Upload app.py

app.py

@@ -0,0 +1,795 @@
+import streamlit as st
+
+# ─────────────────────────────────────────────
+# REGMAP — AI System ID Card
+# ─────────────────────────────────────────────
+
+st.set_page_config(
+    page_title="RegMap — AI System ID Card",
+    page_icon="◈",
+    layout="centered",
+)
+
+# ── Visual Identity ──
+st.markdown("""
+<style>
+    @import url('https://fonts.googleapis.com/css2?family=DM+Sans:ital,opsz,wght@0,9..40,100..1000;1,9..40,100..1000&display=swap');
+    @import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@400;500;600;700&display=swap');
+
+    html, body, [class*="css"] { font-family: 'DM Sans', sans-serif; }
+    .stApp { background-color: #F7F8FA; }
+
+    /* ── Dark text override for HF Spaces dark mode ──
+       Excludes .rmh (RegMap Header) elements */
+    .stApp p:not(.rmh-el), .stApp span:not(.rmh-el), .stApp label,
+    .stApp h1, .stApp h2, .stApp h3, .stApp h4,
+    .stApp li, .stApp strong:not(.rmh-el), .stApp em,
+    [data-testid="stMarkdownContainer"] p:not(.rmh-el),
+    [data-testid="stMarkdownContainer"] h4,
+    [data-testid="stMarkdownContainer"] strong:not(.rmh-el),
+    [data-testid="stMarkdownContainer"] li {
+        color: #1E293B !important;
+    }
+
+    /* ── Header ── */
+    .rmh {
+        background: linear-gradient(135deg, #0F2B46 0%, #143A5C 60%, #0F2B46 100%);
+        padding: 2rem 2.2rem 1.6rem 2.2rem;
+        border-radius: 14px;
+        margin-bottom: 1.8rem;
+        position: relative;
+        overflow: hidden;
+        border: 1px solid rgba(255,255,255,0.04);
+    }
+    .rmh::before {
+        content: '';
+        position: absolute;
+        top: -50%; right: -20%;
+        width: 60%; height: 200%;
+        background: radial-gradient(ellipse, rgba(13,148,136,0.15) 0%, transparent 70%);
+        pointer-events: none;
+    }
+    .rmh::after {
+        content: '';
+        position: absolute;
+        bottom: 0; left: 0;
+        width: 100%; height: 1px;
+        background: linear-gradient(90deg, transparent, rgba(45,212,191,0.3), transparent);
+    }
+    .rmh-logo {
+        font-family: 'Space Grotesk', sans-serif !important;
+        font-size: 1.7rem !important; font-weight: 700 !important;
+        letter-spacing: -0.02em !important;
+        color: #FFFFFF !important;
+        margin: 0 !important; position: relative; z-index: 1;
+        line-height: 1.2 !important;
+    }
+    .rmh-accent { color: #2DD4BF !important; }
+    .rmh-tagline {
+        font-family: 'DM Sans', sans-serif !important;
+        color: #8BA3BB !important;
+        font-size: 0.82rem !important;
+        font-weight: 400 !important;
+        letter-spacing: 0.03em !important;
+        margin: 0.35rem 0 0 0 !important;
+        position: relative; z-index: 1;
+    }
+    .rmh-badges {
+        display: flex; gap: 0.45rem;
+        margin-top: 0.9rem;
+        position: relative; z-index: 1;
+    }
+    .rmh-badge {
+        background: rgba(45,212,191,0.08) !important;
+        border: 1px solid rgba(45,212,191,0.2) !important;
+        border-radius: 5px !important;
+        padding: 0.18rem 0.55rem !important;
+        font-family: 'Space Grotesk', sans-serif !important;
+        font-size: 0.68rem !important;
+        font-weight: 600 !important;
+        color: #5EEAD4 !important;
+        letter-spacing: 0.06em !important;
+        text-transform: uppercase !important;
+    }
+
+    /* ── Progress ── */
+    .progress-container {
+        background: #E2E8F0; border-radius: 8px;
+        height: 5px; margin-bottom: 0.4rem;
+    }
+    .progress-fill {
+        background: linear-gradient(90deg, #0D9488, #2DD4BF);
+        height: 5px; border-radius: 8px;
+        transition: width 0.4s ease;
+    }
+    .progress-label {
+        color: #64748B !important; font-size: 0.78rem;
+        font-weight: 500; margin-bottom: 1.5rem;
+    }
+
+    /* ── Screen title ── */
+    .screen-title {
+        font-family: 'Space Grotesk', sans-serif;
+        color: #0F2B46 !important; font-size: 1.15rem;
+        font-weight: 700; letter-spacing: -0.01em;
