Update app.py

app.py

@@ -99,6 +99,142 @@ def chat_fn(message, history):
 # =============================================
 # 6️⃣ Gradio 介面
 # =============================================
+import os, re, base64
+from langchain_core.documents import Document
+from langchain_chroma import Chroma
+from openai import OpenAI
+from langchain.embeddings.base import Embeddings
+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:
+    try:
+        from langchain.memory import ConversationBufferMemory
+    except ImportError:
+        from langchain_community.memory import ConversationBufferMemory
+
+
+# =============================================
+# 1️⃣ 自訂 LM Studio Embedding 類別
+# =============================================
+class LmStudioEmbeddings(Embeddings):
+    def __init__(self, model_name, url):
+        self.model_name = model_name
+        self.client = OpenAI(base_url=url, api_key="lm-studio")
+
+    def embed_query(self, text: str):
+        res = self.client.embeddings.create(input=text, model=self.model_name)
+        return res.data[0].embedding
+
+    def embed_documents(self, texts: list[str]):
+        res = self.client.embeddings.create(input=texts, model=self.model_name)
+        return [x.embedding for x in res.data]
+
+
+# =============================================
+# 2️⃣ 載入 QA 檔案並分類
+# =============================================
+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")
+
+
+# =============================================
+# 3️⃣ 建立向量資料庫
+# =============================================
+embedding = LmStudioEmbeddings(
+    model_name="text-embedding-bge-large-zh-v1.5",
+    url="http://127.0.0.1:1234/v1"
+)
+client = chromadb.PersistentClient(path="./chroma_db")
+
+collection_names = {"證券": "stocks", "期貨": "futures", "複委託": "overseas"}
+vectordbs = {}
+for cat, docs in qa_docs.items():
+    vectordbs[cat] = Chroma(
+        client=client,
+        collection_name=collection_names[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")
+
+
+# =============================================
+# 4️⃣ 初始化 Gemini LLM
+# =============================================
+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。")
+
+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):
+    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"]):
+        return "期貨"
+    elif any(k in text for k in ["複委託", "海外", "美股", "港股"]):
+        return "複委託"
+    else:
+        return "證券"
+
+
+def chat_fn(message, history):
+    category = auto_detect_category(message)
+    vectordb = vectordbs.get(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"
+
+    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：
+---
+{context}
+---
+使用者問題：{message}
+    """
+
+    try:
+        response = llm.invoke(prompt)
+        reply = response.content.strip()
+    except Exception as e:
+        reply = f"⚠️ 生成錯誤：{e}"
+    return reply or "請洽營業員"
+
+
+# =============================================
+# 6️⃣ 介面（LINE風格 + 純白footer + 小輸入按鈕）
+# =============================================
 logo_path = os.path.join(BASE_DIR, "mega.png")
 logo_base64 = ""
 if os.path.exists(logo_path):
@@ -155,28 +291,22 @@ with gr.Blocks(
             box-shadow: inset 0 0 1px rgba(0,0,0,0.05);
         }
 
-        /* 🟢 小巧箭頭按鈕（含飛出動畫） */
+        /* 🟢 小巧文字版「輸入」按鈕 */
         #send-btn {
-            background-color: #00b800; border: none; border-radius: 50%;
-            width: 28px; height: 28px; cursor: pointer;
-            display: flex; align-items: center; justify-content: center;
+            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); padding: 0; overflow: hidden;
-        }
-        #send-btn svg {
-            width: 12px; height: 12px; fill: white;
-            transition: transform 0.25s ease;
+            box-shadow: 0 1px 2px rgba(0,0,0,0.1);
         }
         #send-btn:hover { background-color: #00a000; }
-        #send-btn:hover svg { transform: rotate(10deg) scale(1.15); }
-        #send-btn:active { transform: scale(0.9); }
-        #send-btn:active svg { animation: send-fly 0.5s ease-out; }
-
-        @keyframes send-fly {
-            0% { transform: translateX(0) scale(1); opacity: 1; }
-            50% { transform: translateX(8px) scale(1.2); opacity: 0; }
-            100% { transform: translateX(0) scale(1); opacity: 1; }
-        }
+        #send-btn:active { transform: scale(0.95); }
     """
 ) as demo:
     # 左上角 logo
@@ -200,11 +330,7 @@ with gr.Blocks(
 
             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(
-                    value="""
-                    <svg viewBox="0 0 24 24"><path d="M3 12l18-9-6 9 6 9z"/></svg>
-                    """, elem_id="send-btn", scale=1
-                )
+                send_btn = gr.Button("輸入", elem_id="send-btn", scale=1)
 
             def handle_input(message, history):
                 if not message.strip():