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 +1,98 @@
+"""
+NextBestActionEngine (Rules 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91):
+- Conversational State Machine Evaluation
+- Priority Scoring & Action Selection
+- Cooldown & Intent Deduplication
+- Status-aware field tracking (reported, confirmed_none, unknown, declined, skipped, not_asked)
+"""
+
+from typing import Dict, Any, List, Optional, Tuple
+
+
+class NextBestActionEngine:
+    """
+    Evaluates intake state and determines the next-best action and target question.
+    """
+
+    def calculate_priority_score(
+        self,
+        field: str,
+        current_state: Dict[str, Any],
+        is_psych: bool = False,
+        asked_intents: Optional[List[str]] = None
+    ) -> float:
+        """
+        Calculates question priority score based on Rule 83:
+        priority = safety_weight + clinical_importance + symptom_completeness
+                   + specialty_relevance + information_value
+                   - repetition_penalty - already_answered_penalty - unnecessary_question_penalty
+        """
+        score = 0.0
+        asked_intents = asked_intents or []
+
+        weights = {
+            "emergency": 100.0,
+            "crisis": 100.0,
+            "reason_for_visit": 50.0,
+            "symptoms": 50.0,
+            "duration": 45.0,
+            "severity": 30.0,
+            "medical_history": 35.0,
+            "medications": 30.0,
+            "allergies": 25.0,
+            "previous_episodes": 15.0,
+            "family_history": 10.0,
+            "additional_information": 5.0,
+        }
+
+        score += weights.get(field, 10.0)
+
+        # Repetition penalty (Rule 84 & 85)
+        if field in asked_intents:
+            score -= 60.0
+
+        # Specialty relevance bonus
+        if is_psych and field in ["duration", "medical_history"]:
+            score += 10.0
+
+        return score
+
+    def determine_next_action(
+        self,
+        current_state: Dict[str, Any],
+        is_emergency: bool = False,
+        is_crisis: bool = False,
+        is_psych: bool = False,
+        missing_fields: Optional[List[str]] = None
+    ) -> Tuple[str, Optional[str]]:
+        """
+        Returns (action_type, target_field)
+        Action types (Rule 82):
+        - SAFETY_ACTION
+        - CLARIFY
+        - ASK_QUESTION
+        - COMPLETE
+        - HANDLE_REFUSAL
+        - HANDLE_UNKNOWN
+        """
+        if is_crisis or is_emergency:
+            return "SAFETY_ACTION", None
+
+        # Check for state conflicts requiring clarification (Rule 67)
+        if current_state and current_state.get("conflicts"):
+            return "CLARIFY", current_state["conflicts"][-1].get("field")
+
+        missing_fields = missing_fields or []
+        if not missing_fields:
+            return "COMPLETE", None
+
+        # Score missing fields using priority score (Rule 83)
+        scored_fields = []
+        for field in missing_fields:
+            score = self.calculate_priority_score(field, current_state, is_psych=is_psych)
+            scored_fields.append((score, field))
+
+        scored_fields.sort(key=lambda x: x[0], reverse=True)
+        best_field = scored_fields[0][1]
+
+        return "ASK_QUESTION", best_field