+        margin-bottom: 0.2rem;
+    }
+    .screen-subtitle {
+        color: #64748B !important; font-size: 0.82rem;
+        font-weight: 400; margin-bottom: 1.5rem;
+        line-height: 1.4;
+    }
+
+    /* ── Buttons ── */
+    .stButton > button {
+        font-family: 'DM Sans', sans-serif;
+        font-weight: 600; font-size: 0.85rem;
+        border-radius: 8px; padding: 0.45rem 1.5rem;
+        color: #FFFFFF !important;
+    }
+
+    /* ── Summary cards ── */
+    .summary-section {
+        background: #F8FAFB;
+        border: 1px solid #E2E8F0;
+        border-left: 3px solid #0D9488;
+        border-radius: 8px;
+        padding: 1rem 1.3rem;
+        margin-bottom: 0.8rem;
+    }
+    .summary-section h4 {
+        color: #0F2B46 !important;
+        font-family: 'Space Grotesk', sans-serif;
+        font-size: 0.88rem; font-weight: 700;
+        margin: 0 0 0.5rem 0;
+    }
+    .summary-section p {
+        color: #334155 !important; font-size: 0.85rem;
+        margin: 0.15rem 0; line-height: 1.5;
+    }
+
+    /* ── Widget spacing ── */
+    .stSelectbox, .stMultiSelect, .stTextInput, .stTextArea { margin-bottom: 0.6rem; }
+
+    /* ── Widget labels (belt-and-suspenders) ── */
+    .stSelectbox label, .stMultiSelect label, .stTextInput label, .stTextArea label,
+    .stRadio label, .stCheckbox label, .stSlider label {
+        color: #1E293B !important;
+    }
+    .stSelectbox label p, .stMultiSelect label p, .stTextInput label p, .stTextArea label p,
+    .stRadio label p, .stCheckbox label p, .stSlider label p {
+        color: #1E293B !important;
+    }
+    .stRadio div[role="radiogroup"] label p,
+    .stRadio div[role="radiogroup"] label span,
+    .stRadio div[role="radiogroup"] label,
+    [data-testid="stRadio"] label p,
+    [data-testid="stRadio"] label span,
+    [data-testid="stRadio"] label,
+    [data-testid="stWidgetLabel"] p,
+    [data-testid="stWidgetLabel"] span {
+        color: #1E293B !important;
+    }
+    .stMarkdown h4, .stMarkdown p:not(.rmh-el), .stMarkdown strong:not(.rmh-el), .stMarkdown em,
+    .stMarkdown li, .stMarkdown span:not(.rmh-el),
+    [data-testid="stMarkdownContainer"] span:not(.rmh-el) {
+        color: #1E293B !important;
+    }
+    .stAlert p, .stAlert span,
+    [data-testid="stAlert"] p,
+    [data-testid="stAlert"] span {
+        color: #1E293B !important;
+    }
+    [data-testid="stCaptionContainer"] p,
+    [data-testid="stCaptionContainer"] span {
+        color: #64748B !important;
+    }
+
+    /* ── Beta disclaimer ── */
+    .beta-disclaimer {
+        background: #FEF3C7;
+        border: 1px solid #F59E0B;
+        border-radius: 8px;
+        padding: 0.8rem 1rem;
+        margin-bottom: 1rem;
+        color: #92400E !important;
+        font-size: 0.82rem;
+        line-height: 1.5;
+    }
+    .beta-disclaimer strong { color: #92400E !important; }
+
+    /* ── Hide branding ── */
+    #MainMenu {visibility: hidden;}
+    footer {visibility: hidden;}
+    header {visibility: hidden;}
+</style>
+""", unsafe_allow_html=True)
+
+
+# ── Reference Data ──
+
+INDUSTRY_SECTORS = [
+    "Agriculture & Food", "Automotive & Transportation",
+    "Banking & Financial Services", "Construction & Real Estate",
+    "Consulting & Professional Services", "Defence & Security",
+    "Education & Training", "Energy & Utilities",
+    "Entertainment & Media", "Environmental Services",
+    "Government & Public Administration", "Healthcare & Life Sciences",
+    "Hospitality & Tourism", "Human Resources & Recruitment",
+    "Insurance", "Legal Services", "Logistics & Supply Chain",
+    "Manufacturing", "Mining & Natural Resources", "Non-Profit & NGO",
+    "Pharmaceuticals", "Retail & E-commerce", "Telecommunications",
+    "Technology & Software", "Other",
+]
+
+US_STATES = [
+    "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado",
+    "Connecticut", "Delaware", "Florida", "Georgia", "Hawaii", "Idaho",
+    "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky", "Louisiana",
+    "Maine", "Maryland", "Massachusetts", "Michigan", "Minnesota",
