feat: AI assistant phase 2 - configurable prompt, action operations, FAQ matching, NVIDIA provider

- Admin-configurable AI prompt/quick questions from system_configs DB
- GET /api/v1/ai/quick-questions endpoint for fetching quick questions
- Local FAQ matching for instant responses (avoid AI calls for common Qs)
- AI action extraction: "add customer" intent detected, structured data returned
- Frontend action confirmation card with editable fields, calls customer API on confirm
- NVIDIA provider (stepfun-ai/step-3.5-flash) for faster chat vs deepseek-v4-flash
- Fixed httpx client timeout preventing backend hangs
- Added log_usage calls for auth events (register/login/guest/wechat)
- Admin tabs (users/stats/logs/config) fully functional with real backend
- AiAssistant component added to all tabbar pages

backend/app/ai/base.py

@@ -31,6 +31,9 @@ class AIProvider(ABC):
     ) -> Dict[str, Any]:
         pass
 
+    async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
+        raise NotImplementedError
+
     @property
     @abstractmethod
     def name(self) -> str:

backend/app/ai/local_faq.py

@@ -0,0 +1,104 @@
+from typing import Optional, List, Tuple
+import re
+
+FAQ = [
+    {
+        "keywords": ["有哪些功能", "能做什么", "有什么功能", "功能介绍", "可以做什么"],
+        "answer": "TradeMate（外贸小助手）主要有以下功能模块：\n\n"
+                  "1. **翻译** — 多语言翻译，支持外贸专业术语\n"
+                  "2. **客户管理** — 添加、编辑、分类客户，跟进记录\n"
+                  "3. **产品管理** — 产品库管理，支持分类和搜索\n"
+                  "4. **报价单** — 在线生成报价单，导出 PDF\n"
+                  "5. **营销文案** — AI 生成营销文案和开发信\n"
+                  "6. **WhatsApp 集成** — 发送消息、管理对话\n"
+                  "7. **数据看板** — 销售漏斗、客户分析\n\n"
+                  "你想了解哪个功能的详细用法？",
+    },
+    {
+        "keywords": ["添加客户", "新增客户", "创建客户", "怎么加客户", "客户录入"],
+        "answer": "添加客户很简单：\n\n"
+                  "1. 点击底部导航栏 **「客户」** 进入客户列表\n"
+                  "2. 点击右上角 **「+」** 按钮\n"
+                  "3. 填写客户信息（名称、电话、邮箱、公司、国家等）\n"
+                  "4. 点击 **保存** 即可\n\n"
+                  "你也可以直接对我说「添加客户张三，电话13800138000」，我会帮你自动提取信息并创建客户。",
+    },
+    {
+        "keywords": ["生成报价单", "创建报价单", "怎么报价", "如何报价"],
+        "answer": "生成报价单的步骤：\n\n"
+                  "1. 点击底部导航栏 **「报价」** 进入报价单列表\n"
+                  "2. 点击 **「新建报价单」**\n"
+                  "3. 选择客户（可从客户管理导入）\n"
+                  "4. 添加产品（从产品库选择或手动输入）\n"
+                  "5. 设置价格、数量、折扣等\n"
+                  "6. 点击 **生成**，系统会自动生成报价单\n"
+                  "7. 可以导出为 PDF 发送给客户",
+    },
+    {
+        "keywords": ["导出客户", "导出数据", "怎么导出", "下载客户"],
+        "answer": "导出客户数据的方法：\n\n"
+                  "1. 进入 **「客户」** 页面\n"
+                  "2. 点击右上角菜单，选择 **「导出」**\n"
+                  "3. 支持 CSV 和 Excel 两种格式\n"
+                  "4. 选择导出范围（全部/当前筛选）\n"
+                  "5. 点击确认即可下载\n\n"
+                  "导出的文件包含客户名称、电话、邮箱、公司、国家等字段。",
+    },
+    {
+        "keywords": ["营销文案", "营销", "开发信", "怎么写开发信", "营销文案生成"],
+        "answer": "生成营销文案的步骤：\n\n"
+                  "1. 进入 **「营销」** 页面\n"
+                  "2. 点击 **「新建营销文案」**\n"
+                  "3. 选择产品和目标客户\n"
+                  "4. 选择风格（专业/友好/促销等）和语言\n"
+                  "5. AI 会自动生成多版文案供你选择\n"
+                  "6. 你可以编辑修改后直接使用或保存",
+    },
+    {
+        "keywords": ["FOB", "CIF", "贸易术语", "EXW", "DDP"],
+        "answer": "**FOB（Free On Board，离岸价）**\n"
+                  "卖方负责将货物运至装运港并装上船，风险在装运港越过船舷时转移给买方。\n\n"
+                  "**CIF（Cost, Insurance and Freight，到岸价）**\n"
+                  "卖方承担运费和保险费，将货物运至目的港，风险在装运港越过船舷时转移。\n\n"
+                  "主要区别：\n"
+                  "- FOB：买方负责运费和保险\n"
+                  "- CIF：卖方负责运费和保险\n\n"
+                  "选择哪种取决于你和客户的谈判约定。",
+    },
+    {
+        "keywords": ["忘记密码", "重置密码", "修改密码"],
+        "answer": "目前 TradeMate 支持通过手机号验证码重置密码：\n\n"
+                  "1. 在登录页面点击 **「忘记密码」**\n"
+                  "2. 输入注册手机号\n"
+                  "3. 点击 **获取验证码**\n"
+                  "4. 输入验证码后设置新密码\n\n"
+                  "如有问题请联系管理员。",
+    },
+    {
+        "keywords": ["怎么登录", "无法登录", "登录不了"],
+        "answer": "登录方式：\n\n"
+                  "1. **手机号登录** — 输入手机号和密码\n"
+                  "2. **微信登录** — 点击微信图标快速登录\n"
+                  "3. **游客模式** — 无需注册即可体验部分功能\n\n"
+                  "如果无法登录，请检查网络连接，或尝试重置密码。",
+    },
+]
+
+
+def match_faq(query: str) -> Optional[str]:
+    query_lower = query.lower().strip()
+    best_score = 0
+    best_answer = None
+
+    for item in FAQ:
+        score = 0
+        for kw in item["keywords"]:
+            if kw.lower() in query_lower:
+                score += 1
+        if score > best_score:
+            best_score = score
+            best_answer = item["answer"]
+
+    if best_score >= 1:
+        return best_answer
+    return None

backend/app/ai/providers/__init__.py

@@ -5,5 +5,6 @@ from .local import LocalProvider
 from .spark import SparkProvider
 from .sensenova import SensenovaProvider
 from .opencode_go import OpencodeGoProvider
+from .nvidia import NvidiaProvider
 
-__all__ = ["OpenAIProvider", "ClaudeProvider", "DeepLProvider", "LocalProvider", "SparkProvider", "SensenovaProvider", "OpencodeGoProvider"]
+__all__ = ["OpenAIProvider", "ClaudeProvider", "DeepLProvider", "LocalProvider", "SparkProvider", "SensenovaProvider", "OpencodeGoProvider", "NvidiaProvider"]

backend/app/ai/providers/nvidia.py

@@ -0,0 +1,50 @@
+from typing import Dict, Any, Optional, List
+from app.ai.providers.openai import OpenAIProvider, SYSTEM_PROMPTS
+import logging
+import time
+import httpx
+
+logger = logging.getLogger(__name__)
+
+
+class NvidiaProvider(OpenAIProvider):
+    def __init__(self, api_key: str, model: str = "stepfun-ai/step-3.5-flash", base_url: str = "https://integrate.api.nvidia.com/v1"):
+        super().__init__(
+            api_key=api_key,
+            model=model,
+            base_url=base_url,
+            http_client=httpx.AsyncClient(timeout=httpx.Timeout(60.0)),
+        )
+        self._name = f"nvidia-{model}"
+
+    async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
+        t0 = time.time()
+
+        system = system_prompt or SYSTEM_PROMPTS["chat"]
+        messages = [{"role": "system", "content": system}]
+        if history:
+            for h in history[-10:]:
+                messages.append(h)
+        messages.append({"role": "user", "content": message})
+        t1 = time.time()
+
+        kwargs = {
+            "model": self.model,
+            "messages": messages,
+            "max_tokens": 300,
+            "temperature": 0.3,
+        }
+        resp = await self.client.chat.completions.create(**kwargs)
+        t2 = time.time()
+
+        content = resp.choices[0].message.content or ""
+        if not content and hasattr(resp.choices[0].message, "reasoning"):
+            content = resp.choices[0].message.reasoning
+        t3 = time.time()
+
+        logger.info(
+            f"NVIDIA timing: build_msgs={t1-t0:.1f}s api_call={t2-t1:.1f}s process={t3-t2:.1f}s "
+            f"chars_in={sum(len(m.get('content','')) for m in messages)} chars_out={len(content)}"
+        )
+
+        return {"reply": content, "provider": self.name, "model": self.model}

