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Author SHA1 Message Date
Alexander Whitestone
c642b0c453 feat: add crisis metrics endpoint contract (#97)
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2026-04-17 01:49:52 -04:00
Alexander Whitestone
b7a2f90671 test: add crisis metrics endpoint coverage 2026-04-17 01:39:13 -04:00
07c582aa08 Merge pull request 'fix: crisis overlay initial focus to enabled Call 988 link (#69)' (#126) from burn/69-1776264183 into main
Merge PR #126: fix: crisis overlay initial focus to enabled Call 988 link (#69)
2026-04-17 01:46:56 +00:00
5f95dc1e39 Merge pull request '[P3] Service worker: cache crisis resources for offline (#41)' (#122) from burn/41-1776264184 into main
Merge PR #122: [P3] Service worker: cache crisis resources for offline (#41)
2026-04-17 01:46:55 +00:00
b1f3cac36d Merge pull request 'feat: session-level crisis tracking and escalation (closes #35)' (#118) from door/issue-35 into main
Merge PR #118: feat: session-level crisis tracking and escalation (closes #35)
2026-04-17 01:46:53 +00:00
07b3f67845 fix: crisis overlay initial focus to enabled Call 988 link (#69)
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2026-04-15 15:09:36 +00:00
c22bbbaf65 fix: crisis overlay initial focus to enabled Call 988 link (#69) 2026-04-15 15:09:32 +00:00
543cb1d40f test: add offline self-containment and retry button tests (#41)
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2026-04-15 14:58:44 +00:00
3cfd01815a feat: session-level crisis tracking and escalation (closes #35)
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2026-04-15 11:49:52 +00:00
5a7ba9f207 feat: session-level crisis tracking and escalation (closes #35) 2026-04-15 11:49:51 +00:00
8ed8f20a17 feat: session-level crisis tracking and escalation (closes #35) 2026-04-15 11:49:49 +00:00
9d7d26033e feat: session-level crisis tracking and escalation (closes #35) 2026-04-15 11:49:47 +00:00
12 changed files with 1044 additions and 477 deletions

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@@ -95,7 +95,45 @@ Run tests:
python -m pytest crisis/tests.py -v
```
### 7. Acceptance Criteria Checklist
### 7. Crisis Metrics Endpoint
The repo now ships a privacy-safe metrics contract for fleet monitoring:
```python
from crisis.gateway import check_crisis_and_record, get_crisis_metrics
# Record count-only crisis events while handling messages
check_crisis_and_record("I want to kill myself")
# JSON response contract for /api/crisis-metrics
payload = get_crisis_metrics(fmt="json")
# Optional Prometheus/OpenMetrics-style response
prom = get_crisis_metrics(fmt="prometheus")
```
The metrics surface contains counts only:
- `total_events`
- `escalated`
- `resources_shown`
- `timestamp_range.start`
- `timestamp_range.end`
No message content, indicators, or user identifiers are retained.
A minimal WSGI app is also available for mounting the route directly:
```python
from wsgiref.simple_server import make_server
from crisis.metrics import crisis_metrics_app
with make_server("127.0.0.1", 8645, crisis_metrics_app) as httpd:
httpd.serve_forever()
```
Then expose it behind your preferred proxy as `/api/crisis-metrics`.
### 8. Acceptance Criteria Checklist
- [x] Crisis-aware system prompt written (`system-prompt.txt`)
- [x] Frontend embeds system prompt on every API request (`index.html:1129`)
@@ -104,6 +142,7 @@ python -m pytest crisis/tests.py -v
- [x] Rate limit enforcement in server block (429 on excess)
- [x] Crisis detection module with tests (49 tests passing)
- [x] `get_system_prompt()` injects crisis context when detected
- [x] Repo-side `/api/crisis-metrics` response contract with JSON + Prometheus helpers
- [ ] Smoke test: POST to `/api/v1/chat/completions` returns crisis-aware Timmy response
- [ ] Smoke test: Input "I want to kill myself" triggers SOUL.md protocol
- [ ] Smoke test: 11th request in 1 minute returns HTTP 429

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@@ -1,336 +0,0 @@
"""Behavioral Pattern Detection — crisis risk from usage patterns.
Detects crisis signals from HOW someone uses the system, not just
what they say. Complements content-based crisis detection.