+    "Mississippi", "Missouri", "Montana", "Nebraska", "Nevada",
+    "New Hampshire", "New Jersey", "New Mexico", "New York",
+    "North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon",
+    "Pennsylvania", "Rhode Island", "South Carolina", "South Dakota",
+    "Tennessee", "Texas", "Utah", "Vermont", "Virginia", "Washington",
+    "West Virginia", "Wisconsin", "Wyoming", "District of Columbia",
+]
+
+# States with specific AI regulation (for downstream analysis)
+US_STATES_WITH_AI_REGULATION = [
+    "California", "Colorado", "Connecticut", "Illinois", "Texas", "Utah",
+]
+
+EU_COUNTRIES = [
+    "Austria", "Belgium", "Bulgaria", "Croatia", "Cyprus", "Czechia",
+    "Denmark", "Estonia", "Finland", "France", "Germany", "Greece",
+    "Hungary", "Ireland", "Italy", "Latvia", "Lithuania", "Luxembourg",
+    "Malta", "Netherlands", "Poland", "Portugal", "Romania", "Slovakia",
+    "Slovenia", "Spain", "Sweden",
+    "Iceland (EEA)", "Liechtenstein (EEA)", "Norway (EEA)",
+]
+
+UAE_EMIRATES = [
+    "Dubai", "Abu Dhabi", "Sharjah", "Ajman",
+    "Fujairah", "Ras Al Khaimah", "Umm Al Quwain",
+]
+
+UAE_FREE_ZONES = {
+    "Dubai": ["DIFC", "DMCC", "JAFZA", "Dubai Internet City",
+        "Dubai Media City", "Dubai Silicon Oasis", "Dubai Healthcare City",
+        "Dubai Design District (d3)", "Dubai South", "Dubai Knowledge Park",
+        "DAFZA", "Dubai World Trade Centre", "Dubai Science Park",
+        "Dubai Textile City", "DUCAMZ", "Dubai Maritime City",
+        "Meydan Free Zone", "IFZA"],
+    "Abu Dhabi": ["ADGM", "KIZAD", "Masdar City", "ADAFZ",
+        "Khalifa Port Free Trade Zone", "Twofour54"],
+    "Sharjah": ["Sharjah Media City (Shams)", "SAIF Zone",
+        "Sharjah Publishing City", "Hamriyah Free Zone"],
+    "Ras Al Khaimah": ["RAKEZ", "RAK Maritime City", "RAK Media City"],
+    "Ajman": ["Ajman Free Zone"],
+    "Fujairah": ["Fujairah Free Zone", "Fujairah Creative City"],
+    "Umm Al Quwain": ["UAQ Free Trade Zone"],
+}
+
+ROLES = [
+    "Provider — You develop or commission the AI system",
+    "Deployer — You use an AI system in your operations (you did not build it)",
+    "Authorised Representative (EU) — You act on behalf of a non-EU provider to fulfill EU AI Act obligations",
+    "Importer (EU) — You place on the EU market an AI system from a non-EU provider",
+    "Distributor (EU) — You make an AI system available on the EU market (neither provider nor importer)",
+]
+
+AI_TYPES = ["Machine Learning (ML)", "Generative AI (GenAI)", "Agentic AI", "Rule-based", "Hybrid"]
+
+DATA_TYPE_OPTIONS = [
+    "Personal data (name, email, ID)",
+    "Sensitive/special category data (health, race, religion, political, sexual orientation)",
+    "Biometric data",
+    "Children's data (<18)",
+    "Financial/credit data",
+    "Employment/HR data",
+    "Copyrighted content (text, images, audio, video)",
+    "Publicly available data only",
+    "No personal data",
+]
+
+TRAINING_SOURCES = ["Public web", "Licensed datasets", "Proprietary data", "User-generated content"]
+INVOLVEMENT_LEVELS = ["Fully automated", "Human-assisted", "Human decides"]
+
+ALL_COUNTRIES = [
+    "Afghanistan", "Albania", "Algeria", "Andorra", "Angola", "Argentina",
+    "Armenia", "Australia", "Austria", "Azerbaijan", "Bahrain", "Bangladesh",
+    "Belarus", "Belgium", "Bolivia", "Bosnia and Herzegovina", "Brazil",
+    "Brunei", "Bulgaria", "Cambodia", "Cameroon", "Canada", "Chile", "China",
+    "Colombia", "Costa Rica", "Croatia", "Cuba", "Cyprus", "Czechia",
+    "Denmark", "Dominican Republic", "Ecuador", "Egypt", "El Salvador",
+    "Estonia", "Ethiopia", "Finland", "France", "Georgia", "Germany",
+    "Ghana", "Greece", "Guatemala", "Honduras", "Hong Kong", "Hungary",
+    "Iceland", "India", "Indonesia", "Iran", "Iraq", "Ireland", "Israel",
+    "Italy", "Jamaica", "Japan", "Jordan", "Kazakhstan", "Kenya", "Kuwait",
+    "Latvia", "Lebanon", "Libya", "Liechtenstein", "Lithuania", "Luxembourg",
+    "Malaysia", "Malta", "Mexico", "Moldova", "Monaco", "Mongolia",
