commit 48146b1c8c0e143578d884ab623aa2134204f2ca Author: caoqianming Date: Fri Oct 31 16:18:15 2025 +0800 feat: cp_app首次提交 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..4be6e16 --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +dist/* \ No newline at end of file diff --git a/cp_app.py b/cp_app.py new file mode 100644 index 0000000..035eb55 --- /dev/null +++ b/cp_app.py @@ -0,0 +1,326 @@ +from flask import Flask, jsonify, request, send_from_directory +from flask_cors import CORS +import json +from docx import Document +import io +import fitz # PyMuPDF +import requests +import os +import re +from flask_jwt_extended import JWTManager, create_access_token, jwt_required, get_jwt_identity + +app = Flask(__name__, static_folder='dist/assets', static_url_path='/assets') +CORS(app) +VUE_DIST_DIR = os.path.join(os.path.dirname(__file__), 'dist') +app.config['JWT_SECRET_KEY'] = 'carbon' +jwt = JWTManager(app) + +LLM_URL = "http://106.0.4.200:9000/v1/chat/completions" +API_KEY = "JJVAide0hw3eaugGmxecyYYFw45FX2LfhnYJtC+W2rw" +MODEL = "Qwen/QwQ-32B" +HEADERS = { + "Authorization": f"Bearer {API_KEY}", + "Content-Type": "application/json" +} +OCR_URL = "http://127.0.0.1:3402/ocr_full" + +def get_standard(): + with open("./standard.json", "r", encoding="utf-8") as f: + standard = json.load(f) + return standard + + +@app.route("/api/standard/", methods=["GET"]) +def get_s(): + return get_standard() + +@app.route('/') +def index(): + return send_from_directory(VUE_DIST_DIR, 'index.html') + +def get_users(): + with open("./users.json", "r", encoding="utf-8") as f: + users = json.load(f) + return users + +@app.route('/api/login/', methods=["POST"]) +def login(): + username = request.json.get("username", "unknown") + password = request.json.get("password", "unknown") + users = get_users() + if username in users and users[username]["password"] == password: + access = create_access_token(identity=username) + return jsonify({"access": access, "userInfo": {"username": username, "name": users[username]["name"]}}), 200 + return jsonify({"err_msg": "用户名或密码错误"}), 400 + +@app.route("/api/cal/", methods=["POST"]) +@jwt_required() +def cal(): + data = get_standard() + file1 = request.files.get("file1", None) + file2 = request.files.get("file2", None) + file3 = request.files.get("file3", None) + file4 = request.files.get("file4", None) + file5 = request.files.get("file5", None) + file6 = request.files.get("file6", None) + if file1 or file2 or file3 or file4 or file5 or file6: + pass + else: + return jsonify({"err_msg": "请至少上传一个文件"}), 400 + total_score = 0 + if file1: + for item in data: + if item["thirdLevel"] in [ + "碳中和路线图", + "短期/中期/长期减碳目标", + "设立碳管理相关部门", + "气候相关风险评估机制", + "内部碳定价机制", + "碳管理数字化平台建设", + "碳交易与履约能力", + "CCER等减排项目开发管理", + "数字化碳管理平台", + ]: + item["result"] = item["scoringCriteria"][0]["选项"] + item["score"] = item["fullScore"] + total_score += item["score"] + if file2: + for item in data: + if item["thirdLevel"] in [ + "能源与碳排放管理体系", + "碳排放数据监测、报告与核查", + "参与权威信息平台披露", + "碳中和目标与进展经第三方认证", + "碳排放实时监测覆盖率达标", + "数据自动化采集比例达标", + "数据质量与校验机制", + ]: + item["result"] = item["scoringCriteria"][0]["选项"] + item["score"] = item["fullScore"] + total_score += item["score"] + if file3: + for item in data: + if item["thirdLevel"] in [ + "ESG报告", + "工业固废/生物质资源利用率数据", + "硫化物减排措施", + "氮氧化物减排措施", + "其他污染物减排措施", + "项目选址生态避让与保护", + "矿山生态修复与复垦方案", + "厂区绿化与生态碳汇措施", + "低碳产品认证与标识", + "产品耐久性与回收性设计", + "无环保处罚与信访记录", + "环境应急管理体系", + "员工健康安全管理体系与制度", + "符合标准的物理环境与防护措施", + "员工心理健康支持计划", + "社区沟通与透明度机制", + "社区经济与发展贡献措施", + "社区负面影响缓解措施", + "供应商行为准则", + "供应商筛查与评估机制", + "供应商审核与改进机制", + "完善的治理结构", + "商业道德与反腐败制度", + ]: + item["result"] = item["scoringCriteria"][0]["选项"] + item["score"] = item["fullScore"] + total_score += item["score"] + if file4: + for item in data: + if item["thirdLevel"] in [ + "资金分配明细", + "资本金比例与到位证明", + "融资渠道多样性", + "成本效益分析", + "碳减排收益量化", + "社会效益评估", + "风险管控方案", + "关键风险应对策略与预案", + "金融机构或第三方风险分担机制", + "绿色金融资质认证与资金用途", + "融资条款与ESG绩效挂钩", + "国际合作资金申请与利用", + "应急响应与能力建设机制", + ]: + item["result"] = item["scoringCriteria"][0]["选项"] + item["score"] = item["fullScore"] + total_score += item["score"] + if file5: + for item in data: + if item["thirdLevel"] in [ + "AI预测减碳潜力应用", + "智能优化控制算法应用", + "ERP/EMS/MES系统集成度达标", + "IoT设备覆盖率达标", + "跨系统数据协同能力", + "碳数据安全管理措施", + "系统抗攻击能力达标", + "数据合规性与审计追踪机制", + ]: + item["result"] = item["scoringCriteria"][0]["选项"] + item["score"] = item["fullScore"] + total_score += item["score"] + + e_filename = None + e_content, e_err_msg = None, None + if file6: + # 获取文件名和类型 + filename = file6.filename + e_filename = filename + file_type = filename.rsplit('.', 1)[1].lower() if '.' in filename else None + + content, err_msg = parse_file(file6, file_type) + e_content = content + e_err_msg = err_msg + if content: + res = ask(f'以下内容为用户报告: {content}', "tec") + if res == "是": + for item in data: + if item["firstLevel"] == "二、技术路径（35 分）": + item["result"] = item["scoringCriteria"][0]["选项"] + item["score"] = item["fullScore"] + total_score += item["score"] + else: + return jsonify({"err_msg": err_msg}), 400 + + if file1: + filename = file1.filename + file_type = filename.rsplit('.', 1)[1].lower() if '.' in filename else None + if filename == e_filename: + content, err_msg = e_content, e_err_msg + else: + content, err_msg = parse_file(file1, file_type) + if content: + if bool(re.search(r'碳?减排目标', content)): + data[3]["result"] = "有" + data[3]["score"] = data[3]["fullScore"] + total_score += data[3]["score"] + + + def cal_percent(decline_patterns, content, data, index, total_score): + decline_percent = None + for pattern in decline_patterns: + match = re.search(pattern, content, re.DOTALL) + if match: + decline_percent = float(match.group(1)) + break + if decline_percent: + if decline_percent >= 10: + data[index]["result"] = 3 + data[index]["score"] = 5 + elif decline_percent >= 5: + data[index]["result"] = 2 + data[index]["score"] = 2.5 + elif decline_percent > 0: + data[index]["result"] = 1 + data[index]["score"] = 1.5 + total_score += data[index].get("score", 0) + return total_score + + # 碳排放总量 + decline_patterns1 = [ + r'碳排放总量[^，。]*?下降\s*([\d.]+)%', + r'碳排放[^，。]*?总量[^，。]*?下降\s*([\d.]+)%', + r'碳总量[^，。]*?下降\s*([\d.]+)%', + r'排放总量[^，。]*?下降\s*([\d.]+)%', + r'排放[^，。]*?下降\s*([\d.]+)%' + ] + total_score = cal_percent(decline_patterns1, content, data, 0, total_score) + + # 碳排放强度 + decline_patterns2 = [ + r'碳排放强度[^，。]*?下降\s*([\d.]+)%', + r'碳强度[^，。]*?总量[^，。]*?下降\s*([\d.]+)%', + r'排放强度[^，。]*?