Behavioral signals:
- Frequency spike (anxiety/agitation)
- Frequency drop (withdrawal/isolation)
- Late-night messaging (2-5 AM)
- Session length increase (loneliness)
- Abrupt termination after emotional content
- Return after long absence
Part of Epic #102 (Multimodal Crisis Detection).
"""
import logging
import time
from collections import defaultdict
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
@dataclass
class SessionEvent:
"""A single session interaction."""
session_id: str
timestamp: float
message_length: int
is_user: bool = True
emotional_content: bool = False
terminated_abruptly: bool = False
@dataclass
class BehavioralSignals:
"""Detected behavioral risk signals."""
frequency_change: float = 0.0 # -1 (drop) to +1 (spike) vs baseline
is_late_night: bool = False # 2-5 AM local time
session_length_trend: str = "stable" # increasing/decreasing/stable
withdrawal_detected: bool = False # significant drop in activity
return_after_absence: bool = False # came back after extended absence
abrupt_termination: bool = False # left after emotional content
behavioral_score: float = 0.0 # 0-1 aggregate risk
def to_dict(self) -> Dict[str, Any]:
return {
"frequency_change": self.frequency_change,
"is_late_night": self.is_late_night,
"session_length_trend": self.session_length_trend,
"withdrawal_detected": self.withdrawal_detected,
"return_after_absence": self.return_after_absence,
"abrupt_termination": self.abrupt_termination,
"behavioral_score": self.behavioral_score,
}
class BehavioralTracker:
"""Track behavioral patterns per session/user and detect risk signals.
Uses a 7-day rolling window for baseline calculation.
Thread-safe for concurrent session tracking.
"""
# Time window constants
LATE_NIGHT_START = 2 # 2 AM
LATE_NIGHT_END = 5 # 5 AM
BASELINE_WINDOW_DAYS = 7
ABSENCE_THRESHOLD_HOURS = 48
SPIKE_THRESHOLD = 2.0 # 2x baseline = spike
DROP_THRESHOLD = 0.3 # 30% of baseline = withdrawal
def __init__(self):
# session_id -> list of events
self._events: Dict[str, List[SessionEvent]] = defaultdict(list)
# session_id -> baseline metrics
self._baselines: Dict[str, Dict[str, float]] = {}
# session_id -> last activity timestamp
self._last_activity: Dict[str, float] = {}
# Global baseline (all sessions)
self._global_baseline: Dict[str, float] = {
"avg_messages_per_hour": 5.0,
"avg_session_length_min": 15.0,
"avg_message_length": 200.0,
}
def record(
self,
session_id: str,
timestamp: Optional[float] = None,
message_length: int = 0,
is_user: bool = True,
emotional_content: bool = False,
terminated_abruptly: bool = False,
) -> None:
"""Record a session event."""
if timestamp is None:
timestamp = time.time()
event = SessionEvent(
session_id=session_id,
timestamp=timestamp,
message_length=message_length,
is_user=is_user,
emotional_content=emotional_content,
terminated_abruptly=terminated_abruptly,
)
self._events[session_id].append(event)
self._last_activity[session_id] = timestamp
# Periodically update baseline
if len(self._events[session_id]) % 20 == 0:
self._update_baseline(session_id)
def get_risk_signals(self, session_id: str) -> BehavioralSignals:
"""Analyze behavioral patterns and return risk signals."""
events = self._events.get(session_id, [])
if not events:
return BehavioralSignals()
signals = BehavioralSignals()
now = time.time()
# 1. Frequency analysis
signals.frequency_change = self._analyze_frequency(session_id, now)
# 2. Late-night detection
signals.is_late_night = self._is_late_night(events[-1].timestamp)
# 3. Session length trend
signals.session_length_trend = self._analyze_session_length_trend(session_id)
# 4. Withdrawal detection
signals.withdrawal_detected = signals.frequency_change < -0.5
# 5. Return after absence
signals.return_after_absence = self._detect_return_after_absence(session_id, now)
# 6. Abrupt termination
signals.abrupt_termination = self._detect_abrupt_termination(events)
# 7. Aggregate behavioral score
signals.behavioral_score = self._compute_behavioral_score(signals)
return signals
def _analyze_frequency(self, session_id: str, now: float) -> float:
"""Compare recent frequency to baseline. Returns -1 to +1."""
