generate_supporting_sentences

app.py

@@ -457,35 +457,51 @@ def update_topic_sentence_input(topic_sentences_json, selected_topic_sentence):
 
 def generate_supporting_sentences(model, max_tokens, sys_content, scenario, eng_level, topic, points, topic_sentence, user_generate_supporting_sentences_prompt):
     """
-    根据系统提示和用户输入的情境、主题、要点、主题句，调用OpenAI API生成相关的支持句。
+    根据系统提示和用户输入的情境、主题、要点、主题句，调用 LLM API 生成相关的支持句。
     """
-    user_content = f"""
-        scenario is: {scenario}
-        english level is: {eng_level}
-        topic is: {topic}
-        points is: {points}
-        topic sentence is: {topic_sentence}
-        ---
-        {user_generate_supporting_sentences_prompt}
-    """
-    messages = [
-        {"role": "system", "content": sys_content},
-        {"role": "user", "content": user_content}
-    ]
+    try:
+        user_content = f"""
+            scenario is: {scenario}
+            english level is: {eng_level}
+            topic is: {topic}
+            points is: {points}
+            topic sentence is: {topic_sentence}
+            ---
+            {user_generate_supporting_sentences_prompt}
+        """
+        
+        messages = [
+            {"role": "system", "content": sys_content},
+            {"role": "user", "content": user_content}
+        ]
 
-    request_payload = {
-        "model": model,
-        "messages": messages,
-        "max_tokens": max_tokens,
-    }
+        # 根據模型選擇 provider
+        if "gemini" in model.lower():
+            print("====gemini====")
+            provider = GeminiProvider()
+        else:
+            print("====openai====")
+            provider = OpenAIProvider(OPEN_AI_CLIENT)
+
+        # 使用 LLMService 處理請求
+        llm_service = LLMService(provider)
+        content = llm_service.chat(
+            prompt=f"{sys_content}\n{user_content}" if "gemini" in model.lower() else None,
+            messages=messages,
+            model=model,
+            max_tokens=max_tokens
+        )
 
-    try:
-        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
-        content = response.choices[0].message.content.strip()
         gr_update = gr.update(choices=[content], visible=True)
+
     except Exception as e:
-        print(f"An error occurred while generating supporting sentences: {e}")
-        raise gr.Error("網路塞車，請重新嘗試一次！")
+        print(f"An error occurred while generating supporting sentences: {str(e)}")
+        error_msg = "網路塞車，請重新嘗試一次！"
+        if "rate limit" in str(e).lower():
+            error_msg = "請求過於頻繁，請稍後再試"
+        elif "invalid_request_error" in str(e).lower():
+            error_msg = "請求格式錯誤，請檢查輸入"
+        raise gr.Error(error_msg)
 
     return gr_update