Update src/prompt_builder.py

src/prompt_builder.py

@@ -1,4 +1,3 @@
-# src/prompt_builder.py
 from __future__ import annotations
 import json
 import re
@@ -36,7 +35,7 @@ def _safe_json_extract(text: str) -> Dict[str, Any]:
 def build_referral_summary(intake: Dict[str, Any]) -> str:
     """
     Canonical, MedGemma-friendly referral summary used for all generations.
-    This ensures consistent input formatting between PCP and Specialist.
+    Ensures consistent input formatting between PCP and Specialist.
     """
     c = (intake or {}).get("consult", {}) or {}
     p = (intake or {}).get("patient", {}) or {}
@@ -48,7 +47,7 @@ def build_referral_summary(intake: Dict[str, Any]) -> str:
     if isinstance(meds, str):
         meds = [m.strip() for m in meds.split(",") if m.strip()]
 
-    lines = [
+    # ---- Header (Age preferred, MRN/DOB removed) ----
     patient_header = f"Patient: {p.get('name','')}"
     age_val = str(p.get("age_years", "")).strip()
     if age_val != "":
@@ -65,13 +64,12 @@ def build_referral_summary(intake: Dict[str, Any]) -> str:
         f"Medications: {', '.join(meds)}",
     ]
 
-            return "\n".join(lines).strip()
+    return "\n".join(lines).strip()
 
 
 def chat_to_structured(chat_msgs: List[Dict[str, str]]) -> Dict[str, Any]:
     """
     Convert a PCP chat thread into structured fields suitable for intake.
-
     🚧 For stability (avoids meta-tensor / GPU initialization errors),
         LLM summarization via generate_chat() is currently disabled.
         This uses a deterministic heuristic to capture the last message