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fix/135
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fix/131-vo
| Author | SHA1 | Date | |
|---|---|---|---|
| dd38f362d6 |
142
augmentation.py
142
augmentation.py
@@ -1,142 +0,0 @@
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"""Local-only counselor augmentation helpers for the-door."""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import List
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import re
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from crisis.detect import detect_crisis
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@dataclass(frozen=True)
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class SignalGuide:
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label: str
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patterns: List[str]
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talking_point: str
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deescalation: str
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follow_up: str
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@dataclass
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class CounselorAugmentation:
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risk_level: str
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risk_score: int
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signals: List[str]
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suggested_talking_points: List[str]
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deescalation_techniques: List[str]
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follow_up_prompt: str
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operator_notice: str
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local_only: bool = True
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advisory_only: bool = True
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SIGNAL_GUIDES: List[SignalGuide] = [
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SignalGuide(
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label="Explicit self-harm intent",
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patterns=[
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r"\bkill\s*(my)?self\b",
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r"\bend\s*my\s*life\b",
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r"\bwrote\s+a\s+suicide\s*(?:note|letter)\b",
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r"\bgoing\s+to\s+(?:kill\s+myself|die)\b",
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],
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talking_point="Ask directly whether they are safe right now and keep the next question concrete.",
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deescalation="Move to immediate safety: ask about means, people nearby, and whether they can call or text 988 now.",
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follow_up="You said you're ready to die. Are you alone right now, and can you tell me what is within reach?",
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),
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SignalGuide(
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label="Hopelessness / collapse",
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patterns=[
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r"\bhopeless\b",
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r"\bcan'?t\s+go\s+on\b",
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r"\bno\s+future\b",
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r"\bnothing\s+left\b",
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],
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talking_point="Reflect the hopelessness plainly before offering options. Avoid arguing with the feeling.",
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deescalation="Narrow the time horizon: focus on the next ten minutes, one breath, one call, one person.",
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follow_up="You said things feel hopeless. What feels most dangerous about the next hour?",
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),
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SignalGuide(
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label="Isolation / burden",
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patterns=[
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r"\bnobody\s+cares\b",
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r"\bbetter\s+off\s+without\s+me\b",
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r"\balone\b",
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r"\bburden\b",
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],
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talking_point="Counter isolation with immediacy: name one real person or service they can contact now.",
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deescalation="Invite a tiny reconnection step: text one safe person, unlock the door, move closer to others, or stay in the chat.",
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follow_up="You said you feel alone. Who is the safest real person we could bring into this moment with you?",
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),
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SignalGuide(
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label="Overwhelm / panic",
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patterns=[
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r"\bdesperate\b",
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r"\boverwhelm(?:ed|ing)\b",
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r"\btrapped\b",
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r"\bpanic\b",
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],
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talking_point="Offer one regulating action at a time instead of a list. Slow the pace of the chat.",
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deescalation="Ground in the room: feet on the floor, name five visible objects, one sip of water, one slow exhale.",
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follow_up="You said this feels overwhelming. What is the smallest thing in the room you can touch right now?",
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),
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]
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class CounselorAugmentationEngine:
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BASE_SCORES = {
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"NONE": 5,
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"LOW": 25,
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"MEDIUM": 55,
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"HIGH": 75,
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"CRITICAL": 95,
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}
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def _matched_guides(self, text: str) -> List[SignalGuide]:
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lowered = text.lower()
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matched: List[SignalGuide] = []
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for guide in SIGNAL_GUIDES:
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if any(re.search(pattern, lowered) for pattern in guide.patterns):
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matched.append(guide)
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return matched
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def build_augmented_guidance(self, text: str, assistant_text: str = "") -> CounselorAugmentation:
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detection = detect_crisis(text)
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guides = self._matched_guides(text)
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risk_level = detection.level
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signals = [guide.label for guide in guides]
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if risk_level == "CRITICAL" and "Explicit self-harm intent" not in signals:
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signals.insert(0, "Explicit self-harm intent")
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risk_score = self.BASE_SCORES.get(risk_level, 5) + min(len(signals) * 5, 10)
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if risk_level == "CRITICAL":
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risk_score = max(risk_score, 95)
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talking_points = [guide.talking_point for guide in guides] or [
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"Keep the response advisory and grounded in immediate safety, not abstract reassurance."