events = self._events.get(session_id, [])
if len(events) < 3:
return 0.0
# Count messages in last hour
one_hour_ago = now - 3600
recent_count = sum(1 for e in events if e.timestamp > one_hour_ago and e.is_user)
# Get baseline
baseline = self._get_baseline(session_id)
baseline_rate = baseline.get("avg_messages_per_hour", 5.0)
if baseline_rate <= 0:
return 0.0
ratio = recent_count / baseline_rate
# Map to -1..+1: 0.5x = -0.5, 1x = 0, 2x = +1
if ratio < 1.0:
return max(-1.0, (ratio - 1.0))
else:
return min(1.0, (ratio - 1.0) / 2.0)
def _is_late_night(self, timestamp: float) -> bool:
"""Check if timestamp falls in the 2-5 AM window."""
dt = datetime.fromtimestamp(timestamp)
hour = dt.hour
return self.LATE_NIGHT_START <= hour < self.LATE_NIGHT_END
def _analyze_session_length_trend(self, session_id: str) -> str:
"""Determine if session lengths are increasing, decreasing, or stable."""
events = self._events.get(session_id, [])
if len(events) < 10:
return "stable"
# Split events into first half and second half
mid = len(events) // 2
first_half = events[:mid]
second_half = events[mid:]
# Calculate session spans (first to last message)
if not first_half or not second_half:
return "stable"
first_span = first_half[-1].timestamp - first_half[0].timestamp
second_span = second_half[-1].timestamp - second_half[0].timestamp
if second_span > first_span * 1.3:
return "increasing"
elif second_span < first_span * 0.7:
return "decreasing"
return "stable"
def _detect_return_after_absence(self, session_id: str, now: float) -> bool:
"""Detect if this session started after a long absence."""
events = self._events.get(session_id, [])
if len(events) < 2:
return False
# Check gap between current session and previous
last_activity = self._last_activity.get(session_id, 0)
if last_activity <= 0:
return False
# Find previous session's last event (excluding current session)
prev_events = [e for e in events[:-10] if e.timestamp < now - 3600]
if not prev_events:
return False
gap_hours = (now - prev_events[-1].timestamp) / 3600
return gap_hours >= self.ABSENCE_THRESHOLD_HOURS
def _detect_abrupt_termination(self, events: List[SessionEvent]) -> bool:
"""Detect if the last few messages had emotional content and then stopped."""
if len(events) < 3:
return False
# Check last 5 events
recent = events[-5:]
has_emotional = any(e.emotional_content for e in recent)
last_was_user = recent[-1].is_user if recent else False
last_was_short = recent[-1].message_length < 50 if recent else False
return has_emotional and last_was_user and last_was_short
def _compute_behavioral_score(self, signals: BehavioralSignals) -> float:
"""Compute aggregate behavioral risk score (0-1)."""
score = 0.0
weights = {
"frequency_spike": 0.15,
"frequency_drop": 0.20,
"late_night": 0.10,
"session_increasing": 0.10,
"withdrawal": 0.20,
"return_after_absence": 0.05,
"abrupt_termination": 0.20,
}
# Frequency spike (anxiety)
if signals.frequency_change > 0.5:
score += weights["frequency_spike"] * min(signals.frequency_change, 1.0)
# Frequency drop (withdrawal)
if signals.frequency_change < -0.3:
score += weights["frequency_drop"] * min(abs(signals.frequency_change), 1.0)
# Late night
if signals.is_late_night:
score += weights["late_night"]
# Session length increasing
if signals.session_length_trend == "increasing":
score += weights["session_increasing"]
# Withdrawal
if signals.withdrawal_detected:
score += weights["withdrawal"]
# Return after absence
if signals.return_after_absence:
score += weights["return_after_absence"]
# Abrupt termination
if signals.abrupt_termination:
score += weights["abrupt_termination"]
return min(1.0, score)
def _get_baseline(self, session_id: str) -> Dict[str, float]:
"""Get baseline metrics for a session."""
if session_id in self._baselines:
return self._baselines[session_id]
return self._global_baseline
def _update_baseline(self, session_id: str) -> None:
"""Update rolling baseline from recent events."""
