feat: voice message distress analysis — paralinguistic features (#131)\n\nAnalyzes speech rate, pitch variability, silence ratio, vocal tremor, volume drops.\nComposite distress score with LOW/MEDIUM/HIGH classification.\nIntegrates with crisis_detector.py for multimodal coverage.\nCloses #131

Merge PR #126: fix: crisis overlay initial focus to enabled Call 988 link (#69)

crisis/__init__.py

@@ -7,6 +7,7 @@ Stands between a broken man and a machine that would tell him to die.
 from .detect import detect_crisis, CrisisDetectionResult, format_result, get_urgency_emoji
 from .response import process_message, generate_response, CrisisResponse
 from .gateway import check_crisis, get_system_prompt, format_gateway_response
+from .session_tracker import CrisisSessionTracker, SessionState, check_crisis_with_session
 
 __all__ = [
     "detect_crisis",
@@ -19,4 +20,7 @@ __all__ = [
     "format_result",
     "format_gateway_response",
     "get_urgency_emoji",
+    "CrisisSessionTracker",
+    "SessionState",
+    "check_crisis_with_session",
 ]

crisis/gateway.py

@@ -22,6 +22,7 @@ from .response import (
     get_system_prompt_modifier,
     CrisisResponse,
 )
+from .session_tracker import CrisisSessionTracker
 
 
 def check_crisis(text: str) -> dict:

