TradeMate Dev
c6206787da
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
116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
from typing import Dict, Any, Optional, List
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from app.ai.router import get_ai_router
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from app.ai.trade_corpus import TradeCorpus
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import logging
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logger = logging.getLogger(__name__)
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class TranslationService:
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def __init__(self):
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self.ai = get_ai_router()
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self.corpus = TradeCorpus()
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async def translate(
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self, text: str, target_lang: str, source_lang: Optional[str] = None,
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context: Optional[str] = None, user_id: Optional[str] = None,
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) -> Dict[str, Any]:
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similar = await self.corpus.find_similar(text, "translate")
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if similar:
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best = similar[0]
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if len(best["source"]) > 20 and self._similarity_ratio(text, best["source"]) > 0.85:
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return {
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"translated_text": best["target"],
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"source_lang": source_lang or "auto",
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"provider_used": "corpus_cache",
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"from_cache": True,
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}
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result = await self.ai.translate(text, target_lang, source_lang, context)
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translated = result.get("translated_text", "")
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provider = result.get("provider_used", "unknown")
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await self.corpus.record(
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source_text=text,
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target_text=translated,
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task_type="translate",
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provider=provider,
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source_lang=source_lang,
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target_lang=target_lang,
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metadata={"user_id": user_id} if user_id else None,
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)
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result["source_lang"] = result.get("detected_source_lang", source_lang or "auto")
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result["from_cache"] = False
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return result
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async def generate_reply(
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self, inquiry: str, context: Optional[Dict[str, Any]] = None,
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tone: str = "professional", count: int = 3,
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) -> List[Dict[str, Any]]:
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similar = await self.corpus.find_similar(inquiry, "reply")
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if similar and count > 1:
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pass
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results = []
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tones = self._get_tones(tone, count)
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for t in tones:
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try:
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result = await self.ai.reply(inquiry, context, t)
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results.append({
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"reply": result.get("reply", ""),
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"tone": t,
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"provider": result.get("provider_used", "unknown"),
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})
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except Exception as e:
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logger.warning(f"Reply generation failed for tone '{t}': {e}")
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results.append({"reply": "", "tone": t, "error": str(e)})
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return results
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async def extract_info(self, text: str, extract_type: str = "auto") -> Dict[str, Any]:
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schemas = {
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"product": {
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"type": "object",
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"properties": {
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"product_name": {"type": "string"},
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"quantity": {"type": "string"},
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"price": {"type": "string"},
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"currency": {"type": "string"},
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"delivery_terms": {"type": "string"},
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"target_country": {"type": "string"},
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},
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},
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"inquiry": {
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"type": "object",
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"properties": {
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"intent": {"type": "string"},
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"product_interest": {"type": "string"},
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"quantity": {"type": "string"},
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"budget": {"type": "string"},
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"urgency": {"type": "string"},
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"contact_info": {"type": "string"},
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},
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},
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}
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schema = schemas.get(extract_type, schemas["inquiry"])
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result = await self.ai.extract(text, schema)
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return result.get("data", {})
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def _get_tones(self, base: str, count: int) -> List[str]:
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tones = ["professional", "friendly", "formal"]
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if base in tones:
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tones.remove(base)
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tones.insert(0, base)
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return tones[:count]
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def _similarity_ratio(self, a: str, b: str) -> float:
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if not a or not b:
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return 0.0
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set_a, set_b = set(a.lower().split()), set(b.lower().split())
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if not set_a or not set_b:
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return 0.0
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return len(set_a & set_b) / len(set_a | set_b)
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