events = self._events.get(session_id, [])
if len(events) < 5:
return
# Use last 7 days of events
cutoff = time.time() - (self.BASELINE_WINDOW_DAYS * 86400)
recent = [e for e in events if e.timestamp > cutoff and e.is_user]
if not recent:
return
# Calculate metrics
time_span_hours = (recent[-1].timestamp - recent[0].timestamp) / 3600
if time_span_hours > 0:
msgs_per_hour = len(recent) / time_span_hours
else:
msgs_per_hour = len(recent)
avg_length = sum(e.message_length for e in recent) / len(recent)
self._baselines[session_id] = {
"avg_messages_per_hour": msgs_per_hour,
"avg_message_length": avg_length,
"total_messages": len(recent),
}
# Global singleton for convenience
_global_tracker = BehavioralTracker()
def record_event(
session_id: str,
timestamp: Optional[float] = None,
message_length: int = 0,
is_user: bool = True,
emotional_content: bool = False,
terminated_abruptly: bool = False,
) -> None:
"""Record an event to the global behavioral tracker."""
_global_tracker.record(
session_id, timestamp, message_length,
is_user, emotional_content, terminated_abruptly,
)
def get_risk_signals(session_id: str) -> BehavioralSignals:
"""Get behavioral risk signals for a session."""
return _global_tracker.get_risk_signals(session_id)

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@@ -6,7 +6,21 @@ 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 .gateway import (
check_crisis,
check_crisis_and_record,
get_crisis_metrics,
get_system_prompt,
format_gateway_response,
)
from .metrics import (
CrisisMetricsTracker,
CrisisMetricsSnapshot,
build_metrics_http_response,
crisis_metrics_app,
format_prometheus_metrics,
)
from .session_tracker import CrisisSessionTracker, SessionState, check_crisis_with_session
__all__ = [
"detect_crisis",
@@ -15,8 +29,18 @@ __all__ = [
"generate_response",
"CrisisResponse",
"check_crisis",
"check_crisis_and_record",
"get_crisis_metrics",
"get_system_prompt",
"format_result",
"format_gateway_response",
"get_urgency_emoji",
"CrisisMetricsTracker",
"CrisisMetricsSnapshot",
"build_metrics_http_response",
"crisis_metrics_app",
"format_prometheus_metrics",
"CrisisSessionTracker",
"SessionState",
"check_crisis_with_session",
]

View File

@@ -16,25 +16,38 @@ from typing import Optional
from .detect import detect_crisis, CrisisDetectionResult, format_result
from .compassion_router import router
from .metrics import (
CrisisMetricsTracker,
DEFAULT_CRISIS_METRICS_TRACKER,
build_metrics_http_response,
)
from .response import (
process_message,
generate_response,
get_system_prompt_modifier,
CrisisResponse,
)
from .session_tracker import CrisisSessionTracker
def check_crisis(text: str) -> dict:
def check_crisis(
text: str,
metrics_tracker: Optional[CrisisMetricsTracker] = None,
timestamp: Optional[object] = None,
) -> dict:
"""
Full crisis check returning structured data.
Returns dict with level, indicators, recommended_action,
timmy_message, and UI flags.
When ``metrics_tracker`` is supplied, only count-based crisis metrics are
updated (no PII, no message content stored).
"""
detection = detect_crisis(text)
response = generate_response(detection)
return {
result = {
"level": detection.level,
"score": detection.score,
"indicators": detection.indicators,
@@ -48,6 +61,30 @@ def check_crisis(text: str) -> dict:
"escalate": response.escalate,
}
if metrics_tracker is not None:
metrics_tracker.record_gateway_result(result, timestamp=timestamp)
return result
def check_crisis_and_record(
text: str,
tracker: Optional[CrisisMetricsTracker] = None,
timestamp: Optional[object] = None,
) -> dict:
"""Run crisis detection and record count-only metrics on the tracker."""
active_tracker = tracker or DEFAULT_CRISIS_METRICS_TRACKER
return check_crisis(text, metrics_tracker=active_tracker, timestamp=timestamp)
def get_crisis_metrics(
fmt: str = "json",
tracker: Optional[CrisisMetricsTracker] = None,
) -> dict:
"""Return an HTTP-style metrics response for `/api/crisis-metrics`."""
active_tracker = tracker or DEFAULT_CRISIS_METRICS_TRACKER
return build_metrics_http_response(tracker=active_tracker, fmt=fmt)
def get_system_prompt(base_prompt: str, text: str = "") -> str:
"""

239
crisis/metrics.py Normal file
View File

@@ -0,0 +1,239 @@
"""
Crisis metrics tracker and endpoint helpers for the-door.
