From 9fc3021bce0bde37d741c6e16287ef5852461ef2 Mon Sep 17 00:00:00 2001
From: "majiahui@haimaqingfan.com" <majiahui@haimaqingfan.com>
Date: Tue, 31 Oct 2023 14:50:11 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E5=BE=A9=E9=A2=84=E5=A4=84=E7=90=86bu?=
 =?UTF-8?q?g?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 flask_drop_rewrite_request.py | 488 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 488 insertions(+)
 create mode 100644 flask_drop_rewrite_request.py

diff --git a/flask_drop_rewrite_request.py b/flask_drop_rewrite_request.py
new file mode 100644
index 0000000..938e50d
--- /dev/null
+++ b/flask_drop_rewrite_request.py
@@ -0,0 +1,488 @@
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = "2"
+from flask import Flask, jsonify
+from flask import request
+import requests
+import redis
+import uuid
+import json
+from threading import Thread
+import time
+import re
+import logging
+from vllm import LLM, SamplingParams
+
+
+logging.basicConfig(level=logging.DEBUG,  # 控制台打印的日志级别
+                    filename='rewrite.log',
+                    filemode='a',  ##模式，有w和a，w就是写模式，每次都会重新写日志，覆盖之前的日志
+                    # a是追加模式，默认如果不写的话，就是追加模式
+                    format=
+                    '%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s'
+                    # 日志格式
+                    )
+
+pool = redis.ConnectionPool(host='localhost', port=63179, max_connections=100, db=7, password="zhicheng123*")
+redis_ = redis.Redis(connection_pool=pool, decode_responses=True)
+
+db_key_query = 'query'
+db_key_querying = 'querying'
+db_key_queryset = 'queryset'
+batch_size = 32
+
+app = Flask(__name__)
+app.config["JSON_AS_ASCII"] = False
+
+import logging
+
+pattern = r"[。]"
+RE_DIALOG = re.compile(r"\".*?\"|\'.*?\'|“.*?”")
+fuhao_end_sentence = ["。", "，", "？", "！", "…"]
+pantten_biaoti_0 = '^[1-9一二三四五六七八九ⅠⅡⅢⅣⅤⅥⅦⅧⅨ][、.]\s{0,}?[\u4e00-\u9fa5a-zA-Z]+'
+pantten_biaoti_1 = '^第[一二三四五六七八九]章\s{0,}?[\u4e00-\u9fa5a-zA-Z]+'
+pantten_biaoti_2 = '^[0-9.]+\s{0,}?[\u4e00-\u9fa5a-zA-Z]+'
+pantten_biaoti_3 = '^[(（][1-9一二三四五六七八九ⅠⅡⅢⅣⅤⅥⅦⅧⅨ][)_）][、.]{0,}?\s{0,}?[\u4e00-\u9fa5a-zA-Z]+'
+
+
+
+class log:
+    def __init__(self):
+        pass
+
+    def log(*args, **kwargs):
+        format = '%Y/%m/%d-%H:%M:%S'
+        format_h = '%Y-%m-%d'
+        value = time.localtime(int(time.time()))
+        dt = time.strftime(format, value)
+        dt_log_file = time.strftime(format_h, value)
+        log_file = 'log_file/access-%s' % dt_log_file + ".log"
+        if not os.path.exists(log_file):
+            with open(os.path.join(log_file), 'w', encoding='utf-8') as f:
+                print(dt, *args, file=f, **kwargs)
+        else:
+            with open(os.path.join(log_file), 'a+', encoding='utf-8') as f:
+                print(dt, *args, file=f, **kwargs)
+
+
+def dialog_line_parse(url, text):
+    """
+    将数据输入模型进行分析并输出结果
+    :param url: 模型url
+    :param text: 进入模型的数据
+    :return: 模型返回结果
+    """
+
+    response = requests.post(
+        url,
+        json=text,
+        timeout=100000
+    )
+    if response.status_code == 200:
+        return response.json()
+    else:
+        # logger.error(
+        #     "【{}】 Failed to get a proper response from remote "
+        #     "server. Status Code: {}. Response: {}"
+        #     "".format(url, response.status_code, response.text)
