# coding:utf8 import os, sys import io sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf8') cur_dir = os.path.dirname(os.path.abspath(__file__)) or os.getcwd() par_dir = os.path.abspath(os.path.join(cur_dir, os.path.pardir)) sys.path.append(cur_dir) sys.path.append(par_dir) import json from django.http import HttpResponse from text_analysis.tools import to_kafka from django.views.decorators.csrf import csrf_exempt from log_util.set_logger import set_logger from openai import OpenAI logging = set_logger('logs/results.log') import traceback import queue import requests from text_analysis.tools.tool import get_content,parse_gptResult import uuid import time from kazoo.client import KazooClient from kazoo.protocol.states import EventType # openai_api_key = "EMPTY" # openai_api_base = "http://10.0.32.225:9000/v1" # client = OpenAI(api_key=openai_api_key,base_url=openai_api_base) task_queue = queue.Queue() stop_dict={} @csrf_exempt def QwenModel(request): if request.method == 'POST': try: # txt=request.body.encode("utf-8") raw_data = json.loads(request.body) task_queue.put(raw_data) return HttpResponse(json.dumps({"code": 1, "msg": "请求正常!"}, ensure_ascii=False)) except: logging.error(traceback.format_exc()) return HttpResponse(json.dumps({"code": 0, "msg": "请求json格式不正确!"}, ensure_ascii=False)) else: return HttpResponse(json.dumps({"code": 0, "msg": "请求方式错误,改为post请求"}, ensure_ascii=False)) def Qwen(): while True: if task_queue.qsize() > 0: try: logging.info("取任务队列长度{}".format(task_queue.qsize())) raw_data = task_queue.get() output = raw_data["output"] res_tmp = {key: "" for key in output} if "id" in res_tmp.keys(): res_tmp["id"] = str(uuid.uuid4()) task_id=raw_data["scenes_id"] task_version=raw_data["version"] logging.info("任务数据为:{}".format(raw_data)) logging.info("当前version信息为:{}".format(stop_dict)) if task_id in stop_dict.keys() and task_version!=stop_dict[task_id]["version"]: logging.info("已暂停任务,过滤掉。{}".format(raw_data)) continue data = get_content(raw_data, logging) # logging.info("请求信息为{},解析后模型请求为{}".format(raw_data,data)) url="http://10.0.32.225:9000/v1/chat/completions" headers = { "Content-Type": "application/json;charset=UTF-8" } payload = json.dumps({ "model":"Qwen2-72B-Instruct-GPTQ-Int4", "messages": [{"role": "user", "content": data["prompt"]}], "temperature": float(data["temperature"]), "top_p": float(data["top_p"]), "n": int(data["n"]) }) # logging.info("prompt为{}".format(data["prompt"])) response = requests.request("POST", url, headers=headers, data=payload,timeout=180) logging.info("Prompt为:{}—Qwen返回值:{}-{}".format(data["prompt"],response,response.text)) d = json.loads(response.text) result = d['choices'][0]['message']['content'] # response = client.chat.completions.create( # model="Qwen2-72B-Instruct-GPTQ-Int4", # messages=[{"role": "user", "content": data["prompt"]}], # temperature=float(data["temperature"]), # top_p=float(data["top_p"]), # n=int(data["n"]) # # stream=True # ) # logging.info("Qwen返回值:{}—请求信息:{}".format(response,data)) # result = response.choices[0].message.content #添加 0是文本,1是json格式 fieldType = raw_data["input"]['fieldType'] if fieldType == 0: res_tmp["content"] = result res_tmp_json = json.dumps(res_tmp, ensure_ascii=False) raw_data["result"] = {"successCode": "1", "errorLog": "", "results": res_tmp_json,"status":1,"message":"成功"} else: res=parse_gptResult(res_tmp,result) if res: res_tmp_json = json.dumps(res, ensure_ascii=False) raw_data["result"] = {"successCode": "1", "errorLog": "", "results": res_tmp_json,"status":1,"message":"成功"} else: res_tmp_json = json.dumps(res_tmp, ensure_ascii=False) raw_data["result"] = {"successCode": "0", "errorLog": "Qwen返回值不是json格式,无法解析!", "results": res_tmp_json,"status":2,"message":"GPT返回结果非json格式"} logging.info(raw_data) to_kafka.send_kafka(raw_data, logging) except: raw_data["result"] = {"successCode": "0", "errorLog": "", "results": "","status":2,"message":"异常"} raw_data["result"]["errorLog"] = traceback.format_exc() res_tmp_json = json.dumps(res_tmp, ensure_ascii=False) raw_data["result"]["results"] = res_tmp_json logging.info("调用Qwen失败{}-{}".format(raw_data, traceback.format_exc())) to_kafka.send_kafka(raw_data, logging) else: logging.info("暂无任务,进入休眠--") time.sleep(10) def zk_monitoring(): try: #线上环境 zk = KazooClient(hosts='172.18.1.146:2181,172.18.1.147:2181,172.18.1.148:2181') #测试环境 # zk = KazooClient(hosts='172.16.12.55:2181,172.16.12.56:2181,172.16.12.57:2181') zk.start() # 设置监听器 @zk.DataWatch("/analyze") def watch_node(data, stat, event): if event is not None and event.type == EventType.CHANGED: data, stat = zk.get("/analyze") logging.info("执行删除操作:{}".format(data)) d = json.loads(data) id = d["scenes_id"] stop_dict[id] = {} stop_dict[id]["version"] = d["version"] stop_dict[id]["operation"] = d["operation"] # 保持程序运行以监听节点变化 try: while True: time.sleep(1) except: logging.info("Stopping...") # 关闭连接 zk.stop() zk.close() except: logging.error(traceback.format_exc())