413 lines
14 KiB
Python
413 lines
14 KiB
Python
"""Competitors API endpoints."""
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import asyncio
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import json
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import logging
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import uuid
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from fastapi import APIRouter, Depends, HTTPException, status
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from sqlalchemy import select, func
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.api.deps import get_current_user
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from app.config import settings
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from app.database import get_db
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from app.models.user import User
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from app.models.brand import Brand
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from app.models.competitor import Competitor
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from app.schemas.competitor import (
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CompetitorCreate,
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CompetitorResponse,
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CompetitorListResponse,
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CompetitorRecommendationItem,
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CompetitorRecommendationResponse,
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)
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from app.utils.json_extractor import extract_json
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logger = logging.getLogger(__name__)
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router = APIRouter()
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async def get_brand_if_owned(
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brand_id: uuid.UUID,
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current_user: User,
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db: AsyncSession,
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) -> Brand:
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"""Helper to get brand if owned by current user."""
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stmt = select(Brand).where(Brand.id == brand_id, Brand.user_id == current_user.id)
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result = await db.execute(stmt)
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brand = result.scalar_one_or_none()
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if not brand:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail="品牌不存在",
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)
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return brand
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@router.get("/{brand_id}/competitors/", response_model=CompetitorListResponse)
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async def get_competitors(
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brand_id: uuid.UUID,
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current_user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Get all competitors for a brand."""
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# Verify brand ownership
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await get_brand_if_owned(brand_id, current_user, db)
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stmt = select(Competitor).where(Competitor.brand_id == brand_id)
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result = await db.execute(stmt)
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competitors = result.scalars().all()
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return {"items": competitors, "total": len(competitors)}
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@router.post("/{brand_id}/competitors/", response_model=CompetitorResponse, status_code=status.HTTP_201_CREATED)
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async def create_competitor(
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brand_id: uuid.UUID,
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competitor_data: CompetitorCreate,
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current_user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Create a new competitor for a brand."""
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# Verify brand ownership
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await get_brand_if_owned(brand_id, current_user, db)
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# Check competitor limit (max 5)
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count_stmt = select(func.count()).select_from(Competitor).where(
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Competitor.brand_id == brand_id
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)
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count_result = await db.execute(count_stmt)
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current_count = count_result.scalar_one()
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if current_count >= 5:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail="竞品数量已达上限（最多5个）",
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)
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# Check for duplicate name
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dup_stmt = select(Competitor).where(
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Competitor.brand_id == brand_id,
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Competitor.name == competitor_data.name,
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)
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dup_result = await db.execute(dup_stmt)
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if dup_result.scalar_one_or_none():
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raise HTTPException(
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status_code=status.HTTP_409_CONFLICT,
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detail=f"竞品 '{competitor_data.name}' 已存在",
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)
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competitor = Competitor(
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brand_id=brand_id,
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name=competitor_data.name,
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aliases=competitor_data.aliases,
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)
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db.add(competitor)
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await db.commit()
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await db.refresh(competitor)
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return competitor
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@router.delete("/{brand_id}/competitors/{competitor_id}/", status_code=status.HTTP_204_NO_CONTENT)
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async def delete_competitor(
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brand_id: uuid.UUID,
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competitor_id: uuid.UUID,
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current_user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Delete a competitor."""