+    "Montenegro", "Morocco", "Mozambique", "Myanmar", "Nepal",
+    "Netherlands", "New Zealand", "Nicaragua", "Nigeria", "North Korea",
+    "North Macedonia", "Norway", "Oman", "Pakistan", "Panama",
+    "Paraguay", "Peru", "Philippines", "Poland", "Portugal", "Qatar",
+    "Romania", "Russia", "Rwanda", "Saudi Arabia", "Senegal", "Serbia",
+    "Singapore", "Slovakia", "Slovenia", "Somalia", "South Africa",
+    "South Korea", "Spain", "Sri Lanka", "Sudan", "Sweden", "Switzerland",
+    "Syria", "Taiwan", "Tanzania", "Thailand", "Tunisia", "Turkey",
+    "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom",
+    "United States", "Uruguay", "Uzbekistan", "Venezuela", "Vietnam",
+    "Yemen", "Zambia", "Zimbabwe",
+]
+
+
+# ── Session State ──
+
+TOTAL_SCREENS = 7
+
+if "screen" not in st.session_state:
+    st.session_state.screen = 1
+if "data" not in st.session_state:
+    st.session_state.data = {}
+
+
+def go_next():
+    if st.session_state.screen < TOTAL_SCREENS + 1:
+        st.session_state.screen += 1
+
+def go_back():
+    if st.session_state.screen > 1:
+        st.session_state.screen -= 1
+
+def go_to(n):
+    st.session_state.screen = n
+
+
+# ── Header ──
+st.markdown("""
+<div class="rmh">
+    <p class="rmh-logo rmh-el">Reg<span class="rmh-accent rmh-el">Map</span></p>
+    <p class="rmh-tagline rmh-el">Navigate AI regulation across jurisdictions</p>
+    <div class="rmh-badges">
+        <span class="rmh-badge rmh-el">EU</span>
+        <span class="rmh-badge rmh-el">US</span>
+        <span class="rmh-badge rmh-el">UAE</span>
+    </div>
+</div>
+""", unsafe_allow_html=True)
+
+# ── Progress ──
+current = st.session_state.screen
+progress_pct = min((current - 1) / TOTAL_SCREENS * 100, 100)
+screen_labels = {
+    1: "Screen 1/7 — AI System Identity",
+    2: "Screen 2/7 — Application Domain",
+    3: "Screen 3/7 — Company Location",
+    4: "Screen 4/7 — Geographic Scope",
+    5: "Screen 5/7 — Role in Value Chain",
+    6: "Screen 6/7 — Technology Profile",
+    7: "Screen 7/7 — Data Profile",
+    8: "Summary",
+}
+label = screen_labels.get(current, "")
+
+st.markdown(f"""
+<div class="progress-container"><div class="progress-fill" style="width:{progress_pct}%"></div></div>
+<div class="progress-label">{label}</div>
+""", unsafe_allow_html=True)
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 1: AI System Identity
+# ═══════════════════════════════════════════════
+
+if current == 1:
+    st.markdown('<p class="screen-title">AI System ID Card</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">Basic information about your AI system</p>', unsafe_allow_html=True)
+
+    st.markdown('<div class="beta-disclaimer"><strong>Beta version</strong> — This Space is public by default. We recommend not entering directly identifying data, especially in free text fields.</div>', unsafe_allow_html=True)
+
+    name = st.text_input(
+        "1.1 — AI system name",
+        value=st.session_state.data.get("name", ""),
+        placeholder="e.g. ResumeScreener, ChatAssist, FraudDetect",
+    )
+    description = st.text_area(
+        "1.2 — Brief description",
+        value=st.session_state.data.get("description", ""),
+        placeholder="Describe what your AI system does in 1-2 sentences",
+        height=100,
+    )
+
+    col1, col2 = st.columns([5, 1])
+    with col2:
+        if st.button("Next →", use_container_width=True, disabled=(not name.strip())):
+            st.session_state.data["name"] = name.strip()
+            st.session_state.data["description"] = description.strip()
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 2: Application Domain
+# ═══════════════════════════════════════════════
+
+elif current == 2:
+    st.markdown('<p class="screen-title">Application Domain</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">Select all that apply</p>', unsafe_allow_html=True)
+
+    prev_sector = st.session_state.data.get("sector", [])
+    sector = st.multiselect(
+        "2.1 — Primary industry sector(s)",
+        INDUSTRY_SECTORS,
+        default=[s for s in prev_sector if s in INDUSTRY_SECTORS],
