Update app.py

app.py

@@ -37,6 +37,12 @@ def generate_question(topic, difficulty):
     )
     return response['choices'][0]['message']['content']
 
+# 學習者語音輸入（STT）
+def transcribe_speech(audio_file):
+    with open(audio_file, "rb") as audio:
+        response = openai.Audio.transcribe("whisper-1", audio)
+    return response["text"]
+
 # AI 語音輸出（TTS）
 def ai_speak(text):
     response = openai.ChatCompletion.create(
@@ -46,43 +52,6 @@ def ai_speak(text):
     )
     return response['choices'][0]['message']['content']
 
-# 學習者語音輸入（STT）
-def transcribe_speech(audio_file):
-    with open(audio_file, "rb") as audio:
-        response = openai.Audio.transcribe("whisper-1", audio)
-    return response["text"]
-
-# 分析回答完整性 + 記錄弱點（新增長期歷史紀錄）
-def analyze_answer(user_input, correct_answer, topic):
-    global user_errors
-    
-    if user_input.strip().lower() == correct_answer.strip().lower():
-        return "✅ 正確！"
-    
-    elif user_input in correct_answer:
-        feedback = "⚠️ 部分正確，請補充完整"
-    else:
-        feedback = "❌ 答非所問，請重新思考"
-    
-    # 記錄錯誤主題（長期紀錄）
-    if feedback != "✅ 正確！":
-        if topic in user_errors:
-            user_errors[topic] += 1
-        else:
-            user_errors[topic] = 1
-
-    return feedback
-
-# 列出可加強的知識點（新增歷史紀錄顯示）
-def get_weaknesses():
-    if not user_errors:
-        return "🎯 目前沒有明顯弱點，繼續保持！"
-
-    sorted_weaknesses = sorted(user_errors.items(), key=lambda x: x[1], reverse=True)
-    
-    history_text = "\n".join([f"{k}: {v} 次錯誤" for k, v in sorted_weaknesses])
-    return f"📌 **你的弱點領域**：\n{history_text}"
-
 # 設定 Gradio 介面
 with gr.Blocks() as demo:
     gr.Markdown("# 教師檢定智慧陪讀家教 🚀")
@@ -94,26 +63,16 @@ with gr.Blocks() as demo:
     ask_btn = gr.Button("生成問題")
     ask_btn.click(generate_question, inputs=[topic_input, difficulty_input], outputs=question_output)
 
-    user_answer = gr.Textbox(label="你的回答")
-    analysis_result = gr.Textbox(label="分析結果")
-
-    analyze_btn = gr.Button("分析回答")
-    analyze_btn.click(analyze_answer, inputs=[user_answer, question_output, topic_input], outputs=analysis_result)
-
-    weaknesses_output = gr.Textbox(label="智能弱點分析")
-    weakness_btn = gr.Button("查看可加強的知識點")
-    weakness_btn.click(get_weaknesses, outputs=weaknesses_output)
-
-    # 新增語音輸入功能（使用檔案模式）
+    # 直接用語音回答問題
     speech_input = gr.Audio(type="filepath", label="你的語音回答")
     transcribed_text = gr.Textbox(label="語音轉文字")
 
-    speech_to_text_btn = gr.Button("轉換語音")
+    speech_to_text_btn = gr.Button("提交回答")
     speech_to_text_btn.click(transcribe_speech, inputs=speech_input, outputs=transcribed_text)
 
-    # 新增 AI 語音回應功能
-    ai_speech_output = gr.Textbox(label="AI 語音回答")
-    speech_response_btn = gr.Button("語音回應")
-    speech_response_btn.click(ai_speak, inputs=transcribed_text, outputs=ai_speech_output)
+    # 以語音輸出分析結果
+    speech_analysis_output = gr.Textbox(label="AI 分析結果")
+    analysis_btn = gr.Button("分析回答")
+    analysis_btn.click(ai_speak, inputs=transcribed_text, outputs=speech_analysis_output)
 
 demo.launch()