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# Verify brand ownership
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await get_brand_if_owned(brand_id, current_user, db)
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stmt = select(Competitor).where(
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Competitor.id == competitor_id,
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Competitor.brand_id == brand_id,
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)
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result = await db.execute(stmt)
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competitor = result.scalar_one_or_none()
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if not competitor:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail="竞品不存在",
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)
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await db.delete(competitor)
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await db.commit()
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return None
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@router.get("/{brand_id}/competitors/recommendations/", response_model=CompetitorRecommendationResponse)
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async def get_competitor_recommendations(
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brand_id: uuid.UUID,
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current_user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""
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基于品牌行业和名称，使用LLM推荐竞品。
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当ENABLE_LLM=True时调用DeepSeek API进行智能推荐；
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否则返回基于行业规则的默认推荐。
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"""
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brand = await get_brand_if_owned(brand_id, current_user, db)
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# Get existing competitor names to exclude
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existing_stmt = select(Competitor.name).where(Competitor.brand_id == brand_id)
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existing_result = await db.execute(existing_stmt)
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existing_names = [row[0] for row in existing_result.all()]
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if settings.ENABLE_LLM and settings.DEEPSEEK_API_KEY:
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try:
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recommendations = await _get_llm_recommendations(
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brand_name=brand.name,
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industry=brand.industry,
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existing_names=existing_names,
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)
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except Exception as e:
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logger.warning(f"LLM推荐竞品失败，回退到规则推荐: {e}")
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recommendations = _get_rule_based_recommendations(
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brand_name=brand.name,
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industry=brand.industry,
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existing_names=existing_names,
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)
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else:
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recommendations = _get_rule_based_recommendations(
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brand_name=brand.name,
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industry=brand.industry,
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existing_names=existing_names,
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)
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return CompetitorRecommendationResponse(
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brand_name=brand.name,
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industry=brand.industry,
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recommendations=recommendations,
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)
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# ============================================================
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# 竞品推荐辅助函数
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# ============================================================
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# 行业竞品知识库
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INDUSTRY_COMPETITORS = {
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"technology": [
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{"name": "华为", "reason": "国内科技巨头，覆盖云计算、终端设备等多个领域"},
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{"name": "阿里巴巴", "reason": "电商与云计算领域的领导者"},
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{"name": "腾讯", "reason": "社交与游戏领域的巨头，云服务快速增长"},
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{"name": "字节跳动", "reason": "内容平台与AI领域的新兴力量"},
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{"name": "百度", "reason": "AI与搜索领域的先行者"},
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{"name": "小米", "reason": "智能硬件与IoT生态的领先者"},
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],
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"finance": [
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{"name": "蚂蚁集团", "reason": "数字金融科技领域的领导者"},
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{"name": "京东数科", "reason": "数字科技与金融服务的创新者"},
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{"name": "平安科技", "reason": "金融科技综合解决方案提供商"},
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{"name": "陆金所", "reason": "线上财富管理平台的先行者"},
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],
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"retail": [
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{"name": "京东", "reason": "自营电商与物流体系的领导者"},
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{"name": "拼多多", "reason": "社交电商模式的创新者"},
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{"name": "美团", "reason": "本地生活服务与即时零售的领先者"},
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{"name": "盒马鲜生", "reason": "新零售模式的代表企业"},
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],
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"healthcare": [
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{"name": "平安好医生", "reason": "互联网医疗健康平台的领先者"},
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{"name": "微医", "reason": "数字医疗与健康管理的先行者"},
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{"name": "丁香园", "reason": "专业医疗知识与服务的平台"},
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{"name": "京东健康", "reason": "医药电商与互联网医疗的综合平台"},
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],
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"education": [
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{"name": "好未来", "reason": "K12教育领域的领先品牌"},
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{"name": "新东方", "reason": "语言培训与教育服务的老牌企业"},
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{"name": "网易有道", "reason": "智能学习硬件与在线教育平台"},
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{"name": "作业帮", "reason": "K12在线教育工具的领先者"},
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],
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"automotive": [
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{"name": "比亚迪", "reason": "新能源汽车领域的领导者"},
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{"name": "蔚来", "reason": "高端智能电动汽车的代表"},
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{"name": "小鹏汽车", "reason": "智能驾驶技术的创新者"},
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{"name": "理想汽车", "reason": "增程式电动SUV的先行者"},
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],
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"entertainment": [
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{"name": "哔哩哔哩", "reason": "年轻人文化与视频社区的领先者"},
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{"name": "快手", "reason": "短视频与直播平台的代表"},
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{"name": "爱奇艺", "reason": "在线视频与内容制作的领先者"},
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{"name": "芒果TV", "reason": "综艺内容与流媒体平台的创新者"},
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],
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"food": [
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{"name": "美团外卖", "reason": "外卖与本地生活服务的领导者"},
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{"name": "饿了么", "reason": "即时配送与餐饮服务平台"},
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{"name": "瑞幸咖啡", "reason": "新零售咖啡连锁的代表"},
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{"name": "海底捞", "reason": "餐饮服务体验的标杆企业"},
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],
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}
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def _get_rule_based_recommendations(
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brand_name: str,
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industry: str | None,
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existing_names: list[str],
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) -> list[CompetitorRecommendationItem]:
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"""
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基于行业规则的竞品推荐。
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Args:
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brand_name: 品牌名称
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industry: 行业标识
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existing_names: 已有竞品名称列表（用于排除）
