feat: complete production hardening implementation, specialty canonicalization, google-genai migration, voice reliability, sqlite concurrency, and test suite consolidation

ai-patient-onboarding/app/ai/safety/__init__.py

@@ -0,0 +1,8 @@
+"""
+Safety package.
+"""
+
+from app.ai.safety.emergency import check_emergency
+from app.ai.safety.crisis import check_crisis
+
+__all__ = ["check_emergency", "check_crisis"]

ai-patient-onboarding/app/ai/safety/crisis.py

@@ -0,0 +1,69 @@
+"""
+Mental health crisis and self-harm detection engine.
+"""
+
+import re
+from typing import Optional, Tuple
+
+from app.ai.prompt_rules.safety_rules import CRISIS_KEYWORDS_EN, CRISIS_KEYWORDS_INDIC
+
+
+TRANSLITERATED_CRISIS_PHRASES = [
+    "saaganam pola irukku", "uyiroda irukka virumbala", "saaga poraen", "valave pidikala",
+    "mar jane ka man", "apne aap ko nuksan", "khudkushee",
+    "chani povali", "sathokobeku",
+]
+
+
+def check_crisis(user_message: str, lang: str = "en") -> Tuple[bool, Optional[str], Optional[str]]:
+    """
+    Evaluates patient message for mental health crisis or self-harm intent.
+    Returns: (is_crisis, reason, crisis_reply)
+    """
+    if not user_message or not user_message.strip():
+        return False, None, None
+
+    # Check Indic script crisis keywords FIRST against raw message
+    for kw in CRISIS_KEYWORDS_INDIC:
+        if kw in user_message:
+            reply = _build_crisis_reply(lang)
+            return True, f"Matched Indic crisis phrase: '{kw}'", reply
+
+    indic_extra = ["காயப்படுத்திக்கணும்", "கொல்லணும்", "வாழவே பிடிக்கல", "உயிரோட இருக்க", "தற்கொலை", "உயிரை"]
+    for kw in indic_extra:
+        if kw in user_message:
+            reply = _build_crisis_reply(lang)
+            return True, f"Matched Indic crisis phrase: '{kw}'", reply
+
+    msg = user_message.strip().lower()
+    msg_clean = re.sub(r"[^\w\s]", " ", msg)
+    msg_clean = re.sub(r"\s+", " ", msg_clean)
+
+    # Check English crisis keywords
+    for kw in CRISIS_KEYWORDS_EN:
+        kw_clean = re.sub(r"[^\w\s]", " ", kw.lower())
+        if re.search(rf"\b{re.escape(kw_clean)}\b", msg_clean) or kw.lower() in msg:
+            reply = _build_crisis_reply(lang)
+            return True, f"Matched crisis phrase: '{kw}'", reply
+
+    # Check Transliterated crisis phrases
+    for kw in TRANSLITERATED_CRISIS_PHRASES:
+        if kw in msg_clean or kw in msg:
+            reply = _build_crisis_reply(lang)
+            return True, f"Matched transliterated crisis phrase: '{kw}'", reply
+
+    return False, None, None
+
+
+def _build_crisis_reply(lang: str) -> str:
+    lang_clean = lang.lower() if lang else "en"
+    if lang_clean.startswith("ta"):
+        return "உங்களுக்கு மன உளைச்சல் இருந்தால், தயவுசெய்து டெலி-மானாஸ் (Tele-MANAS) உதவி எண் 14416-ஐ தொடர்பு கொள்ளவும் அல்லது மருத்துவமனை ஊழியர்களிடம் தெரிவிக்கவும்."
+    elif lang_clean.startswith("hi"):
+        return "यदि आप परेशानी में हैं, तो कृपया तुरंत टेली-मानस (Tele-MANAS) 14416 पर संपर्क करें या अस्पताल के कर्मचारियों को सूचित करें।"
+    elif lang_clean.startswith("te"):
+        return "మీరు తీవ్రమైన ఒత్తిడిలో ఉంటే, దయచేసి టెలి-మానస్ (Tele-MANAS) 14416 కు ఫోన్ చేయండి లేదా ఆసుపత్రి సిబ్బందికి చెప్పండి."
+    elif lang_clean.startswith("kn"):
+        return "ನೀವು ಮನೋಒತ್ತಡದಲ್ಲಿದ್ದರೆ, ದಯವಿಟ್ಟು ಟೆಲಿ-ಮಾನಸ್ (Tele-MANAS) 14416 ಗೆ ಕರೆ ಮಾಡಿ ಅಥವಾ ಆಸ್ಪತ್ರೆಯ ಸಿಬ್ಬಂದಿಗೆ ತಿಳಿಸಿ."
+    else:
+        return "If you're in distress, please reach out to Tele-MANAS at 14416 or alert the hospital staff right now."