+        # )
+        print("【{}】 Failed to get a proper response from remote "
+              "server. Status Code: {}. Response: {}"
+              "".format(url, response.status_code, response.text))
+        print(text)
+        return {}
+
+
+def get_dialogs_index(line: str):
+    """
+    获取对话及其索引
+    :param line 文本
+    :return dialogs 对话内容
+            dialogs_index: 对话位置索引
+            other_index: 其他内容位置索引
+    """
+    dialogs = re.finditer(RE_DIALOG, line)
+    dialogs_text = re.findall(RE_DIALOG, line)
+    dialogs_index = []
+    for dialog in dialogs:
+        all_ = [i for i in range(dialog.start(), dialog.end())]
+        dialogs_index.extend(all_)
+    other_index = [i for i in range(len(line)) if i not in dialogs_index]
+
+    return dialogs_text, dialogs_index, other_index
+
+
+def chulichangju_1(text, snetence_id, chulipangban_return_list, short_num):
+    fuhao = ["，", "？", "！", "…"]
+    dialogs_text, dialogs_index, other_index = get_dialogs_index(text)
+    text_1 = text[:120]
+    text_2 = text[120:]
+    text_1_new = ""
+    if text_2 == "":
+        chulipangban_return_list.append([text_1, snetence_id, short_num])
+        return chulipangban_return_list
+    for i in range(len(text_1) - 1, -1, -1):
+        if text_1[i] in fuhao:
+            if i in dialogs_index:
+                continue
+            text_1_new = text_1[:i]
+            text_1_new += text_1[i]
+            chulipangban_return_list.append([text_1_new, snetence_id, short_num])
+            if text_2 != "":
+                if i + 1 != 120:
+                    text_2 = text_1[i + 1:] + text_2
+            break
+        # else:
+        #     chulipangban_return_list.append(text_1)
+    if text_1_new == "":
+        chulipangban_return_list.append([text_1, snetence_id, short_num])
+    if text_2 != "":
+        short_num += 1
+        chulipangban_return_list = chulichangju_1(text_2, snetence_id, chulipangban_return_list, short_num)
+    return chulipangban_return_list
+
+
+def chulipangban_test_1(snetence_id, text):
+    # 引号处理
+
+    dialogs_text, dialogs_index, other_index = get_dialogs_index(text)
+    for dialogs_text_dan in dialogs_text:
+        text_dan_list = text.split(dialogs_text_dan)
+        text = dialogs_text_dan.join(text_dan_list)
+
+    # text_new_str = "".join(text_new)
+
+    sentence_list = text.split("。")
+    # sentence_list_new = []
+    # for i in sentence_list:
+    #     if i != "":
+    #         sentence_list_new.append(i)
+    # sentence_list = sentence_list_new
+    sentence_batch_list = []
+    sentence_batch_one = []
+    sentence_batch_length = 0
+    return_list = []
+
+    for sentence in sentence_list[:-1]:
+        if len(sentence) < 120:
+            sentence_batch_length += len(sentence)
+            sentence_batch_list.append([sentence + "。", snetence_id, 0])
+            # sentence_pre = autotitle.gen_synonyms_short(sentence)
+            # return_list.append(sentence_pre)
+        else:
+            sentence_split_list = chulichangju_1(sentence, snetence_id, [], 0)
+            for sentence_short in sentence_split_list[:-1]:
+                sentence_batch_list.append(sentence_short)
+            sentence_split_list[-1][0] = sentence_split_list[-1][0] + "。"
+            sentence_batch_list.append(sentence_split_list[-1])