backend/app/ai/providers/openai.py

@@ -14,11 +14,21 @@ SYSTEM_PROMPTS = {
                  "marketing content that drives action. Adapt to the target audience's culture. "
                  "Return ONLY the copy, no explanations.",
     "extract": "You extract structured data from text. Return ONLY valid JSON matching the requested schema.",
+    "chat": "你是 TradeMate（外贸小助手）的 AI 助手。你的职责是帮助外贸从业者解答关于本工具使用的问题，以及提供外贸业务建议。\n"
+            "你可以回答的问题包括：\n"
+            "- 功能介绍：翻译、客户管理、产品管理、报价单、营销文案、WhatsApp 集成等\n"
+            "- 使用帮助：如何添加客户、如何生成报价单、如何导出数据等\n"
+            "- 外贸知识：贸易术语（FOB、CIF 等）、谈判技巧、跟进策略等\n\n"
+            "回答要求：\n"
+            "- 简洁扼要，用中文回答\n"
+            "- 涉及操作步骤时用数字列表说明\n"
+            "- 不确定的问题不要编造，直接说需要查证\n"
+            "- 语气友好专业",
 }
 
 
 class OpenAIProvider(AIProvider):
-    def __init__(self, api_key: str, model: str = "gpt-4o", base_url: Optional[str] = None):
+    def __init__(self, api_key: str, model: str = "gpt-4o", base_url: Optional[str] = None, http_client=None):
         try:
             from openai import AsyncOpenAI
         except ImportError:
@@ -29,6 +39,8 @@ class OpenAIProvider(AIProvider):
         kwargs = {"api_key": api_key}
         if base_url:
             kwargs["base_url"] = base_url
+        if http_client:
+            kwargs["http_client"] = http_client
         self.client = AsyncOpenAI(**kwargs)
         self.model = model
         self._name = f"openai-{model}"
@@ -92,6 +104,24 @@ class OpenAIProvider(AIProvider):
         except json.JSONDecodeError:
             return {"data": {}, "confidence": 0.0, "provider": self.name, "error": "parse_failed"}
 
+    async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
+        system = system_prompt or SYSTEM_PROMPTS["chat"]
+        messages = [{"role": "system", "content": system}]
+        if history:
+            for h in history[-10:]:
+                messages.append(h)
+        messages.append({"role": "user", "content": message})
+
+        kwargs = {
+            "model": self._cheap_model,
+            "messages": messages,
+            "max_tokens": 2000,
+            "temperature": 0.7,
+        }
+        resp = await self.client.chat.completions.create(**kwargs)
+        content = resp.choices[0].message.content or ""
+        return {"reply": content, "provider": self.name, "model": self.model}
+
     async def _call(self, system: str, prompt: str, max_tokens: int = 3000, response_format: Optional[Dict] = None, model: Optional[str] = None) -> str:
         kwargs = {
             "model": model or self.model,

backend/app/ai/router.py

@@ -1,6 +1,6 @@
 from typing import Dict, Any, Optional, List
 from app.ai.base import AIProvider
-from app.ai.providers import OpenAIProvider, ClaudeProvider, DeepLProvider, LocalProvider, SparkProvider, SensenovaProvider, OpencodeGoProvider
+from app.ai.providers import OpenAIProvider, ClaudeProvider, DeepLProvider, LocalProvider, SparkProvider, SensenovaProvider, OpencodeGoProvider, NvidiaProvider
 from app.config import settings
 from app.ai.trade_corpus import TradeCorpus
 import logging
@@ -45,6 +45,17 @@ class AIRouter:
             except Exception as e:
                 logger.warning(f"OpencodeGo init failed: {e}")
 
+        if settings.NVIDIA_API_KEY:
+            try:
+                self.providers["nvidia"] = NvidiaProvider(
+                    api_key=settings.NVIDIA_API_KEY,
+                    model=settings.NVIDIA_MODEL,
+                    base_url=settings.NVIDIA_BASE_URL,
+                )
+                logger.info("Nvidia provider ready")
+            except Exception as e:
+                logger.warning(f"Nvidia init failed: {e}")
+
         if settings.ANTHROPIC_API_KEY:
             try:
                 self.providers["anthropic"] = ClaudeProvider(api_key=settings.ANTHROPIC_API_KEY)
@@ -132,6 +143,9 @@ class AIRouter:
     async def extract(self, text: str, schema: Dict[str, Any]) -> Dict[str, Any]:
         return await self.execute("extract", "extract_info", text, schema)
 
+    async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
+        return await self.execute("chat", "chat", message, history, system_prompt)
+
 