crisis/session_tracker.py

@@ -0,0 +1,259 @@
+"""
+Session-level crisis tracking and escalation for the-door (P0 #35).
+
+Tracks crisis detection across messages within a single conversation,
+detecting escalation and de-escalation patterns. Privacy-first: no
+persistence beyond the conversation session.
+
+Each message is analyzed in isolation by detect.py, but this module
+maintains session state so the system can recognize patterns like:
+  - "I'm fine" → "I'm struggling" → "I can't go on"  (rapid escalation)
+  - "I want to die" → "I'm calmer now" → "feeling better"  (de-escalation)
+
+Usage:
+    from crisis.session_tracker import CrisisSessionTracker
+
+    tracker = CrisisSessionTracker()
+
+    # Feed each message's detection result
+    state = tracker.record(detect_crisis("I'm having a tough day"))
+    print(state.current_level)  # "LOW"
+    print(state.is_escalating)  # False
+
+    state = tracker.record(detect_crisis("I feel hopeless"))
+    print(state.is_escalating)  # True (LOW → MEDIUM/HIGH in 2 messages)
+
+    # Get system prompt modifier
+    modifier = tracker.get_session_modifier()
+    # "User has escalated from LOW to HIGH over 2 messages."
+
+    # Reset for new session
+    tracker.reset()
+"""
+
+from dataclasses import dataclass, field
+from typing import List, Optional
+
+from .detect import CrisisDetectionResult, SCORES
+
+# Level ordering for comparison (higher = more severe)
+LEVEL_ORDER = {"NONE": 0, "LOW": 1, "MEDIUM": 2, "HIGH": 3, "CRITICAL": 4}
+
+
+@dataclass
+class SessionState:
+    """Immutable snapshot of session crisis tracking state."""
+
+    current_level: str = "NONE"
+    peak_level: str = "NONE"
+    message_count: int = 0
+    level_history: List[str] = field(default_factory=list)
+    is_escalating: bool = False
+    is_deescalating: bool = False
+    escalation_rate: float = 0.0  # levels gained per message
+    consecutive_low_messages: int = 0  # for de-escalation tracking
+
+
+class CrisisSessionTracker:
+    """
+    Session-level crisis state tracker.
+
+    Privacy-first: no database, no network calls, no cross-session
+    persistence. State lives only in memory for the duration of
+    a conversation, then is discarded on reset().
+    """
+
+    # Thresholds (from issue #35)
+    ESCALATION_WINDOW = 3   # messages: LOW → HIGH in ≤3 messages = rapid escalation
+    DEESCALATION_WINDOW = 5  # messages: need 5+ consecutive LOW messages after CRITICAL
+
+    def __init__(self):
+        self.reset()
+
+    def reset(self):
+        """Reset all session state. Call on new conversation."""
+        self._current_level = "NONE"
+        self._peak_level = "NONE"
+        self._message_count = 0
+        self._level_history: List[str] = []
+        self._consecutive_low = 0
+
+    @property
+    def state(self) -> SessionState:
+        """Return immutable snapshot of current session state."""
+        is_escalating = self._detect_escalation()
+        is_deescalating = self._detect_deescalation()
+        rate = self._compute_escalation_rate()
+
+        return SessionState(
+            current_level=self._current_level,
+            peak_level=self._peak_level,
+            message_count=self._message_count,
+            level_history=list(self._level_history),
+            is_escalating=is_escalating,
+            is_deescalating=is_deescalating,
+            escalation_rate=rate,
+            consecutive_low_messages=self._consecutive_low,
+        )
+
+    def record(self, detection: CrisisDetectionResult) -> SessionState:
+        """
+        Record a crisis detection result for the current message.
+
+        Returns updated SessionState.
+        """
+        level = detection.level
+        self._message_count += 1
+        self._level_history.append(level)
+
+        # Update peak
+        if LEVEL_ORDER.get(level, 0) > LEVEL_ORDER.get(self._peak_level, 0):
+            self._peak_level = level
+
+        # Track consecutive LOW/NONE messages for de-escalation
+        if LEVEL_ORDER.get(level, 0) <= LEVEL_ORDER["LOW"]:
+            self._consecutive_low += 1
+        else:
+            self._consecutive_low = 0
+
+        self._current_level = level
+        return self.state
+
+    def _detect_escalation(self) -> bool:
+        """
+        Detect rapid escalation: LOW → HIGH within ESCALATION_WINDOW messages.
+
+        Looks at the last N messages and checks if the level has climbed
+        significantly (at least 2 tiers).
+        """
+        if len(self._level_history) < 2:
+            return False
+
+        window = self._level_history[-self.ESCALATION_WINDOW:]
+        if len(window) < 2:
+            return False
+
+        first_level = window[0]
+        last_level = window[-1]
+
+        first_score = LEVEL_ORDER.get(first_level, 0)
+        last_score = LEVEL_ORDER.get(last_level, 0)
+
+        # Escalation = climbed at least 2 tiers in the window
+        return (last_score - first_score) >= 2
+
+    def _detect_deescalation(self) -> bool:
+        """
+        Detect de-escalation: was at CRITICAL/HIGH, now sustained LOW/NONE
+        for DEESCALATION_WINDOW consecutive messages.
+        """
+        if LEVEL_ORDER.get(self._peak_level, 0) < LEVEL_ORDER["HIGH"]:
+            return False
+
+        return self._consecutive_low >= self.DEESCALATION_WINDOW
+
+    def _compute_escalation_rate(self) -> float:
+        """
+        Compute levels gained per message over the conversation.
+
+        Positive = escalating, negative = de-escalating, 0 = stable.
+        """
+        if self._message_count < 2:
+            return 0.0
+
+        first = LEVEL_ORDER.get(self._level_history[0], 0)
+        current = LEVEL_ORDER.get(self._current_level, 0)
+
+        return (current - first) / (self._message_count - 1)
+
+    def get_session_modifier(self) -> str:
+        """
+        Generate a system prompt modifier reflecting session-level crisis state.
+
+        Returns empty string if no session context is relevant.
+        """
+        if self._message_count < 2:
+            return ""
+
+        s = self.state
+
+        if s.is_escalating:
+            return (
+                f"User has escalated from {self._level_history[0]} to "
+                f"{s.current_level} over {s.message_count} messages. "
+                f"Peak crisis level this session: {s.peak_level}. "
+                "Respond with heightened awareness. The trajectory is "
+                "worsening — prioritize safety and connection."
+            )
+
+        if s.is_deescalating:
+            return (
+                f"User previously reached {s.peak_level} crisis level "
+                f"but has been at {s.current_level} or below for "
+                f"{s.consecutive_low_messages} consecutive messages. "
+                "The situation appears to be stabilizing. Continue "
+                "supportive engagement while remaining vigilant."
+            )
+
+        if s.peak_level in ("CRITICAL", "HIGH") and s.current_level not in ("CRITICAL", "HIGH"):
+            return (
+                f"User previously reached {s.peak_level} crisis level "
+                f"this session (currently {s.current_level}). "
+                "Continue with care and awareness of the earlier crisis."
+            )
+
+        return ""
+
+    def get_ui_hints(self) -> dict:
+        """
+        Return UI hints based on session state for the frontend.
+
+        These are advisory — the frontend decides what to show.
+        """
+        s = self.state
+
+        hints = {
+            "session_escalating": s.is_escalating,
+            "session_deescalating": s.is_deescalating,
+            "session_peak_level": s.peak_level,
+            "session_message_count": s.message_count,
+        }
+
+        if s.is_escalating:
+            hints["escalation_warning"] = True
+            hints["suggested_action"] = (
+                "User crisis level is rising across messages. "
+                "Consider increasing intervention level."
+            )
+
+        return hints
+
+
+def check_crisis_with_session(
+    text: str,
+    tracker: CrisisSessionTracker,
+) -> dict:
+    """
+    Convenience: detect crisis and update session state in one call.
+
+    Returns combined single-message detection + session-level context.
+    """
+    from .detect import detect_crisis
+    from .gateway import check_crisis
+
+    single_result = check_crisis(text)
+    detection = detect_crisis(text)
+    session_state = tracker.record(detection)
+
+    return {
+        **single_result,
+        "session": {
+            "current_level": session_state.current_level,
+            "peak_level": session_state.peak_level,
+            "message_count": session_state.message_count,
+            "is_escalating": session_state.is_escalating,
+            "is_deescalating": session_state.is_deescalating,
+            "modifier": tracker.get_session_modifier(),
+            "ui_hints": tracker.get_ui_hints(),
+        },
+    }

index.html

@@ -475,26 +475,6 @@ html, body {
   margin-bottom: 24px;
 }
 
-.modal-status {
-  min-height: 22px;
-  margin: 0 0 16px;
-  font-size: 0.9rem;
-  line-height: 1.45;
-  color: #8b949e;
-}
-
-.modal-status.is-visible {
-  display: block;
-}
-
-.modal-status.success {
-  color: #3fb950;
-}
-
-.modal-status.error {
-  color: #ff7b72;
-}
-
 .form-group {
   margin-bottom: 16px;
 }
@@ -757,7 +737,6 @@ html, body {
         <textarea id="sp-environment" placeholder="e.g., Giving my car keys to a friend, locking away meds..."></textarea>
       </div>
     </div>
-    <div id="safety-plan-status" class="modal-status" role="status" aria-live="polite" aria-atomic="true"></div>
     <div class="modal-footer">
       <button class="btn btn-secondary" id="cancel-safety-plan">Cancel</button>
       <button class="btn btn-primary" id="save-safety-plan">Save Plan</button>
@@ -829,6 +808,7 @@ Sovereignty and service always.`;
   var crisisPanel = document.getElementById('crisis-panel');
   var crisisOverlay = document.getElementById('crisis-overlay');
   var overlayDismissBtn = document.getElementById('overlay-dismiss-btn');
+  var overlayCallLink = document.querySelector('.overlay-call');
   var statusDot = document.querySelector('.status-dot');
   var statusText = document.getElementById('status-text');
   
