def generate_topic_sentences(model, max_tokens, sys_content, scenario, eng_level, topic, points, user_generate_topic_sentences_prompt):

app.py

@@ -58,6 +58,32 @@ def generate_points(model, max_tokens, sys_content, scenario, eng_level, topic,
 
     return content
 
+def generate_topic_sentences(model, max_tokens, sys_content, scenario, eng_level, topic, points, user_generate_topic_sentences_prompt):
+    """
+    根据系统提示和用户输入的情境及要点，调用OpenAI API生成相关的主题句及其合理性解释。
+    """
+    user_content = f"""
+        scenario is {scenario}
+        english level is {eng_level}
+        topic is {topic}
+        points is {points}
+        {user_generate_topic_sentences_prompt}
+    """
+    messages = [
+        {"role": "system", "content": sys_content},
+        {"role": "user", "content": user_content}
+    ]
+
+    request_payload = {
+        "model": model,
+        "messages": messages,
+        "max_tokens": max_tokens,
+    }
+
+    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+    content = response.choices[0].message.content.strip()
+
+    return content
 
 with gr.Blocks() as demo:
     with gr.Row():
@@ -89,7 +115,26 @@ with gr.Blocks() as demo:
             user_generate_points_prompt = gr.Textbox(label="Points Prompt", value=default_generate_points_prompt)
             generate_points_button = gr.Button("Generate Points")
 
-
+            gr.Markdown("## 4. Generate Topic Sentences")
+            points_input = gr.Textbox(label="Points")
+            default_generate_topic_sentences_prompt = """
+                Please provide one appropriate topic sentence that aptly introduces the subject for the given scenario and topic. 
+                Additionally, provide two topic sentences that, while related to the topic, 
+                would be considered inappropriate or less effective for the specified context. 
+                Those sentences must include the three main points:". 
+                Use English language and each sentence should not be too long.
+                For each sentence, explain the reason in Traditional Chinese, Taiwan, 繁體中文 zh-TW. 
+
+                Make sure the vocabulary you use is at level.
+                Only return the result in JSON format starting as: 
+                {{ 
+                    "0": [ {{ "topic-sentence": "#","appropriate": "Y/N", "reason": "#中文解釋" }} ], 
+                    "1": [ {{ "topic-sentence": "#","appropriate": "Y/N", "reason": "#中文解釋" }} ],
+                    "2": [ {{ "topic-sentence": "#","appropriate": "Y/N", "reason": "#中文解釋" }} ] 
+                }}            
+            """
+            user_generate_topic_sentences_prompt = gr.Textbox(label="Topic Sentences Prompt", value=default_generate_topic_sentences_prompt)
+            generate_topic_sentences_button = gr.Button("Generate Topic Sentences")
 
         
         with gr.Column():
@@ -124,4 +169,19 @@ with gr.Blocks() as demo:
         outputs=points_output
     )
 
+    generate_topic_sentences_button.click(
+        fn=generate_topic_sentences,
+        inputs=[
+            model, 
+            max_tokens, 
+            sys_content_input, 
+            scenario_input, 
+            eng_level_input,
+            topic_input,
+            points_input,
+            user_generate_topic_sentences_prompt
+        ],
+        outputs=topic_output
+    )
+
 demo.launch()