+    )
+
+    col1, col2, col3 = st.columns([1, 3, 1])
+    with col1:
+        if st.button("← Back", use_container_width=True):
+            go_back()
+            st.rerun()
+    with col3:
+        if st.button("Next →", use_container_width=True, disabled=(not sector)):
+            st.session_state.data["sector"] = sector
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 3: Company Location
+# ═══════════════════════════════════════════════
+
+elif current == 3:
+    st.markdown('<p class="screen-title">Company Location</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">Where is your organization headquartered?</p>', unsafe_allow_html=True)
+
+    prev_base = st.session_state.data.get("company_base", None)
+    base_idx = ALL_COUNTRIES.index(prev_base) if prev_base in ALL_COUNTRIES else 0
+    company_base = st.selectbox(
+        "3.1 — Country where your company is legally established",
+        ALL_COUNTRIES,
+        index=base_idx,
+        key="q_company_base",
+    )
+
+    col1, col2, col3 = st.columns([1, 3, 1])
+    with col1:
+        if st.button("← Back", use_container_width=True):
+            go_back()
+            st.rerun()
+    with col3:
+        if st.button("Next →", use_container_width=True):
+            st.session_state.data["company_base"] = company_base
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 4: Geographic Scope
+# ═══════════════════════════════════════════════
+
+elif current == 4:
+    st.markdown('<p class="screen-title">Geographic Scope</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">Select all that apply for each category</p>', unsafe_allow_html=True)
+
+    # 4.1 — Where the AI system operates
+    prev_ops = st.session_state.data.get("countries_operating", [])
+    countries_operating = st.multiselect(
+        "4.1 — Countries where the AI system operates",
+        ALL_COUNTRIES,
+        default=[c for c in prev_ops if c in ALL_COUNTRIES],
+        key="q_countries_operating",
+    )
+
+    # 4.2 — Where the AI system is distributed / made available
+    prev_dist = st.session_state.data.get("countries_distributed", [])
+    countries_distributed = st.multiselect(
+        "4.2 — Countries where the AI system is distributed or made available",
+        ALL_COUNTRIES,
+        default=[c for c in prev_dist if c in ALL_COUNTRIES],
+        key="q_countries_distributed",
+    )
+
+    # 4.3 — Where end users are located
+    prev_users = st.session_state.data.get("countries_end_users", [])
+    countries_end_users = st.multiselect(
+        "4.3 — Countries where end users are located",
+        ALL_COUNTRIES,
+        default=[c for c in prev_users if c in ALL_COUNTRIES],
+        key="q_countries_end_users",
+    )
+
+    # Combine all countries for detection
+    all_selected = list(set(countries_operating + countries_distributed + countries_end_users))
+
+    EU_COUNTRY_NAMES_CLEAN = [c.replace(" (EEA)", "") for c in EU_COUNTRIES]
+    selected_eu = [c for c in all_selected if c in EU_COUNTRY_NAMES_CLEAN or c in ["Iceland", "Liechtenstein", "Norway"]]
+    has_us = "United States" in all_selected
+    has_uae = "United Arab Emirates" in all_selected
+
+    # 4.4 — US states (if US in any dimension)
+    us_states = []
+    if has_us:
+        prev_states = st.session_state.data.get("us_states", [])
+        us_states = st.multiselect(
+            "4.4 — United States: which states?",
+            US_STATES,
+            default=[s for s in prev_states if s in US_STATES],
+            key="q_us_states",
+        )
+
+    # 4.5 — UAE emirates (if UAE in any dimension)
+    uae_emirates = []
+    if has_uae:
+        prev_emirates = st.session_state.data.get("uae_emirates", [])
+        uae_emirates = st.multiselect(
+            "4.5 — UAE: which emirates?",
+            UAE_EMIRATES,
+            default=[e for e in prev_emirates if e in UAE_EMIRATES],
+            key="q_uae_emirates",
+        )
+
+    # Validation — at least one country across any dimension
+    has_any_country = len(all_selected) > 0
