Update app.py

app.py

@@ -11,51 +11,40 @@ import folium
 from streamlit_folium import st_folium
 from streamlit_geolocation import streamlit_geolocation
 
-# --- 1. CORE SYSTEM CONFIG ---
+# --- 1. SYSTEM CONFIG ---
 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 secrets.")
+    st.error("⚠️ API Key Missing!")
     st.stop()
 
-st.set_page_config(page_title="IntelliCare Portal | Hassan Naseer", layout="wide", page_icon="🏥")
+st.set_page_config(page_title="IntelliCare | Hassan Naseer", layout="wide", page_icon="🏥")
 
-# --- 2. PREMIUM CSS ---
+# --- 2. 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;
-        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;
-    }
+    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; }
 </style>
 """, unsafe_allow_html=True)
 
-# --- 3. DATA UTILS ---
+# --- 3. CORE LOGIC ---
 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 Setup
 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 "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
 
 # --- 4. AUTHENTICATION ---
 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)
     c2 = st.columns([1, 2, 1])[1]
     with c2:
         t1, t2 = st.tabs(["🔐 Login", "📝 Register"])
@@ -76,57 +65,50 @@ if not st.session_state.logged_in:
                     st.success("Registered!")
     st.stop()
 
-# --- 5. SIDEBAR & LANGUAGE ---
+# --- 5. SIDEBAR ---
 with st.sidebar:
     st.markdown(f"### 👤 {st.session_state.username}")
-    lang = st.radio("🌐 Language / زبان", ["English", "Urdu"])
-    st.divider()
-    if st.button("🗑️ Clear Chat" if lang == "English" else "🗑️ چیٹ صاف کریں"):
-        st.session_state.msgs, st.session_state.active_doc = [], None
+    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"
+    )
+    
+    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()
-    
-    # Translations
-    chat_nav = "💬 AI Chat" if lang == "English" else "💬 اے آئی چیٹ"
-    tools_nav = "🧪 Health Tools" if lang == "English" else "🧪 صحت کے اوزار"
-    map_nav = "📍 Nearby Clinics" if lang == "English" else "📍 قریبی کلینک"
-    call_nav = "📞 Video Consult" if lang == "English" else "📞 ویڈیو کال"
-    hist_nav = "📜 Call History" if lang == "English" else "📜 کال ریکارڈ"
-
-    nav = st.radio("Menu", [chat_nav, tools_nav, map_nav, call_nav, hist_nav]) if st.session_state.role == "Patient" else st.radio("Menu", ["🖥️ Desk", "📜 Logs"])
+    nav = st.radio("Menu", ["💬 Chat", "🧪 Lab", "📍 Maps", "📞 Video"]) if st.session_state.role == "Patient" else st.radio("Menu", ["🖥️ Desk", "📜 Logs"])
 
-# --- 6. AI CHAT (FIXED PDF REFERENCE & DOWNLOAD) ---
-if nav in [chat_nav, "💬 AI Chat", "💬 اے آئی چیٹ"]:
-    st.markdown(f"### {chat_nav}")
-    
-    if st.session_state.active_doc:
-        st.info("📂 Medical PDF Loaded. AI is analyzing your report." if lang == "English" else "📂 میڈیکل پی ڈی ایف لوڈ ہوگئی ہے۔ اے آئی تجزیہ کر رہا ہے۔")
-        # PDF Summary Downloader
-        st.download_button(
-            label="📄 Download Analysis Summary" if lang == "English" else "📄 خلاصہ ڈاؤن لوڈ کریں",
-            data=st.session_state.active_doc,
-            file_name="clinical_summary.txt",
-            mime="text/plain"
-        )
+# --- 6. CHAT MODULE (FIXED INPUT BAR & PDF TEXT) ---
+if nav == "💬 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")
+        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!")
+
+    # 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)
     
-    cv, cp, cq = st.columns([0.6, 0.6, 8.8])
-    with cv: v = st.audio_input("🎤", key=f"v_{len(st.session_state.msgs)}", label_visibility="collapsed")
-    with cp:
-        with st.popover("➕"):
-            up = st.file_uploader("Upload 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("Extracted!" if lang == "English" else "ڈیٹا حاصل کر لیا گیا!")
-                    st.rerun()
-    with cq: q = st.chat_input("Ask about your health..." if lang == "English" else "اپنی صحت کے بارے میں پوچھیں...")
+    # 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...")
 
     final_q = q if q else None
-    if v and not final_q:
+    if v and not final_q: # Voice-to-Text Logic
         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")
@@ -134,40 +116,18 @@ if nav in [chat_nav, "💬 AI Chat", "💬 اے آئی چیٹ"]:
 
     if final_q:
         st.session_state.msgs.append({"role": "user", "content": final_q})
-        # Strict Medical Prompt with explicit PDF reference
-        sys_p = f"You are the IntelliCare Medical Assistant. Language: {lang}. If PDF_CONTEXT is provided, explicitly state you are reading the user's report. Answer clinical 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"PDF_CONTEXT: {st.session_state.active_doc}"}] + st.session_state.msgs)
+        # 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)
         st.session_state.msgs.append({"role": "assistant", "content": ans.choices[0].message.content})
         st.rerun()
 
-# --- 7. ADDITIONAL TOOLS (MAPS, TOOLS, CALLS) ---
-elif nav in [tools_nav, "🧪 Health Tools", "🧪 صحت کے اوزار"]:
-    st.markdown(f"### {tools_nav}")
-    t = st.selectbox("Tool", ["⚖️ BMI Analyzer", "🩸 Glucose Tracker"])
-    if t == "⚖️ 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)
-        st.plotly_chart(go.Figure(go.Indicator(mode="gauge+number", value=bmi, gauge={'bar': {'color': "#3b82f6"}})))
-
-elif nav in [map_nav, "📍 Nearby Clinics", "📍 قریبی کلینک"]:
-    st.markdown(f"### {map_nav}")
+# --- 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":
     loc = streamlit_geolocation()
     if loc.get("latitude"):
-        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 in [call_nav, "📞 Video Consult", "📞 ویڈیو کال"]:
-    st.markdown(f"### {call_nav}")
-    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 Call"):
-        room = f"IntelliCare-{st.session_state.username}-{sel_doc}"
-        log_entry = pd.DataFrame([{"Time": datetime.now().strftime("%Y-%m-%d %H:%M"), "Caller": st.session_state.username, "Receiver": sel_doc, "RoomID": room}])
-        pd.concat([load_db(CALL_LOG_DB, ["Time", "Caller", "Receiver", "RoomID"]), log_entry]).to_csv(CALL_LOG_DB, index=False)
-        pd.DataFrame([{"Caller": st.session_state.username, "Receiver": sel_doc, "RoomID": room, "Status": "Active"}]).to_csv(CALL_SIGNAL_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)
+        st_folium(folium.Map(location=[loc["latitude"], loc["longitude"]], zoom_start=14), width=1000)
+elif nav == "📞 Video":
+    st.write("Specialist Call Section")