+
+    if sentence_list[-1] != "":
+        if len(sentence_list[-1]) < 120:
+            sentence_batch_length += len(sentence_list[-1])
+            sentence_batch_list.append([sentence_list[-1], snetence_id, 0])
+            # sentence_pre = autotitle.gen_synonyms_short(sentence)
+            # return_list.append(sentence_pre)
+        else:
+            sentence_split_list = chulichangju_1(sentence_list[-1], snetence_id, [], 0)
+            for sentence_short in sentence_split_list:
+                sentence_batch_list.append(sentence_short)
+
+    return sentence_batch_list
+
+
+def paragraph_test(texts: dict):
+    text_new = []
+    for i, text in texts.items():
+        text_list = chulipangban_test_1(i, text)
+        text_new.extend(text_list)
+
+    # text_new_str = "".join(text_new)
+    return text_new
+
+
+def batch_data_process(text_list):
+    sentence_batch_length = 0
+    sentence_batch_one = []
+    sentence_batch_list = []
+
+    for sentence in text_list:
+        sentence_batch_length += len(sentence[0])
+        sentence_batch_one.append(sentence)
+        if sentence_batch_length > 500:
+            sentence_batch_length = 0
+            sentence_ = sentence_batch_one.pop(-1)
+            sentence_batch_list.append(sentence_batch_one)
+            sentence_batch_one = []
+            sentence_batch_one.append(sentence_)
+    sentence_batch_list.append(sentence_batch_one)
+    return sentence_batch_list
+
+
+def batch_predict(batch_data_list):
+    '''
+    一个bacth数据预测
+    @param data_text:
+    @return:
+    '''
+    batch_data_list_new = []
+    batch_data_text_list = []
+    batch_data_snetence_id_list = []
+    for i in batch_data_list:
+        batch_data_text_list.append(i[0])
+        batch_data_snetence_id_list.append(i[1:])
+    # batch_pre_data_list = autotitle.generate_beam_search_batch(batch_data_text_list)
+    batch_pre_data_list = batch_data_text_list
+    for text, sentence_id in zip(batch_pre_data_list, batch_data_snetence_id_list):
+        batch_data_list_new.append([text] + sentence_id)
+
+    return batch_data_list_new
+
+
+def predict_data_post_processing(text_list):
+    text_list_sentence = []
+    # text_list_sentence.append([text_list[0][0], text_list[0][1]])
+
+    for i in range(len(text_list)):
+        if text_list[i][2] != 0:
+            text_list_sentence[-1][0] += text_list[i][0]
+        else:
+            text_list_sentence.append([text_list[i][0], text_list[i][1]])
+
+    return_list = {}
+    sentence_one = []
+    sentence_id = text_list_sentence[0][1]
+    for i in text_list_sentence:
+        if i[1] == sentence_id:
+            sentence_one.append(i[0])
+        else:
+            return_list[sentence_id] = "".join(sentence_one)
+            sentence_id = i[1]
+            sentence_one = []
+            sentence_one.append(i[0])
+    if sentence_one != []:
+        return_list[sentence_id] = "".join(sentence_one)
+    return return_list
+
+
+# def main(text:list):
+#     # text_list = paragraph_test(text)
+#     # batch_data = batch_data_process(text_list)
+#     # text_list = []
+#     # for i in batch_data:
+#     #     text_list.extend(i)
+#     # return_list = predict_data_post_processing(text_list)
+#     # return return_list
+def post_sentence_ulit(sentence, text_info):
+    '''
+    后处理
