Create app.py

app.py

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+import gradio as gr
+import openai
+import fitz  # PyMuPDF
+import os
+import time
+
+
+# ✅ 使用環境變數來安全存取 OpenAI API Key
+openai_key = os.getenv("OPENAI_API_KEY")
+if not openai_key:
+    raise ValueError("API Key 未設置，請確保已設定環境變數 OPENAI_API_KEY")
+
+# ✅ PDF 檔案名稱（將 PDF 上傳到 Space 目錄）
+PDF_FILE = "statistics.pdf"
+
+# ✅ 萃取 PDF 內容
+def extract_text_from_pdf(pdf_path):
+    try:
+        doc = fitz.open(pdf_path)
+        text = ""
+        for page in doc:
+            text += page.get_text()
+        print(f"✅ 成功讀取 {pdf_path}")
+        return text
+    except Exception as e:
+        print(f"❌ PDF 解析錯誤: {e}")
+        return ""
+
+# ✅ 嘗試載入 PDF 內容
+if os.path.exists(PDF_FILE):
+    content = extract_text_from_pdf(PDF_FILE)
+else:
+    print(f"⚠️ 找不到 {PDF_FILE}，請將 PDF 上傳到 Space。")
+    content = ""
+
+# ✅ 調用 OpenAI API
+def openai_api(messages, openai_key):
+    try:
+        client = openai.OpenAI(api_key=openai_key)
+        completion = client.chat.completions.create(
+            model="gpt-4o",
+            messages=messages
+        )
+        if not completion or not completion.choices:
+            return "API 沒有回應，請檢查 API Key 或伺服器狀態。"
+        response = completion.choices[0].message.content
+        return response
+    except Exception as e:
+        return f"API 呼叫發生錯誤：{str(e)}"
+
+# ✅ 準備對話訊息
+def predict(inputs, chatbot):
+    messages = []
+    system_prompt = {
+        "role": "system",
+        "content": f"請扮演助教機器人，針對我所上傳的『統計學』PDF 文件進行問答。以下是學習內容：\n\n{content}"
+    }
+    messages.append(system_prompt)
+
+    if chatbot is None:
+        chatbot = []
+
+    for conv in chatbot:
+        if isinstance(conv, dict) and "role" in conv and "content" in conv:
+            messages.append({"role": conv["role"], "content": conv["content"]})
+
+    messages.append({"role": "user", "content": inputs})
+    return messages
+
+# ✅ 逐字輸出訊息
+def slow_echo(inputs, chatbot):
+    messages = predict(inputs, chatbot)
+    re_message = openai_api(messages, openai_key)
+
+    if not re_message:
+        re_message = "無法取得回應，請稍後再試。"
+
+    for i in range(len(re_message)):
+        yield re_message[: i + 1]
+        time.sleep(0.05)
+
+# ✅ 建立 Gradio 介面
+def setup_gradio_interface():
+    demo = gr.ChatInterface(
+        slow_echo,
+        chatbot=gr.Chatbot(height=500, type="messages"),  # ✅ 修正 type 參數
+        title="📊 統計學助教機器人",
+        description="請輸入與統計學有關的問題，機器人將基於所上傳的 PDF 內容來回答。"
+    )
+    return demo
+
+# ✅ 啟動應用程式
+if __name__ == "__main__":
+    demo = setup_gradio_interface()
+    port = int(os.environ.get("PORT", 7860))
+    demo.queue()
+    #demo.launch(server_name="0.0.0.0", server_port=port)
+    demo.launch()