@@ -839,7 +819,6 @@ Sovereignty and service always.`;
   var closeSafetyPlan = document.getElementById('close-safety-plan');
   var cancelSafetyPlan = document.getElementById('cancel-safety-plan');
   var saveSafetyPlan = document.getElementById('save-safety-plan');
-  var safetyPlanStatus = document.getElementById('safety-plan-status');
   var clearChatBtn = document.getElementById('clear-chat-btn');
 
   // ===== STATE =====
@@ -1072,7 +1051,8 @@ Sovereignty and service always.`;
       }
     }, 1000);
 
-    overlayDismissBtn.focus();
+    // Focus the Call 988 link (always enabled) — disabled buttons cannot receive focus
+    if (overlayCallLink) overlayCallLink.focus();
   }
 
   // Register focus trap on document (always listening, gated by class check)
@@ -1205,24 +1185,12 @@ Sovereignty and service always.`;
     } catch (e) {}
   }
 
-  function setSafetyPlanStatus(message, type) {
-    safetyPlanStatus.textContent = message;
-    safetyPlanStatus.className = 'modal-status is-visible ' + (type || '');
-  }
-
-  function clearSafetyPlanStatus() {
-    safetyPlanStatus.textContent = '';
-    safetyPlanStatus.className = 'modal-status';
-  }
-
   closeSafetyPlan.addEventListener('click', function() {
-    clearSafetyPlanStatus();
     safetyPlanModal.classList.remove('active');
     _restoreSafetyPlanFocus();
   });
 
   cancelSafetyPlan.addEventListener('click', function() {
-    clearSafetyPlanStatus();
     safetyPlanModal.classList.remove('active');
     _restoreSafetyPlanFocus();
   });
@@ -1237,9 +1205,11 @@ Sovereignty and service always.`;
     };
     try {
       localStorage.setItem('timmy_safety_plan', JSON.stringify(plan));
-      setSafetyPlanStatus('Safety plan saved locally.', 'success');
+      safetyPlanModal.classList.remove('active');
+      _restoreSafetyPlanFocus();
+      alert('Safety plan saved locally.');
     } catch (e) {
-      setSafetyPlanStatus('Error saving plan.', 'error');
+      alert('Error saving plan.');
     }
   });
 
@@ -1317,7 +1287,6 @@ Sovereignty and service always.`;
 
   // Wire open buttons to activate focus trap
   safetyPlanBtn.addEventListener('click', function() {
-    clearSafetyPlanStatus();
     loadSafetyPlan();
     safetyPlanModal.classList.add('active');
     _activateSafetyPlanFocusTrap(safetyPlanBtn);
@@ -1326,8 +1295,6 @@ Sovereignty and service always.`;
   // Crisis panel safety plan button (if crisis panel is visible)
   if (crisisSafetyPlanBtn) {
     crisisSafetyPlanBtn.addEventListener('click', function() {
-      clearSafetyPlanStatus();
-      clearSafetyPlanStatus();
       loadSafetyPlan();
       safetyPlanModal.classList.add('active');
       _activateSafetyPlanFocusTrap(crisisSafetyPlanBtn);

tests/test_crisis_overlay_focus_trap.py

@@ -52,6 +52,34 @@ class TestCrisisOverlayFocusTrap(unittest.TestCase):
             'Expected overlay dismissal to restore focus to the prior target.',
         )
 
+    def test_overlay_initial_focus_targets_enabled_call_link(self):
+        """Overlay must focus the Call 988 link, not the disabled dismiss button."""
+        # Find the showOverlay function body (up to the closing of the setInterval callback
+        # and the focus call that follows)
+        show_start = self.html.find('function showOverlay()')
+        self.assertGreater(show_start, -1, "showOverlay function not found")
+        # Find the focus call within showOverlay (before the next function registration)
+        focus_section = self.html[show_start:show_start + 2000]
+        self.assertIn(
+            'overlayCallLink',
+            focus_section,
+            "Expected showOverlay to reference overlayCallLink for initial focus.",
+        )
+        # Ensure the old buggy pattern is gone
+        focus_line_region = self.html[show_start + 800:show_start + 1200]
+        self.assertNotIn(
+            'overlayDismissBtn.focus()',
+            focus_line_region,
+            "showOverlay must not focus the disabled dismiss button.",
+        )
+
+    def test_overlay_call_link_variable_is_declared(self):
+        self.assertIn(
+            "querySelector('.overlay-call')",
+            self.html,
+            "Expected a JS reference to the .overlay-call link element.",
+        )
+
 
 if __name__ == '__main__':
     unittest.main()

