Update app.py

app.py

@@ -1,11 +1,24 @@
+"""
+======================================================
+📘 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
 from langchain_google_genai import ChatGoogleGenerativeAI
-import chromadb
-import gradio as gr
 
+# === 記憶模組相容多版本 ===
 try:
     from langchain_memory import ConversationBufferMemory
 except ImportError:
@@ -14,59 +27,90 @@ except ImportError:
     except ImportError:
         from langchain_community.memory import ConversationBufferMemory
 
-# === Embedding ===
+
+# =============================================
+# 1️⃣ Embedding 與基礎設定
+# =============================================
 embedding = HuggingFaceEmbeddings(model_name="BAAI/bge-small-zh-v1.5")
 
-# === 載入 QA ===
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
-qa_path = os.path.join(BASE_DIR, "QA_v2.txt")
-if not os.path.exists(qa_path):
-    raise FileNotFoundError(f"❌ 找不到 QA 檔案：{qa_path}")
-
-with open(qa_path, "r", encoding="utf-8") as f:
-    text = f.read()
-
-pattern = r"(Ｑ[:：].*?)(?=Ｑ[:：]|$)"
-qas = re.findall(pattern, text, flags=re.S)
-qa_docs = {"證券": [], "期貨": [], "複委託": []}
-for qa in qas:
-    if "證券" in qa:
-        qa_docs["證券"].append(Document(page_content=qa.strip()))
-    elif "期貨" in qa:
-        qa_docs["期貨"].append(Document(page_content=qa.strip()))
-    elif "複委託" in qa:
-        qa_docs["複委託"].append(Document(page_content=qa.strip()))
-
-print("✅ 已成功讀取 QA 並完成分類：")
-for k, v in qa_docs.items():
-    print(f"　{k}：{len(v)} 筆")
-
-# === 向量資料庫 ===
+QA_PATH = os.path.join(BASE_DIR, "QA_v2.txt")
+LOGO_PATH = os.path.join(BASE_DIR, "mega.png")
+
+if not os.path.exists(QA_PATH):
+    raise FileNotFoundError("❌ 找不到 QA 檔案 QA_v2.txt，請確認路徑。")
+
+API_KEY = os.getenv("GOOGLE_API_KEY")
+if not API_KEY:
+    print("⚠️ 尚未設定 GOOGLE_API_KEY，系統將以模擬回覆運行。")
+
+
+# =============================================
+# 2️⃣ QA 載入與分類（改進版正規化）
+# =============================================
+def load_qa_documents(path: str):
+    with open(path, "r", encoding="utf-8") as f:
+        text = f.read()
+
+    # 改進版正規表達式，確保每筆 QA 含問題與答案
+    pattern = r"(Ｑ[:：].*?Ａ[:：].*?)(?=Ｑ[:：]|$)"
+    qas = re.findall(pattern, text, flags=re.S)
+
+    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
+
+    return categories
+
+
+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 向量資料庫初始化（避免重複寫入）
+# =============================================
 client = chromadb.PersistentClient(path="./chroma_db")
-collections = {"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=collections[cat],
+        collection_name=collection_map[cat],
         embedding_function=embedding
     )
-    if len(vectordbs[cat].get()["documents"]) == 0:
-        vectordbs[cat].add_documents(docs)
-    else:
-        print(f"⚙️ 已載入現有向量資料庫：{collections[cat]}")
-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
 
-# === Gemini ===
-API_KEY = os.getenv("GOOGLE_API_KEY")
-if not API_KEY:
-    raise ValueError("⚠️ 未設定 GOOGLE_API_KEY。")
+print("✅ 向量資料庫已建立完成。")
+
+
+# =============================================
+# 4️⃣ 初始化 LLM 與對話記憶
+# =============================================
+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)
 
-# === 對話主邏輯 ===
-def auto_detect_category(text):
+
+# =============================================
+# 5️⃣ 對話邏輯
+# =============================================
+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"]):
@@ -76,95 +120,102 @@ def auto_detect_category(text):
     else:
         return "證券"
 
+
 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}
 ---
 使用者問題：{message}
     """
+
     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"
 
-# === Gradio 介面 ===
-logo_path = os.path.join(BASE_DIR, "mega.png")
+    # 保存對話記憶
+    memory.save_context({"role": "user", "content": message},
+                        {"role": "assistant", "content": reply})
+    return reply
+
+
+# =============================================
+# 6️⃣ Gradio 介面（重構版）
+# =============================================
 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-top {position:fixed;top:12px;left:18px;z-index:1000;
-            background:white;border-radius:10px;padding:6px 8px;
-            box-shadow:0 0 8px rgba(0,0,0,0.15);}
-        #logo-top img{width:120px;height:auto;display:block;}
-
-        #main-title{text-align:center;font-size:28px;font-weight:bold;margin:0;line-height:1.4;}
-        @media (max-width:768px){
-            #main-title{white-space:pre-line;font-size:24px;}
+        #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; }
 
-        #footer{text-align:center;font-size:13px;color:#999;border-top:1px solid #ddd;
-            padding-top:8px;margin-top:30px;background:transparent;}
-
-        #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;}
-        #send-btn{background:#00b800;color:white;border:none;border-radius:14px;
-            height:26px;padding:0 10px;font-size:13px;font-weight:600;cursor:pointer;}
-        #send-btn:hover{background:#00a000;}
+        #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}'></div>")
 
-    gr.HTML("""
-        <h1 id='main-title'>👨‍💼 我是小智<br>您的金融好幫手 🫰</h1>
-        <p style='text-align:center;margin-top:8px;color:#666;'>Powered by Gemini & LangChain</p>
-    """)
+    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 += [{"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])
-        with gr.Column(scale=1):
-            gr.Markdown("### 👇 快速提問")
-            for label,q in [
-                ("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.Button(label).click(lambda h,q=q: handle_input(q,h),[chatbox],[chatbox,user_input])
-            def clear_memory():
+
+            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="",placeholder="輸入訊息...")
-            gr.Button("🧹 整理畫面").click(clear_memory,outputs=[chatbox,user_input])
+                return [], gr.update(value="")
+            gr.Button("🧹 清除對話").click(clear_all, outputs=[chatbot, user_input])
+
+        with gr.Column(scale=1):
+            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 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.launch()
+demo.launch()