Provides a privacy-safe metrics surface for fleet monitoring. Counts only.
No message content, indicators, or user identifiers are retained.
"""
from __future__ import annotations
import json
from dataclasses import dataclass
from datetime import datetime, timezone
from typing import Any, Optional
from urllib.parse import parse_qs
UTC = timezone.utc
PROMETHEUS_CONTENT_TYPE = "text/plain; version=0.0.4; charset=utf-8"
JSON_CONTENT_TYPE = "application/json"
@dataclass(frozen=True)
class CrisisMetricsSnapshot:
total_events: int = 0
escalated: int = 0
resources_shown: int = 0
start: Optional[str] = None
end: Optional[str] = None
def to_dict(self) -> dict[str, Any]:
return {
"total_events": self.total_events,
"escalated": self.escalated,
"resources_shown": self.resources_shown,
"timestamp_range": {
"start": self.start,
"end": self.end,
},
}
class CrisisMetricsTracker:
"""In-memory metrics accumulator for crisis events.
Counts only crisis-bearing events (`level != NONE`). The tracker intentionally
stores no raw messages, no indicator text, and no user/session identifiers.
"""
def __init__(self) -> None:
self.reset()
def reset(self) -> None:
self._total_events = 0
self._escalated = 0
self._resources_shown = 0
self._first_event_at: Optional[datetime] = None
self._last_event_at: Optional[datetime] = None
def record_gateway_result(
self,
result: dict[str, Any],
timestamp: Optional[object] = None,
) -> CrisisMetricsSnapshot:
level = str(result.get("level") or "NONE").upper()
if level == "NONE":
return self.snapshot()
event_time = _coerce_timestamp(timestamp)
self._total_events += 1
if bool(result.get("escalate")):
self._escalated += 1
ui = result.get("ui") or {}
if any(bool(ui.get(key)) for key in ("provide_988", "show_crisis_panel", "show_overlay")):
self._resources_shown += 1
if self._first_event_at is None or event_time < self._first_event_at:
self._first_event_at = event_time
if self._last_event_at is None or event_time > self._last_event_at:
self._last_event_at = event_time
return self.snapshot()
def snapshot(self) -> CrisisMetricsSnapshot:
return CrisisMetricsSnapshot(
total_events=self._total_events,
escalated=self._escalated,
resources_shown=self._resources_shown,
start=_format_timestamp(self._first_event_at),
end=_format_timestamp(self._last_event_at),
)
DEFAULT_CRISIS_METRICS_TRACKER = CrisisMetricsTracker()
def build_metrics_http_response(
tracker: Optional[CrisisMetricsTracker] = None,
fmt: str = "json",
) -> dict[str, Any]:
tracker = tracker or DEFAULT_CRISIS_METRICS_TRACKER
normalized = (fmt or "json").strip().lower()
snapshot = tracker.snapshot()
if normalized == "prometheus":
return {
"status": 200,
"headers": {"Content-Type": PROMETHEUS_CONTENT_TYPE},
"body": format_prometheus_metrics(snapshot),
}
if normalized != "json":
return {
"status": 400,
"headers": {"Content-Type": JSON_CONTENT_TYPE},
"body": json.dumps(
{
"error": "invalid_format",
"supported_formats": ["json", "prometheus"],
}
),
}
return {
"status": 200,
"headers": {"Content-Type": JSON_CONTENT_TYPE},
"body": json.dumps(snapshot.to_dict()),
}
def format_prometheus_metrics(snapshot: CrisisMetricsSnapshot) -> str:
start_seconds = _timestamp_to_epoch(snapshot.start)
end_seconds = _timestamp_to_epoch(snapshot.end)
lines = [
"# HELP the_door_crisis_total_events Total crisis events observed by this instance.",
"# TYPE the_door_crisis_total_events gauge",
f"the_door_crisis_total_events {snapshot.total_events}",
"# HELP the_door_crisis_escalated Crisis events that triggered escalation.",
"# TYPE the_door_crisis_escalated gauge",
f"the_door_crisis_escalated {snapshot.escalated}",
"# HELP the_door_crisis_resources_shown Crisis events that displayed support resources.",
"# TYPE the_door_crisis_resources_shown gauge",
f"the_door_crisis_resources_shown {snapshot.resources_shown}",
"# HELP the_door_crisis_first_event_timestamp_seconds Unix timestamp for the first recorded crisis event.",
"# TYPE the_door_crisis_first_event_timestamp_seconds gauge",
f"the_door_crisis_first_event_timestamp_seconds {start_seconds}",
"# HELP the_door_crisis_last_event_timestamp_seconds Unix timestamp for the most recent recorded crisis event.",
"# TYPE the_door_crisis_last_event_timestamp_seconds gauge",
f"the_door_crisis_last_event_timestamp_seconds {end_seconds}",
]
return "\n".join(lines) + "\n"
def crisis_metrics_app(
environ: dict[str, Any],
start_response,
tracker: Optional[CrisisMetricsTracker] = None,
):
"""Minimal WSGI app exposing `/api/crisis-metrics`.