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]
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deescalation = [guide.deescalation for guide in guides] or [
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"Use short sentences, slow the conversation, and invite one concrete grounding step."
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]
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quote = text.strip().replace("\n", " ")[:120]
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follow_up = (guides[0].follow_up if guides else "What feels most dangerous or heavy for you right now?")
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follow_up_prompt = f'You said "{quote}". Consider following up with: {follow_up}'
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if assistant_text and "988" not in assistant_text and risk_level in {"HIGH", "CRITICAL"}:
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talking_points.append("Surface 988 or Crisis Text Line explicitly if the assistant has not already done so.")
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return CounselorAugmentation(
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risk_level=risk_level,
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risk_score=min(risk_score, 100),
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signals=signals,
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suggested_talking_points=talking_points,
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deescalation_techniques=deescalation,
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follow_up_prompt=follow_up_prompt,
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operator_notice="Local-only advisory. This never replaces human judgment.",
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)
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def build_augmented_guidance(text: str, assistant_text: str = "") -> CounselorAugmentation:
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return CounselorAugmentationEngine().build_augmented_guidance(text, assistant_text=assistant_text)
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280
index.html
280
index.html
@@ -241,105 +241,6 @@ html, body {
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opacity: 0.5;
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}
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/* ===== OPERATOR AUGMENTATION SIDEBAR ===== */
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#augmentation-toggle {
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margin: 10px 16px 0;
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padding: 8px 12px;
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border-radius: 999px;
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border: 1px solid #5b6b7a;
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background: #11161d;
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color: #b9c7d5;
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font-size: 0.9rem;
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cursor: pointer;
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}
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#augmentation-toggle.active {
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border-color: #b388ff;
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color: #e2d4ff;
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background: #1a1324;
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}
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#augmentation-sidebar {
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position: fixed;
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top: 90px;
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right: 16px;
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width: 320px;
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max-height: calc(100vh - 120px);
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overflow-y: auto;
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background: #11161d;
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border: 1px solid #30363d;
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border-left: 3px solid #b388ff;
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border-radius: 8px;
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padding: 14px;
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box-shadow: 0 12px 32px rgba(0,0,0,0.35);
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display: none;
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z-index: 70;
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}
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#augmentation-sidebar.visible {
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display: block;
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}
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#augmentation-sidebar .augmentation-heading {
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color: #d2b8ff;
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font-size: 0.78rem;
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letter-spacing: 0.08em;
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margin-bottom: 10px;
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}
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#augmentation-risk-score {
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color: #fff;
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font-size: 1rem;
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font-weight: 700;
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margin-bottom: 10px;
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}
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#augmentation-sidebar .augmentation-section {
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margin-top: 10px;
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}
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#augmentation-sidebar .augmentation-section h3 {
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color: #c9d1d9;
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font-size: 0.78rem;
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margin: 0 0 6px;
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text-transform: uppercase;
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letter-spacing: 0.04em;
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}
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#augmentation-sidebar ul {
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margin: 0;
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padding-left: 18px;
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color: #b9c7d5;
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font-size: 0.9rem;
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line-height: 1.45;
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}
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#augmentation-follow-up,
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#augmentation-notice {
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color: #b9c7d5;
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font-size: 0.9rem;
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line-height: 1.45;
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margin: 0;
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}
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#augmentation-notice {
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color: #8b949e;
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margin-top: 12px;
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border-top: 1px solid #21262d;
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padding-top: 10px;
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}
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@media (max-width: 980px) {
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#augmentation-sidebar {
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left: 16px;
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right: 16px;
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width: auto;
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top: auto;
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bottom: 82px;
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max-height: 40vh;
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}
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}
