Update app.py

app.py

@@ -1,73 +1,73 @@
-import openai
-import gradio as gr
-import fitz  # PyMuPDF
-
-api_key = ""
-selected_model = ""
-summary_text = ""
-
-def set_api_key(user_api_key):
-    global api_key
-    api_key = user_api_key
-    return "✅ API Key 已設定"
-
-def set_model(model_name):
-    global selected_model
-    selected_model = model_name
-    return f"✅ 模型已選：{model_name}"
-
-def extract_pdf_text(file_obj):
-    doc = fitz.open(stream=file_obj.read(), filetype="pdf")
-    text = ""
-    for page in doc:
-        text += page.get_text()
-    return text
-
-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(
-        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
-    return summary_text
-
-def ask_question(user_question):
-    client = openai.OpenAI(api_key=api_key)
-    response = client.chat.completions.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
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 📄 PDF 摘要 & 問答助手 (Hugging Face 版)")
-    api_key_input = gr.Textbox(label="輸入 OpenAI API Key", type="password")
-    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_status = gr.Textbox(label="模型狀態", interactive=False)
-    model_choice.change(set_model, inputs=model_choice, outputs=model_status)
-
-    pdf_upload = gr.File(label="上傳 PDF")
-    summary_output = gr.Textbox(label="PDF 摘要", lines=10)
-    summary_btn = gr.Button("生成摘要")
-    summary_btn.click(generate_summary, inputs=pdf_upload, outputs=summary_output)
-
-    question_input = gr.Textbox(label="請輸入您的問題")
-    answer_output = gr.Textbox(label="AI 回答", lines=5)
-    question_btn = gr.Button("送出問題")
-    question_btn.click(ask_question, inputs=question_input, outputs=answer_output)
-
-demo.launch()
+import openai
+import gradio as gr
+import fitz  # PyMuPDF
+
+api_key = ""
+selected_model = ""
+summary_text = ""
+
+def set_api_key(user_api_key):
+    global api_key
+    api_key = user_api_key
+    return "✅ API Key 已設定"
+
+def set_model(model_name):
+    global selected_model
+    selected_model = model_name
+    return f"✅ 模型已選：{model_name}"
+
+def extract_pdf_text(file_obj):
+    doc = fitz.open(stream=file_obj.read(), filetype="pdf")
+    text = ""
+    for page in doc:
+        text += page.get_text()
+    return text
+
+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(
+        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
+    return summary_text
+
+def ask_question(user_question):
+    client = openai.OpenAI(api_key=api_key)
+    response = client.chat.completions.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
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 📄 PDF 摘要 & 問答助手 (Hugging Face 版)")
+    api_key_input = gr.Textbox(label="輸入 OpenAI API Key", type="password")
+    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_status = gr.Textbox(label="模型狀態", interactive=False)
+    model_choice.change(set_model, inputs=model_choice, outputs=model_status)
+
+    pdf_upload = gr.File(label="上傳 PDF")
+    summary_output = gr.Textbox(label="PDF 摘要", lines=10)
+    summary_btn = gr.Button("生成摘要")
+    summary_btn.click(generate_summary, inputs=pdf_upload, outputs=summary_output)
+
+    question_input = gr.Textbox(label="請輸入您的問題")
+    answer_output = gr.Textbox(label="AI 回答", lines=5)
+    question_btn = gr.Button("送出問題")
+    question_btn.click(ask_question, inputs=question_input, outputs=answer_output)
+
+demo.launch(share=True)