Update app.py

app.py

@@ -1,160 +1,212 @@
 import streamlit as st
 import pandas as pd
+import numpy as np
 import os
 import hashlib
+import requests
+from datetime import datetime
+from fpdf import FPDF
+import plotly.graph_objects as go
+import google.generativeai as genai
+import folium
+from streamlit_folium import st_folium
+from streamlit_geolocation import streamlit_geolocation
 from groq import Groq
 import pdfplumber
 
-# --- 1. CONFIGURATION ---
+# --- 1. CORE SYSTEM CONFIG ---
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-if not GROQ_API_KEY:
-    st.error("⚠️ API Key Missing! Please add it to your environment variables.")
+GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
+
+if not GROQ_API_KEY or not GOOGLE_API_KEY:
+    st.error("⚠️ API Keys Missing! Please set them in Space Secrets.")
+    st.stop()
+
+st.set_page_config(page_title="IntelliCare Portal | Hassan Naseer", layout="wide", page_icon="🏥")
+
+# --- 2. THEME & PDF GENERATOR ---
+if "theme" not in st.session_state: st.session_state.theme = "Light"
+
+def generate_medical_pdf(chat_history, username):
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", 'B', 16)
+    pdf.cell(200, 10, txt="IntelliCare Portal - Clinical Summary", ln=True, align='C')
+    pdf.set_font("Arial", size=10)
+    pdf.cell(200, 10, txt=f"Patient: {username} | Date: {datetime.now().strftime('%Y-%m-%d %H:%M')}", ln=True, align='C')
+    pdf.ln(10)
+    for msg in chat_history:
+        role = "PATIENT" if msg["role"] == "user" else "CLINICAL AI"
+        pdf.set_font("Arial", 'B', 10); pdf.cell(0, 10, txt=f"{role}:", ln=True)
+        pdf.set_font("Arial", size=10); pdf.multi_cell(0, 8, txt=msg["content"]); pdf.ln(4)
+    return pdf.output(dest='S').encode('latin-1')
+
+def inject_theme():
+    bg = "#000000" if st.session_state.theme == "Dark" else "#FFFFFF"
+    txt = "#FFFFFF" if st.session_state.theme == "Dark" else "#000000"
+    card = "#111111" if st.session_state.theme == "Dark" else "#F0F2F6"
+    brd = "#FFFFFF" if st.session_state.theme == "Dark" else "#000000"
+    st.markdown(f"""<style>
+    .stApp {{ background-color: {bg} !important; color: {txt} !important; }}
+    .chat-bubble {{ padding: 15px; border-radius: 15px; margin-bottom: 10px; border: 1px solid {brd}; }}
+    .user-msg {{ background-color: rgba(59, 130, 246, 0.1); border-left: 5px solid #3b82f6; }}
+    .ai-msg {{ background-color: rgba(16, 185, 129, 0.1); border-left: 5px solid #10b981; }}
+    .clinical-card {{ background-color: {card}; border: 2px solid {brd}; padding: 25px; border-radius: 15px; color: {txt}; }}
+    </style>""", unsafe_allow_html=True)
+
+inject_theme()
+
+# --- 3. DATA PERSISTENCE ---
+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 get_vector_db():
+    import chromadb
+    from chromadb.utils import embedding_functions
+    client = chromadb.PersistentClient(path="./med_vector_db")
+    emb_fn = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="paraphrase-MiniLM-L3-v2")
+    main = client.get_or_create_collection(name="intellicare_vFinal", embedding_function=emb_fn)
+    signal = client.get_or_create_collection(name="signals_targeted", embedding_function=emb_fn)
+    return main, signal
+
+# --- 4. AUTHENTICATION & SESSION ---
+if "logged_in" not in st.session_state: st.session_state.logged_in = False
+if "last_processed_audio" not in st.session_state: st.session_state.last_processed_audio = None
+if "active_doc_text" not in st.session_state: st.session_state.active_doc_text = None
+if "active_doc_name" not in st.session_state: st.session_state.active_doc_name = None
+
+if not st.session_state.logged_in:
+    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", "📝 Create Account"])
+        with t1:
+            u, p = st.text_input("Username", key="l_u"), st.text_input("Password", type="password", key="l_p")
+            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, st.session_state.msgs = match.iloc[0]['role'], []
+                    st.rerun()
     st.stop()
 