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/* ===== CHAT AREA ===== */
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#chat-area {
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flex: 1;
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@@ -748,29 +649,6 @@ html, body {
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</div>
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</div>
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<button id="augmentation-toggle" type="button" aria-pressed="false" aria-controls="augmentation-sidebar">Operator assist: off</button>
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<aside id="augmentation-sidebar" aria-live="polite" aria-label="Local operator augmentation sidebar">
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<div class="augmentation-heading">LOCAL OPERATOR AUGMENTATION</div>
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<div id="augmentation-risk-score">Risk score: —</div>
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<div class="augmentation-section">
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<h3>Signals</h3>
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<ul id="augmentation-signals"><li>No signals yet.</li></ul>
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</div>
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<div class="augmentation-section">
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<h3>Talking points</h3>
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<ul id="augmentation-talking-points"><li>Enable operator assist to surface local advisory guidance.</li></ul>
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</div>
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<div class="augmentation-section">
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<h3>De-escalation</h3>
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<ul id="augmentation-techniques"><li>Suggestions stay local and never replace human judgment.</li></ul>
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</div>
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<div class="augmentation-section">
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<h3>Follow-up</h3>
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<p id="augmentation-follow-up">No follow-up prompt yet.</p>
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</div>
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<p id="augmentation-notice">Local-only advisory. Never replaces human judgment.</p>
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</aside>
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<!-- Chat messages -->
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<div id="chat-area" role="log" aria-label="Chat messages" aria-live="polite" tabindex="0">
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<!-- Messages inserted here -->
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@@ -802,7 +680,7 @@ html, body {
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<!-- Footer -->
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<footer id="footer">
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<a href="/about.html" aria-label="About The Door">about</a>
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<a href="/about" aria-label="About The Door">about</a>
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<button id="safety-plan-btn" aria-label="Open My Safety Plan">my safety plan</button>
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<button id="clear-chat-btn" aria-label="Clear chat history">clear chat</button>
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</footer>
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@@ -928,14 +806,6 @@ Sovereignty and service always.`;
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var sendBtn = document.getElementById('send-btn');
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var typingIndicator = document.getElementById('typing-indicator');
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var crisisPanel = document.getElementById('crisis-panel');
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var augmentationToggle = document.getElementById('augmentation-toggle');
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var augmentationSidebar = document.getElementById('augmentation-sidebar');
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var augmentationRiskScore = document.getElementById('augmentation-risk-score');
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var augmentationSignals = document.getElementById('augmentation-signals');
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var augmentationTalkingPoints = document.getElementById('augmentation-talking-points');
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var augmentationTechniques = document.getElementById('augmentation-techniques');
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var augmentationFollowUp = document.getElementById('augmentation-follow-up');
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var augmentationNotice = document.getElementById('augmentation-notice');
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var crisisOverlay = document.getElementById('crisis-overlay');
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var overlayDismissBtn = document.getElementById('overlay-dismiss-btn');
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var overlayCallLink = document.querySelector('.overlay-call');
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@@ -956,8 +826,6 @@ Sovereignty and service always.`;
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var isStreaming = false;
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var overlayTimer = null;
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var crisisPanelShown = false;
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var lastUserMessage = '';
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var augmentationEnabled = false;
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// ===== SERVICE WORKER =====
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if ('serviceWorker' in navigator) {
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@@ -1115,142 +983,6 @@ Sovereignty and service always.`;
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}
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function escapeHtml(text) {
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return String(text || '')
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.replace(/&/g, '&')
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.replace(/</g, '<')
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.replace(/>/g, '>')
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.replace(/"/g, '"')
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.replace(/'/g, ''');
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}
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var AUGMENTATION_SIGNAL_GUIDES = [
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{
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label: 'Explicit self-harm intent',
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patterns: [/kill\s*(my)?self/i, /end\s*my\s*life/i, /suicide\s*(note|letter)/i, /going\s+to\s+(kill\s+myself|die)/i],
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talkingPoint: 'Ask directly whether they are safe right now and keep the next question concrete.',
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technique: 'Move to immediate safety: ask about means, people nearby, and whether 988 can be called or texted now.',
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followUp: 'You said you might die tonight. Are you alone right now, and what is within reach?'
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},
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{
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label: 'Hopelessness / collapse',
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patterns: [/hopeless/i, /can'?t\s+go\s+on/i, /no\s+future/i, /nothing\s+left/i],
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talkingPoint: 'Reflect the hopelessness plainly before offering options. Avoid arguing with the feeling.',
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technique: 'Narrow the time horizon to the next ten minutes and one immediate action.',
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followUp: 'You said things feel hopeless. What feels most dangerous about the next hour?'
