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

2026-09-07 12:57:54 +05:30
parent c23d979338
commit 92fa71ae4a
99 changed files with 5167 additions and 3550 deletions
@@ -0,0 +1,68 @@
+"""
+Medication extraction engine supporting structured dosage, frequency, and confirmed_none status.
+"""
+
+import re
+from typing import Dict, Any, List, Optional, Union
+
+KNOWN_MED_PATTERNS = [
+    (r"(metformin(?:\s+\d+\s*mg)?(?:\s+twice\s+a\s+day)?)", "Metformin"),
+    (r"(paracetamol(?:\s+\d+\s*mg)?)", "Paracetamol"),
+    (r"(dolo(?:\s*650)?)", "Dolo 650 (Paracetamol)"),
+    (r"(pantocid|pan-d|pan 40|omez|omeprazole)", "Pantoprazole / Antacid"),
+    (r"(telmisartan|telma\s*\d+)", "Telmisartan (BP)"),
+    (r"(amlodipine|amlong\s*\d+)", "Amlodipine (BP)"),
+    (r"((?:bp|பிபி|blood\s*pressure)\s*(?:மாத்திரை|medicine|tablet|tablets|மருந்து))", "BP Medication"),
+    (r"((?:sugar|சுகர்|சர்க்கரை)\s*(?:மாத்திரை|medicine|tablet|tablets|மருந்து))", "Diabetes Medication"),
+    (r"((?:thyroid|தைராய்டு)\s*(?:மாத்திரை|medicine|tablet|tablets|மருந்து))", "Thyroid Medication"),
+]
+
+
+def extract_medications(
+    message: str,
+    normalized_msg: str,
+    last_ai_message: Optional[str] = None,
+    is_allergy_utterance: bool = False
+) -> Optional[Union[List[Dict[str, Any]], Dict[str, Any]]]:
+    """
+    Extracts structured medications or confirmed_none container.
+    """
+    msg_lower = normalized_msg.lower()
+
+    # Check for explicit negation of medicines
+    neg_phrases = [
+        "no medicines", "no medication", "don't take any medicine", "don't take medicines",
+        "no tablets", "not taking any medicine", "no daily medicines", "no regular medicines",
+        "மாத்திரை எதுவும் இல்லை", "எந்த மாத்திரையும் சாப்பிடல", "மருந்து எதுவும் இல்லை",
+        "कोई दवा नहीं", "दवाई नहीं लेते", "दवा नहीं लेता", "ఏ మందులు లేవు", "ಯಾವ ಮಾತ್ರೆ ಇಲ್ಲ"
+    ]
+    if any(neg in msg_lower for neg in neg_phrases):
+        return {"status": "confirmed_none", "items": []}
+
+    meds: List[Dict[str, Any]] = []
+
+    # Known medicine matchers
+    for pat, med_label in KNOWN_MED_PATTERNS:
+        m_match = re.search(pat, msg_lower)
+        if m_match:
+            matched_str = m_match.group(1).strip()
+            med_obj: Dict[str, Any] = {"name": med_label}
+
+            dosage_m = re.search(r"(\d+\s*mg|\d+\s*ml)", matched_str)
+            if dosage_m:
+                med_obj["dosage"] = dosage_m.group(1).strip()
+
+            freq_m = re.search(r"(twice\s+a\s+day|once\s+a\s+day|\d+\s+times\s+a\s+day|daily|twice)", matched_str)
+            if freq_m:
+                med_obj["frequency"] = freq_m.group(1).strip()
+
+            if not any(x.get("name") == med_obj["name"] for x in meds):
+                meds.append(med_obj)
+
+    # Generic medicine indicator matchers (only if not an allergy utterance)
+    if not meds and not is_allergy_utterance:
+        generic_pat = r"(tablets|goli|mathirai|மாத்திரை|மருந்து|दवाई|दवा|మాత్రలు|ಮಾತ್ರೆಗಳು)"
+        if re.search(generic_pat, msg_lower) and any(verb in msg_lower for verb in ["take", "taking", "சாப்பிடுறேன்", "சாப்பிட்டேன்", "வாங்குறேன்", "लेता", "लेती", "వాడుతున్నాను"]):
+            meds.append({"name": "Unspecified medication"})
+
+    return meds if meds else None