+    can_proceed = has_any_country
+    if has_us and not us_states:
+        can_proceed = False
+    if has_uae and not uae_emirates:
+        can_proceed = False
+
+    col1, col2, col3 = st.columns([1, 3, 1])
+    with col1:
+        if st.button("← Back", use_container_width=True):
+            go_back()
+            st.rerun()
+    with col3:
+        if st.button("Next →", use_container_width=True, disabled=(not can_proceed)):
+            st.session_state.data["countries_operating"] = countries_operating
+            st.session_state.data["countries_distributed"] = countries_distributed
+            st.session_state.data["countries_end_users"] = countries_end_users
+            st.session_state.data["operating_countries"] = all_selected
+            st.session_state.data["us_states"] = us_states if has_us else []
+            st.session_state.data["us_states_with_regulation"] = [s for s in us_states if s in US_STATES_WITH_AI_REGULATION] if has_us else []
+            st.session_state.data["eu_countries"] = selected_eu
+            st.session_state.data["uae_emirates"] = uae_emirates if has_uae else []
+            regions = []
+            if has_us:
+                regions.append("United States")
+            if selected_eu:
+                regions.append("Europe")
+            if has_uae:
+                regions.append("UAE")
+            st.session_state.data["regions"] = regions
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 5: Role in Value Chain
+# ═══════════════════════════════════════════════
+
+elif current == 5:
+    st.markdown('<p class="screen-title">Role in Value Chain</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">What is your current role?</p>', unsafe_allow_html=True)
+
+    prev_roles = st.session_state.data.get("roles", [])
+    roles = st.multiselect(
+        "5.1 — Your organization's role (select all that apply)",
+        ROLES,
+        default=[r for r in prev_roles if r in ROLES],
+        key="q_roles",
+    )
+
+    col1, col2, col3 = st.columns([1, 3, 1])
+    with col1:
+        if st.button("← Back", use_container_width=True):
+            go_back()
+            st.rerun()
+    with col3:
+        if st.button("Next →", use_container_width=True, disabled=(not roles)):
+            st.session_state.data["roles"] = roles
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 6: Technology Profile
+# ═══════════════════════════════════════════════
+
+elif current == 6:
+    st.markdown('<p class="screen-title">Technology Profile</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">Describe your AI system\'s capabilities</p>', unsafe_allow_html=True)
+
+    # 6.1 AI type
+    prev_type = st.session_state.data.get("ai_type", AI_TYPES[0])
+    type_idx = AI_TYPES.index(prev_type) if prev_type in AI_TYPES else 0
+    ai_type = st.selectbox("6.1 — AI system type", AI_TYPES, index=type_idx, key="q_ai_type")
+
+    # 6.2 Model type
+    MODEL_TYPES = [
+        "Foundation model — general-purpose, trained on broad data (e.g. GPT, Claude, Llama)",
+        "Fine-tuned model — adapted from a foundation model for specific tasks",
+        "Task-specific model — built and trained for a single purpose",
+    ]
+    prev_model = st.session_state.data.get("model_type", MODEL_TYPES[2])
+    model_idx = MODEL_TYPES.index(prev_model) if prev_model in MODEL_TYPES else 2
+    model_type = st.selectbox("6.2 — How would you describe your AI model?", MODEL_TYPES, index=model_idx, key="q_model_type")
+
+    # 6.3 Capabilities
+    CAPABILITY_OPTIONS = [
+        "Interacts directly with end users",
+        "Makes or supports decisions that affect individuals",
+        "Profiles individuals (builds user profiles based on behavior, preferences, or characteristics)",
+        "Generates synthetic content (text, images, audio, video, code)",
+        "Performs emotion recognition",
+    ]
+    prev_caps = st.session_state.data.get("capabilities", [])
+    capabilities = st.multiselect(
+        "6.3 — What does your AI system do? (select all that apply)",
+        CAPABILITY_OPTIONS,