+    :param sentence:
+    :return:
+    '''
+    # if len(text_list[i][0]) > 7:
+    #     generated_text_list[i] = post_sentence_ulit(generated_text_list[i])
+    # else:
+    #     generated_text_list[i] = text_list[i][0]
+    if_change = text_info[3]
+
+    if if_change == True:
+        if "改写后：" in sentence:
+            sentence_lable_index = sentence.index("改写后：")
+            sentence = sentence[sentence_lable_index + 4:]
+        if sentence[-1] == "\n":
+            sentence = sentence[:-1]
+    else:
+        sentence = text_info[0]
+    return sentence
+
+
+def pre_sentence_ulit(sentence):
+    '''
+    预处理
+    :param sentence:
+    :return:
+    '''
+    sentence = str(sentence).strip()
+    if_change = True
+    if len(sentence) > 7:
+        text = "You are a helpful assistant.\n\nUser:改写下面这句话，要求意思接近但是改动幅度比较大，字数只能多不能少:\n{}\nAssistant:".format(sentence)
+    else:
+        text = "You are a helpful assistant.\n\nUser:下面词不做任何变化:\n{}\nAssistant:".format(sentence)
+        if_change = False
+        return text, if_change
+
+    result_biaoti_list_0 = re.findall(pantten_biaoti_0, sentence)
+    result_biaoti_list_1 = re.findall(pantten_biaoti_1, sentence)
+    result_biaoti_list_2 = re.findall(pantten_biaoti_2, sentence)
+    result_biaoti_list_3 = re.findall(pantten_biaoti_3, sentence)
+
+    if list(set(result_biaoti_list_0 + result_biaoti_list_1 + result_biaoti_list_2 + result_biaoti_list_3)) != []:
+        if_change = False
+        return text, if_change
+
+    return text, if_change
+
+
+def main(texts: dict):
+    text_list = paragraph_test(texts)
+
+    text_info = []
+    text_sentence = []
+    text_list_new = []
+
+    # for i in text_list:
+    #     pre = one_predict(i)
+    #     text_list_new.append(pre)
+
+    # vllm预测
+    for i in text_list:
+        text, if_change = pre_sentence_ulit(i[0])
+        text_sentence.append(text)
+        text_info.append([i[0], i[1], i[2], if_change])
+
+
+    # outputs = llm.generate(text_sentence, sampling_params)  # 调用模型
+    #
+    # generated_text_list = [""] * len(text_sentence)
+    #
+    # # generated_text_list = ["" if len(i[0]) > 5 else i[0] for i in text_list]
+    #
+    # for i, output in enumerate(outputs):
+    #     index = output.request_id
+    #     generated_text = output.outputs[0].text
+    #     generated_text_list[int(index)] = generated_text
+    generated_text_list = dialog_line_parse(
+        "http://192.168.31.145:14010/predict",
+        {
+            "texts":text_sentence
+         }
+    )["resilt"]
+
+    for i in range(len(generated_text_list)):
+        # if len(text_list[i][0]) > 7:
+        #     generated_text_list[i] = post_sentence_ulit(generated_text_list[i])
+        # else:
+        #     generated_text_list[i] = text_list[i][0]
+        generated_text_list[i] = post_sentence_ulit(generated_text_list[i], text_info[i])
+
+    for i, j in zip(generated_text_list, text_info):
+        text_list_new.append([i] + j[1:3])
+
+    return_list = predict_data_post_processing(text_list_new)
+    return return_list
+
+
+# @app.route('/droprepeat/', methods=['POST'])
+# def sentence():
+#     print(request.remote_addr)
+#     texts = request.json["texts"]
+#     text_type = request.json["text_type"]
+#     print("原始语句" + str(texts))
+#     # question = question.strip('。、！？?')
