330 lines
14 KiB
Python
330 lines
14 KiB
Python
from django.shortcuts import render
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from .models import Work, Fingerprint
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from .serializers import WorkSerializer, WorkCreateSerializer, WorkDqCalSerializer, WorkDhCalSerializer
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from apps.utils.viewsets import CustomModelViewSet
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from rest_framework.decorators import action
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import os
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from django.conf import settings
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import json
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from apps.carbon.service import parse_file, get_fingerprint, hamming_distance, split_simhash
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import requests
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from rest_framework.exceptions import ParseError
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import re
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from rest_framework.response import Response
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from django.db import transaction, IntegrityError
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from django.db.models import Q
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# Create your views here.
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LLM_URL = "http://106.0.4.200:9000/v1/chat/completions"
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API_KEY = "JJVAide0hw3eaugGmxecyYYFw45FX2LfhnYJtC+W2rw"
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MODEL = "Qwen/QwQ-32B"
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HEADERS = {
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"Authorization": f"Bearer {API_KEY}",
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"Content-Type": "application/json"
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}
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HAMMING_THRESHOLD = 5 # 指纹相似阈值，可调
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def get_standard():
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standard_path = os.path.join(settings.BASE_DIR, 'apps', 'carbon', 'standard.json')
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with open(standard_path, 'r', encoding='utf-8') as f:
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standard_content = json.load(f)
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return standard_content
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def ask(input:str, p_name:str, stream=False):
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promot_path = os.path.join(settings.BASE_DIR, 'apps', 'carbon', 'promot', f"{p_name}.md")
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with open(promot_path, "r", encoding="utf-8") as f:
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promot_str = f.read()
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his = [{"role":"system", "content": promot_str}]
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his.append({"role":"user", "content": input})
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payload = {
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"model": MODEL,
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"messages": his,
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"temperature": 0,
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"stream": stream,
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"chat_template_kwargs": {"enable_thinking": False}
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}
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response = requests.post(LLM_URL, headers=HEADERS, json=payload, stream=stream, timeout=(60, 240))
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if not stream:
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if response.json().get("detail") == "Internal server error":
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raise ParseError("模型处理错误超过最大token限制")
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return response.json()["choices"][0]["message"]["content"]
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def simhash_to_db(n: int) -> int:
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return n if n < (1 << 63) else n - (1 << 64)
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def simhash_from_db(n: int) -> int:
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return n if n >= 0 else n + (1 << 64)
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class WorkViewSet(CustomModelViewSet):
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queryset = Work.objects.all()
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serializer_class = WorkSerializer
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create_serializer_class = WorkCreateSerializer
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search_fields = ['name', "description"]
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@action(methods=['get'], detail=False, perms_map={'get': '*'})
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def my(self, request, *args, **kwargs):
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user = self.request.user
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queryset = self.filter_queryset(self.get_queryset().filter(create_by=user))
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page = self.paginate_queryset(queryset)
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if page is not None:
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serializer = self.get_serializer(page, many=True)
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return self.get_paginated_response(serializer.data)
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serializer = self.get_serializer(queryset, many=True)
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return Response(serializer.data)
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@action(detail=True, methods=['post'], serializer_class=WorkDqCalSerializer)
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@transaction.atomic
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def cal_dq(self, request, pk):
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work = self.get_object()
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sr = WorkDqCalSerializer(work, data=request.data)
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sr.is_valid(raise_exception=True)
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sr.save()
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total_score = 0
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work = Work.objects.get(pk=pk)
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# 开始计算贷前评分和指纹
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data = get_standard()
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if work.dq_file1:
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for item in data:
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if item["thirdLevel"] in [
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"碳中和路线图",
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"短期/中期/长期减碳目标",
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"设立碳管理相关部门",
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"气候相关风险评估机制",
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"内部碳定价机制",
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"碳管理数字化平台建设",
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"碳交易与履约能力",
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"CCER等减排项目开发管理",
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"数字化碳管理平台",
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]:
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item["result"] = item["scoringCriteria"][0]["选项"]
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item["score"] = item["fullScore"]