下降\s*([\d.]+)%' + ] + total_score = cal_percent(decline_patterns2, content, data, 1, total_score) + + # 产品碳足迹 + decline_patterns3 = [ + r'产品碳足迹[^，。]*?下降\s*([\d.]+)%', + r'碳足迹[^，。]*?下降\s*([\d.]+)%', + r'产品足迹[^，。]*?下降\s*([\d.]+)%' + ] + total_score = cal_percent(decline_patterns3, content, data, 2, total_score) + else: + return jsonify({"err_msg": err_msg}), 400 + return jsonify({"total_score": round(total_score, 2), "data": data}) + +def ask(input:str, p_name:str, stream=False): + with open (f"promot/{p_name}.md", "r", encoding="utf-8") as f: + promot_str = f.read() + his = [{"role":"system", "content": promot_str}] + his.append({"role":"user", "content": input}) + payload = { + "model": MODEL, + "messages": his, + "temperature": 0, + "stream": stream, + "chat_template_kwargs": {"enable_thinking": False} + } + response = requests.post(LLM_URL, headers=HEADERS, json=payload, stream=stream, timeout=(60, 240)) + print(response.json()) + if not stream: + return response.json()["choices"][0]["message"]["content"] + +def parse_file(file_content, file_type): + try: + if file_type == "pdf": + # 将文件内容转换为字节流 + pdf_bytes = file_content.read() + pdf_stream = io.BytesIO(pdf_bytes) + doc = fitz.open(stream=pdf_stream, filetype="pdf") + text_content = "" + + # 首先尝试直接提取文本 + for page_num in range(len(doc)): + page = doc[page_num] + text_content += page.get_text() + "\n" + + t_plain = text_content.strip() + if t_plain: + doc.close() + return t_plain, None + else: + # 直接转发字节流 + # resp = requests.post(OCR_URL, + # files={"pdf": (file_content.filename, + # pdf_stream, + # "application/pdf")}, + # timeout=120) # 大文件酌情加长 + # resp.raise_for_status() + # return resp.json()["full_text"], None + return None, "无法直接提取文本，请使用OCR处理" + + elif file_type == "docx": + # 将文件内容转换为字节流 + doc_stream = io.BytesIO(file_content.read()) + doc = Document(doc_stream) + + # 提取所有段落的文本 + text_content = "" + for paragraph in doc.paragraphs: + text_content += paragraph.text + "\n" + + # 提取表格中的文本 + for table in doc.tables: + for row in table.rows: + for cell in row.cells: + text_content += cell.text + " " + text_content += "\n" + return text_content, None + + # 如果需要支持其他文件类型，可以在这里添加处理逻辑 + elif file_type == "txt": + text_content = file_content.read().decode("utf-8") + return text_content, None + return None, "不支持的文件类型" + except Exception as e: + return None, f"文件解析错误: {str(e)}" + +if __name__ == "__main__": + # get_ocr_engine() + app.run(debug=True, port=3401) diff --git a/cp_ocr.py b/cp_ocr.py new file mode 100644 index 0000000..08cfde4 --- /dev/null +++ b/cp_ocr.py @@ -0,0 +1,32 @@ +from flask import Flask, request, jsonify +from paddleocr import PaddleOCR +import fitz +from concurrent.futures import ThreadPoolExecutor +import numpy as np +from PIL import Image +import io +import paddle + +app = Flask(__name__) +paddle.set_device("gpu") +ocr = PaddleOCR(use_textline_orientation=True, lang="ch") # PaddleOCR初始化 +executor = ThreadPoolExecutor(max_workers=4) # 并行页 + +@app.route("/ocr_full", methods=["POST"]) +def ocr_full(): + pdf_bytes = request.files["pdf"].read() + doc = fitz.open(stream=pdf_bytes, filetype="pdf") + results = list(executor.map(_ocr_page, doc)) + doc.close() + print(results) + return jsonify({"full_text": "\n\n".join(results)}) + +def _ocr_page(page: fitz.Page): + pix = page.get_pixmap(matrix=fitz.Matrix(300/72, 300/72)) + img = Image.open(io.BytesIO(pix.tobytes("png"))) + result = ocr.predict(np.array(img)) + texts = [line[1][0] for line in result[0]] + return f"--- 第 {page.number+1} 页 ---\n" + " ".join(texts) + +if __name__ == '__main__': + app.run(host='127.0.0.1', port=3402, threaded=False) \ No newline at end of file diff --git a/promot/tec.md b/promot/tec.md new file mode 100644 index 0000000..da74497 --- /dev/null +++ b/promot/tec.md @@ -0,0 +1,9 @@ +# 角色 +你是一位低碳技术专家，具备深厚的专业知识和丰富的实践经验。你能够精准理解用户的报告。 +# 技能 +1. 仔细分析用户提供的技术报告，获取里面的技术关键点。 +2. 根据技术关键点，判断报告中的技术是否属于低碳技术。 +3 回答 是否采用所列绿色能源、原燃料替代、能效提升、低碳水泥、碳捕集等任一技术（关键技术词汇包括石灰石原料替代减碳技术、熟料烧成化石能源替代减碳技术、水泥工厂近零购电改造技术、水泥低碳烧成技术与装备、节能低碳粉磨工艺及装备、水泥窑炉系统隔热保温整体提升技术、矿渣粉磨制备水泥技术、水泥窑富氧燃烧技术、水泥工厂数字化、智能化技术、高贝利特低热/中热硅酸盐水泥及其制备技术、硫铝酸盐和铁铝酸盐水泥及其制备技术、贝利特-硫铝酸钙-硫硅酸钙新型低碳熟料及其制备技术、大掺量固废制备少熟料低碳水泥技术、镁质低碳水泥及其制备技术、热活化高岭土制备低碳水泥技术、全氧燃烧耦合低能耗碳捕集技术、水泥窑炉烟气捕集CO2技术、水泥窑全氧燃烧耦合CO2纯化捕集技术、水泥工业固体胺碳捕集技术、建材矿山均化开采配矿技术、建材矿山生态修复、绿色改造技术、绿色清洁运输技术、水泥超低排放改造、建设碳排放和污染物排放全过程智能管控与评估平台） +# 回答要求 +仅回答 是 或者 否 不要回复其他内容 +# 以下是用户报告内容 \ No newline at end of file diff --git a/standard.json b/standard.json new file mode 100644 index 0000000..05bc744 --- /dev/null +++ b/standard.json @@ -0,0 +1,1188 @@ +[ + { + "firstLevel": "一、碳排放（20分）", + "secondLevel": "碳排放总量", + "thirdLevel": null, + "scoringCriteria": [ + { + "选项": "下降0至5%", + "得分": 1.5 + }, + { + "选项": "下降5%（含）至10%", + "得分": 2.5 + }, + { + "选项": "下降10%及以上", + "得分": 5 + } + ], + "fullScore": 5, + "result": "", + "id": 1 + }, + { + "firstLevel": "一、碳排放（20分）", + "secondLevel": "碳排放强度", + "thirdLevel": null, + "scoringCriteria": [ + { + "选项": "下降0至5%", + "得分": 1.5 + }, + { + "选项": "下降5%（含）至10%", + "得分": 2.5 + }, + { + "选项": "下降10%及以上", + "得分": 5 + } + ], + "fullScore": 5, + "result": "", + "id": 2 + }, + { + "firstLevel": "一、碳排放（20分）", + "secondLevel": "产品碳足迹", + "thirdLevel": null, + "scoringCriteria": [ + { + "选项": "下降0至5%", + "得分": 1.5 + }, + { + "选项": "下降5%（含）至10%", + "得分": 2.5 + }, + { + "选项": "下降10%及以上", + "得分": 5 + } + ], + "fullScore": 5, + "result": "", + "id": 3 + }, + { + "firstLevel": "一、碳排放（20分）", + "secondLevel": "碳减排目标", + "thirdLevel": null, + "scoringCriteria": [ + { + "选项": "有", + "得分": 5 + }, + { + "选项": "无", + "得分": 0 + } + ], + "fullScore": 5, + "result": "", + "id": 4 + }, + { + "firstLevel": "二、技术路径（35 分）", + "secondLevel": "水泥绿色能源及原燃料替代;能效提升;低碳水泥;碳捕集封存和利用;其他绿色制造技术", + "thirdLevel": "水泥低碳烧成技术与装备、水泥低碳烧成技术与装备、高贝利特低热/中热硅酸盐水泥及其制备技术、全氧燃烧耦合低能耗碳捕集技术、建材矿山均化开采配矿技术等节能减碳技术的应用", + "scoringCriteria": [ + { + "选项": "有", + "得分": 35 + }, + { + "选项": "无", + "得分": 0 + } + ], + "fullScore": 35, + "result": "", + "id": 5 + }, + { + "firstLevel": "三、企业碳治理（10分）", + "secondLevel": "战略与目标", + "thirdLevel": "碳中和路线图", + "scoringCriteria": [ + { + "选项": "有", + "得分": 0.8 + }, + { + "选项": "无", + "得分": 0 + } + ], + "fullScore": 0.8, + "result": "", + "id": 6 + }, + { + "firstLevel": "三、企业碳治理（10分）", + "secondLevel": "战略与目标", + "thirdLevel": "短期/中期/长期减碳目标", + "scoringCriteria": [ + { + "选项": "有", + "得分": 0.8 + }, + { + "选项": "无", + "得分": 0 + } + ], + "fullScore": 0.8, + "result": "", + "id": 7 + }, + { + "firstLevel": "三、企业碳治理（10分）", + 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