Update app.py

app.py

@@ -46,7 +46,7 @@ def init_rag_system():
     rag_initialized = True
 
 # ==========================================
-# 2. 核心功能 (已修復除錯模式)
+# 2. 核心功能 (修改：回傳分開的除錯資訊)
 # ==========================================
 def get_restaurant_data(mood_score_str, food_choice):
     init_rag_system()
@@ -73,24 +73,31 @@ def get_restaurant_data(mood_score_str, food_choice):
     return result, is_random, rec_categories, mood_reason
 
 def generate_content_with_groq(restaurant_name, restaurant_detail, user_diary, mood_score, mood_guide_reason, debug_mode=False):
-    if not GROQ_API_KEY: return "⚠️ 請設定 GROQ_API_KEY"
+    if not GROQ_API_KEY: return "⚠️ 請設定 GROQ_API_KEY", ""
     
     client = OpenAI(api_key=GROQ_API_KEY, base_url="https://api.groq.com/openai/v1")
     
     system_prompt = "你是一個幽默、懂吃且善解人意的 AI 朋友..."
     user_msg = f"【狀態】心情分數：{mood_score}\n【日記】{user_diary}\n【建議原因】{mood_guide_reason}\n【餐廳】{restaurant_name}\n資料：{restaurant_detail}"
     
+    # 準備除錯資訊
+    debug_log = ""
+    if debug_mode:
+        debug_log = f"""
+### 🔧 Groq Prompt Debug
+**System Prompt:**
+{system_prompt}
+
+**User Message:**
+{user_msg}
+"""
+
     try:
         response = client.chat.completions.create(model="llama-3.3-70b-versatile", messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": user_msg}])
         content = response.choices[0].message.content
-        
-        # ### [修復] 除錯模式邏輯 ###
-        if debug_mode:
-            content += f"\n\n--- 🔧 DEBUG: Groq Prompt ---\n**System:** {system_prompt}\n\n**User:** {user_msg}\n-----------------------"
-        # ########################
-        
-        return content
-    except Exception as e: return f"Groq Error: {str(e)}"
+        return content, debug_log # 回傳 (內容, 除錯資訊)
+    except Exception as e: 
+        return f"Groq Error: {str(e)}", debug_log
 
 def generate_image_huggingface(prompt):
     if not HF_TOKEN: return None
@@ -101,26 +108,40 @@ def generate_image_huggingface(prompt):
 
 def mood_agent_logic(score_input, food_input, diary_input, debug_mode):
     restaurant, is_random, rec_categories, mood_reason = get_restaurant_data(score_input, food_input)
-    if restaurant is None: yield "資料庫讀取錯誤", None, ""; return
+    if restaurant is None: yield "資料庫讀取錯誤", None, "", gr.update(); return
+    
     name = restaurant['Name']; address = restaurant['Address']; url = restaurant['URL']; img_prompt = restaurant.get('Visual_prompt')
+    
     rag_info = str(restaurant.get('RAG_Content', ''))
     if global_retriever:
         docs = global_retriever.invoke(name)
         if docs: rag_info = "\n".join([d.page_content for d in docs])
         
-    ai_text = generate_content_with_groq(name, rag_info, diary_input, score_input, mood_reason, debug_mode)
+    # 呼叫 Groq 生成內容與取得除錯資訊
+    ai_text, groq_debug_log = generate_content_with_groq(name, rag_info, diary_input, score_input, mood_reason, debug_mode)
     
-    # ### [修復] 除錯模式邏輯 (圖片 Prompt) ###
+    # 準備完整的除錯資訊 (包含圖片 Prompt)
+    full_debug_log = ""
     if debug_mode:
-        ai_text += f"\n\n--- 🔧 DEBUG: Image Prompt ---\n{img_prompt}\n-----------------------"
-    # ######################################
+        img_debug_log = f"""
+### 🎨 Image Prompt Debug
+**Visual Prompt:**
+{img_prompt}
+"""
+        full_debug_log = groq_debug_log + "\n\n" + img_debug_log
+
+    # 設定除錯視窗的狀態 (有勾選才顯示)
+    debug_output_update = gr.update(value=full_debug_log, visible=debug_mode)
 
     final_response = f"### 🍽️ 推薦：{name}\n\n{ai_text}"
     map_html = f'<div style="text-align:center"><a href="{url}" target="_blank" style="background:#4CAF50;color:white;padding:8px 16px;border-radius:20px;text-decoration:none">🗺️ Google Map 導航</a></div>'
     
-    yield final_response, None, map_html
+    # 先回傳文字與除錯資訊
+    yield final_response, None, map_html, debug_output_update
+    
+    # 再回傳圖片
     image_output = generate_image_huggingface(img_prompt)
-    yield final_response, image_output, map_html
+    yield final_response, image_output, map_html, debug_output_update
 
 
 # ==========================================
@@ -133,21 +154,17 @@ def _score_to_radio_value(score):
     except: score = 3
     return mapping.get(score, "3 (普通)")
 
-# 橋接 1：開始
 def bridge_start_click(st):
     res = emotion.on_restart(st)
     return res[1], res[0], gr.update(visible=True), res[5], res[4]
 
-# 橋接 2：停止
 def bridge_stop_click(st):
     res = emotion.on_stop(st)
     return res[1], res[0], gr.update(visible=False), res[5], res[4]
 
-# 橋接 3：Webcam 串流
 def bridge_predict_frame(frame, st):
     res = emotion.on_stream(frame, st)
     out_cam = res[0]; out_result = res[1]; out_st = res[4]; out_btn_start = res[5]
-    
     score_update = gr.update(); tabs_update = gr.update(); out_btn_stop = gr.update()
 
     if out_st.finished and hasattr(out_st, 'final_score'):
@@ -197,7 +214,12 @@ with gr.Blocks(title="AI 心情食堂", css=combined_css) as demo:
                         food_input = gr.Radio(["吃飯", "吃麵", "隨便"], label="2. 想吃什麼", value="隨便")
                         diary_input = gr.Textbox(lines=4, label="3. 心情日記", placeholder="寫下今天發生的事...")
                         debug_mode_btn = gr.Checkbox(label="🔧 開啟除錯模式", value=False)
+                        
                         submit_btn = gr.Button("🍱 送出給 Agent", variant="primary")
+                        
+                        # --- [新增] 除錯資訊顯示區 (位於按鈕下方) ---
+                        debug_output = gr.Markdown(label="除錯資訊 (Debug Log)", visible=False)
+                        # ----------------------------------------
                     
                     with gr.Column(scale=1):
                         agent_output = gr.Markdown(label="AI 回應")
@@ -232,7 +254,7 @@ with gr.Blocks(title="AI 心情食堂", css=combined_css) as demo:
     submit_btn.click(
         fn=mood_agent_logic,
         inputs=[score_input, food_input, diary_input, debug_mode_btn],
-        outputs=[agent_output, image_output, map_output]
+        outputs=[agent_output, image_output, map_output, debug_output] # 加入 debug_output
     )
 
 if __name__ == "__main__":