Update src/ai_core.py

src/ai_core.py

@@ -87,6 +87,43 @@ def _flatten_intake(intake: Dict[str, Any]) -> str:
         f"Meds: {', '.join(meds)}",
     ]).strip()
 
+def aiTriageSuggest(intake: Dict[str, Any]) -> Dict[str, Any]:
+    """Keyword + LLM-based specialty triage."""
+    rule_spec, rule_mode = _keyword_triage(intake)
+    sys = {"role": "system", "content": (
+        "You are an intake triage assistant for an e-consult service. "
+        "Return STRICT JSON with keys: specialty (lowercase), "
+        "care_mode in ['e_consult_ok','in_person_recommended','urgent_emergent'], "
+        "supported (bool), rationale (<=50 words)."
+    )}
+    user = {
+        "role": "user",
+        "content": _flatten_intake(intake)
+                   + f"\n\nRule engine suggestion: specialty={rule_spec}, care_mode={rule_mode}."
+    }
+    try:
+        out = generate_chat([sys, user], max_new_tokens=160, temperature=0.0, do_sample=False)
+        obj = _safe_json_extract(out)
+    except Exception:
+        obj = {}
+
+    specialty = (obj.get("specialty") or rule_spec or "general").lower()
+    care_mode = (obj.get("care_mode") or rule_mode or "e_consult_ok")
+    supported = bool(obj.get("supported")) if "supported" in obj else (care_mode == "e_consult_ok")
+    rationale = obj.get("rationale") or (
+        f"Keyword triage matched => specialty={specialty}, care_mode={care_mode}."
+    )
+
+    return {
+        "status": "ok" if obj else "rule_only",
+        "specialty": specialty,
+        "care_mode": care_mode,
+        "supported": supported,
+        "rationale": rationale[:400],
+        "model_notes": "LLM+rules" if obj else "rules_only",
+    }
+
+
 
 # ----------------- SOAP generation -----------------
 def _build_corpus_context(chunks: List[Dict[str, Any]], max_chars_per_chunk: int = 400) -> str: