Update app.py

app.py

@@ -1,10 +1,22 @@
+"""
+======================================================
+📘 金融客服小智（Fintech Assistant）
+版本：v2 (重構示範 by Supervisor)
+改進重點：
+1. 模組化程式結構（易維護）
+2. 加入記憶體保存（多輪對話）
+3. 改善 Chroma 初始化與 QA 擷取
+4. 加強異常處理與容錯提示
+======================================================
+"""
+
 import os, re, base64
+import chromadb
+import gradio as gr
 from langchain_core.documents import Document
 from langchain_chroma import Chroma
-from langchain_huggingface import HuggingFaceEmbeddings   # ✅ 雲端可直接用
+from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_google_genai import ChatGoogleGenerativeAI
-import chromadb
-import gradio as gr
 
 # === 記憶模組相容多版本 ===
 try:
@@ -17,71 +29,88 @@ except ImportError:
 
 
 # =============================================
-# 1️⃣ 使用 Hugging Face 雲端 embedding 模型
+# 1️⃣ Embedding 與基礎設定
 # =============================================
 embedding = HuggingFaceEmbeddings(model_name="BAAI/bge-small-zh-v1.5")
 
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+QA_PATH = os.path.join(BASE_DIR, "QA_v2.txt")
+LOGO_PATH = os.path.join(BASE_DIR, "mega.png")
+
+if not os.path.exists(QA_PATH):
+    raise FileNotFoundError("❌ 找不到 QA 檔案 QA_v2.txt，請確認路徑。")
+
+API_KEY = os.getenv("GOOGLE_API_KEY")
+if not API_KEY:
+    print("⚠️ 尚未設定 GOOGLE_API_KEY，系統將以模擬回覆運行。")
+
+
 # =============================================
-# 2️⃣ 載入 QA 檔案並分類
+# 2️⃣ QA 載入與分類（改進版正規化）
 # =============================================
-BASE_DIR = os.path.dirname(os.path.abspath(__file__))
-qa_path = os.path.join(BASE_DIR, "QA_v2.txt")
+def load_qa_documents(path: str):
+    with open(path, "r", encoding="utf-8") as f:
+        text = f.read()
+
+    # 改進版正規表達式，確保每筆 QA 含問題與答案
+    pattern = r"(Ｑ[:：].*?Ａ[:：].*?)(?=Ｑ[:：]|$)"
+    qas = re.findall(pattern, text, flags=re.S)
 
-if not os.path.exists(qa_path):
-    raise FileNotFoundError(f"❌ 找不到 QA 檔案：{qa_path}")
+    categories = {"證券": [], "期貨": [], "複委託": []}
+    for qa in qas:
+        doc = Document(page_content=qa.strip())
+        if "證券" in qa:
+            categories["證券"].append(doc)
+        elif "期貨" in qa:
+            categories["期貨"].append(doc)
+        elif "複委託" in qa:
+            categories["複委託"].append(doc)
+        else:
+            categories["證券"].append(doc)  # 預設分類
 
-with open(qa_path, "r", encoding="utf-8") as f:
-    text = f.read()
+    return categories
 
-pattern = r"(Ｑ[:：].*?)(?=Ｑ[:：]|$)"
-qas = re.findall(pattern, text, flags=re.S)
-qa_docs = {"證券": [], "期貨": [], "複委託": []}
-for qa in qas:
-    if "證券" in qa:
-        qa_docs["證券"].append(Document(page_content=qa.strip()))
-    elif "期貨" in qa:
-        qa_docs["期貨"].append(Document(page_content=qa.strip()))
-    elif "複委託" in qa:
-        qa_docs["複委託"].append(Document(page_content=qa.strip()))
 
-print("✅ 已成功讀取 QA 並完成分類：")
-for k, v in qa_docs.items():
-    print(f"　{k}：{len(v)} 筆")
+qa_docs = load_qa_documents(QA_PATH)
+print("✅ 已成功載入 QA 檔案，共分為：", {k: len(v) for k, v in qa_docs.items()})
 
 
 # =============================================
-# 3️⃣ 建立向量資料庫
+# 3️⃣ 向量資料庫初始化（避免重複寫入）
 # =============================================
 client = chromadb.PersistentClient(path="./chroma_db")
-collection_names = {"證券": "stocks", "期貨": "futures", "複委託": "overseas"}
-
+collection_map = {"證券": "stocks", "期貨": "futures", "複委託": "overseas"}
 vectordbs = {}
+
 for cat, docs in qa_docs.items():
-    vectordbs[cat] = Chroma(
+    vectordb = Chroma(
         client=client,
-        collection_name=collection_names[cat],
+        collection_name=collection_map[cat],
         embedding_function=embedding
     )
-    if len(vectordbs[cat].get()["documents"]) == 0:
-        vectordbs[cat].add_documents(docs)
-print("✅ 各類別向量資料庫建立完成")
+    if vectordb._collection.count() == 0:
+        vectordb.add_documents(docs)
+    vectordbs[cat] = vectordb
+
+print("✅ 向量資料庫已建立完成。")
 
 
 # =============================================
-# 4️⃣ 初始化 Gemini LLM（雲端）
+# 4️⃣ 初始化 LLM 與對話記憶
 # =============================================
-API_KEY = os.getenv("GOOGLE_API_KEY")
-if not API_KEY:
-    raise ValueError("⚠️ 未設定 GOOGLE_API_KEY，請在 Hugging Face Secrets 中新增。")
+if API_KEY:
+    llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash", google_api_key=API_KEY)
+else:
+    llm = None  # 模擬模式
 
-llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash", google_api_key=API_KEY)
 memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
 
 
 # =============================================
 # 5️⃣ 對話邏輯
 # =============================================
-def auto_detect_category(text):
+def auto_detect_category(text: str):
+    """根據關鍵詞自動偵測使用者詢問的業務類別"""
     if any(k in text for k in ["股票", "證券", "開戶", "下單", "交割"]):
         return "證券"
     elif any(k in text for k in ["期貨", "選擇權", "保證金"]):
@@ -93,13 +122,14 @@ def auto_detect_category(text):
 
 
 def chat_fn(message, history):
+    """核心對話函式"""
     category = auto_detect_category(message)
-    vectordb = vectordbs.get(category)
+    vectordb = vectordbs[category]
     docs = vectordb.similarity_search(message, k=2)
-    context = "\n\n".join([d.page_content for d in docs]) if docs else "查無資料"
+    context = "\n\n".join(d.page_content for d in docs) if docs else "查無相關資料"
 
     prompt = f"""
-你是一位金融客服人員，根據以下公司QA回答客戶問題：
+你是一位金融客服人員，請根據以下QA知識回答：
 ---
 {context}
 ---
@@ -107,140 +137,85 @@ def chat_fn(message, history):
     """
 
     try:
-        response = llm.invoke(prompt)
-        reply = response.content.strip()
+        if llm:
+            response = llm.invoke(prompt)
+            reply = getattr(response, "content", None) or getattr(response, "text", "⚠️ 無回覆")
+        else:
+            reply = "（模擬模式）這是示範回覆：請確認是否已設定 GOOGLE_API_KEY。"
     except Exception as e:
         reply = f"⚠️ 生成錯誤：{e}"
-    return reply or "請洽營業員"
+
+    # 保存對話記憶
+    memory.save_context({"role": "user", "content": message},
+                        {"role": "assistant", "content": reply})
+    return reply
 
 
 # =============================================
-# 6️⃣ Gradio 介面（純雲端版）
+# 6️⃣ Gradio 介面（重構版）
 # =============================================
-logo_path = os.path.join(BASE_DIR, "mega.png")
 logo_base64 = ""
-if os.path.exists(logo_path):
-    with open(logo_path, "rb") as f:
+if os.path.exists(LOGO_PATH):
+    with open(LOGO_PATH, "rb") as f:
         logo_base64 = base64.b64encode(f.read()).decode("utf-8")
 
 with gr.Blocks(
     theme="soft",
     css="""
-        /* ====== logo ====== */
         #logo-top {
             position: fixed; top: 12px; left: 18px;
             background-color: white; border-radius: 10px;
             padding: 6px 8px; box-shadow: 0 0 8px rgba(0,0,0,0.15);
+            pointer-events: none;
         }
         #logo-top img { width: 120px; height: auto; display: block; }
 
-        /* ====== 標題 ====== */
-        #main-title {
-            font-size: 28px; font-weight: bold; text-align: center;
-            line-height: 1.4; margin: 0; display: inline-block;
-        }
-        @media (max-width: 768px) {
-            #main-title { font-size: 24px; white-space: pre-line; }
-            #main-title::before {
-                content: "👨‍💼 我是小智\\A您的金融好幫手 🫰";
-                white-space: pre;
-            }
-            #main-title span { display: none; }
-        }
-
-        /* ====== footer（純白背景） ====== */
-        #footer {
-            position: fixed; bottom: 40px; left: 0; width: 100%;
-            text-align: center; font-size: 13px; color: #aaa;
-            border-top: 1px solid #ddd; padding-top: 8px;
-            background-color: transparent;
-        }
-        @media (max-width: 768px) {
-            #footer { position: relative; margin-top: 40px; }
-        }
-
-        /* ====== LINE 風格輸入區 ====== */
-        #input-row { display: flex; align-items: center; gap: 8px; margin-top: 10px; }
-        #user-input {
-            flex-grow: 1; border-radius: 20px; border: 1px solid #ccc;
-            padding: 6px 12px; font-size: 15px; background-color: #fff;
-            box-shadow: inset 0 0 1px rgba(0,0,0,0.05);
-        }
-
-        /* 🟢 小巧文字版「輸入」按鈕 */
-        #send-btn {
-            background-color: #00b800;
-            color: white;
-            border: none;
-            border-radius: 14px;
-            height: 26px;
-            padding: 0 10px;
-            font-size: 13px;
-            font-weight: 600;
-            cursor: pointer;
-            transition: background-color 0.2s ease, transform 0.1s ease;
-            box-shadow: 0 1px 2px rgba(0,0,0,0.1);
-        }
-        #send-btn:hover { background-color: #00a000; }
-        #send-btn:active { transform: scale(0.95); }
+        #footer { text-align:center; font-size:13px; color:#aaa; margin-top: 20px; }
     """
 ) as demo:
     if logo_base64:
-        gr.HTML(f"""
-            <div id="logo-top"><img src="data:image/png;base64,{logo_base64}" alt="logo"></div>
-        """)
+        gr.HTML(f"<div id='logo-top'><img src='data:image/png;base64,{logo_base64}'></div>")
 