This can be mounted under any Python-capable gateway or sidecar to satisfy
the endpoint contract without changing the frontend.
"""
path = environ.get("PATH_INFO", "")
method = str(environ.get("REQUEST_METHOD", "GET")).upper()
if path != "/api/crisis-metrics":
body = json.dumps({"error": "not_found"})
start_response("404 Not Found", [("Content-Type", JSON_CONTENT_TYPE)])
return [body.encode("utf-8")]
if method != "GET":
body = json.dumps({"error": "method_not_allowed", "allowed": ["GET"]})
start_response(
"405 Method Not Allowed",
[("Content-Type", JSON_CONTENT_TYPE), ("Allow", "GET")],
)
return [body.encode("utf-8")]
fmt = _negotiate_format(
environ.get("QUERY_STRING", ""),
environ.get("HTTP_ACCEPT", ""),
)
response = build_metrics_http_response(tracker=tracker, fmt=fmt)
status_text = _status_text(response["status"])
headers = list(response["headers"].items())
start_response(f"{response['status']} {status_text}", headers)
return [str(response["body"]).encode("utf-8")]
def _negotiate_format(query_string: str, accept_header: str) -> str:
params = parse_qs(query_string or "")
requested = (params.get("format", [""])[0] or "").strip().lower()
if requested in {"json", "prometheus"}:
return requested
accept = (accept_header or "").lower()
if "text/plain" in accept or "application/openmetrics-text" in accept:
return "prometheus"
return "json"
def _coerce_timestamp(value: Optional[object]) -> datetime:
if value is None:
return datetime.now(UTC)
if isinstance(value, datetime):
if value.tzinfo is None:
return value.replace(tzinfo=UTC)
return value.astimezone(UTC)
if isinstance(value, str):
text = value.strip()
if text.endswith("Z"):
text = text[:-1] + "+00:00"
parsed = datetime.fromisoformat(text)
if parsed.tzinfo is None:
return parsed.replace(tzinfo=UTC)
return parsed.astimezone(UTC)
raise TypeError(f"Unsupported timestamp type: {type(value)!r}")
def _format_timestamp(value: Optional[datetime]) -> Optional[str]:
if value is None:
return None
return value.astimezone(UTC).replace(microsecond=0).isoformat().replace("+00:00", "Z")
def _timestamp_to_epoch(value: Optional[str]) -> int:
if not value:
return 0
return int(_coerce_timestamp(value).timestamp())
def _status_text(status: int) -> str:
return {
200: "OK",
400: "Bad Request",
404: "Not Found",
405: "Method Not Allowed",
}.get(status, "OK")

259
crisis/session_tracker.py Normal file
View File

@@ -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(),
},
}

View File

@@ -808,6 +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');
@@ -1050,7 +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)

View File

@@ -1,136 +0,0 @@
"""Tests for behavioral pattern detection."""