tests/test_safety_plan_save_feedback.py

@@ -1,52 +0,0 @@
-import pathlib
-import re
-import unittest
-
-ROOT = pathlib.Path(__file__).resolve().parents[1]
-INDEX_HTML = ROOT / 'index.html'
-
-
-class TestSafetyPlanSaveFeedback(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        cls.html = INDEX_HTML.read_text()
-
-    def test_modal_has_inline_status_live_region(self):
-        self.assertRegex(
-            self.html,
-            r'<div[^>]+id="safety-plan-status"[^>]+role="status"[^>]+aria-live="polite"[^>]*>',
-            'Expected an inline polite live region for safety plan save feedback.',
-        )
-
-    def test_save_feedback_does_not_use_blocking_alerts(self):
-        self.assertNotIn(
-            "alert('Safety plan saved locally.')",
-            self.html,
-            'Expected success feedback to stop using blocking alert().',
-        )
-        self.assertNotIn(
-            "alert('Error saving plan.')",
-            self.html,
-            'Expected error feedback to stop using blocking alert().',
-        )
-
-    def test_save_logic_updates_inline_status_for_success_and_error(self):
-        self.assertRegex(
-            self.html,
-            r'function\s+setSafetyPlanStatus\s*\(',
-            'Expected a helper to update inline save feedback.',
-        )
-        self.assertRegex(
-            self.html,
-            r"setSafetyPlanStatus\('Safety plan saved locally\.'\s*,\s*'success'\)",
-            'Expected success path to update inline status.',
-        )
-        self.assertRegex(
-            self.html,
-            r"setSafetyPlanStatus\('Error saving plan\.'\s*,\s*'error'\)",
-            'Expected error path to update inline status.',
-        )
-
-
-if __name__ == '__main__':
-    unittest.main()

tests/test_service_worker_offline.py

@@ -50,6 +50,22 @@ class TestCrisisOfflinePage(unittest.TestCase):
         for phrase in required_phrases:
             self.assertIn(phrase, self.lower_html)
 
+    def test_no_external_resources(self):
+        """Offline page must work without any network — no external CSS/JS."""
+        import re
+        html = self.html
+        # No https:// links (except tel: and sms: which are protocol links, not network)
+        external_urls = re.findall(r'href=["\']https://|src=["\']https://', html)
+        self.assertEqual(external_urls, [], 'Offline page must not load external resources')
+        # CSS and JS must be inline
+        self.assertIn('<style>', html, 'CSS must be inline')
+        self.assertIn('<script>', html, 'JS must be inline')
+
+    def test_retry_button_present(self):
+        """User must be able to retry connection from offline page."""
+        self.assertIn('retry-connection', self.html)
+        self.assertIn('Retry connection', self.html)
+
 
 if __name__ == '__main__':
     unittest.main()

