use_container_width=True)
+
+# --- 8. MAPS & VIDEO CALLS (RESTORED) ---
+elif nav == "📍 Nearby Clinics":
+    st.markdown("### 📍 Specialist Hospital Locator")
     loc = streamlit_geolocation()
     if loc.get("latitude"):
-        st_folium(folium.Map(location=[loc["latitude"], loc["longitude"]], zoom_start=14), width=1000)
-elif nav == "📞 Video":
-    st.write("Specialist Call Section")
+        m = folium.Map(location=[loc["latitude"], loc["longitude"]], zoom_start=14)
+        folium.Marker([loc["latitude"], loc["longitude"]], popup="You").add_to(m)
+        st_folium(m, width=1000, height=500)
+
+elif nav == "📞 Video Consult":
+    db = load_db(USER_DB, ["username", "role"])
+    docs = db[db['role'] == 'Doctor']['username'].tolist()
+    sel_doc = st.selectbox("Select Specialist", docs)
+    if st.button("Request Video Consultation"):
+        room = f"IntelliCare-{st.session_state.username}-{sel_doc}"
+        pd.DataFrame([{"Caller": st.session_state.username, "Receiver": sel_doc, "RoomID": room, "Status": "Active"}]).to_csv(CALL_SIGNAL_DB, index=False)
+        pd.concat([load_db(CALL_LOG_DB, ["Time", "Caller", "Receiver", "RoomID"]), pd.DataFrame([{"Time": datetime.now().strftime("%Y-%m-%d %H:%M"), "Caller": st.session_state.username, "Receiver": sel_doc, "RoomID": room}])]).to_csv(CALL_LOG_DB, index=False)
+        st.session_state.p_room = room
+    if "p_room" in st.session_state:
+        st.components.v1.html(f'<iframe src="https://meet.jit.si/{st.session_state.p_room}" width="100%" height="600px"></iframe>', height=650)
+
+elif nav == "🖥️ Consultation Desk":
+    signals = load_db(CALL_SIGNAL_DB, ["Caller", "Receiver", "RoomID"])
+    my_calls = signals[signals['Receiver'] == st.session_state.username]
+    if not my_calls.empty:
+        st.info(f"🔔 Request from {my_calls.iloc[0]['Caller']}")
+        c1, c2 = st.columns(2)
+        with c1:
+            if st.button("✅ Accept"): st.session_state.d_room = my_calls.iloc[0]['RoomID']
+        with c2:
+            if st.button("❌ Decline"): 
+                load_db(CALL_SIGNAL_DB, ["Caller", "Receiver", "RoomID", "Status"])[load_db(CALL_SIGNAL_DB, ["Caller", "Receiver", "RoomID", "Status"])['Receiver'] != st.session_state.username].to_csv(CALL_SIGNAL_DB, index=False)
+                st.rerun()
+    if "d_room" in st.session_state:
+        st.components.v1.html(f'<iframe src="https://meet.jit.si/{st.session_state.d_room}" width="100%" height="600px"></iframe>', height=650)
+
+elif nav in ["📜 History", "📜 Call Logs"]:
+    st.dataframe(load_db(CALL_LOG_DB, ["Time", "Caller", "Receiver", "RoomID"]), use_container_width=True)