+#
+#     if isinstance(texts, dict):
+#         texts_list = []
+#         y_pred_label_list = []
+#         position_list = []
+#
+#         # texts = texts.replace('\'', '\"')
+#         if texts is None:
+#             return_text = {"texts": "输入了空值", "probabilities": None, "status_code": False}
+#             return jsonify(return_text)
+#         else:
+#             assert text_type in ['focus', 'chapter']
+#             if text_type == 'focus':
+#                 texts_list = main(texts)
+#             if text_type == 'chapter':
+#                 texts_list = main(texts)
+#             return_text = {"texts": texts_list, "probabilities": None, "status_code": True}
+#     else:
+#         return_text = {"texts": "输入格式应该为list", "probabilities": None, "status_code": False}
+#     return jsonify(return_text)
+
+
+def classify():  # 调用模型，设置最大batch_size
+    while True:
+        if redis_.llen(db_key_query) == 0:  # 若队列中没有元素就继续获取
+            time.sleep(3)
+            continue
+        query = redis_.lpop(db_key_query).decode('UTF-8')  # 获取query的text
+        data_dict_path = json.loads(query)
+        path = data_dict_path['path']
+        # text_type = data_dict["text_type"]
+
+        with open(path, encoding='utf8') as f1:
+            # 加载文件的对象
+            data_dict = json.load(f1)
+
+        query_id = data_dict['id']
+        texts = data_dict["text"]
+        text_type = data_dict["text_type"]
+
+        assert text_type in ['focus', 'chapter']
+        if text_type == 'focus':
+            texts_list = main(texts)
+        elif text_type == 'chapter':
+            texts_list = main(texts)
+        else:
+            texts_list = []
+
+        return_text = {"texts": texts_list, "probabilities": None, "status_code": 200}
+        load_result_path = "./new_data_logs/{}.json".format(query_id)
+
+        print("query_id: ", query_id)
+        print("load_result_path: ", load_result_path)
+
+        with open(load_result_path, 'w', encoding='utf8') as f2:
+            # ensure_ascii=False才能输入中文，否则是Unicode字符
+            # indent=2 JSON数据的缩进，美观
+            json.dump(return_text, f2, ensure_ascii=False, indent=4)
+        debug_id_1 = 1
+        redis_.set(query_id, load_result_path, 86400)
+        debug_id_2 = 2
+        redis_.srem(db_key_querying, query_id)
+        debug_id_3 = 3
+        log.log('start at',
+                'query_id:{},load_result_path:{},return_text:{}, debug_id_1:{}, debug_id_2:{}, debug_id_3:{}'.format(
+                    query_id, load_result_path, return_text, debug_id_1, debug_id_2, debug_id_3))
+
+
+@app.route("/predict", methods=["POST"])
+def handle_query():
+    print(request.remote_addr)
+    texts = request.json["texts"]
+    text_type = request.json["text_type"]
+    if texts is None:
+        return_text = {"texts": "输入了空值", "probabilities": None, "status_code": 402}
+        return jsonify(return_text)
+    if isinstance(texts, dict):
+        id_ = str(uuid.uuid1())  # 为query生成唯一标识
+        print("uuid: ", uuid)
+        d = {'id': id_, 'text': texts, "text_type": text_type}  # 绑定文本和query id
+
+        load_request_path = './request_data_logs/{}.json'.format(id_)
+        with open(load_request_path, 'w', encoding='utf8') as f2:
+            # ensure_ascii=False才能输入中文，否则是Unicode字符
+            # indent=2 JSON数据的缩进，美观
+            json.dump(d, f2, ensure_ascii=False, indent=4)
+        redis_.rpush(db_key_query, json.dumps({"id": id_, "path": load_request_path}))  # 加入redis
+        redis_.sadd(db_key_querying, id_)
+        redis_.sadd(db_key_queryset, id_)
+        return_text = {"texts": {'id': id_, }, "probabilities": None, "status_code": 200}
+        print("ok")
+    else:
+        return_text = {"texts": "输入格式应该为字典", "probabilities": None, "status_code": 401}
+    return jsonify(return_text)  # 返回结果
+
+
+t = Thread(target=classify)
+t.start()
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.DEBUG,  # 控制台打印的日志级别
+                        filename='rewrite.log',
+                        filemode='a',  ##模式，有w和a，w就是写模式，每次都会重新写日志，覆盖之前的日志
+                        # a是追加模式，默认如果不写的话，就是追加模式
+                        format=
+                        '%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s'
+                        # 日志格式
+                        )
+    app.run(host="0.0.0.0", port=14004, threaded=True, debug=False)