run

app.py

@@ -0,0 +1,61 @@
+import gradio as gr
+import os
+from openai import OpenAI
+import json
+
+
+
+OPEN_AI_KEY = os.getenv("OPEN_AI_KEY")
+OPEN_AI_CLIENT = OpenAI(api_key=OPEN_AI_KEY)
+
+def generate_article(reference_text, seed_words, derivative_words, prompt_text):    
+    # 結合用戶輸入來形成最終的prompt
+    reference_text = f"""
+        文章：{reference_text}
+        關鍵詞：{seed_words}
+        衍生詞：{derivative_words}
+    """
+
+
+
+    sys_content = "你是一個擅長中文教學的老師，使用 zh-TW"
+    user_content = f"""
+        請根據 {reference_text} 
+        {prompt_text}
+    """
+    messages = [
+        {"role": "system", "content": sys_content},
+        {"role": "user", "content": user_content}
+    ]
+
+    request_payload = {
+        "model": "gpt-4-1106-preview",
+        "messages": messages,
+        "max_tokens": 4000,
+    }
+
+    response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+    article = response.choices[0].message.content.strip()
+    
+    # 返回生成的文章
+    return article
+
+# 定義Gradio介面
+with gr.Blocks() as demo:
+    with gr.Row():
+        reference_text = gr.Textbox(label="原文參考", placeholder="貼上原文參考...", lines=4)
+        seed_words = gr.Textbox(label="文章生字", placeholder="貼上文章生字...", lines=2)
+        derivative_words = gr.Textbox(label="衍生生字", placeholder="貼上衍生生字...", lines=2)
+        prompt_text = gr.Textbox(label="prompt的文字", placeholder="輸入或修改prompt的文字...")
+        generate_article_btn = gr.Button(label="生成文章")
+    
+    with gr.Row():
+        new_article = gr.Textbox(label="生成的文章")
+
+    generate_article_btn.click(
+        generate_article, 
+        inputs =[reference_text, seed_words, derivative_words, prompt_text],
+        outputs=new_article
+    )
+
+demo.launch()