-# --- 2. THE DESIGN ENGINE (Fixed Frame & Static UI) ---
-def inject_assistant_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. LOCK THE MAIN FRAME */
-    .main { overflow: hidden; height: 100vh; }
-
-    /* 2. GRADIENT SIDEBAR (STATIC) */
-    [data-testid="stSidebar"] {
-        background: linear-gradient(180deg, #0f172a 0%, #1e3a8a 100%);
-        border-right: 1px solid rgba(255,255,255,0.1);
-    }
-    [data-testid="stSidebar"] * { color: #f8fafc !important; }
-
-    /* 3. SCROLLABLE CHAT DASHBOARD */
-    .chat-scroll-area {
-        height: 62vh;
-        overflow-y: auto;
-        padding: 25px;
-        background: #f8fafc;
-        border-radius: 20px;
-        border: 1px solid #e2e8f0;
-        margin-bottom: 20px;
-        display: flex;
-        flex-direction: column;
-    }
-
-    /* 4. PREMIUM BUBBLES */
-    .user-msg {
-        background: #3b82f6; color: white; padding: 15px 20px;
-        border-radius: 20px 20px 0 20px; align-self: flex-end;
-        margin-bottom: 15px; max-width: 75%; box-shadow: 0 4px 10px rgba(59,130,246,0.1);
-    }
-    .ai-msg {
-        background: #ffffff; color: #1e293b; padding: 15px 20px;
-        border-radius: 20px 20px 20px 0; align-self: flex-start;
-        margin-bottom: 15px; max-width: 75%; border: 1px solid #e2e8f0;
-        position: relative;
-    }
-
-    /* 5. FIXED BOTTOM PROMPT BOX (THE GEMINI BAR) */
-    div[data-testid="stChatInput"] {
-        position: fixed !important;
-        bottom: 35px !important;
-        width: 65% !important;
-        left: 20% !important;
-        z-index: 1000 !important;
-        border-radius: 30px !important;
-        border: 2px solid #3b82f6 !important;
-        background: white !important;
-        box-shadow: 0 4px 20px rgba(0,0,0,0.05) !important;
-    }
-
-    /* 6. SPEAKER ICON */
-    .voice-btn {
-        background: none; border: none; cursor: pointer;
-        font-size: 1.2rem; float: right; margin-left: 10px;
-    }
-    </style>
-
-    <script>
-    function speak(text) {
-        window.speechSynthesis.cancel();
-        const msg = new SpeechSynthesisUtterance(text);
-        window.speechSynthesis.speak(msg);
-    }
-    </script>
-    """, unsafe_allow_html=True)
-
-inject_assistant_design()
-
-# --- 3. SESSION STATE ---
-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 ---
+# --- 5. NAVIGATION ---
 with st.sidebar:
-    st.markdown(f"### 👤 {st.session_state.get('username', 'Hassan')}")
+    st.markdown(f"### 👤 {st.session_state.username}")
+    if st.button("Logout"): st.session_state.logged_in = False; st.rerun()
     st.divider()
-    st.markdown("### AI Assistant Settings")
-    if st.button("🗑️ Clear Chat History"):
-        st.session_state.msgs = []
-        st.rerun()
+    nav = st.radio("Menu", ["💬 AI Chat", "🧪 Health Lab", "📍 Nearby Hospitals", "📞 Video Call", "📜 History"]) if st.session_state.role == "Patient" else st.radio("Menu", ["🖥️ Consultation Desk", "📋 Patient Records"])
 
