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# coding:utf-8
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import os
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import pandas as pd
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os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
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os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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import torch
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from transformers import (
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AutoModelForSequenceClassification, AutoTokenizer, DataCollatorWithPadding,
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Trainer, TrainingArguments
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)
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from flask import Flask, jsonify
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from flask import request
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import uuid
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app = Flask(__name__)
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app.config["JSON_AS_ASCII"] = False
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from threading import Thread
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import redis
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import uuid
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import time
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import json
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import docx2txt
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pool = redis.ConnectionPool(host='localhost', port=63179, max_connections=100, db=13, password="zhicheng123*")
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redis_ = redis.Redis(connection_pool=pool, decode_responses=True)
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db_key_query = 'query'
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db_key_querying = 'querying'
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db_key_queryset = 'queryset'
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batch_size = 32
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def ulit_request_file(file):
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file_name = file.filename
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file_name_save = "data/request/{}".format(file_name)
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file.save(file_name_save)
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if file_name.split(".")[-1] == "txt":
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try:
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with open(file_name_save, encoding="gbk") as f:
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content = f.read()
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except:
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with open(file_name_save, encoding="utf-8") as f:
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content = f.read()
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# elif file_name.split(".")[-1] == "docx":
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# content = docx2txt.process(file_name_save)
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content_list = [i for i in content.split("\n")]
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print(content_list)
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return content_list
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@app.route("/predict", methods=["POST"])
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def handle_query_predict():
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print(request.remote_addr)
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# request.form.get('prompt')
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dataBases = ""
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minSimilarity = "" # txt
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minWords = ""
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title = request.form.get("title")
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author = request.form.get("author") # txt
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file = request.files.get('file')
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token = ""
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account = ""
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goodsId = ""
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callbackUrl = ""
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content_list = ulit_request_file(file)
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id_ = str(uuid.uuid1()) # 为query生成唯一标识
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id_ = id_.upper()
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print("uuid: ", id_)
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print(id_)
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d = {
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'id': id_,
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'dataBases': dataBases,
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'minSimilarity': minSimilarity,
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'minWords': minWords,
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'title': title,
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'author': author,
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'content_list': content_list,
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'token': token,
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'account': account,
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'goodsId': goodsId,
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'callbackUrl': callbackUrl
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}
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print(d)
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# 绑定文本和query id
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# recall_10(id_, title, abst_zh, content)
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load_request_path = './request_data_logs/{}.json'.format(id_)
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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
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json.dump(d, f2, ensure_ascii=False, indent=4)
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redis_.rpush(db_key_query, json.dumps({"id": id_, "path": load_request_path})) # 加入redis
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return_text = {
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'code': 0,
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'msg': "请求成功",
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'data': {
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'balances': "",
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'orderId': id_,
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'consumeNum': ""
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}
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}
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return jsonify(return_text) # 返回结果
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if __name__ == "__main__":
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app.run(host="0.0.0.0", port=16005, threaded=True, debug=False)
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