""" ====================================================== 📘 金融客服小智(Fintech Assistant) 版本:v3.2 (穩定正式版) 更新重點: 1. 修正 LangChain 記憶格式(避免 ValueError) 2. 回復原生輸入框樣式(類似 LINE 的簡潔列) 3. 保留手機自適應、桌面置中、右欄清除鍵 ====================================================== """ 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 # === 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 Embedding 與基礎設定 # ============================================= embedding = HuggingFaceEmbeddings(model_name="BAAI/bge-small-zh-v1.5") BASE_DIR = os.getcwd() QA_PATH = os.path.join(BASE_DIR, "QA_v2.txt") LOGO_PATH = os.path.join(BASE_DIR, "mega.png") API_KEY = os.getenv("GOOGLE_API_KEY") if not API_KEY: print("⚠️ 尚未設定 GOOGLE_API_KEY,系統將以模擬模式運行。") # ============================================= # 2️⃣ QA 載入與分類 # ============================================= def load_qa_documents(path: str): with open(path, "r", encoding="utf-8") as f: text = f.read() 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) return categories if os.path.exists(QA_PATH): qa_docs = load_qa_documents(QA_PATH) print("✅ 已載入 QA 檔案,共分為:", {k: len(v) for k, v in qa_docs.items()}) else: print("⚠️ 未找到 QA_v2.txt,啟用空白知識庫模式。") qa_docs = {"證券": [], "期貨": [], "複委託": []} # ============================================= # 3️⃣ 向量資料庫初始化 # ============================================= client = chromadb.Client() collection_map = {"證券": "stocks", "期貨": "futures", "複委託": "overseas"} vectordbs = {} for cat, docs in qa_docs.items(): vectordb = Chroma(client=client, collection_name=collection_map[cat], embedding_function=embedding) if hasattr(vectordb._collection, "count") and vectordb._collection.count() == 0 and docs: vectordb.add_documents(docs) vectordbs[cat] = vectordb print("✅ 向量資料庫初始化完成。") # ============================================= # 4️⃣ 初始化 LLM 與記憶體 # ============================================= if API_KEY: llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", google_api_key=API_KEY) else: llm = None # 模擬模式 memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) # ============================================= # 5️⃣ 對話邏輯 # ============================================= def auto_detect_category(text: str): 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" return "證券" def chat_fn(message, history): category = auto_detect_category(message) vectordb = vectordbs[category] docs = vectordb.similarity_search(message, k=2) context = "\n\n".join(d.page_content for d in docs) if docs else "查無相關資料" prompt = f""" 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: 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}" # ✅ 修正記憶體格式,避免 ValueError memory.save_context({"input": message}, {"output": reply}) return reply # ============================================= # 6️⃣ Gradio 介面 # ============================================= # === Logo 圖片處理 === logo_base64 = "" 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; 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:#aaa; margin-top: 20px; } /* 手機寬度下讓 Row 自動垂直排列 */ @media (max-width: 768px) { .gr-block.gr-row { flex-direction: column !important; } #logo-top img { width: 90px; } .gradio-container { padding: 8px; } #footer { font-size: 12px; margin-top: 10px; } } /* === 桌機/手機自適應標題 === */ #main-title { text-align: center; font-weight: bold; font-size: 26px; margin-top: 60px; margin-bottom: 6px; } .title-line { display: flex; justify-content: center; align-items: center; gap: 8px; flex-wrap: nowrap; } .subtitle { white-space: nowrap; } @media (max-width: 768px) { .title-line { flex-direction: column; gap: 4px; } #main-title { font-size: 22px; line-height: 1.4; } } /* ✅ 修正輸入框高度與按鈕比例 */ #chat-input textarea { height: 48px !important; min-height: 48px !important; font-size: 16px !important; padding: 8px 12px !important; border-radius: 10px !important; } #chat-row { align-items: center !important; gap: 4px !important; } #send-btn { height: 48px !important; font-size: 16px !important; border-radius: 10px !important; } /* ✅ 桌機版比例:輸入框 9、按鈕 1 */ #chat-row > .gr-textbox { flex: 9 !important; } #chat-row > .gr-button { flex: 1 !important; } /* ✅ 手機版比例:輸入框 9、按鈕 1 */ @media (max-width: 768px) { #chat-row > .gr-textbox { flex: 9 !important; } #chat-row > .gr-button { flex: 1 !important; } } """ ) as demo: if logo_base64: gr.HTML(f"
") # 🔹 標題(桌機同行、手機自動換行) gr.HTML("""
👨‍💼 我是小智 您的金融好幫手 🫰
""") gr.Markdown("
Powered by Gemini & LangChain
") with gr.Row(equal_height=False): # 左側:聊天區 with gr.Column(scale=4, min_width=300): chatbot = gr.Chatbot(label="💬 對話紀錄", type="messages", height=500) # ✅ 輸入框與送出鍵同行排列(桌機 8:2、手機 9:1) with gr.Row(elem_id="chat-row"): user_input = gr.Textbox( placeholder="請輸入您的問題(Enter 送出 / Shift+Enter 換行)...", show_label=False, lines=1, max_lines=3, elem_id="chat-input", scale=9 ) send_btn = gr.Button( "送出", variant="primary", elem_id="send-btn", scale=1 ) # === 輸入邏輯 === def handle_input(message, history): if history is None: history = [] if not message.strip(): return history, gr.update(value="") reply = chat_fn(message, history) history += [ {"role": "user", "content": message}, {"role": "assistant", "content": reply} ] return history, gr.update(value="") # ✅ 綁定事件(Enter送出、Shift+Enter換行) user_input.submit(handle_input, [user_input, chatbot], [chatbot, user_input]) # Enter 觸發送出 send_btn.click(handle_input, [user_input, chatbot], [chatbot, user_input]) # 按鈕觸發送出 # ✅ 修正版 JS:適用桌機與手機 gr.HTML(""" """) # 右側:常見問題 + 整理畫面 with gr.Column(scale=1, min_width=200): 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( fn=lambda q=q, history=[]: handle_input(q, history), inputs=[], outputs=[chatbot, user_input] ) def clear_all(): memory.clear() return [], gr.update(value="") gr.Markdown("---") gr.Button("🧹 整理畫面").click(clear_all, outputs=[chatbot, user_input]) gr.HTML("") demo.launch()