ai-patient-onboarding/app/ai/safety/emergency.py

@@ -0,0 +1,91 @@
+"""
+Emergency detection engine with strict safety precedence and false-positive protection.
+"""
+
+import re
+from typing import Optional, Tuple
+
+from app.ai.prompt_rules.safety_rules import EMERGENCY_KEYWORDS_EN, EMERGENCY_KEYWORDS_INDIC
+
+
+TRANSLITERATED_EMERGENCY_PHRASES = [
+    "nenju romba valikuthu", "nenju valla valikuthu", "nenju kadumaya valikuthu",
+    "moochu vida mudiyala", "moochu adaikuthu", "moochu thinaral",
+    "mayangi vilunthuten", "mayakkam varuthu", "paralysis vanthuruchu",
+    "cheest mein bahut dard", "seene mein bahut tej dard", "saans lene mein bahut dikkat",
+    "saans nahi aa rahi", "behosh ho gaya", "behosh ho gayi",
+    "chathi lo thivramaina noppi", "oophiri aadam ledhu", "spruha thappi",
+    "edeyalli theevra novu", "usiraadalu thumba kashta", "pragne thappi",
+]
+
+
+def check_emergency(user_message: str, lang: str = "en") -> Tuple[bool, Optional[str], Optional[str]]:
+    """
+    Evaluates patient message for medical emergency indicators.
+    Returns: (is_emergency, reason, emergency_reply)
+    """
+    if not user_message or not user_message.strip():
+        return False, None, None
+
+    # Check Indic script emergency keywords against raw user_message FIRST
+    for kw in EMERGENCY_KEYWORDS_INDIC:
+        if kw in user_message:
+            reply = _build_emergency_reply(lang)
+            return True, f"Matched Indic emergency phrase: '{kw}'", reply
+
+    # Additional Tamil/Hindi spoken emergency phrases
+    indic_extra = ["மூச்சு விட முடியல", "மூச்சு திணறல்", "நெஞ்சு வலி", "நெஞ்சு பாரம்", "கடும் நெஞ்சு வலி", "நெஞ்சு அதிகமா வலி"]
+    for kw in indic_extra:
+        if kw in user_message and any(x in user_message for x in ["மூச்சு", "கடும்", "வலி", "அதிகமா"]):
+            reply = _build_emergency_reply(lang)
+            return True, f"Matched Indic emergency phrase: '{kw}'", reply
+
+    msg = user_message.strip().lower()
+    msg_clean = re.sub(r"[^\w\s]", " ", msg)
+    msg_clean = re.sub(r"\s+", " ", msg_clean)
+
+    # False Positive Protection: Negated emergency statements ("no chest pain")
+    negation_patterns = [
+        r"\bno\s+(?:chest\s+pain|breathing\s+difficulty|heart\s+attack|paralysis|bleeding)\b",
+        r"\bdon't\s+have\s+(?:chest\s+pain|breathing\s+difficulty|heart\s+attack)\b",
+        r"\bnot\s+having\s+(?:chest\s+pain|breathing\s+difficulty)\b",
+        r"\bnever\s+had\s+(?:chest\s+pain|breathing\s+difficulty)\b",
+        r"\billness\s+none\b",
+    ]
+    for neg_pat in negation_patterns:
+        if re.search(neg_pat, msg_clean):
+            if not any(pos in msg_clean for pos in ["severe chest pain", "cannot breathe", "collapsed"]):
+                return False, None, None
+
+    # Check English emergency keywords
+    for kw in EMERGENCY_KEYWORDS_EN:
+        if re.search(rf"\b{re.escape(kw)}\b", msg_clean):
+            reply = _build_emergency_reply(lang)
+            return True, f"Matched emergency phrase: '{kw}'", reply
+
+    # Check combinations (e.g. "chest pain" AND "difficulty breathing")
+    if "chest pain" in msg_clean and ("breath" in msg_clean or "shortness" in msg_clean or "difficulty" in msg_clean):
+        reply = _build_emergency_reply(lang)
+        return True, "Matched combined chest pain and breathing difficulty", reply
+
+    # Check Transliterated emergency phrases
+    for kw in TRANSLITERATED_EMERGENCY_PHRASES:
+        if kw in msg_clean:
+            reply = _build_emergency_reply(lang)
+            return True, f"Matched transliterated emergency phrase: '{kw}'", reply
+
+    return False, None, None
+
+
+def _build_emergency_reply(lang: str) -> str:
+    lang_clean = lang.lower() if lang else "en"
+    if lang_clean.startswith("ta"):
+        return "இது அவசர மருத்துவ உதவி தேவைப்படும் நிலை. தயவுசெய்து உடனடியாக அருகில் உள்ள மருத்துவமனை அவசர சிகிச்சைப் பிரிவுக்குச் செல்லவும்."
+    elif lang_clean.startswith("hi"):
+        return "यह एक आपातकालीन स्थिति हो सकती है। कृपया तुरंत निकटतम अस्पताल के आपातकालीन कक्ष (ER) में जाएँ।"
+    elif lang_clean.startswith("te"):
+        return "ఇది అత్యవసర వైద్య పరిస్థితి కావచ్చు. దయచేసి వెంటనే దగ్గరలోని ఆసుపత్రి ఎమర్జెన్సీ విభాగానికి వెళ్ళండి."
+    elif lang_clean.startswith("kn"):
+        return "ಇದು ತುರ್ತು ವೈದ್ಯಕೀಯ ಪರಿಸ್ಥಿತಿಯಾಗಿರಬಹುದು. ದಯವಿಟ್ಟು ತಕ್ಷಣ ಹತ್ತಿರದ ಆಸ್ಪತ್ರೆಯ ತುರ್ತು ವಿಭಾಗಕ್ಕೆ ಹೋಗಿ."
+    else:
+        return "This requires urgent medical attention. Please inform the nearest hospital staff or proceed directly to the Emergency Room right away."