import json
import jsonlines
import argparse
import pandas as pd
import pprint

def main(args):
    mainDict = {}
    with jsonlines.open(args.input_file) as reader:
        for obj in reader:
            #Check if the value already exists
            neutral = ""
            entailment = ""
            contradiction = ""
            prompt = ""

            if mainDict.get(obj['promptID'], None):
                prompt = obj['sentence1']
                entailment = mainDict[obj['promptID']].get('entailment','')
                contradiction = mainDict[obj['promptID']].get('contradiction','')
                neutral = mainDict[obj['promptID']].get('neutral','')

            if obj['gold_label'] == "neutral":
                neutral = obj['sentence2']
            elif obj['gold_label'] == "contradiction":
                contradiction =  obj['sentence2']
            elif obj['gold_label'] == "entailment":
                entailment = obj['sentence2']
            
            mainDict[obj['promptID']] = {'prompt': prompt, 'entailment' : entailment, 'neutral' : neutral, 'contradiction' : contradiction}
    
    myList = []
    for promptID in mainDict:
        myList.append({'sent0':mainDict[promptID]['prompt'], 'sent1':mainDict[promptID]['entailment'], 'hard_neg':mainDict[promptID]['contradiction']})
    
    df = pd.DataFrame.from_records(myList)        
    
    #Drop empty
    df.replace("", float("NaN"), inplace=True)
    df.dropna(subset = ["sent0","sent1","hard_neg"], inplace=True)
    
    #Save csv
    df.to_csv(args.output_file, index=False)

if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--input_file', help="Input file.", required=True)
    parser.add_argument('--output_file', help="Output file.", required=True)
    
    args = parser.parse_args()
    main(args)