 _router_instance = None
 

backend/app/api/v1/ai_assistant.py

@@ -0,0 +1,135 @@
+from fastapi import APIRouter, Depends, HTTPException, Request
+from pydantic import BaseModel
+from typing import Optional, List, Dict, Any
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select
+from app.database import get_db
+from app.ai.router import get_ai_router
+from app.ai.local_faq import match_faq
+from app.api.v1.deps import get_current_user_id
+from app.models.system_config import SystemConfig
+from app.services.admin import AdminService
+import logging
+import time
+import re
+import json
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter()
+
+
+ACTION_INSTRUCTIONS = """
+当用户想要执行操作时（如添加客户、创建产品、生成报价单等），请执行以下步骤：
+1. 从用户消息中提取所有必要的信息
+2. 在回复末尾附上 JSON 格式的动作块，格式如下：
+
+```actions
+[{"type": "create_customer", "label": "添加客户", "fields": {"name": "...", "phone": "...", "email": "...", "company": "...", "country": "...", "notes": "..."}}]
+```
+
+支持的 action type：
+- create_customer：添加客户，fields 支持 name(必填), phone, email, company, country, notes
+- create_product：添加产品（开发中）
+
+如果用户没有提供足够信息，请先询问缺少的字段，不要生成 action。
+如果用户明确表示要执行操作但缺少信息，生成 action 但标注缺失的字段。
+"""
+
+
+class ChatRequest(BaseModel):
+    message: str
+    history: Optional[List[Dict[str, str]]] = None
+
+
+@router.get("/quick-questions")
+async def get_quick_questions(
+    db: AsyncSession = Depends(get_db),
+):
+    result = await db.execute(
+        select(SystemConfig).where(SystemConfig.key == "ai_assistant_quick_questions")
+    )
+    cfg = result.scalar_one_or_none()
+    return cfg.value if cfg and cfg.value else []
+
+
+@router.post("/chat")
+async def chat(
+    data: ChatRequest,
+    request: Request,
+    user_id: str = Depends(get_current_user_id),
+    db: AsyncSession = Depends(get_db),
+):
+    t_start = time.time()
+
+    if not data.message.strip():
+        raise HTTPException(status_code=422, detail="Message is required")
+
+    t0 = time.time()
+    prompt_config = await db.execute(
+        select(SystemConfig).where(SystemConfig.key == "ai_assistant_prompt")
+    )
+    quick_config = await db.execute(
+        select(SystemConfig).where(SystemConfig.key == "ai_assistant_quick_questions")
+    )
+    t1 = time.time()
+
+    prompt_row = prompt_config.scalar_one_or_none()
+    base_prompt = prompt_row.value if prompt_row else None
+    quick_row = quick_config.scalar_one_or_none()
+    quick_questions = quick_row.value if quick_row else None
+    t2 = time.time()
+
+    action_keywords = ["帮我添加", "帮我创建", "帮我新增", "帮我新建", "帮我录入", "帮.+加", "添加客户.*电话", "创建客户.*电话"]
+    needs_action = any(re.search(k, data.message) for k in action_keywords)
+    system_prompt = base_prompt or ""
+    if needs_action:
+        system_prompt += "\n\n" + ACTION_INSTRUCTIONS
+
+    faq_answer = match_faq(data.message)
+    if faq_answer and not needs_action:
+        reply = faq_answer
+        provider = "local-faq"
+        actions = []
+        t4 = time.time()
+        logger.info(
+            f"CHAT [{user_id[:8]}] FAQ match | "
+            f"db={t1-t0:.2f}s orm={t2-t1:.2f}s total={t4-t_start:.2f}s"
+        )
+    else:
+        t3 = time.time()
+        ai = get_ai_router()
+        result = await ai.chat(data.message, data.history or [], system_prompt)
+        t4 = time.time()
+
+        reply = result.get("reply", "")
+        provider = result.get("provider_used", "")
+
+        actions = []
+        action_match = re.search(r'```actions\s*\n(.*?)\n```', reply, re.DOTALL)
+        if action_match:
+            try:
+                actions = json.loads(action_match.group(1))
+                reply = reply[:action_match.start()].strip()
+            except (json.JSONDecodeError, Exception) as e:
+                logger.warning(f"Failed to parse actions: {e}")
+
+        logger.info(
+            f"CHAT [{user_id[:8]}] AI | "
+            f"db={t1-t0:.2f}s orm={t2-t1:.2f}s setup={t3-t2:.2f}s ai={t4-t3:.2f}s total={t4-t_start:.2f}s"
+        )
+
+    client_ip = request.client.host if request.client else None
+    await AdminService(db).log_usage(
+        user_id, "ai.chat",
+        {"message": data.message[:200], "reply_length": len(reply), "provider": provider},
+        ip=client_ip,
+    )
+    logger.info(f"CHAT [{user_id[:8]}] done total={time.time()-t_start:.2f}s")
+
+    return {
+        "reply": reply,
+        "provider": provider,
+        "quick_questions": quick_questions,
+        "actions": actions,
+    }

backend/app/config.py

@@ -45,7 +45,11 @@ class Settings(BaseSettings):
 