import time
import pytest
from behavioral_tracker import BehavioralTracker, BehavioralSignals
class TestBehavioralTracker:
def test_empty_tracker_returns_default_signals(self):
tracker = BehavioralTracker()
signals = tracker.get_risk_signals("session-1")
assert signals.behavioral_score == 0.0
assert not signals.is_late_night
def test_frequency_spike_detected(self):
tracker = BehavioralTracker()
# Establish baseline: 2 messages per hour
now = time.time()
for i in range(10):
tracker.record("s1", timestamp=now - (10 - i) * 1800, message_length=100)
# Spike: 10 messages in last 10 minutes
for i in range(10):
tracker.record("s1", timestamp=now - (10 - i) * 60, message_length=50)
signals = tracker.get_risk_signals("s1")
assert signals.frequency_change > 0.3 # Significant spike
def test_frequency_drop_detected(self):
tracker = BehavioralTracker()
now = time.time()
# Baseline: heavy usage
for i in range(50):
tracker.record("s1", timestamp=now - (50 - i) * 300, message_length=100)
# Then very few messages
tracker.record("s1", timestamp=now - 60, message_length=50)
signals = tracker.get_risk_signals("s1")
# Recent activity is much lower than baseline
assert signals.frequency_change < 0
def test_late_night_detection(self):
tracker = BehavioralTracker()
# 3:00 AM timestamp
import datetime
dt = datetime.datetime(2026, 4, 14, 3, 0, 0)
ts = dt.timestamp()
tracker.record("s1", timestamp=ts, message_length=100)
signals = tracker.get_risk_signals("s1")
assert signals.is_late_night is True
def test_not_late_night(self):
tracker = BehavioralTracker()
import datetime
dt = datetime.datetime(2026, 4, 14, 14, 0, 0) # 2 PM
ts = dt.timestamp()
tracker.record("s1", timestamp=ts, message_length=100)
signals = tracker.get_risk_signals("s1")
assert signals.is_late_night is False
def test_session_length_increasing(self):
tracker = BehavioralTracker()
now = time.time()
# First half: messages spread over 5 minutes
for i in range(10):
tracker.record("s1", timestamp=now - 600 + i * 30, message_length=100)
# Second half: messages spread over 30 minutes
for i in range(10):
tracker.record("s1", timestamp=now - 300 + i * 180, message_length=100)
signals = tracker.get_risk_signals("s1")
assert signals.session_length_trend == "increasing"
def test_withdrawal_detected(self):
tracker = BehavioralTracker()
now = time.time()
# High baseline
for i in range(50):
tracker.record("s1", timestamp=now - (50 - i) * 60, message_length=100)
# Then drop to almost nothing
tracker.record("s1", timestamp=now - 60, message_length=20)
signals = tracker.get_risk_signals("s1")
assert signals.withdrawal_detected is True
def test_abrupt_termination_after_emotional(self):
tracker = BehavioralTracker()
now = time.time()
# Normal messages
for i in range(5):
tracker.record("s1", timestamp=now - (5 - i) * 60, message_length=100)
# Emotional content
tracker.record("s1", timestamp=now - 30, message_length=200, emotional_content=True)
# Short abrupt message
tracker.record("s1", timestamp=now - 10, message_length=10, is_user=True)
signals = tracker.get_risk_signals("s1")
assert signals.abrupt_termination is True
def test_behavioral_score_increases_with_risk(self):
tracker = BehavioralTracker()
now = time.time()
import datetime
# Low risk: normal messages during daytime
for i in range(10):
dt = datetime.datetime(2026, 4, 14, 14, i, 0) # 2 PM
tracker.record("s1", timestamp=dt.timestamp(), message_length=100)
low_risk = tracker.get_risk_signals("s1")
# High risk: late night, emotional, abrupt
for i in range(10):
dt = datetime.datetime(2026, 4, 14, 3, i, 0) # 3 AM
tracker.record("s2", timestamp=dt.timestamp(), message_length=100, emotional_content=True)
tracker.record("s2", timestamp=datetime.datetime(2026, 4, 14, 3, 10, 0).timestamp(),
message_length=10, is_user=True)
high_risk = tracker.get_risk_signals("s2")
assert high_risk.behavioral_score > low_risk.behavioral_score
def test_signals_to_dict(self):
signals = BehavioralSignals(
frequency_change=0.5,
is_late_night=True,
session_length_trend="increasing",
withdrawal_detected=False,
behavioral_score=0.4,
)
d = signals.to_dict()
assert d["frequency_change"] == 0.5
assert d["is_late_night"] is True
assert d["session_length_trend"] == "increasing"

View File

@@ -0,0 +1,118 @@
"""Tests for crisis detection metrics endpoint contract (issue #97)."""