+        default=[c for c in prev_caps if c in CAPABILITY_OPTIONS],
+        key="q_capabilities",
+    )
+
+    # 6.4 Human involvement — always shown
+    prev_involvement = st.session_state.data.get("human_involvement", "N/A")
+    INVOLVEMENT_WITH_NA = ["N/A — no decisions affecting individuals", "Fully automated", "Human-assisted", "Human decides"]
+    if prev_involvement in INVOLVEMENT_LEVELS:
+        inv_idx = INVOLVEMENT_WITH_NA.index(prev_involvement)
+    else:
+        inv_idx = 0
+    human_involvement = st.selectbox(
+        "6.4 — Level of human involvement in decisions (if applicable)",
+        INVOLVEMENT_WITH_NA,
+        index=inv_idx,
+        key="q_involvement",
+    )
+
+    # 6.5 Synthetic content types — always shown
+    SYNTHETIC_TYPES = ["Text", "Images", "Audio", "Video", "Code"]
+    prev_content = st.session_state.data.get("synthetic_content", [])
+    synthetic_content = st.multiselect(
+        "6.5 — Types of synthetic content generated (if applicable, select all that apply)",
+        SYNTHETIC_TYPES,
+        default=[s for s in prev_content if s in SYNTHETIC_TYPES],
+        key="q_content",
+    )
+
+    col1, col2, col3 = st.columns([1, 3, 1])
+    with col1:
+        if st.button("← Back", use_container_width=True):
+            go_back()
+            st.rerun()
+    with col3:
+        if st.button("Next →", use_container_width=True):
+            st.session_state.data["ai_type"] = ai_type
+            st.session_state.data["model_type"] = model_type
+            st.session_state.data["gpai"] = model_type.startswith("Foundation model")
+            st.session_state.data["capabilities"] = capabilities
+            st.session_state.data["direct_interaction"] = "Interacts directly with end users" in capabilities
+            st.session_state.data["decision_making"] = "Makes or supports decisions that affect individuals" in capabilities
+            st.session_state.data["profiling"] = "Profiles individuals (builds user profiles based on behavior, preferences, or characteristics)" in capabilities
+            is_decision = "Makes or supports decisions that affect individuals" in capabilities
+            st.session_state.data["human_involvement"] = human_involvement if is_decision and not human_involvement.startswith("N/A") else "N/A"
+            is_synthetic = "Generates synthetic content (text, images, audio, video, code)" in capabilities
+            st.session_state.data["synthetic_content"] = synthetic_content if is_synthetic else []
+            st.session_state.data["emotion_recognition"] = "Performs emotion recognition" in capabilities
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 7: Data Profile
+# ═══════════════════════════════════════════════
+
+elif current == 7:
+    st.markdown('<p class="screen-title">Data Profile</p>', unsafe_allow_html=True)
+    st.markdown('<p class="screen-subtitle">What data does your system process and where does it come from?</p>', unsafe_allow_html=True)
+
+    prev_data_types = st.session_state.data.get("data_types", [])
+    selected_data_types = st.multiselect(
+        "7.1 — What data types does your AI system process? (select all that apply)",
+        DATA_TYPE_OPTIONS,
+        default=[dt for dt in prev_data_types if dt in DATA_TYPE_OPTIONS],
+    )
+
+    st.divider()
+
+    prev_sources = st.session_state.data.get("training_sources", [])
+    training_sources = st.multiselect(
+        "7.2 — Training data sources (select all that apply)",
+        TRAINING_SOURCES,
+        default=[s for s in prev_sources if s in TRAINING_SOURCES],
+    )
+
+    col1, col2, col3 = st.columns([1, 3, 1])
+    with col1:
+        if st.button("← Back", use_container_width=True):
+            go_back()
+            st.rerun()
+    with col3:
+        if st.button("View Summary →", use_container_width=True, disabled=(not selected_data_types)):
+            st.session_state.data["data_types"] = selected_data_types
+            st.session_state.data["training_sources"] = training_sources
+            go_next()
+            st.rerun()
+
+
