Extract the string content from the LLM response object before passing it to `format_response_for_user`, and ensure it is a dictionary.

app.py

@@ -110,11 +110,16 @@ def on_submit(symptoms_text, history):
     # Call LLM
     response = llm.complete(prompt)
     raw = response
+    # Extract text from CompletionResponse if needed
+    if hasattr(raw, "text"):
+        raw = raw.text
+    elif hasattr(raw, "content"):
+        raw = raw.content
+    # Now ensure it's a dict
     if isinstance(raw, str):
         try:
             raw = json.loads(raw)
         except Exception:
-            # If not JSON, wrap in a dict or handle gracefully
             raw = {"diagnoses": [], "confidences": [], "follow_up": raw}
     assistant_msg = format_response_for_user(raw)
     history = history + [{"role": "assistant", "content": assistant_msg}]