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},
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{
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label: 'Isolation / burden',
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patterns: [/nobody\s+cares/i, /better\s+off\s+without\s+me/i, /\balone\b/i, /\bburden\b/i],
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talkingPoint: 'Counter isolation with one real contact point: a person, 988, or Crisis Text Line.',
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technique: 'Invite a tiny reconnection step: text one safe person, unlock the door, or stay in the chat.',
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followUp: 'You said you feel alone. Who is the safest real person we could bring into this moment with you?'
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},
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{
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label: 'Overwhelm / panic',
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patterns: [/desperate/i, /overwhelm(?:ed|ing)/i, /trapped/i, /panic/i],
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talkingPoint: 'Offer one regulating step at a time instead of a long list.',
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technique: 'Ground in the room: feet on the floor, name five visible objects, one sip of water, one slow exhale.',
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followUp: 'You said this feels overwhelming. What is the smallest thing in the room you can touch right now?'
|
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}
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];
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function deriveAugmentationSignals(userText) {
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var text = (userText || '').toLowerCase();
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return AUGMENTATION_SIGNAL_GUIDES.filter(function(guide) {
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return guide.patterns.some(function(pattern) { return pattern.test(text); });
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});
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}
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function buildAugmentationState(userText, assistantText) {
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var text = userText || '';
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var guides = deriveAugmentationSignals(text);
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var level = getCrisisLevel(userText);
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var signals = guides.map(function(guide) { return guide.label; });
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var explicitIntent = signals.indexOf('Explicit self-harm intent') !== -1;
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var riskLevel = explicitIntent ? 'CRITICAL' : (level === 2 ? 'CRITICAL' : level === 1 ? 'HIGH' : (guides.length ? 'LOW' : 'NONE'));
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var riskScore = riskLevel === 'CRITICAL' ? 95 : riskLevel === 'HIGH' ? 75 : riskLevel === 'LOW' ? 25 : 5;
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riskScore = Math.min(100, riskScore + Math.min(guides.length * 5, 10));
|
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if (riskLevel === 'CRITICAL' && signals.indexOf('Explicit self-harm intent') === -1) {
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signals.unshift('Explicit self-harm intent');
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riskScore = Math.max(riskScore, 95);
|
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}
|
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|
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var talkingPoints = guides.map(function(guide) { return guide.talkingPoint; });
|
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var techniques = guides.map(function(guide) { return guide.technique; });
|
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if (!talkingPoints.length) {
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talkingPoints = ['Keep the response advisory, local-only, and focused on immediate safety rather than abstract reassurance.'];
|
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}
|
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if (!techniques.length) {
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techniques = ['Slow the pace. Use short sentences. Invite one concrete grounding step.'];
|
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}
|
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if ((assistantText || '').indexOf('988') === -1 && (riskLevel === 'HIGH' || riskLevel === 'CRITICAL')) {
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talkingPoints.push('Surface 988 or Crisis Text Line explicitly if the assistant has not already done so.');
|
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}
|
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|
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var quoted = (text || '').replace(/\s+/g, ' ').slice(0, 120);
|
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var followUp = guides.length ? guides[0].followUp : 'What feels heaviest or most dangerous for you right now?';
|
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|
