Update thicc/app.py

thicc/app.py

@@ -9,11 +9,25 @@ HOSPITAL_CHOICES = list(HOSPITALS.keys())
 PLAN_CHOICES = list(plans.SAMPLE_PLANS.keys()) + ["No Insurance"]
 
 
-def _extract_hospital_and_plan(text: str):
+def _extract_hospital_and_plan(text):
     """Best-effort extraction of hospital and plan names from free text."""
     if not text:
         return None, None
 
+    # Handle case where text might be a list (multimodal Gradio format)
+    if isinstance(text, list):
+        # Extract text content from list of content parts
+        text_parts = []
+        for part in text:
+            if isinstance(part, str):
+                text_parts.append(part)
+            elif isinstance(part, dict) and part.get("type") == "text":
+                text_parts.append(part.get("text", ""))
+        text = " ".join(text_parts)
+    
+    if not text:
+        return None, None
+
     lower = text.lower()
     hospital_name = None
     plan_name = None
@@ -62,9 +76,29 @@ def _get_current_hospital_and_plan(message, history):
     return hospital_name, plan_name
 
 
+def _normalize_message(text):
+    """Convert message content to a plain string (handles Gradio's multimodal format)."""
+    if not text:
+        return ""
+    
+    if isinstance(text, list):
+        text_parts = []
+        for part in text:
+            if isinstance(part, str):
+                text_parts.append(part)
+            elif isinstance(part, dict) and part.get("type") == "text":
+                text_parts.append(part.get("text", ""))
+        return " ".join(text_parts)
+    
+    return text
+
+
 def respond(message, history):
     """Main response function - now asks for hospital/plan conversationally."""
 
+    # Normalize message in case it's a list (multimodal Gradio format)
+    message = _normalize_message(message)
+
     # Determine the user's current hospital & plan from history/message
     hospital_name, plan_name = _get_current_hospital_and_plan(message, history)