     OPENCODE_GO_API_KEY: Optional[str] = None
     OPENCODE_GO_BASE_URL: str = "https://opencode.ai/zen/go/v1"
-    OPENCODE_GO_MODEL: str = "deepseek-v4-flash"
+    OPENCODE_GO_MODEL: str = "minimax-m2.7"
+
+    NVIDIA_API_KEY: Optional[str] = None
+    NVIDIA_BASE_URL: str = "https://integrate.api.nvidia.com/v1"
+    NVIDIA_MODEL: str = "stepfun-ai/step-3.5-flash"
 
     WHATSAPP_API_TOKEN: Optional[str] = None
     WHATSAPP_PHONE_NUMBER_ID: Optional[str] = None
@@ -72,6 +76,7 @@ class Settings(BaseSettings):
         "marketing": {"primary": "opencode_go", "fallback": ["sensenova", "openai", "local"]},
         "extract": {"primary": "opencode_go", "fallback": ["sensenova", "openai"]},
         "quotation": {"primary": "opencode_go", "fallback": ["sensenova", "openai"]},
+        "chat": {"primary": "nvidia", "fallback": ["opencode_go", "openai", "sensenova"]},
     }
 
     FREE_DAILY_TRANSLATE_CHARS: int = 5000

backend/app/services/admin.py

@@ -298,6 +298,8 @@ class AdminService:
             SystemConfig(key="feature_registration", value={"enabled": True}, description="新用户注册开关"),
             SystemConfig(key="free_daily_limits", value={"translate_chars": 5000, "replies": 20, "marketing": 5, "customers": 5, "products": 1, "quotations": 3}, description="免费版每日配额"),
             SystemConfig(key="pro_daily_limits", value={"translate_chars": 50000, "replies": 200, "marketing": 50, "customers": 100, "products": 20, "quotations": 30}, description="Pro 版每日配额"),
+            SystemConfig(key="ai_assistant_prompt", value="你是 TradeMate（外贸小助手）的 AI 助手。你的职责是帮助外贸从业者解答关于本工具使用的问题，以及提供外贸业务建议。\n你可以回答的问题包括：\n- 功能介绍：翻译、客户管理、产品管理、报价单、营销文案、WhatsApp 集成等\n- 使用帮助：如何添加客户、如何生成报价单、如何导出数据等\n- 外贸知识：贸易术语（FOB、CIF 等）、谈判技巧、跟进策略等\n\n回答要求：\n- 简洁扼要，用中文回答\n- 涉及操作步骤时用数字列表说明\n- 不确定的问题不要编造，直接说需要查证\n- 语气友好专业", description="AI 助手系统提示词"),
+            SystemConfig(key="ai_assistant_quick_questions", value=["TradeMate 有哪些功能？", "如何添加客户？", "如何生成报价单？", "怎么导出客户数据？", "营销文案怎么生成？", "什么是 FOB、CIF？"], description="AI 助手快捷提问列表"),
         ]
         for cfg in defaults:
             self.db.add(cfg)