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return {
|
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riskLevel: riskLevel,
|
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riskScore: riskScore,
|
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signals: signals,
|
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talkingPoints: talkingPoints,
|
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techniques: techniques,
|
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followUpPrompt: 'You said "' + quoted + '". Consider following up with: ' + followUp,
|
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operatorNotice: 'Local-only advisory. Never replaces human judgment.',
|
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localOnly: true,
|
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advisoryOnly: true
|
||||
};
|
||||
}
|
||||
|
||||
function renderAugmentationSidebar(state) {
|
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if (!augmentationSidebar) return;
|
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augmentationRiskScore.textContent = 'Risk score: ' + state.riskScore + ' / 100 (' + state.riskLevel + ')';
|
||||
augmentationSignals.innerHTML = state.signals.length
|
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? state.signals.map(function(signal) { return '<li>' + escapeHtml(signal) + '</li>'; }).join('')
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: '<li>No crisis signals detected.</li>';
|
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augmentationTalkingPoints.innerHTML = state.talkingPoints.map(function(item) { return '<li>' + escapeHtml(item) + '</li>'; }).join('');
|
||||
augmentationTechniques.innerHTML = state.techniques.map(function(item) { return '<li>' + escapeHtml(item) + '</li>'; }).join('');
|
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augmentationFollowUp.textContent = state.followUpPrompt;
|
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augmentationNotice.textContent = state.operatorNotice;
|
||||
augmentationSidebar.classList.add('visible');
|
||||
}
|
||||
|
||||
function updateAugmentationState(userText, assistantText) {
|
||||
if (!augmentationEnabled) return;
|
||||
renderAugmentationSidebar(buildAugmentationState(userText, assistantText));
|
||||
}
|
||||
|
||||
function setOperatorAugmentationEnabled(enabled) {
|
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augmentationEnabled = !!enabled;
|
||||
try { localStorage.setItem('door_operator_augmentation_enabled', augmentationEnabled ? '1' : '0'); } catch (e) {}
|
||||
if (!augmentationToggle) return;
|
||||
augmentationToggle.setAttribute('aria-pressed', augmentationEnabled ? 'true' : 'false');
|
||||
augmentationToggle.classList.toggle('active', augmentationEnabled);
|
||||
augmentationToggle.textContent = augmentationEnabled ? 'Operator assist: on' : 'Operator assist: off';
|
||||
if (!augmentationEnabled && augmentationSidebar) {
|
||||
augmentationSidebar.classList.remove('visible');
|
||||
return;
|
||||
}
|
||||
if (augmentationEnabled && lastUserMessage) {
|
||||
var lastAssistant = '';
|
||||
for (var i = messages.length - 1; i >= 0; i--) {
|
||||
if (messages[i].role === 'assistant') { lastAssistant = messages[i].content; break; }
|
||||
}
|
||||
updateAugmentationState(lastUserMessage, lastAssistant);
|
||||
}
|
||||
}
|
||||
|
||||
function loadOperatorAugmentationPreference() {
|
||||
try {
|
||||
return localStorage.getItem('door_operator_augmentation_enabled') === '1';
|
||||
} catch (e) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// ===== OVERLAY =====
|
||||
|
||||
// Focus trap: cycle through focusable elements within the crisis overlay
|
||||
@@ -1583,10 +1315,9 @@ Sovereignty and service always.`;
|
||||
|
||||
addMessage('user', text);
|
||||
messages.push({ role: 'user', content: text });
|
||||
lastUserMessage = text;
|
||||
var lastUserMessage = text;
|
||||
|
||||
checkCrisis(text);
|
||||
updateAugmentationState(text, '');
|
||||
|
||||
msgInput.value = '';
|
||||
msgInput.style.height = 'auto';
|
||||
@@ -1675,7 +1406,6 @@ Sovereignty and service always.`;
|
||||
messages.push({ role: 'assistant', content: fullText });
|
||||
saveMessages();
|
||||
checkCrisis(fullText);
|
||||
updateAugmentationState(lastUserMessage || '', fullText);
|
||||
}
|
||||
isStreaming = false;
|
||||
sendBtn.disabled = msgInput.value.trim().length === 0;
|
||||
@@ -1702,11 +1432,6 @@ Sovereignty and service always.`;
|
||||
});
|
||||
|
||||
sendBtn.addEventListener('click', sendMessage);
|
||||
if (augmentationToggle) {
|
||||
augmentationToggle.addEventListener('click', function() {
|
||||
setOperatorAugmentationEnabled(!augmentationEnabled);
|
||||
});
|
||||
}
|
||||
|
||||
// ===== WELCOME MESSAGE =====
|
||||
function init() {
|
||||
@@ -1726,7 +1451,6 @@ Sovereignty and service always.`;
|
||||
window.history.replaceState({}, document.title, window.location.pathname);
|
||||
}
|
||||
|
||||
setOperatorAugmentationEnabled(loadOperatorAugmentationPreference());
|
||||
msgInput.focus();
|
||||
}
|
||||
|
||||
|
||||
@@ -1,33 +0,0 @@
|
||||
from augmentation import CounselorAugmentationEngine
|
||||
|
||||
|
||||
def test_explicit_intent_forces_critical_sidebar_guidance():
|
||||
engine = CounselorAugmentationEngine()
|
||||
result = engine.build_augmented_guidance(
|
||||
"I want to kill myself tonight. I already wrote a note.",
|
||||
assistant_text="I'm here with you."