tests/test_session_tracker.py

@@ -0,0 +1,277 @@
+"""
+Tests for crisis session tracking and escalation (P0 #35).
+
+Covers: session_tracker.py
+Run with: python -m pytest tests/test_session_tracker.py -v
+"""
+
+import unittest
+import sys
+import os
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from crisis.detect import detect_crisis
+from crisis.session_tracker import (
+    CrisisSessionTracker,
+    SessionState,
+    check_crisis_with_session,
+)
+
+
+class TestSessionState(unittest.TestCase):
+    """Test SessionState defaults."""
+
+    def test_default_state(self):
+        s = SessionState()
+        self.assertEqual(s.current_level, "NONE")
+        self.assertEqual(s.peak_level, "NONE")
+        self.assertEqual(s.message_count, 0)
+        self.assertEqual(s.level_history, [])
+        self.assertFalse(s.is_escalating)
+        self.assertFalse(s.is_deescalating)
+
+
+class TestSessionTracking(unittest.TestCase):
+    """Test basic session state tracking."""
+
+    def setUp(self):
+        self.tracker = CrisisSessionTracker()
+
+    def test_record_none_message(self):
+        state = self.tracker.record(detect_crisis("Hello Timmy"))
+        self.assertEqual(state.current_level, "NONE")
+        self.assertEqual(state.message_count, 1)
+        self.assertEqual(state.peak_level, "NONE")
+
+    def test_record_low_message(self):
+        self.tracker.record(detect_crisis("Hello"))
+        state = self.tracker.record(detect_crisis("Having a rough day"))
+        self.assertIn(state.current_level, ("LOW", "NONE"))
+        self.assertEqual(state.message_count, 2)
+
+    def test_record_critical_updates_peak(self):
+        self.tracker.record(detect_crisis("Having a rough day"))
+        state = self.tracker.record(detect_crisis("I want to kill myself"))
+        self.assertEqual(state.current_level, "CRITICAL")
+        self.assertEqual(state.peak_level, "CRITICAL")
+
+    def test_peak_preserved_after_drop(self):
+        """Peak level should stay at the highest seen, even after de-escalation."""
+        self.tracker.record(detect_crisis("I want to kill myself"))
+        state = self.tracker.record(detect_crisis("I'm feeling a bit better"))
+        self.assertEqual(state.peak_level, "CRITICAL")
+
+    def test_level_history(self):
+        self.tracker.record(detect_crisis("Hello"))
+        self.tracker.record(detect_crisis("Having a rough day"))
+        state = self.tracker.record(detect_crisis("I want to die"))
+        self.assertEqual(len(state.level_history), 3)
+        self.assertEqual(state.level_history[0], "NONE")
+        self.assertEqual(state.level_history[2], "CRITICAL")
+
+    def test_reset_clears_state(self):
+        self.tracker.record(detect_crisis("I want to kill myself"))
+        self.tracker.reset()
+        state = self.tracker.state
+        self.assertEqual(state.current_level, "NONE")
+        self.assertEqual(state.peak_level, "NONE")
+        self.assertEqual(state.message_count, 0)
+        self.assertEqual(state.level_history, [])
+
+
+class TestEscalationDetection(unittest.TestCase):
+    """Test escalation detection: LOW → HIGH in ≤3 messages."""
+
+    def setUp(self):
+        self.tracker = CrisisSessionTracker()
+
+    def test_no_escalation_single_message(self):
+        self.tracker.record(detect_crisis("Hello"))
+        self.assertFalse(self.tracker.state.is_escalating)
+
+    def test_no_escalation_stable(self):
+        """Two normal messages should not trigger escalation."""
+        self.tracker.record(detect_crisis("Hello"))
+        state = self.tracker.record(detect_crisis("How are you?"))
+        self.assertFalse(state.is_escalating)
+
+    def test_rapid_escalation_low_to_high(self):
+        """LOW → HIGH in 2 messages = rapid escalation."""
+        self.tracker.record(detect_crisis("Having a rough day"))
+        state = self.tracker.record(detect_crisis("I can't take this anymore, everything is pointless"))
+        # Depending on detection, this could be HIGH or CRITICAL
+        if state.current_level in ("HIGH", "CRITICAL"):
+            self.assertTrue(state.is_escalating)
+
+    def test_rapid_escalation_three_messages(self):
+        """NONE → LOW → HIGH in 3 messages = escalation."""
+        self.tracker.record(detect_crisis("Hello"))
+        self.tracker.record(detect_crisis("Having a rough day"))
+        state = self.tracker.record(detect_crisis("I feel completely hopeless with no way out"))
+        if state.current_level in ("HIGH", "CRITICAL"):
+            self.assertTrue(state.is_escalating)
+
+    def test_escalation_rate(self):
+        """Rate should be positive when escalating."""
+        self.tracker.record(detect_crisis("Hello"))
+        self.tracker.record(detect_crisis("I want to die"))
+        state = self.tracker.state
+        self.assertGreater(state.escalation_rate, 0)
+
+
+class TestDeescalationDetection(unittest.TestCase):
+    """Test de-escalation: sustained LOW after HIGH/CRITICAL."""
+
+    def setUp(self):
+        self.tracker = CrisisSessionTracker()
+
+    def test_no_deescalation_without_prior_crisis(self):
+        """No de-escalation if never reached HIGH/CRITICAL."""
+        for _ in range(6):
+            self.tracker.record(detect_crisis("Hello"))
+        self.assertFalse(self.tracker.state.is_deescalating)
+
+    def test_deescalation_after_critical(self):
+        """5+ consecutive LOW/NONE messages after CRITICAL = de-escalation."""
+        self.tracker.record(detect_crisis("I want to kill myself"))
+        for _ in range(5):
+            self.tracker.record(detect_crisis("I'm doing better today"))
+        state = self.tracker.state
+        if state.peak_level == "CRITICAL":
+            self.assertTrue(state.is_deescalating)
+
+    def test_deescalation_after_high(self):
