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
This commit is contained in:
TradeMate Dev
@@ -31,6 +31,9 @@ class AIProvider(ABC):
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) -> Dict[str, Any]:
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pass
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async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
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raise NotImplementedError
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@property
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@abstractmethod
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def name(self) -> str:
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@@ -0,0 +1,104 @@
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from typing import Optional, List, Tuple
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import re
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FAQ = [
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{
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"keywords": ["有哪些功能", "能做什么", "有什么功能", "功能介绍", "可以做什么"],
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"answer": "TradeMate（外贸小助手）主要有以下功能模块：\n\n"
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"1. **翻译** — 多语言翻译，支持外贸专业术语\n"
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"2. **客户管理** — 添加、编辑、分类客户，跟进记录\n"
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"3. **产品管理** — 产品库管理，支持分类和搜索\n"
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"4. **报价单** — 在线生成报价单，导出 PDF\n"
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"5. **营销文案** — AI 生成营销文案和开发信\n"
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"6. **WhatsApp 集成** — 发送消息、管理对话\n"
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"7. **数据看板** — 销售漏斗、客户分析\n\n"
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"你想了解哪个功能的详细用法？",
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},
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{
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"keywords": ["添加客户", "新增客户", "创建客户", "怎么加客户", "客户录入"],
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"answer": "添加客户很简单：\n\n"
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"1. 点击底部导航栏 **「客户」** 进入客户列表\n"
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"2. 点击右上角 **「+」** 按钮\n"
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"3. 填写客户信息（名称、电话、邮箱、公司、国家等）\n"
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"4. 点击 **保存** 即可\n\n"
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"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。",
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},
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{
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"keywords": ["生成报价单", "创建报价单", "怎么报价", "如何报价"],
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"answer": "生成报价单的步骤：\n\n"
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"1. 点击底部导航栏 **「报价」** 进入报价单列表\n"
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"2. 点击 **「新建报价单」**\n"
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"3. 选择客户（可从客户管理导入）\n"
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"4. 添加产品（从产品库选择或手动输入）\n"
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"5. 设置价格、数量、折扣等\n"
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"6. 点击 **生成**，系统会自动生成报价单\n"
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"7. 可以导出为 PDF 发送给客户",
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},
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{
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"keywords": ["导出客户", "导出数据", "怎么导出", "下载客户"],
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"answer": "导出客户数据的方法：\n\n"
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"1. 进入 **「客户」** 页面\n"
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"2. 点击右上角菜单，选择 **「导出」**\n"
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"3. 支持 CSV 和 Excel 两种格式\n"
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"4. 选择导出范围（全部/当前筛选）\n"
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"5. 点击确认即可下载\n\n"
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"导出的文件包含客户名称、电话、邮箱、公司、国家等字段。",
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},
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{
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"keywords": ["营销文案", "营销", "开发信", "怎么写开发信", "营销文案生成"],
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"answer": "生成营销文案的步骤：\n\n"
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"1. 进入 **「营销」** 页面\n"
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"2. 点击 **「新建营销文案」**\n"
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"3. 选择产品和目标客户\n"
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"4. 选择风格（专业/友好/促销等）和语言\n"
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"5. AI 会自动生成多版文案供你选择\n"
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"6. 你可以编辑修改后直接使用或保存",
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},
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{
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"keywords": ["FOB", "CIF", "贸易术语", "EXW", "DDP"],
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"answer": "**FOB（Free On Board，离岸价）**\n"
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"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"
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"**CIF（Cost, Insurance and Freight，到岸价）**\n"
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"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"
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"主要区别：\n"
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"- FOB：买方负责运费和保险\n"
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"- CIF：卖方负责运费和保险\n\n"
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"选择哪种取决于你和客户的谈判约定。",
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},
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{
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"keywords": ["忘记密码", "重置密码", "修改密码"],
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"answer": "目前 TradeMate 支持通过手机号验证码重置密码：\n\n"
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"1. 在登录页面点击 **「忘记密码」**\n"
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"2. 输入注册手机号\n"
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"3. 点击 **获取验证码**\n"
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"4. 输入验证码后设置新密码\n\n"
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"如有问题请联系管理员。",
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},
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{
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"keywords": ["怎么登录", "无法登录", "登录不了"],
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"answer": "登录方式：\n\n"
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"1. **手机号登录** — 输入手机号和密码\n"
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"2. **微信登录** — 点击微信图标快速登录\n"
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"3. **游客模式** — 无需注册即可体验部分功能\n\n"
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"如果无法登录，请检查网络连接，或尝试重置密码。",
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},
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]
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def match_faq(query: str) -> Optional[str]:
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query_lower = query.lower().strip()
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best_score = 0
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best_answer = None
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for item in FAQ:
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score = 0
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for kw in item["keywords"]:
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if kw.lower() in query_lower:
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score += 1
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if score > best_score:
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best_score = score
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best_answer = item["answer"]
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if best_score >= 1:
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return best_answer
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return None
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@@ -5,5 +5,6 @@ from .local import LocalProvider
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from .spark import SparkProvider
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from .sensenova import SensenovaProvider
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from .opencode_go import OpencodeGoProvider
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from .nvidia import NvidiaProvider
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__all__ = ["OpenAIProvider", "ClaudeProvider", "DeepLProvider", "LocalProvider", "SparkProvider", "SensenovaProvider", "OpencodeGoProvider"]
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__all__ = ["OpenAIProvider", "ClaudeProvider", "DeepLProvider", "LocalProvider", "SparkProvider", "SensenovaProvider", "OpencodeGoProvider", "NvidiaProvider"]
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@@ -0,0 +1,50 @@
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from typing import Dict, Any, Optional, List
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from app.ai.providers.openai import OpenAIProvider, SYSTEM_PROMPTS
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import logging
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import time
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import httpx
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logger = logging.getLogger(__name__)
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class NvidiaProvider(OpenAIProvider):
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def __init__(self, api_key: str, model: str = "stepfun-ai/step-3.5-flash", base_url: str = "https://integrate.api.nvidia.com/v1"):
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super().__init__(
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api_key=api_key,
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model=model,
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base_url=base_url,
