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101 lines
4.4 KiB
101 lines
4.4 KiB
# coding:utf8
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import os, sys
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import io
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sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf8')
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cur_dir = os.path.dirname(os.path.abspath(__file__)) or os.getcwd()
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par_dir = os.path.abspath(os.path.join(cur_dir, os.path.pardir))
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sys.path.append(cur_dir)
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sys.path.append(par_dir)
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import json
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from django.http import HttpResponse
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from text_analysis.tools import to_kafka
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from django.views.decorators.csrf import csrf_exempt
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from log_util.set_logger import set_logger
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logging = set_logger('logs/results.log')
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import traceback
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import queue
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import requests
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from text_analysis.tools.tool import get_content,parse_gptResult
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import uuid
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import time
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global task_queue
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task_queue = queue.Queue()
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@csrf_exempt
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def chatGptNew(request):
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if request.method == 'POST':
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try:
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# txt=request.body.encode("utf-8")
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raw_data = json.loads(request.body)
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task_queue.put(raw_data)
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return HttpResponse(json.dumps({"code": 1, "msg": "请求正常！"}, ensure_ascii=False))
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except:
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logging.error(traceback.format_exc())
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return HttpResponse(json.dumps({"code": 0, "msg": "请求json格式不正确！"}, ensure_ascii=False))
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else:
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return HttpResponse(json.dumps({"code": 0, "msg": "请求方式错误，改为post请求"}, ensure_ascii=False))
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def chatgpt():
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while True:
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if task_queue.qsize() > 0:
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# try:
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logging.info("取任务队列长度{}".format(task_queue.qsize()))
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raw_data = task_queue.get()
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try:
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output = raw_data["output"]
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res_tmp = {key: "" for key in output}
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if "id" in res_tmp.keys():
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res_tmp["id"] = str(uuid.uuid4())
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data = get_content(raw_data, logging)
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url = "https://api.openai.com/v1/chat/completions"
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headers = {
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"Content-Type": "application/json;charset=UTF-8",
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"Authorization": "Bearer " + data["authorization"]
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}
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payload = json.dumps({
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"model": data["model"],
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"messages": [{"role": "user", "content": data["prompt"]}],
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"temperature": float(data["temperature"]),
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"top_p": float(data["top_p"]),
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"n": int(data["n"])
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})
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logging.info("prompt为{}".format(data["prompt"]))
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response = requests.request("POST", url, headers=headers, data=payload,timeout=180)
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logging.info("GPT返回值：{}-{}".format(response,response.text))
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d = json.loads(response.text)
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result = d['choices'][0]['message']['content']
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#添加 0是文本，1是json格式
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fieldType = raw_data["input"]['fieldType']
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if fieldType == 0:
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res_tmp["content"] = result
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res_tmp_json = json.dumps(res_tmp, ensure_ascii=False)
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raw_data["result"] = {"successCode": "1", "errorLog": "", "results": res_tmp_json,"status":1,"message":"成功"}
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else:
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res=parse_gptResult(res_tmp,result)
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if res:
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res_tmp_json = json.dumps(res, ensure_ascii=False)
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raw_data["result"] = {"successCode": "1", "errorLog": "", "results": res_tmp_json,"status":1,"message":"成功"}
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else:
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res_tmp_json = json.dumps(res_tmp, ensure_ascii=False)
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raw_data["result"] = {"successCode": "0", "errorLog": "GPT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"}
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# logging.info(raw_data)
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to_kafka.send_kafka(raw_data, logging)
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except:
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raw_data["result"] = {"successCode": "0", "errorLog": "", "results": "","status":2,"message":"异常"}
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raw_data["result"]["errorLog"] = traceback.format_exc()
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res_tmp_json = json.dumps(res_tmp, ensure_ascii=False)
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raw_data["result"]["results"] = res_tmp_json
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logging.info("调用gpt失败{}-{}".format(raw_data, traceback.format_exc()))
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to_kafka.send_kafka(raw_data, logging)
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else:
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logging.info("暂无任务，进入休眠--")
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time.sleep(10)
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