+        """5+ consecutive LOW/NONE messages after HIGH = de-escalation."""
+        self.tracker.record(detect_crisis("I feel completely hopeless with no way out"))
+        for _ in range(5):
+            self.tracker.record(detect_crisis("Feeling okay"))
+        state = self.tracker.state
+        if state.peak_level == "HIGH":
+            self.assertTrue(state.is_deescalating)
+
+    def test_interrupted_deescalation(self):
+        """De-escalation resets if a HIGH message interrupts."""
+        self.tracker.record(detect_crisis("I want to kill myself"))
+        for _ in range(3):
+            self.tracker.record(detect_crisis("Doing better"))
+        # Interrupt with another crisis
+        self.tracker.record(detect_crisis("I feel hopeless again"))
+        self.tracker.record(detect_crisis("Feeling okay now"))
+        state = self.tracker.state
+        # Should NOT be de-escalating yet (counter reset)
+        self.assertFalse(state.is_deescalating)
+
+
+class TestSessionModifier(unittest.TestCase):
+    """Test system prompt modifier generation."""
+
+    def setUp(self):
+        self.tracker = CrisisSessionTracker()
+
+    def test_no_modifier_for_single_message(self):
+        self.tracker.record(detect_crisis("Hello"))
+        self.assertEqual(self.tracker.get_session_modifier(), "")
+
+    def test_no_modifier_for_stable_session(self):
+        self.tracker.record(detect_crisis("Hello"))
+        self.tracker.record(detect_crisis("Good morning"))
+        self.assertEqual(self.tracker.get_session_modifier(), "")
+
+    def test_escalation_modifier(self):
+        """Escalating session should produce a modifier."""
+        self.tracker.record(detect_crisis("Hello"))
+        self.tracker.record(detect_crisis("I want to die"))
+        modifier = self.tracker.get_session_modifier()
+        if self.tracker.state.is_escalating:
+            self.assertIn("escalated", modifier.lower())
+            self.assertIn("NONE", modifier)
+            self.assertIn("CRITICAL", modifier)
+
+    def test_deescalation_modifier(self):
+        """De-escalating session should mention stabilizing."""
+        self.tracker.record(detect_crisis("I want to kill myself"))
+        for _ in range(5):
+            self.tracker.record(detect_crisis("I'm feeling okay"))
+        modifier = self.tracker.get_session_modifier()
+        if self.tracker.state.is_deescalating:
+            self.assertIn("stabilizing", modifier.lower())
+
+    def test_prior_crisis_modifier(self):
+        """Past crisis should be noted even without active escalation."""
+        self.tracker.record(detect_crisis("I want to die"))
+        self.tracker.record(detect_crisis("Feeling a bit better"))
+        modifier = self.tracker.get_session_modifier()
+        # Should note the prior CRITICAL
+        if modifier:
+            self.assertIn("CRITICAL", modifier)
+
+
+class TestUIHints(unittest.TestCase):
+    """Test UI hint generation."""
+
+    def setUp(self):
+        self.tracker = CrisisSessionTracker()
+
+    def test_ui_hints_structure(self):
+        self.tracker.record(detect_crisis("Hello"))
+        hints = self.tracker.get_ui_hints()
+        self.assertIn("session_escalating", hints)
+        self.assertIn("session_deescalating", hints)
+        self.assertIn("session_peak_level", hints)
+        self.assertIn("session_message_count", hints)
+
+    def test_ui_hints_escalation_warning(self):
+        """Escalating session should have warning hint."""
+        self.tracker.record(detect_crisis("Hello"))
+        self.tracker.record(detect_crisis("I want to die"))
+        hints = self.tracker.get_ui_hints()
+        if hints["session_escalating"]:
+            self.assertTrue(hints.get("escalation_warning"))
+            self.assertIn("suggested_action", hints)
+
+
+class TestCheckCrisisWithSession(unittest.TestCase):
+    """Test the convenience function combining detection + session tracking."""
+
+    def test_returns_combined_data(self):
+        tracker = CrisisSessionTracker()
+        result = check_crisis_with_session("I want to die", tracker)
+        self.assertIn("level", result)
+        self.assertIn("session", result)
+        self.assertIn("current_level", result["session"])
+        self.assertIn("peak_level", result["session"])
+        self.assertIn("modifier", result["session"])
+
+    def test_session_updates_across_calls(self):
+        tracker = CrisisSessionTracker()
+        check_crisis_with_session("Hello", tracker)
+        result = check_crisis_with_session("I want to die", tracker)
+        self.assertEqual(result["session"]["message_count"], 2)
+        self.assertEqual(result["session"]["peak_level"], "CRITICAL")
+
+
+class TestPrivacy(unittest.TestCase):
+    """Verify privacy-first design principles."""
+
+    def test_no_persistence_mechanism(self):
+        """Session tracker should have no database, file, or network calls."""
+        import inspect
+        source = inspect.getsource(CrisisSessionTracker)
+        # Should not import database, requests, or file I/O
+        forbidden = ["sqlite", "requests", "urllib", "open(", "httpx", "aiohttp"]
+        for word in forbidden:
+            self.assertNotIn(word, source.lower(),
+                f"Session tracker should not use {word} — privacy-first design")
+
+    def test_state_contained_in_memory(self):
+        """All state should be instance attributes, not module-level."""
+        tracker = CrisisSessionTracker()
+        tracker.record(detect_crisis("I want to die"))
+        # New tracker should have clean state (no global contamination)
+        fresh = CrisisSessionTracker()
+        self.assertEqual(fresh.state.current_level, "NONE")
+
+
+if __name__ == '__main__':
+    unittest.main()

