Initial commit: TradeMate 外贸小助手 MVP

项目结构: - backend/ Python FastAPI 后端 - uni-app/ uni-app跨端前端 - docs/ 设计文档 - docker-compose.yml Docker编排 - nginx/scripts/systemd 运维配置已完成功能: - 用户认证 (JWT) - 智能翻译 + 回复建议 - 营销素材生成 - 客户管理 + 沉默检测 - 报价单管理 - 产品库管理 - 汇率换算 - 推送通知 (uni-push) - WhatsApp Webhook框架 - Celery定时任务
2026-05-08 18:17:12 +08:00
commit c6206787da
121 changed files with 11743 additions and 0 deletions
@@ -0,0 +1,55 @@
+from typing import Dict, Any, Optional
+import json, httpx
+from app.ai.base import AIProvider
+
+
+class LocalProvider(AIProvider):
+    def __init__(self, model_url: str = "http://localhost:8001", model_name: str = "gemma-3-8b"):
+        self.model_url = model_url.rstrip("/")
+        self.model_name = model_name
+        self._name = f"local-{model_name}"
+
+    async def translate(self, text: str, source_lang: Optional[str], target_lang: str, context: Optional[str] = None) -> Dict[str, Any]:
+        prompt = f"Translate{ f' from {source_lang}' if source_lang else ''} to {target_lang}:\n{text}\n\nTranslation:"
+        result = await self._generate(prompt)
+        return {"translated_text": result, "provider": self.name, "cost": 0.0}
+
+    async def reply(self, inquiry: str, context: Optional[Dict[str, Any]] = None, tone: str = "professional") -> Dict[str, Any]:
+        ctx = ""
+        if context:
+            ctx = "\n".join(f"{k}: {v}" for k, v in context.items() if v)
+        prompt = f"{ctx}\nCustomer: {inquiry}\n\nWrite a {tone} reply:"
+        result = await self._generate(prompt)
+        return {"reply": result, "provider": self.name, "cost": 0.0}
+
+    async def generate_marketing(self, product_info: Dict[str, Any], target: str, style: str = "professional", language: str = "en") -> Dict[str, Any]:
+        info = json.dumps(product_info, ensure_ascii=False)
+        prompt = f"Product: {info}\nTarget: {target}\nStyle: {style}\nLanguage: {language}\n\nMarketing copy:"
+        result = await self._generate(prompt, max_tokens=800)
+        return {"content": result, "provider": self.name, "cost": 0.0}
+
+    async def extract_info(self, text: str, schema: Dict[str, Any]) -> Dict[str, Any]:
+        prompt = f"Extract JSON from text matching schema:\nSchema: {json.dumps(schema)}\n\nText: {text}\n\nJSON:"
+        result = await self._generate(prompt, max_tokens=500)
+        try:
+            return {"data": json.loads(result), "confidence": 0.7, "provider": self.name, "cost": 0.0}
+        except json.JSONDecodeError:
+            return {"data": {}, "confidence": 0.0, "provider": self.name, "cost": 0.0, "error": "parse_failed"}
+
+    async def _generate(self, prompt: str, max_tokens: int = 500) -> str:
+        async with httpx.AsyncClient() as client:
+            resp = await client.post(
+                f"{self.model_url}/v1/completions",
+                json={"model": self.model_name, "prompt": prompt, "max_tokens": max_tokens, "temperature": 0.7, "stream": False},
+                timeout=60,
+            )
+            resp.raise_for_status()
+            return resp.json()["choices"][0]["text"].strip()
+
+    @property
+    def name(self) -> str:
+        return self._name
+
+    @property
+    def cost_per_1k_tokens(self) -> float:
+        return 0.0