-# --- 5. THE ASSISTANT INTERFACE ---
-st.markdown("### 💬 Clinical Intelligence Assistant")
-
-# Only this part scrolls
-st.markdown('<div class="chat-scroll-area">', unsafe_allow_html=True)
-if not st.session_state.msgs:
-    st.markdown('<div class="ai-msg">Hello. I am your clinical assistant. How can I help you today?</div>', unsafe_allow_html=True)
-
-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)
-
-# THE UNIFIED INPUT SUITE (Plus + Text + Mic)
-# These are kept outside the sidebar for the wide look
-st.divider()
-p1, p2, p3 = st.columns([1, 8, 1])
-
-with p1:
-    with st.popover("➕"):
-        up = st.file_uploader("Upload Medical PDF", type=['pdf'])
-        if up:
-            with pdfplumber.open(up) as f:
-                st.session_state.active_doc = " ".join([page.extract_text() for page in f.pages])
-                st.success("Document analyzed successfully.")
-
-with p2:
-    q = st.chat_input("Ask a medical question...")
-
-with p3:
-    v = st.audio_input("🎤", label_visibility="collapsed")
-
-# --- 6. AI RESPONSE ENGINE ---
-final_q = q if q else (v if v else None)
-
-if final_q:
-    # Handle Audio to Text conversion
-    if hasattr(final_q, 'getvalue'):
-        with st.spinner("Transcribing voice..."):
-            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})
+# --- 6. UNIFIED AI CHAT (DUAL-MODE) ---
+if st.session_state.role == "Patient" and nav == "💬 AI Chat":
+    st.markdown('<div class="clinical-card"><h3>💬 Medical Intelligence Assistant</h3></div>', unsafe_allow_html=True)
     
-    # Process with Groq
-    with st.spinner("AI is thinking..."):
-        sys_p = "You are a clinical assistant. Use general medical knowledge or provided PDF context. Strictly refuse non-medical chat."
-        ctx = f"PDF CONTEXT: {st.session_state.active_doc}" if st.session_state.active_doc else "No PDF context."
+    if st.session_state.active_doc_text:
+        c1, c2 = st.columns([8, 2])
+        with c1: st.success(f"📂 **Active Document:** {st.session_state.active_doc_name}")
+        with c2: 
+            if st.button("🗑️ Clear"):
+                st.session_state.active_doc_text = None
+                st.session_state.active_doc_name = None
+                st.rerun()
+
+    for m in st.session_state.msgs:
+        bubble = "user-msg" if m["role"] == "user" else "ai-msg"
+        st.markdown(f'<div class="chat-bubble {bubble}">{m["content"]}</div>', unsafe_allow_html=True)
+
+    st.divider()
+    in1, in2, in3 = st.columns([0.6, 0.6, 8])
+    with in1: v = st.audio_input("🎤", label_visibility="collapsed", key=f"v_{len(st.session_state.msgs)}")
+    with in2:
+        with st.popover("➕"):
+            up_pdf = st.file_uploader("Upload PDF Document", type=['pdf'], key="doc_up")
+    with in3: q = st.chat_input("Ask a medical query or about your document...")
+
+    final_q = None
+    if up_pdf and st.session_state.active_doc_name != up_pdf.name:
+        with pdfplumber.open(up_pdf) as f:
+            st.session_state.active_doc_text = " ".join([p.extract_text() for p in f.pages if p.extract_text()])
+            st.session_state.active_doc_name = up_pdf.name
+            final_q = f"I have uploaded '{up_pdf.name}'. Analyze and explain what is written in this document in detail."
+    elif q: final_q = q
+    elif v:
+        v_hash = hashlib.md5(v.getvalue()).hexdigest()
+        if v_hash != st.session_state.last_processed_audio:
+            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_processed_audio = v_hash
+
+    if final_q:
+        st.session_state.msgs.append({"role": "user", "content": final_q})
+        sys_p = (
+            "You are the IntelliCare Medical System. "
+            "RULE 1 (DOCUMENTS): If document context is provided, analyze and explain it fully. "
+            "RULE 2 (TEXT CHAT): For text queries, be a strict Medical Specialist. "
+            "If asked for Python, essays, or non-medical info, refuse and state you only provide medical assistance."
+        )
+        main_col, _ = get_vector_db()
+        res = main_col.query(query_texts=[final_q], n_results=1)
+        db_ctx = res['documents'][0][0] if (res.get('documents') and len(res['documents'][0]) > 0) else "N/A"
+        full_ctx = f"DOC: {st.session_state.active_doc_text}\nDB: {db_ctx}"
         