uni-app/src/components/ai-assistant.vue

@@ -0,0 +1,372 @@
+<template>
+  <view>
+    <view class="ai-float-btn" @click="open = !open">
+      <text class="ai-float-icon">AI</text>
+    </view>
+
+    <view class="ai-dialog" v-if="open">
+      <view class="ai-header">
+        <text class="ai-title">TradeMate AI 助手</text>
+        <text class="ai-close" @click="open = false">×</text>
+      </view>
+
+      <scroll-view class="ai-messages" scroll-y :scroll-top="scrollTop" ref="msgRef">
+        <view v-for="(msg, i) in messages" :key="i" class="ai-msg-row" :class="msg.role">
+          <view class="ai-msg-bubble">
+            <text class="ai-msg-text">{{ msg.content }}</text>
+
+            <view v-if="msg.actions && msg.actions.length" class="ai-action-card">
+              <view v-for="(action, ai) in msg.actions" :key="ai" class="ai-action-item">
+                <text class="ai-action-title">{{ action.label }}</text>
+                <view v-for="(val, key) in action.fields" :key="key" class="ai-field-row">
+                  <text class="ai-field-label">{{ fieldLabel(key) }}</text>
+                  <input class="ai-field-input" :value="val" @input="e => editField(i, ai, key, e.detail.value)" />
+                </view>
+                <view class="ai-action-btns">
+                  <text class="ai-btn-cancel" @click="cancelAction(i, ai)">取消</text>
+                  <text class="ai-btn-confirm" @click="confirmAction(i, ai)">确认添加</text>
+                </view>
+              </view>
+            </view>
+          </view>
+        </view>
+
+        <view class="ai-loading" v-if="loading">
+          <text class="ai-loading-text">思考中...</text>
+        </view>
+
+        <view class="ai-suggestions" v-if="messages.length === 1">
+          <view class="ai-suggestion" v-for="(s, i) in suggestions" :key="i" @click="sendQuick(s)">
+            <text class="ai-suggestion-text">{{ s }}</text>
+          </view>
+        </view>
+      </scroll-view>
+
+      <view class="ai-input-bar">
+        <input class="ai-input" v-model="inputText" placeholder="输入你的问题..." @confirm="send" :disabled="loading" />
+        <text class="ai-send-btn" :class="{ disabled: !inputText.trim() || loading }" @click="send">发送</text>
+      </view>
+    </view>
+  </view>
+</template>
+
+<script setup>
+import { ref, nextTick, watch } from 'vue'
+import { aiChatApi, customerApi } from '@/utils/api.js'
+
+const open = ref(false)
+const inputText = ref('')
+const loading = ref(false)
+const scrollTop = ref(0)
+const msgRef = ref(null)
+const suggestions = ref([])
+
+const messages = ref([
+  { role: 'assistant', content: '你好！我是 TradeMate AI 助手，可以帮你解答外贸工具使用问题或外贸业务知识。有什么可以帮你的？' },
+])
+
+const fieldLabel = (key) => ({
+  name: '客户名称 *', phone: '电话', email: '邮箱',
+  company: '公司', country: '国家', notes: '备注',
+})[key] || key
+
+const editField = (msgIdx, actionIdx, key, val) => {
+  const msg = messages.value[msgIdx]
+  if (!msg.actions || !msg.actions[actionIdx]) return
+  msg.actions[actionIdx].fields[key] = val
+}
+
+const confirmAction = async (msgIdx, actionIdx) => {
+  const action = messages.value[msgIdx].actions[actionIdx]
+  if (action.type !== 'create_customer') return
+  const { fields } = action
+  if (!fields.name) {
+    uni.showToast({ title: '客户名称不能为空', icon: 'none' })
+    return
+  }
+  loading.value = true
+  try {
+    await customerApi.create(fields)
+    uni.showToast({ title: '客户添加成功', icon: 'success' })
+    messages.value[msgIdx].actions = []
+    setTimeout(() => uni.switchTab({ url: '/pages/customers/customers' }), 1500)
+  } catch (e) {
+    uni.showToast({ title: e.message || '添加失败', icon: 'none' })
+  } finally {
+    loading.value = false
+  }
+}
+
+const cancelAction = (msgIdx, actionIdx) => {
+  const msg = messages.value[msgIdx]
+  if (msg.actions) msg.actions.splice(actionIdx, 1)
+}
+
+const sendQuick = (text) => {
+  inputText.value = text
+  send()
+}
+
+const fetchSuggestions = async () => {
+  try {
+    const res = await aiChatApi.quickQuestions()
+    if (Array.isArray(res)) {
+      suggestions.value = res
+    }
+  } catch {}
+}
+
+const send = async () => {
+  const msg = inputText.value.trim()
+  if (!msg || loading.value) return
+  inputText.value = ''
+  messages.value.push({ role: 'user', content: msg })
+  loading.value = true