|
||||
)
|
||||
|
||||
assert result.risk_level == "CRITICAL"
|
||||
assert result.risk_score >= 90
|
||||
assert result.local_only is True
|
||||
assert result.advisory_only is True
|
||||
assert "Explicit self-harm intent" in result.signals
|
||||
assert result.suggested_talking_points
|
||||
assert result.deescalation_techniques
|
||||
assert "You said" in result.follow_up_prompt
|
||||
assert "never replaces human judgment" in result.operator_notice.lower()
|
||||
|
||||
|
||||
def test_hopelessness_signal_produces_follow_up_and_talking_points():
|
||||
engine = CounselorAugmentationEngine()
|
||||
result = engine.build_augmented_guidance(
|
||||
"I feel so hopeless about my life and I can't go on.",
|
||||
assistant_text=""
|
||||
)
|
||||
|
||||
assert result.risk_level in {"HIGH", "CRITICAL"}
|
||||
assert result.signals
|
||||
assert result.suggested_talking_points
|
||||
assert result.deescalation_techniques
|
||||
assert result.follow_up_prompt
|
||||
@@ -1,20 +0,0 @@
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def test_operator_augmentation_ui_hooks_exist():
|
||||
html = Path('index.html').read_text()
|
||||
|
||||
assert 'id="augmentation-toggle"' in html
|
||||
assert 'id="augmentation-sidebar"' in html
|
||||
assert 'id="augmentation-risk-score"' in html
|
||||
assert 'id="augmentation-signals"' in html
|
||||
assert 'id="augmentation-follow-up"' in html
|
||||
assert 'door_operator_augmentation_enabled' in html
|
||||
assert 'function buildAugmentationState(' in html
|
||||
assert 'function renderAugmentationSidebar(' in html
|
||||
assert 'function updateAugmentationState(' in html
|
||||
assert 'function setOperatorAugmentationEnabled(' in html
|
||||
assert 'function loadOperatorAugmentationPreference(' in html
|
||||
assert 'getCrisisLevel(userText)' in html
|
||||
assert "updateAugmentationState(text, '')" in html
|
||||
assert "updateAugmentationState(lastUserMessage || '', fullText)" in html
|
||||
@@ -1,26 +0,0 @@
|
||||
from pathlib import Path
|
||||
|
||||
from playwright.sync_api import sync_playwright
|
||||
|
||||
|
||||
def test_operator_augmentation_walkthrough_marks_explicit_intent_critical():
|
||||
url = Path('index.html').resolve().as_uri()
|
||||
|
||||
with sync_playwright() as p:
|
||||
browser = p.chromium.launch(headless=True)
|
||||
page = browser.new_page()
|
||||
page.goto(url, wait_until='load')
|
||||
page.click('#augmentation-toggle')
|
||||
page.fill('#msg-input', 'I want to kill myself tonight. I already wrote a note.')
|
||||
page.click('#send-btn')
|
||||
page.wait_for_timeout(300)
|
||||
|
||||
risk = page.locator('#augmentation-risk-score').inner_text()
|
||||
signals = page.locator('#augmentation-signals').inner_text()
|
||||
follow_up = page.locator('#augmentation-follow-up').inner_text()
|
||||
|
||||
browser.close()
|
||||
|
||||
assert 'CRITICAL' in risk
|
||||
assert 'Explicit self-harm intent' in signals
|
||||
assert 'You said "I want to kill myself tonight. I already wrote a note."' in follow_up
|
||||
350
voice_analysis.py
Normal file
350
voice_analysis.py
Normal file
@@ -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
|
||||
Reference in New Issue
Block a user