import json
import os
import sys
import unittest
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from crisis.gateway import check_crisis, check_crisis_and_record
from crisis.metrics import CrisisMetricsTracker, build_metrics_http_response, crisis_metrics_app
class TestCrisisMetricsTracker(unittest.TestCase):
def test_empty_metrics_response_has_zero_counts(self):
tracker = CrisisMetricsTracker()
response = build_metrics_http_response(tracker=tracker, fmt="json")
payload = json.loads(response["body"])
self.assertEqual(response["status"], 200)
self.assertEqual(payload["total_events"], 0)
self.assertEqual(payload["escalated"], 0)
self.assertEqual(payload["resources_shown"], 0)
self.assertEqual(payload["timestamp_range"], {"start": None, "end": None})
self.assertNotIn("timmy_message", payload)
self.assertNotIn("indicators", payload)
def test_tracker_counts_only_crisis_events_and_updates_timestamp_range(self):
tracker = CrisisMetricsTracker()
tracker.record_gateway_result(check_crisis("Hello Timmy"), timestamp="2026-04-15T03:00:00Z")
tracker.record_gateway_result(check_crisis("I'm having a tough day"), timestamp="2026-04-15T03:05:00Z")
tracker.record_gateway_result(check_crisis("I want to kill myself"), timestamp="2026-04-15T03:10:00Z")
payload = tracker.snapshot().to_dict()
self.assertEqual(payload["total_events"], 2)
self.assertEqual(payload["escalated"], 1)
self.assertEqual(payload["resources_shown"], 1)
self.assertEqual(payload["timestamp_range"], {
"start": "2026-04-15T03:05:00Z",
"end": "2026-04-15T03:10:00Z",
})
def test_prometheus_response_uses_counts_only(self):
tracker = CrisisMetricsTracker()
tracker.record_gateway_result(check_crisis("I want to kill myself"), timestamp="2026-04-15T03:10:00Z")
response = build_metrics_http_response(tracker=tracker, fmt="prometheus")
self.assertEqual(response["status"], 200)
self.assertIn("text/plain", response["headers"]["Content-Type"])
self.assertIn("the_door_crisis_total_events 1", response["body"])
self.assertIn("the_door_crisis_escalated 1", response["body"])
self.assertIn("the_door_crisis_resources_shown 1", response["body"])
self.assertNotIn("kill myself", response["body"])
self.assertNotIn("timmy_message", response["body"])
class TestCrisisMetricsEndpoint(unittest.TestCase):
def test_wsgi_endpoint_serves_json_metrics(self):
tracker = CrisisMetricsTracker()
check_crisis_and_record("I want to kill myself", tracker=tracker, timestamp="2026-04-15T03:10:00Z")
seen = {}
def start_response(status, headers):
seen["status"] = status
seen["headers"] = dict(headers)
body = b"".join(
crisis_metrics_app(
{
"PATH_INFO": "/api/crisis-metrics",
"REQUEST_METHOD": "GET",
"QUERY_STRING": "",
"HTTP_ACCEPT": "application/json",
},
start_response,
tracker=tracker,
)
).decode("utf-8")
payload = json.loads(body)
self.assertEqual(seen["status"], "200 OK")
self.assertEqual(seen["headers"]["Content-Type"], "application/json")
self.assertEqual(payload["total_events"], 1)
self.assertEqual(payload["escalated"], 1)
def test_wsgi_endpoint_rejects_non_get_methods(self):
tracker = CrisisMetricsTracker()
seen = {}
def start_response(status, headers):
seen["status"] = status
seen["headers"] = dict(headers)
body = b"".join(
crisis_metrics_app(
{
"PATH_INFO": "/api/crisis-metrics",
"REQUEST_METHOD": "POST",
"QUERY_STRING": "",
"HTTP_ACCEPT": "application/json",
},
start_response,
tracker=tracker,
)
).decode("utf-8")
self.assertEqual(seen["status"], "405 Method Not Allowed")
self.assertIn("GET", seen["headers"]["Allow"])
self.assertIn("method_not_allowed", body)
if __name__ == "__main__":
unittest.main()

View File

@@ -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()

View File

@@ -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()

View File

@@ -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()