+  scrollToBottom()
+
+  try {
+    const hist = messages.value.map(m => ({ role: m.role, content: m.content }))
+    const res = await aiChatApi.chat(msg, hist.slice(0, -1))
+    const newMsg = { role: 'assistant', content: res.reply || '抱歉，我没有理解，请重新描述一下你的问题。' }
+    if (res.actions && res.actions.length) {
+      newMsg.actions = res.actions
+    }
+    messages.value.push(newMsg)
+  } catch {
+    messages.value.push({ role: 'assistant', content: '请求失败，请稍后重试。' })
+  } finally {
+    loading.value = false
+    scrollToBottom()
+  }
+}
+
+watch(open, (val) => { if (val && !suggestions.value.length) fetchSuggestions() })
+
+const scrollToBottom = async () => {
+  await nextTick()
+  scrollTop.value += 1
+}
+</script>
+
+<style lang="scss" scoped>
+.ai-float-btn {
+  position: fixed;
+  right: 30rpx;
+  bottom: 120rpx;
+  width: 100rpx;
+  height: 100rpx;
+  border-radius: 50%;
+  background: linear-gradient(135deg, #667eea, #764ba2);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  box-shadow: 0 4rpx 20rpx rgba(102, 126, 234, 0.4);
+  z-index: 9999;
+}
+
+.ai-float-icon {
+  color: #fff;
+  font-size: 32rpx;
+  font-weight: bold;
+}
+
+.ai-dialog {
+  position: fixed;
+  right: 30rpx;
+  bottom: 240rpx;
+  width: 580rpx;
+  height: 700rpx;
+  background: #fff;
+  border-radius: 20rpx;
+  box-shadow: 0 8rpx 40rpx rgba(0,0,0,0.15);
+  display: flex;
+  flex-direction: column;
+  z-index: 9998;
+  overflow: hidden;
+}
+
+.ai-header {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  padding: 24rpx 30rpx;
+  background: linear-gradient(135deg, #667eea, #764ba2);
+}
+
+.ai-title {
+  color: #fff;
+  font-size: 28rpx;
+  font-weight: 600;
+}
+
+.ai-close {
+  color: rgba(255,255,255,0.8);
+  font-size: 40rpx;
+  line-height: 1;
+}
+
+.ai-messages {
+  flex: 1;
+  padding: 20rpx;
+  overflow-y: auto;
+  background: #f5f5f5;
+}
+
+.ai-msg-row {
+  margin-bottom: 16rpx;
+  display: flex;
+}
+
+.ai-msg-row.user {
+  justify-content: flex-end;
+}
+
+.ai-msg-bubble {
+  max-width: 80%;
+  padding: 16rpx 20rpx;
+  border-radius: 12rpx;
+  background: #fff;
+}
+
+.ai-msg-row.assistant .ai-msg-bubble {
+  background: #fff;
+  border-bottom-left-radius: 4rpx;
+}
+
+.ai-msg-row.user .ai-msg-bubble {
+  background: #667eea;
+  border-bottom-right-radius: 4rpx;
+}
+
+.ai-msg-text {
+  font-size: 26rpx;
+  line-height: 1.5;
+  color: #333;
+  white-space: pre-wrap;
+}
+
+.ai-msg-row.user .ai-msg-text {
+  color: #fff;
+}
+
+.ai-action-card {
+  margin-top: 16rpx;
+  border-top: 2rpx solid #eee;
+  padding-top: 12rpx;
+}
+
+.ai-action-title {
+  font-size: 28rpx;
+  font-weight: 600;
+  color: #333;
+  margin-bottom: 12rpx;
+  display: block;
+}
+
+.ai-field-row {
+  margin-bottom: 10rpx;
+}
+
+.ai-field-label {
+  font-size: 24rpx;
+  color: #666;
+  display: block;
+  margin-bottom: 4rpx;
+}
+
+.ai-field-input {
+  height: 56rpx;
+  background: #f5f5f5;
+  border-radius: 8rpx;
+  padding: 0 12rpx;
+  font-size: 26rpx;
+  width: 100%;
+  box-sizing: border-box;
+}
+
+.ai-action-btns {
+  display: flex;
+  gap: 12rpx;
+  margin-top: 14rpx;
+}
+
+.ai-btn-cancel {
+  flex: 1;
+  height: 56rpx;
+  line-height: 56rpx;
+  text-align: center;
+  background: #f5f5f5;
+  color: #666;
+  border-radius: 8rpx;
+  font-size: 26rpx;
+}
+
+.ai-btn-confirm {
+  flex: 1;
+  height: 56rpx;
+  line-height: 56rpx;
+  text-align: center;
+  background: #667eea;
+  color: #fff;
+  border-radius: 8rpx;
+  font-size: 26rpx;
+}
+
+.ai-loading {
+  text-align: center;
+  padding: 10rpx 0;
+}
+
+.ai-loading-text {
+  font-size: 24rpx;
+  color: #999;
+}
+
+.ai-suggestions {
+  padding: 10rpx 0;
+}
+
+.ai-suggestion {
+  background: #f0edff;
+  border-radius: 8rpx;
+  padding: 14rpx 18rpx;
+  margin-bottom: 10rpx;
+}
+
+.ai-suggestion-text {
+  font-size: 24rpx;
+  color: #667eea;
+}
+
+.ai-input-bar {
+  display: flex;
+  align-items: center;
+  padding: 16rpx 20rpx;
+  border-top: 2rpx solid #f0f0f0;
+  gap: 12rpx;
+}
+
+.ai-input {
+  flex: 1;
+  height: 64rpx;
+  background: #f5f5f5;
+  border-radius: 32rpx;
+  padding: 0 24rpx;
+  font-size: 26rpx;
+}
+
+.ai-send-btn {
+  height: 64rpx;
+  line-height: 64rpx;
+  padding: 0 24rpx;
+  background: #667eea;
+  color: #fff;
+  border-radius: 32rpx;
+  font-size: 26rpx;
+  flex-shrink: 0;
+}
+
+.ai-send-btn.disabled {
+  opacity: 0.4;
+}
+</style>