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Returns:
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推荐竞品列表
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"""
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recommendations = []
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# 从行业知识库中获取推荐
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if industry and industry in INDUSTRY_COMPETITORS:
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for comp in INDUSTRY_COMPETITORS[industry]:
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if comp["name"] not in existing_names and comp["name"] != brand_name:
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recommendations.append(CompetitorRecommendationItem(
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name=comp["name"],
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reason=comp["reason"],
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industry=industry,
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))
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# 如果行业推荐不足3个，添加通用推荐
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if len(recommendations) < 3:
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generic_recs = [
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CompetitorRecommendationItem(
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name=f"{brand_name}行业领先者",
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reason="基于市场份额分析推荐",
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industry=industry,
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),
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CompetitorRecommendationItem(
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name=f"{brand_name}新兴竞争者",
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reason="增长势头强劲的新兴品牌",
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industry=industry,
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),
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CompetitorRecommendationItem(
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name=f"{brand_name}直接竞争对手",
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reason="产品与服务高度重叠",
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industry=industry,
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),
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]
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for rec in generic_recs:
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if rec.name not in existing_names and rec.name != brand_name:
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if not any(r.name == rec.name for r in recommendations):
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recommendations.append(rec)
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# 最多返回5个推荐
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return recommendations[:5]
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async def _get_llm_recommendations(
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brand_name: str,
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industry: str | None,
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existing_names: list[str],
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) -> list[CompetitorRecommendationItem]:
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"""
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使用DeepSeek LLM API推荐竞品。
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Args:
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brand_name: 品牌名称
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industry: 行业标识
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existing_names: 已有竞品名称列表（用于排除）
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Returns:
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推荐竞品列表
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Raises:
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Exception: API调用失败
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"""
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industry_label = _get_industry_label(industry)
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existing_str = "、".join(existing_names) if existing_names else "无"
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prompt = f"""你是一个专业的市场分析专家。请为以下品牌推荐3-5个竞品品牌。
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品牌名称: {brand_name}
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所属行业: {industry_label}
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已有竞品: {existing_str}
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请返回JSON格式（不要包含其他文字）:
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{{
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"recommendations": [
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{{"name": "竞品名称", "reason": "推荐理由（简短说明为什么是竞品）"}}
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]
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}}
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要求:
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1. 推荐的竞品必须是真实存在的品牌
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2. 不要推荐已有竞品列表中的品牌
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3. 不要推荐品牌自身
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4. 推荐理由要具体，说明竞争关系
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5. 优先推荐同行业中知名度高、市场份额大的品牌"""
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try:
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from openai import OpenAI
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client = OpenAI(
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api_key=settings.DEEPSEEK_API_KEY,
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base_url="https://api.deepseek.com",
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)
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response = await asyncio.to_thread(
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client.chat.completions.create,
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model="deepseek-chat",
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messages=[{"role": "user", "content": prompt}],
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temperature=0.3,
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max_tokens=800,
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)
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content = response.choices[0].message.content
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if not content:
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raise ValueError("API返回空响应")
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# 提取JSON
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json_str = extract_json(content)
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data = json.loads(json_str)
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recommendations = []
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for item in data.get("recommendations", []):
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name = item.get("name", "").strip()
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reason = item.get("reason", "").strip()
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if (
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name
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and reason
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and name != brand_name
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and name not in existing_names
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and 2 <= len(name) <= 50
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):
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recommendations.append(CompetitorRecommendationItem(
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name=name,
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reason=reason,
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industry=industry,
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))
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return recommendations[:5]
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except json.JSONDecodeError as e:
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logger.error(f"LLM推荐竞品JSON解析失败: {e}")
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raise
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except Exception as e:
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logger.error(f"LLM推荐竞品API调用失败: {e}")
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raise
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def _get_industry_label(industry: str | None) -> str:
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"""获取行业中文标签。"""
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labels = {
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"technology": "科技",
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"finance": "金融",
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"retail": "零售",
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"healthcare": "医疗健康",
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"education": "教育",
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"manufacturing": "制造业",
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"entertainment": "娱乐",
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"travel": "旅游",
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"food": "餐饮",
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"automotive": "汽车",
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"real_estate": "房地产",
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"other": "其他",
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}
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return labels.get(industry, "未知") if industry else "未知" |