Update app.py

app.py

@@ -9,6 +9,7 @@ summary_text = ""
 def set_api_key(user_api_key):
     global api_key
     api_key = user_api_key
+    openai.api_key = api_key  # ✅ 重點修正：直接全域設置
     return "✅ API Key 已設定"
 
 def set_model(model_name):
@@ -17,7 +18,7 @@ def set_model(model_name):
     return f"✅ 模型已選：{model_name}"
 
 def extract_pdf_text(file_path):
-    doc = fitz.open(file_path)  # 直接用檔案路徑打開
+    doc = fitz.open(file_path)
     text = ""
     for page in doc:
         text += page.get_text()
@@ -25,30 +26,28 @@ def extract_pdf_text(file_path):
 
 def generate_summary(pdf_file):
     global summary_text
-    client = openai.OpenAI(api_key=api_key)
     pdf_text = extract_pdf_text(pdf_file)
     if not pdf_text.strip():
         return "⚠️ 無法解析 PDF 文字，可能為純圖片 PDF。"
-    response = client.chat.completions.create(
+    response = openai.ChatCompletion.create(
         model=selected_model,
         messages=[
             {"role": "system", "content": "請將以下 PDF 內容整理為條列式摘要重點。"},
             {"role": "user", "content": pdf_text[:4000]}
         ]
     )
-    summary_text = response.choices[0].message.content
+    summary_text = response['choices'][0]['message']['content']
     return summary_text
 
 def ask_question(user_question):
-    client = openai.OpenAI(api_key=api_key)
-    response = client.chat.completions.create(
+    response = openai.ChatCompletion.create(
         model=selected_model,
         messages=[
             {"role": "system", "content": f"根據以下 PDF 摘要內容回答問題：\n{summary_text}"},
             {"role": "user", "content": user_question}
         ]
     )
-    return response.choices[0].message.content
+    return response['choices'][0]['message']['content']
 
 with gr.Blocks() as demo:
     gr.Markdown("# 📄 PDF 摘要 & 問答助手 (Hugging Face 版)")
@@ -57,7 +56,7 @@ with gr.Blocks() as demo:
     api_key_status = gr.Textbox(label="狀態", interactive=False)
     api_key_input.submit(set_api_key, inputs=api_key_input, outputs=api_key_status)
 
-    model_choice = gr.Radio(["gpt-4", "gpt-4.1-nano", "gpt-4o"], label="選擇模型")
+    model_choice = gr.Radio(["gpt-3.5-turbo", "gpt-4", "gpt-4o"], label="選擇模型")
     model_status = gr.Textbox(label="模型狀態", interactive=False)
     model_choice.change(set_model, inputs=model_choice, outputs=model_status)