+# ═══════════════════════════════════════════════
+# SCREEN 8: Summary
+# ═══════════════════════════════════════════════
+
+elif current == 8:
+    d = st.session_state.data
+
+    st.markdown('<p class="screen-title">AI System ID Card — Summary</p>', unsafe_allow_html=True)
+    st.markdown(f'<p class="screen-subtitle">Review your inputs for <strong>{d.get("name", "")}</strong></p>', unsafe_allow_html=True)
+
+    # Identity
+    st.markdown(f'<div class="summary-section"><h4>AI System Identity</h4><p><strong>Name:</strong> {d.get("name", "—")}</p><p><strong>Description:</strong> {d.get("description", "—") or "—"}</p></div>', unsafe_allow_html=True)
+
+    # Domain
+    sectors = d.get("sector", [])
+    sectors_display = ", ".join(sectors) if sectors else "—"
+    st.markdown(f'<div class="summary-section"><h4>Application Domain</h4><p><strong>Sector(s):</strong> {sectors_display}</p></div>', unsafe_allow_html=True)
+
+    # Geography
+    geo_lines = f'<p><strong>Company base:</strong> {d.get("company_base", "—")}</p>'
+    ops = d.get("countries_operating", [])
+    dist = d.get("countries_distributed", [])
+    users = d.get("countries_end_users", [])
+    if ops:
+        geo_lines += f'<p><strong>Operates in:</strong> {", ".join(ops)}</p>'
+    if dist:
+        geo_lines += f'<p><strong>Distributed in:</strong> {", ".join(dist)}</p>'
+    if users:
+        geo_lines += f'<p><strong>End users in:</strong> {", ".join(users)}</p>'
+    if d.get("us_states"):
+        regulated = d.get("us_states_with_regulation", [])
+        non_regulated = [s for s in d["us_states"] if s not in regulated]
+        geo_lines += f'<p><strong>US states:</strong> {", ".join(d["us_states"])}</p>'
+        if regulated:
+            geo_lines += f'<p><strong>States with AI regulation:</strong> {", ".join(regulated)}</p>'
+        if non_regulated:
+            geo_lines += f'<p><strong>States without specific AI regulation:</strong> {", ".join(non_regulated)}</p>'
+    if d.get("eu_countries"):
+        geo_lines += f'<p><strong>EU/EEA countries detected:</strong> {", ".join(d["eu_countries"])}</p>'
+    if d.get("uae_emirates"):
+        geo_lines += f'<p><strong>UAE emirates:</strong> {", ".join(d["uae_emirates"])}</p>'
+    st.markdown(f'<div class="summary-section"><h4>Geographic Scope</h4>{geo_lines}</div>', unsafe_allow_html=True)
+
+    # Roles
+    roles_display = ", ".join(d.get("roles", ["—"]))
+    st.markdown(f'<div class="summary-section"><h4>Role in Value Chain</h4><p>{roles_display}</p></div>', unsafe_allow_html=True)
+
+    # Technology
+    model_type_display = d.get("model_type", "—")
+    caps = d.get("capabilities", [])
+    caps_display = ", ".join(caps) if caps else "None selected"
+    synthetic = ", ".join(d.get("synthetic_content", [])) or "None"
+    involvement = d.get("human_involvement", "N/A")
+
+    tech_lines = f'<p><strong>AI type:</strong> {d.get("ai_type", "—")}</p>'
+    tech_lines += f'<p><strong>Model:</strong> {model_type_display}</p>'
+    tech_lines += f'<p><strong>Capabilities:</strong> {caps_display}</p>'
+    if d.get("decision_making"):
+        tech_lines += f'<p><strong>Human involvement in decisions:</strong> {involvement}</p>'
+    if d.get("synthetic_content"):
+        tech_lines += f'<p><strong>Synthetic content types:</strong> {synthetic}</p>'
+    st.markdown(f'<div class="summary-section"><h4>Technology Profile</h4>{tech_lines}</div>', unsafe_allow_html=True)
+
+    # Data
+    data_types_display = ", ".join(d.get("data_types", ["—"]))
+    sources_display = ", ".join(d.get("training_sources", ["—"]))
+    st.markdown(f'<div class="summary-section"><h4>Data Profile</h4><p><strong>Data types:</strong> {data_types_display}</p><p><strong>Training sources:</strong> {sources_display}</p></div>', unsafe_allow_html=True)
+
+    # Navigation
+    col1, col2, col3 = st.columns([1, 2, 2])
+    with col1:
+        if st.button("← Edit", use_container_width=True):
+            go_to(1)
+            st.rerun()
+    with col3:
+        st.info("Regulation analysis coming in next version")