-    gr.HTML("""
-        <div id="main-title-wrapper" style="text-align:center; margin-top:20px;">
-            <h1 id='main-title'><span>👨‍💼 我是小智&nbsp;&nbsp;您的金融好幫手 🫰</span></h1>
-            <p id='sub-title' style='margin-top:10px; font-size:14px; color:#666;'>Powered by Gemini & LangChain</p>
-        </div>
-    """)
+    gr.Markdown("## 👨‍💼 我是小智 · 您的金融好幫手 🫰")
+    gr.Markdown("Powered by Gemini & LangChain")
 
     with gr.Row():
         with gr.Column(scale=4):
-            chatbox = gr.Chatbot(label="💬 對話紀錄", type="messages")
-            with gr.Row(elem_id="input-row"):
-                user_input = gr.Textbox(elem_id="user-input", show_label=False, placeholder="輸入訊息...", scale=8)
-                send_btn = gr.Button("輸入", elem_id="send-btn", scale=1)
+            chatbot = gr.Chatbot(label="💬 對話紀錄", type="messages", height=500)
+
+            with gr.Row():
+                user_input = gr.Textbox(placeholder="請輸入問題...", show_label=False)
+                send_btn = gr.Button("送出", variant="primary")
 
             def handle_input(message, history):
                 if not message.strip():
                     return history, gr.update(value="")
                 reply = chat_fn(message, history)
-                history = history + [
-                    {"role": "user", "content": message},
-                    {"role": "assistant", "content": reply}
-                ]
+                history += [{"role": "user", "content": message},
+                            {"role": "assistant", "content": reply}]
                 return history, gr.update(value="")
 
-            user_input.submit(handle_input, [user_input, chatbox], [chatbox, user_input])
-            send_btn.click(handle_input, [user_input, chatbox], [chatbox, user_input])
+            user_input.submit(handle_input, [user_input, chatbot], [chatbot, user_input])
+            send_btn.click(handle_input, [user_input, chatbot], [chatbot, user_input])
+
+            def clear_all():
+                memory.clear()
+                return [], gr.update(value="")
+            gr.Button("🧹 清除對話").click(clear_all, outputs=[chatbot, user_input])
 
         with gr.Column(scale=1):
-            gr.Markdown("### 👇 快速提問")
-            btns = [
-                ("未成年可以開戶嗎？", "未成年可以開戶嗎?"),
-                ("法人開戶要準備什麼？", "法人開戶要準備什麼?"),
-                ("期貨交易保證金是什麼？", "期貨交易保證金是什麼?"),
-                ("複委託要如何下單？", "複委託要如何下單?"),
-                ("美股交易時間？", "美股交易時間?"),
-                ("美股可以定期定額嗎？", "美股可以定期定額嗎?")
+            gr.Markdown("### 🔍 常見問題")
+            examples = [
+                "未成年可以開戶嗎？",
+                "法人開戶要準備什麼？",
+                "期貨交易保證金是什麼？",
+                "複委託要如何下單？",
+                "美股交易時間？",
+                "美股可以定期定額嗎？"
             ]
-            for label, q in btns:
-                gr.Button(label).click(lambda h, q=q: handle_input(q, h), [chatbox], [chatbox, user_input])
-
-            def clear_memory():
-                memory.clear()
-                return [], gr.update(value="", placeholder="輸入訊息...")
-            gr.Button("🧹 整理畫面").click(clear_memory, outputs=[chatbox, user_input])
+            for q in examples:
+                gr.Button(q).click(lambda h, q=q: handle_input(q, h), [chatbot], [chatbot, user_input])
 
     gr.HTML("<div id='footer'>© Fintech Assistant — 僅業務使用，非官方授權</div>")
 
-    demo.load(None, None, None, js="""
-        window.addEventListener('focusin', () => {
-            document.querySelector('textarea')?.scrollIntoView({ behavior: 'smooth', block: 'center' });
-        });
-    """)
-
 demo.launch()