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
88 lines
3.1 KiB
Python
88 lines
3.1 KiB
Python
from typing import Dict, Any, Optional, List
|
|
from sqlalchemy import select, text
|
|
from datetime import datetime
|
|
import logging
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class TradeCorpus:
|
|
def __init__(self):
|
|
self._ready = False
|
|
|
|
async def record(
|
|
self,
|
|
source_text: str,
|
|
target_text: str,
|
|
task_type: str,
|
|
provider: str,
|
|
source_lang: Optional[str] = None,
|
|
target_lang: Optional[str] = None,
|
|
quality_score: float = 0.5,
|
|
user_edited: bool = False,
|
|
metadata: Optional[Dict] = None,
|
|
):
|
|
try:
|
|
from app.database import AsyncSessionLocal
|
|
from app.models.corpus import CorpusEntry
|
|
|
|
async with AsyncSessionLocal() as session:
|
|
entry = CorpusEntry(
|
|
source_text=source_text[:2000],
|
|
target_text=target_text[:2000],
|
|
source_lang=source_lang,
|
|
target_lang=target_lang,
|
|
task_type=task_type,
|
|
provider_used=provider,
|
|
quality_score=quality_score,
|
|
user_edited=user_edited,
|
|
metadata=metadata or {},
|
|
)
|
|
session.add(entry)
|
|
await session.commit()
|
|
except Exception as e:
|
|
logger.warning(f"Failed to record corpus entry: {e}")
|
|
|
|
async def find_similar(self, text: str, task_type: str, top_k: int = 3) -> List[Dict[str, Any]]:
|
|
try:
|
|
from app.database import AsyncSessionLocal
|
|
from app.models.corpus import CorpusEntry
|
|
|
|
async with AsyncSessionLocal() as session:
|
|
result = await session.execute(
|
|
select(CorpusEntry)
|
|
.where(CorpusEntry.task_type == task_type)
|
|
.where(CorpusEntry.quality_score >= 0.6)
|
|
.order_by(CorpusEntry.quality_score.desc())
|
|
.limit(top_k)
|
|
)
|
|
entries = result.scalars().all()
|
|
return [
|
|
{
|
|
"source": e.source_text,
|
|
"target": e.target_text,
|
|
"score": e.quality_score,
|
|
}
|
|
for e in entries
|
|
]
|
|
except Exception as e:
|
|
logger.warning(f"Corpus search failed: {e}")
|
|
return []
|
|
|
|
async def rate_entry(self, entry_id: str, rating: int):
|
|
try:
|
|
from app.database import AsyncSessionLocal
|
|
from app.models.corpus import CorpusEntry
|
|
|
|
async with AsyncSessionLocal() as session:
|
|
result = await session.execute(
|
|
select(CorpusEntry).where(CorpusEntry.id == entry_id)
|
|
)
|
|
entry = result.scalar_one_or_none()
|
|
if entry:
|
|
entry.user_rating = rating
|
|
entry.quality_score = rating / 5.0
|
|
await session.commit()
|
|
except Exception as e:
|
|
logger.warning(f"Failed to rate corpus entry: {e}")
|