- return markdown format

app.py

@@ -282,6 +282,9 @@ def get_ai_suggestion(topic_result, exercise_quiz_result):
         - The suggestions should be relevant to the course content.
         - use ZH-TW language, this is very important.
         - return markdown format
+        - user will get a knowledge graph and data, 1 will be the best, 0 will be the worst. 
+        then 1 will show color green, 0 will show color red, others will show color orange. 
+        so you can just transfer the number to color to explain the user's performance.
 
         for this student based on the given knowledge graph and data:
         1. How to interpret this knowledge graph.
@@ -292,8 +295,8 @@ def get_ai_suggestion(topic_result, exercise_quiz_result):
         # 針對 emdob01 學生的課程建議
         ### 1. 如何解讀此知識圖與數據
         知識圖呈現學生在不同知識點上的掌握程度，用數字顯示熟悉度(0-1)。例如：
-        - `jnc-4-05-3-1` : 1 代表完全掌握
-        - `jnc-4-06-2-2` : 0 代表未掌握
+        - `jnc-4-05-3-1` : 1(綠色) 代表完全掌握
+        - `jnc-4-06-2-2` : 0（紅色） 代表未掌握
 
         該學生的表現數據顯示各個練習題的回答正確性與所花費的時間。這有助於了解學生對不同題目的理解程度和答題速度。
 
@@ -366,7 +369,7 @@ with gr.Blocks() as app:
 
     all_in_one_button = gr.Button("Fetch Data and Generate Graph")
 
-    with gr.Accordion(open=False):
+    with gr.Accordion(open=False, label="Raw Data"):
         topic_result = gr.JSON(label="Query Result")
         exercise_quiz_result = gr.JSON(label="Quiz Query Result")
 
@@ -376,7 +379,7 @@ with gr.Blocks() as app:
     with gr.Row():
         gr.Markdown("# AI suggestion Powered by Junyi Academy")
     with gr.Row():
-        ai_suggestion = gr.Textbox()
+        ai_suggestion = gr.Markdown()
 
     all_in_one_button.click(
         fn=query_metabase_topic,