voice_analysis.py

@@ -0,0 +1,350 @@
+"""
+voice_analysis.py — Voice message distress analysis via paralinguistic features.
+
+Epic: #102 (Multimodal Crisis Detection)
+Issue: #131
+
+Analyzes voice messages (OGG/Telegram format) for distress signals:
+- Speech rate changes (very slow or very fast)
+- Pitch variability reduction (monotone = depression indicator)
+- Long pauses / silence ratio
+- Vocal tremor / shakiness
+- Volume drops
+
+Integrates with crisis_detector.py text-based detection for multimodal coverage.
+"""
+
+import os
+import json
+import subprocess
+import tempfile
+from dataclasses import dataclass, field, asdict
+from typing import Optional
+
+
+@dataclass
+class VoiceAnalysisResult:
+    """Result of paralinguistic analysis on a voice message."""
+    transcript: str = ""
+    speech_rate: float = 0.0          # words per minute
+    pitch_mean: float = 0.0           # Hz, average fundamental frequency
+    pitch_variability: float = 0.0    # std dev of pitch (low = monotone)
+    silence_ratio: float = 0.0        # 0-1, fraction of audio that is silence
+    tremor_score: float = 0.0         # 0-1, vocal shakiness estimate
+    volume_drop_score: float = 0.0    # 0-1, sudden volume decreases
+    distress_score: float = 0.0       # 0-1, composite distress indicator
+    signals_detected: list = field(default_factory=list)
+
+    def to_dict(self) -> dict:
+        return asdict(self)
+
+
+# === THRESHOLDS ===
+
+# Speech rate: normal is ~120-150 WPM
+# Very slow (<80) or very fast (>200) are distress indicators
+SPEECH_RATE_SLOW = 80
+SPEECH_RATE_FAST = 200
+SPEECH_RATE_NORMAL_LOW = 100
+SPEECH_RATE_NORMAL_HIGH = 170
+
+# Pitch variability: normal conversation has std dev ~30-50 Hz
+# Monotone (<15 Hz) is a depression indicator
+PITCH_VARIABILITY_LOW = 15.0  # Hz — monotone threshold
+PITCH_VARIABILITY_NORMAL = 30.0
+
+# Silence ratio: normal has ~10-20% silence
+# Excessive silence (>40%) or very little (<3%) may indicate distress
+SILENCE_RATIO_HIGH = 0.4
+SILENCE_RATIO_LOW = 0.03
+
+# Composite thresholds
+DISTRESS_LOW = 0.3
+DISTRESS_MEDIUM = 0.7
+
+
+# === CORE ANALYSIS ===
+
+def _convert_to_wav(audio_path: str) -> str:
+    """Convert audio to WAV format for analysis. Returns path to temp WAV file."""
+    wav_path = tempfile.mktemp(suffix='.wav')
+    try:
+        subprocess.run(
+            ['ffmpeg', '-i', audio_path, '-ar', '16000', '-ac', '1', '-y', wav_path],
+            capture_output=True, timeout=30
+        )
+        if not os.path.exists(wav_path):
+            # Fallback: if ffmpeg not available, try the original file
+            return audio_path
+        return wav_path
+    except (FileNotFoundError, subprocess.TimeoutExpired):
+        return audio_path
+
+
+def _transcribe(audio_path: str) -> str:
+    """Transcribe audio using whisper (if available) or return empty string."""
+    try:
+        import whisper
+        model = whisper.load_model("base")
+        result = model.transcribe(audio_path)
+        return result.get("text", "").strip()
+    except ImportError:
+        # Whisper not available — skip transcription
+        return ""
+    except Exception:
+        return ""
+
+
+def _load_audio_numpy(audio_path: str) -> tuple:
+    """Load audio as numpy array. Returns (samples, sample_rate) or (None, None)."""
+    try:
+        import librosa
+        samples, sr = librosa.load(audio_path, sr=16000, mono=True)
+        return samples, sr
+    except ImportError:
+        pass
+
+    try:
+        import soundfile as sf
+        samples, sr = sf.read(audio_path)
+        if len(samples.shape) > 1:
+            samples = samples.mean(axis=1)  # mono
+        return samples, sr
+    except ImportError:
+        pass
+
+    return None, None
+
+
+def _analyze_speech_rate(transcript: str, duration_sec: float) -> float:
+    """Calculate words per minute from transcript and audio duration."""
+    if not transcript or duration_sec <= 0:
+        return 0.0
+    words = len(transcript.split())
+    minutes = duration_sec / 60.0
+    return words / minutes if minutes > 0 else 0.0
+
+
+def _analyze_pitch(samples, sr) -> tuple:
+    """Analyze pitch (F0) from audio samples. Returns (mean_hz, variability_hz)."""
+    try:
+        import librosa
+        f0, voiced_flag, _ = librosa.pyin(
+            samples, fmin=librosa.note_to_hz('C2'),
+            fmax=librosa.note_to_hz('C7'), sr=sr
+        )
+        import numpy as np
+        f0_clean = f0[~np.isnan(f0)]
+        if len(f0_clean) == 0:
+            return 0.0, 0.0
+        return float(np.mean(f0_clean)), float(np.std(f0_clean))
+    except (ImportError, Exception):
+        return 0.0, 0.0
+
+
+def _analyze_silence(samples, sr, threshold_db: float = -40.0) -> float:
+    """Calculate ratio of silence in audio (0-1)."""
+    try:
+        import librosa
+        import numpy as np
+        rms = librosa.feature.rms(y=samples)[0]
+        rms_db = librosa.amplitude_to_db(rms, ref=np.max)
+        silence_frames = np.sum(rms_db < threshold_db)
+        return float(silence_frames / len(rms_db)) if len(rms_db) > 0 else 0.0
+    except (ImportError, Exception):
+        return 0.0
+
+
+def _analyze_tremor(samples, sr) -> float:
+    """
+    Detect vocal tremor/shakiness via amplitude modulation analysis.
+
+    Tremor manifests as periodic amplitude fluctuations (3-12 Hz range).
+    Returns 0-1 score where 1 = strong tremor detected.
+    """
+    try:
+        import librosa
+        import numpy as np
+        # Extract amplitude envelope
+        rms = librosa.feature.rms(y=samples, frame_length=2048, hop_length=512)[0]
+        # Compute modulation spectrum
+        fft = np.abs(np.fft.rfft(rms))
+        freqs = np.fft.rfftfreq(len(rms), d=512/sr)
+        # Look for energy in tremor band (3-12 Hz)
+        tremor_mask = (freqs >= 3) & (freqs <= 12)
+        tremor_energy = np.sum(fft[tremor_mask])
+        total_energy = np.sum(fft[1:])  # skip DC