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total_score += item["score"]
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if work.dq_file2:
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for item in data:
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if item["thirdLevel"] in [
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"能源与碳排放管理体系",
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"碳排放数据监测、报告与核查",
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"参与权威信息平台披露",
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"碳中和目标与进展经第三方认证",
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"碳排放实时监测覆盖率达标",
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"数据自动化采集比例达标",
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"数据质量与校验机制",
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]:
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item["result"] = item["scoringCriteria"][0]["选项"]
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item["score"] = item["fullScore"]
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total_score += item["score"]
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if work.dq_file3:
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for item in data:
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if item["thirdLevel"] in [
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"ESG报告",
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"工业固废/生物质资源利用率数据",
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"硫化物减排措施",
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"氮氧化物减排措施",
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"其他污染物减排措施",
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"项目选址生态避让与保护",
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"矿山生态修复与复垦方案",
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"厂区绿化与生态碳汇措施",
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"低碳产品认证与标识",
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"产品耐久性与回收性设计",
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"无环保处罚与信访记录",
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"环境应急管理体系",
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"员工健康安全管理体系与制度",
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"符合标准的物理环境与防护措施",
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"员工心理健康支持计划",
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"社区沟通与透明度机制",
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"社区经济与发展贡献措施",
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"社区负面影响缓解措施",
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"供应商行为准则",
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"供应商筛查与评估机制",
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"供应商审核与改进机制",
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"完善的治理结构",
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"商业道德与反腐败制度",
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]:
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item["result"] = item["scoringCriteria"][0]["选项"]
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item["score"] = item["fullScore"]
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total_score += item["score"]
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if work.dq_file4:
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for item in data:
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if item["thirdLevel"] in [
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"资金分配明细",
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"资本金比例与到位证明",
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"融资渠道多样性",
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"成本效益分析",
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"碳减排收益量化",
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"社会效益评估",
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"风险管控方案",
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"关键风险应对策略与预案",
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"金融机构或第三方风险分担机制",
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"绿色金融资质认证与资金用途",
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"融资条款与ESG绩效挂钩",
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"国际合作资金申请与利用",
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"应急响应与能力建设机制",
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]:
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item["result"] = item["scoringCriteria"][0]["选项"]
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item["score"] = item["fullScore"]
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total_score += item["score"]
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if work.dq_file5:
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for item in data:
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if item["thirdLevel"] in [
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"AI预测减碳潜力应用",
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"智能优化控制算法应用",
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"ERP/EMS/MES系统集成度达标",
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"IoT设备覆盖率达标",
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"跨系统数据协同能力",
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"碳数据安全管理措施",
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"系统抗攻击能力达标",
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"数据合规性与审计追踪机制",
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]:
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item["result"] = item["scoringCriteria"][0]["选项"]
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item["score"] = item["fullScore"]
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total_score += item["score"]
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if work.dq_file6:
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path = (settings.BASE_DIR + work.dq_file6.path).replace('\\', '/')
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file_content = parse_file(path)
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if file_content:
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res = ask(f'以下内容为用户报告: {file_content}', "tec")
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if res == "是":
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for item in data:
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if item["firstLevel"] == "二、技术路径（35 分）":
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item["result"] = item["scoringCriteria"][0]["选项"]
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item["score"] = item["fullScore"]
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total_score += item["score"]
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if work.dq_file1:
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path = (settings.BASE_DIR + work.dq_file1.path).replace('\\', '/')
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content = parse_file(path)
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if content:
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if bool(re.search(r'碳?减排目标', content)):
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data[3]["result"] = "有"
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data[3]["score"] = data[3]["fullScore"]
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total_score += data[3]["score"]
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def cal_percent(decline_patterns, content, data, index, total_score):
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decline_percent = None
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for pattern in decline_patterns:
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match = re.search(pattern, content, re.DOTALL)
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if match:
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decline_percent = float(match.group(1))
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break
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if decline_percent:
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if decline_percent >= 10:
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data[index]["result"] = 3
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data[index]["score"] = 5
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elif decline_percent >= 5:
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data[index]["result"] = 2
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data[index]["score"] = 2.5
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elif decline_percent > 0:
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data[index]["result"] = 1
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data[index]["score"] = 1.5
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total_score += data[index].get("score", 0)
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return total_score
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# 碳排放总量
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decline_patterns1 = [
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r'碳排放总量[^，。]*?下降\s*([\d.]+)%',
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r'碳排放[^，。]*?总量[^，。]*?下降\s*([\d.]+)%',
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r'碳总量[^，。]*?下降\s*([\d.]+)%',
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r'排放总量[^，。]*?下降\s*([\d.]+)%',
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r'排放[^，。]*?下降\s*([\d.]+)%'
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]
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total_score = cal_percent(decline_patterns1, content, data, 0, total_score)
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# 碳排放强度
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decline_patterns2 = [
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r'碳排放强度[^，。]*?下降\s*([\d.]+)%',
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r'碳强度[^，。]*?总量[^，。]*?下降\s*([\d.]+)%',
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r'排放强度[^，。]*?下降\s*([\d.]+)%'
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]
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total_score = cal_percent(decline_patterns2, content, data, 1, total_score)
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# 产品碳足迹
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decline_patterns3 = [
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r'产品碳足迹[^，。]*?下降\s*([\d.]+)%',
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r'碳足迹[^，。]*?下降\s*([\d.]+)%',
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r'产品足迹[^，。]*?下降\s*([\d.]+)%'
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]
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total_score = cal_percent(decline_patterns3, content, data, 2, total_score)
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total_score = round(total_score, 2)
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work.score_dq = total_score
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work.save(update_fields=["score_dq"])
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return Response({"total_score": total_score, "data": data})
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@staticmethod
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def parse_files(work: Work):
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contents = []
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filenames = []
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for file in [work.dh_file1, work.dh_file2, work.dh_file3, work.dh_file4, work.dh_file5, work.dh_file6]:
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if file:
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if file.name in filenames:
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continue
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path = (settings.BASE_DIR + file.path).replace('\\', '/')
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content = parse_file(path)
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filenames.append(file.name)
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contents.append(content)
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return '\n'.join(contents)
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@action(detail=True, methods=['post'], serializer_class=WorkDhCalSerializer)
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@transaction.atomic
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def cal_dh(self, request, pk):
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work = self.get_object()
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sr = WorkDhCalSerializer(work, data=request.data)
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sr.is_valid(raise_exception=True)
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sr.save()
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work = Work.objects.get(pk=pk)
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content = WorkViewSet.parse_files(work)
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fp_u = get_fingerprint(content) # unsigned
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fp_int = simhash_to_db(fp_u) # signed for db
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fp_hex = format(fp_u, "016x")
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s1, s2, s3, s4 = split_simhash(fp_int)
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# 1️⃣ 分段粗筛
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candidates = (
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Fingerprint.objects
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.filter(
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Q(seg1=s1) |
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Q(seg2=s2) |
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Q(seg3=s3) |
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Q(seg4=s4)
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)
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.only("fp_int", "score")
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)
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# 2️⃣ 精确海明距离
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for obj in candidates:
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if hamming_distance(fp_u, obj.fp_int) <= HAMMING_THRESHOLD:
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work.score_dh = obj.score
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work.save(update_fields=["score_dh"])
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return Response({"total_score": obj.score})
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# 3️⃣ 未命中 → 调用 AI
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res = ask(content, "tec_dh")
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score = round(float(res), 2)
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work.score_dh = score
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work.save(update_fields=["score_dh"])
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# 4️⃣ 并发安全写入指纹库
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try:
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Fingerprint.objects.create(
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fp_hex=fp_hex,
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fp_int=fp_int,
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seg1=s1,
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seg2=s2,
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seg3=s3,
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seg4=s4,
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score=score,
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)
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except IntegrityError:
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# 并发下已存在，忽略即可
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pass
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return Response({"total_score": score})
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