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http_client=httpx.AsyncClient(timeout=httpx.Timeout(60.0)),
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)
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self._name = f"nvidia-{model}"
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async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
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t0 = time.time()
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system = system_prompt or SYSTEM_PROMPTS["chat"]
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messages = [{"role": "system", "content": system}]
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if history:
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for h in history[-10:]:
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messages.append(h)
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messages.append({"role": "user", "content": message})
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t1 = time.time()
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kwargs = {
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"model": self.model,
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"messages": messages,
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"max_tokens": 300,
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"temperature": 0.3,
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}
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resp = await self.client.chat.completions.create(**kwargs)
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t2 = time.time()
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content = resp.choices[0].message.content or ""
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if not content and hasattr(resp.choices[0].message, "reasoning"):
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content = resp.choices[0].message.reasoning
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t3 = time.time()
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logger.info(
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f"NVIDIA timing: build_msgs={t1-t0:.1f}s api_call={t2-t1:.1f}s process={t3-t2:.1f}s "
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f"chars_in={sum(len(m.get('content','')) for m in messages)} chars_out={len(content)}"
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)
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return {"reply": content, "provider": self.name, "model": self.model}
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@@ -14,11 +14,21 @@ SYSTEM_PROMPTS = {
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"marketing content that drives action. Adapt to the target audience's culture. "
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"Return ONLY the copy, no explanations.",
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"extract": "You extract structured data from text. Return ONLY valid JSON matching the requested schema.",
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"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"
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"你可以回答的问题包括：\n"
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"- 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"
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"- 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"
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"- 外贸知识：贸易术语（FOB、CIF 等）、谈判技巧、跟进策略等\n\n"
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"回答要求：\n"
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"- 简洁扼要，用中文回答\n"
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"- 涉及操作步骤时用数字列表说明\n"
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"- 不确定的问题不要编造，直接说需要查证\n"
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"- 语气友好专业",
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}
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class OpenAIProvider(AIProvider):
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def __init__(self, api_key: str, model: str = "gpt-4o", base_url: Optional[str] = None):
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def __init__(self, api_key: str, model: str = "gpt-4o", base_url: Optional[str] = None, http_client=None):
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try:
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from openai import AsyncOpenAI
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except ImportError:
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@@ -29,6 +39,8 @@ class OpenAIProvider(AIProvider):
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kwargs = {"api_key": api_key}
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if base_url:
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kwargs["base_url"] = base_url
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if http_client:
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kwargs["http_client"] = http_client
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self.client = AsyncOpenAI(**kwargs)
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self.model = model
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self._name = f"openai-{model}"
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@@ -92,6 +104,24 @@ class OpenAIProvider(AIProvider):
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except json.JSONDecodeError:
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return {"data": {}, "confidence": 0.0, "provider": self.name, "error": "parse_failed"}
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async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
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system = system_prompt or SYSTEM_PROMPTS["chat"]
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messages = [{"role": "system", "content": system}]
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if history:
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for h in history[-10:]:
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messages.append(h)
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messages.append({"role": "user", "content": message})
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kwargs = {
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"model": self._cheap_model,
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"messages": messages,
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"max_tokens": 2000,
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"temperature": 0.7,
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}
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resp = await self.client.chat.completions.create(**kwargs)
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content = resp.choices[0].message.content or ""
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return {"reply": content, "provider": self.name, "model": self.model}
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async def _call(self, system: str, prompt: str, max_tokens: int = 3000, response_format: Optional[Dict] = None, model: Optional[str] = None) -> str:
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kwargs = {
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"model": model or self.model,
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@@ -1,6 +1,6 @@
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from typing import Dict, Any, Optional, List
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from app.ai.base import AIProvider
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from app.ai.providers import OpenAIProvider, ClaudeProvider, DeepLProvider, LocalProvider, SparkProvider, SensenovaProvider, OpencodeGoProvider
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from app.ai.providers import OpenAIProvider, ClaudeProvider, DeepLProvider, LocalProvider, SparkProvider, SensenovaProvider, OpencodeGoProvider, NvidiaProvider
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from app.config import settings
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from app.ai.trade_corpus import TradeCorpus
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import logging
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@@ -45,6 +45,17 @@ class AIRouter:
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except Exception as e:
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logger.warning(f"OpencodeGo init failed: {e}")
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if settings.NVIDIA_API_KEY:
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try:
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self.providers["nvidia"] = NvidiaProvider(
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api_key=settings.NVIDIA_API_KEY,
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model=settings.NVIDIA_MODEL,
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base_url=settings.NVIDIA_BASE_URL,
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)
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logger.info("Nvidia provider ready")
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except Exception as e:
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logger.warning(f"Nvidia init failed: {e}")
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if settings.ANTHROPIC_API_KEY:
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try:
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self.providers["anthropic"] = ClaudeProvider(api_key=settings.ANTHROPIC_API_KEY)
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@@ -132,6 +143,9 @@ class AIRouter:
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async def extract(self, text: str, schema: Dict[str, Any]) -> Dict[str, Any]:
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return await self.execute("extract", "extract_info", text, schema)
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async def chat(self, message: str, history: list = None, system_prompt: str = None) -> Dict[str, Any]:
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return await self.execute("chat", "chat", message, history, system_prompt)
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_router_instance = None
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