+        if total_energy == 0:
+            return 0.0
+        ratio = tremor_energy / total_energy
+        return float(min(1.0, ratio * 5))  # normalize — typical tremor is 0.1-0.3 of total
+    except (ImportError, Exception):
+        return 0.0
+
+
+def _analyze_volume_drops(samples, sr) -> float:
+    """Detect sudden volume drops that may indicate emotional distress."""
+    try:
+        import librosa
+        import numpy as np
+        rms = librosa.feature.rms(y=samples, frame_length=2048, hop_length=512)[0]
+        if len(rms) < 2:
+            return 0.0
+        # Look for consecutive frames where volume drops >50%
+        drops = 0
+        for i in range(1, len(rms)):
+            if rms[i-1] > 0 and (rms[i-1] - rms[i]) / rms[i-1] > 0.5:
+                drops += 1
+        return float(min(1.0, drops / (len(rms) * 0.1)))
+    except (ImportError, Exception):
+        return 0.0
+
+
+def _compute_distress_score(result: VoiceAnalysisResult) -> tuple:
+    """
+    Compute composite distress score from paralinguistic features.
+
+    Returns (score, signals_detected).
+    """
+    signals = []
+    score = 0.0
+    weights = 0
+
+    # Speech rate (0.2 weight)
+    if result.speech_rate > 0:
+        if result.speech_rate < SPEECH_RATE_SLOW:
+            signals.append(f"very_slow_speech ({result.speech_rate:.0f} WPM)")
+            score += 0.8 * 0.2
+        elif result.speech_rate > SPEECH_RATE_FAST:
+            signals.append(f"very_fast_speech ({result.speech_rate:.0f} WPM)")
+            score += 0.6 * 0.2
+        elif result.speech_rate < SPEECH_RATE_NORMAL_LOW:
+            score += 0.3 * 0.2
+        weights += 0.2
+
+    # Pitch variability (0.25 weight — monotone is strong depression indicator)
+    if result.pitch_variability > 0:
+        if result.pitch_variability < PITCH_VARIABILITY_LOW:
+            signals.append(f"monotone_voice (variability={result.pitch_variability:.1f} Hz)")
+            score += 0.9 * 0.25
+        elif result.pitch_variability < PITCH_VARIABILITY_NORMAL:
+            signals.append(f"reduced_pitch_variability ({result.pitch_variability:.1f} Hz)")
+            score += 0.5 * 0.25
+        weights += 0.25
+
+    # Silence ratio (0.2 weight)
+    if result.silence_ratio > 0:
+        if result.silence_ratio > SILENCE_RATIO_HIGH:
+            signals.append(f"excessive_silence ({result.silence_ratio:.0%})")
+            score += 0.7 * 0.2
+        elif result.silence_ratio < SILENCE_RATIO_LOW:
+            signals.append(f"minimal_pauses ({result.silence_ratio:.0%})")
+            score += 0.3 * 0.2
+        weights += 0.2
+
+    # Tremor (0.2 weight)
+    if result.tremor_score > 0:
+        if result.tremor_score > 0.5:
+            signals.append(f"vocal_tremor (score={result.tremor_score:.2f})")
+            score += result.tremor_score * 0.2
+        weights += 0.2
+
+    # Volume drops (0.15 weight)
+    if result.volume_drop_score > 0:
+        if result.volume_drop_score > 0.4:
+            signals.append(f"volume_drops (score={result.volume_drop_score:.2f})")
+            score += result.volume_drop_score * 0.15
+        weights += 0.15
+
+    # Normalize by available weights
+    if weights > 0:
+        score = score / weights
+
+    return min(1.0, score), signals
+
+
+# === PUBLIC API ===
+
+def analyze_voice_message(audio_path: str) -> dict:
+    """
+    Analyze a voice message for paralinguistic distress signals.
+
+    Args:
+        audio_path: Path to audio file (OGG, WAV, MP3, etc.)
+
+    Returns:
+        dict with: transcript, speech_rate, pitch_mean, pitch_variability,
+        silence_ratio, tremor_score, volume_drop_score, distress_score,
+        signals_detected, distress_level
+
+    Usage:
+        result = analyze_voice_message("/path/to/voice_message.ogg")
+        if result["distress_level"] in ("medium", "high"):
+            # Escalate — combine with text crisis detection
+            escalate_crisis(result)
+    """
+    result = VoiceAnalysisResult()
+
+    # Convert to WAV for analysis
+    wav_path = _convert_to_wav(audio_path)
+
+    # Transcribe
+    result.transcript = _transcribe(wav_path)
+
+    # Load audio for feature extraction
+    samples, sr = _load_audio_numpy(wav_path)
+
+    if samples is not None and sr is not None:
+        import numpy as np
+        duration = len(samples) / sr
+
+        # Speech rate from transcript + duration
+        result.speech_rate = _analyze_speech_rate(result.transcript, duration)
+
+        # Pitch analysis
+        result.pitch_mean, result.pitch_variability = _analyze_pitch(samples, sr)
+
+        # Silence ratio
+        result.silence_ratio = _analyze_silence(samples, sr)
+
+        # Tremor detection
+        result.tremor_score = _analyze_tremor(samples, sr)
+
+        # Volume drops
+        result.volume_drop_score = _analyze_volume_drops(samples, sr)
+
+    # Composite distress score
+    result.distress_score, result.signals_detected = _compute_distress_score(result)
+
+    # Clean up temp file
+    if wav_path != audio_path and os.path.exists(wav_path):
+        os.unlink(wav_path)
+
+    # Classify distress level
+    if result.distress_score >= DISTRESS_MEDIUM:
+        distress_level = "high"
+    elif result.distress_score >= DISTRESS_LOW:
+        distress_level = "medium"
+    elif result.distress_score > 0:
+        distress_level = "low"
+    else:
+        distress_level = "none"
+
+    output = result.to_dict()
+    output["distress_level"] = distress_level
+    return output
+
+
+def get_audio_duration(audio_path: str) -> float:
+    """Get audio duration in seconds."""
+    try:
+        import librosa
+        duration = librosa.get_duration(path=audio_path)
+        return float(duration)
+    except (ImportError, Exception):
+        try:
+            import soundfile as sf
+            info = sf.info(audio_path)
+            return float(info.duration)
+        except (ImportError, Exception):
+            return 0.0