# -*- coding: utf-8 -*-
"""
Created on Fri Apr 16 14:54:31 2021

@author: kane
"""
# /home/Anaconda3/bin/es-serving-start -model_dir /home/NLP_bert/chinese_roberta_wwm_ext_L-12_H-768_A-12   -max_seq_len=120  -max_batch_size=30
import argparse
import json

import pandas as pd
from bert_serving.client import BertClient

server_ip = "192.168.20.68"
bc = BertClient(ip=server_ip, output_fmt='list')


def create_document(doc, emb, index_name):
    return {
        '_op_type': 'index',
        '_index': index_name,
        'phenomenon': doc["phenomenon"],
        'phenomenon_vector': emb
    }


def load_dataset(path):
    docs = []
    df = pd.read_csv(path)
    for row in df.iterrows():
        series = row[1]
        doc = {
            'phenomenon': series.phenomenon,
        }
        docs.append(doc)
    return docs


def bulk_predict(docs, batch_size=256):
    """Predict es embeddings."""
    for i in range(0, len(docs), batch_size):
        batch_docs = docs[i: i + batch_size]
        breakdown_show_embeddings = bc.encode([doc['phenomenon'] for doc in batch_docs])
        for emb in breakdown_show_embeddings:
            yield emb


def main(args):
    docs = load_dataset(args.data)
    with open(args.save, 'w') as f:
        for doc, emb in zip(docs, bulk_predict(docs)):
            d = create_document(doc, emb, args.index_name)
            f.write(json.dumps(d) + '\n')


# bert转换的结果写到文件中
if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='Creating elasticsearch documents.')
    parser.add_argument('--data', default='phenomenon.csv', help='data for creating documents.')
    parser.add_argument('--save', default='documents.jsonl', help='created documents.')
    parser.add_argument('--index_name', default='fault_meter', help='Elasticsearch index name.')
    args = parser.parse_args()
    main(args)