         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
+            model="llama-3.3-70b-versatile", 
+            messages=[{"role": "system", "content": sys_p}, {"role": "system", "content": f"CTX: {full_ctx}"}] + st.session_state.msgs
         )
         st.session_state.msgs.append({"role": "assistant", "content": ans.choices[0].message.content})
+        st.rerun()
+
+# --- 7. HEALTH LAB TOOL LIBRARY ---
+elif nav == "🧪 Health Lab":
+    st.markdown('<div class="clinical-card"><h3>🧪 Clinical Tool Library</h3></div>', unsafe_allow_html=True)
+    tool = st.selectbox("🛠️ Choose Tool", ["Select Tool", "⚖️ BMI Calculator", "🩸 Sugar Tracker", "🫀 Heart Rate"])
     
-    st.rerun()
+    if tool == "⚖️ BMI Calculator":
+        
+        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={'axis': {'range': [10, 40]}, 'bar': {'color': "#10b981"}})), use_container_width=True)
+
+    elif tool == "🩸 Sugar Tracker":
+        
+        sugar = st.number_input("Level (mg/dL)", 50, 500, 100)
+        st.area_chart(pd.DataFrame(np.random.randn(24, 1).cumsum() + 100), color="#ff9800")
+
+    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) + 0.5 * np.sin(4 * np.pi * (hr/60) * t)
+        st.plotly_chart(go.Figure(data=go.Scatter(y=y, mode='lines', line=dict(color='#ff4b4b'))), use_container_width=True)
+
+# --- 8. MAPS & VIDEO ---
+elif nav == "📍 Nearby Hospitals":
+    loc = streamlit_geolocation()
+    if loc and loc.get("latitude"):
+        lat, lon = loc["latitude"], loc["longitude"]
+        m = folium.Map(location=[lat, lon], zoom_start=14)
+        st_folium(m, width=1200, height=500)
+
+elif nav == "📞 Video Call":
+    docs = load_db(USER_DB, ["username", "role"])
+    sel = st.selectbox("Specialist", docs[docs['role'] == 'Doctor']['username'].tolist())
+    if st.button("Start Call"):
+        room = f"IntelliCare-{st.session_state.username}-{sel}"
+        _, signal_col = get_vector_db()
+        signal_col.upsert(documents=[f"CALL|{sel}|{room}|{st.session_state.username}"], ids=["latest"])
+        st.session_state.active_room = room
+    if "active_room" in st.session_state:
+        st.components.v1.html(f'<iframe src="https://meet.jit.si/{st.session_state.active_room}" width="100%" height="550px"></iframe>', height=600)
+
+elif nav == "🖥️ Consultation Desk":
+    _, signal_col = get_vector_db()
+    res = signal_col.get(ids=["latest"])
+    if res.get('documents'):
+        parts = res['documents'][0].split("|")
+        if parts[1] == st.session_state.username:
+            if st.button("✅ Join Call"): st.session_state.active_call = parts[2]
+            if "active_call" in st.session_state:
+                st.components.v1.html(f'<iframe src="https://meet.jit.si/{parts[2]}" width="100%" height="650px"></iframe>', height=650)