uni-app/src/main.js

@@ -1,9 +1,11 @@
 import { createSSRApp } from 'vue'
 import App from './App.vue'
+import AiAssistant from './components/ai-assistant.vue'
 
 export function createApp() {
   const app = createSSRApp(App)
+  app.component('AiAssistant', AiAssistant)
   return {
     app,
   }
-}
+}

uni-app/src/pages/admin/admin.vue

@@ -258,11 +258,13 @@
         </view>
       </view>
     </view>
+    <AiAssistant />
   </view>
 </template>
 
 <script setup>
 import { ref, watch, computed } from 'vue'
+import AiAssistant from '@/components/ai-assistant.vue'
 import { onShow } from '@dcloudio/uni-app'
 import { adminApi } from '@/utils/api.js'
 
@@ -297,6 +299,8 @@ const configLabels = {
   feature_registration: '新用户注册',
   free_daily_limits: '免费版每日配额',
   pro_daily_limits: 'Pro 版每日配额',
+  ai_assistant_prompt: 'AI 助手系统提示词',
+  ai_assistant_quick_questions: 'AI 助手快捷提问',
 }
 
 const fieldLabels = (configKey, fieldKey) => {

uni-app/src/pages/customers/customers.vue

@@ -338,11 +338,13 @@
         </view>
       </view>
     </view>
+    <AiAssistant />
   </view>
 </template>
 
 <script setup>
 import { ref } from 'vue'
+import AiAssistant from '@/components/ai-assistant.vue'
 import { onShow } from '@dcloudio/uni-app'
 import { customerApi, healthApi, silentPatternApi, whatsappApi, translateApi } from '@/utils/api.js'
 

uni-app/src/pages/index/index.vue

@@ -253,6 +253,7 @@
       </view>
       <text class="footer-copyright">© 2026 北京宇之然科技中心. 保留所有权利.</text>
     </view>
+    <AiAssistant />
   </view>
 </template>
 
@@ -260,6 +261,7 @@
 import { ref, computed, onUnmounted } from 'vue'
 import { onShow } from '@dcloudio/uni-app'
 import { authApi, customerApi, analyticsApi, onboardingApi, notificationApi, followupApi, translateApi, BASE_URL } from '@/utils/api.js'
+import AiAssistant from '@/components/ai-assistant.vue'
 
 const showAnnouncement = ref(false)
 const currentAnnouncement = ref(0)

uni-app/src/pages/marketing/marketing.vue

@@ -143,11 +143,13 @@
     <view class="empty" v-if="!loading && (!resultsMap[activeTab] || resultsMap[activeTab].length === 0)">
       <text>{{ tabConfig[activeTab].emptyHint }}</text>
     </view>
+    <AiAssistant />
   </view>
 </template>
 
 <script setup>
 import { ref, reactive, computed } from 'vue'
+import AiAssistant from '@/components/ai-assistant.vue'
 import { marketingApi, interactionApi, translateApi, BASE_URL } from '@/utils/api.js'
 
 const tabConfig = {

uni-app/src/pages/product/product.vue

@@ -191,11 +191,13 @@
         </view>
       </view>
     </view>
+    <AiAssistant />
   </view>
 </template>
 
 <script setup>
 import { ref } from 'vue'
+import AiAssistant from '@/components/ai-assistant.vue'
 import { onShow } from '@dcloudio/uni-app'
 import { productApi } from '@/utils/api.js'
 

uni-app/src/pages/quotation/quotation.vue

@@ -242,11 +242,13 @@
         </view>
       </view>
     </view>
+    <AiAssistant />
   </view>
 </template>
 
 <script setup>
 import { ref } from 'vue'
+import AiAssistant from '@/components/ai-assistant.vue'
 import { onShow } from '@dcloudio/uni-app'
 import { quotationApi, customerApi } from '@/utils/api.js'
 

uni-app/src/pages/translate/translate.vue

@@ -105,11 +105,13 @@
     </view>
 
     <view class="keyboard-height" :style="{ height: keyboardHeight + 'px' }"></view>
+    <AiAssistant />
   </view>
 </template>
 
 <script setup>
 import { ref } from 'vue'
+import AiAssistant from '@/components/ai-assistant.vue'
 import { translateApi, interactionApi, BASE_URL } from '@/utils/api.js'
 
 const mode = ref('translate')

uni-app/src/utils/api.js

@@ -176,6 +176,11 @@ export const adminApi = {
   updateConfig: (key, value) => request(`/admin/config/${key}`, 'PUT', { value }),
 }
 
+export const aiChatApi = {
+  chat: (message, history = []) => request('/ai/chat', 'POST', { message, history }),
+  quickQuestions: () => request('/ai/quick-questions'),
+}
+
 export const analyticsApi = {
   getOverview: () => request('/analytics/overview'),
   getCustomers: () => request('/analytics/customers'),