main.py

import os
import SSF_converter.SSF_to_Input as input_converter
import SSF_converter.output_to_SSF as ssf_converter
import SSF_converter.output_to_SSF2 as ssf_converter2
import morph_analyser.make_prediction as morph_analyser
import Pos_Tagger.final_predict_model as pos_tagger
import chunking.predict as chunker
import lexical.dictionary as lexical
import morph_generation.predict as morph_generator 
# from morph_generation.main_file import Seq2Seq,DecoderLSTM,EncoderLSTM,Attention

BASE_DIR = os.path.dirname(os.path.abspath(__file__))
BASE_DIR+='/SSF_converter/'
main_file = BASE_DIR+"main_format.txt"
local_add = os.path.dirname(os.path.abspath(__file__))
pos_tagger_input_file = local_add + '/Pos_Tagger/sentinput.txt'
chunker_input_file = local_add + '/chunking/input.txt'


def main_format_writer(data):
	# This file writes in main_format.txt.
	out_main_file = open(main_file, 'w', encoding='utf-8')
	for each in main_format_data:
		out_main_file.write('\t'.join(each)+'\n')
	out_main_file.write('\n')
	out_main_file.flush()
	out_main_file.close()

def block_maker():
	# This function print a line in the output file SSF.txt
	for  i in range(80):
		ssf_converter.out_temp_file.write('-')
	ssf_converter.out_temp_file.write('\n\n')
	ssf_converter.out_temp_file.flush()

while 1:
	block_maker()
	# Input taken from terminal
	print("Please enter your input :",end=' ')
	inp = input().split()
	
	ssf_converter.out_temp_file.write('New Sentence = '+' '.join(inp)+'\n\n')	
	
	# main format data store the output of different modules.
	main_format_data = []
	
	for i  in range(1,len(inp)+1):
		temp = []
		temp.append(str(i))
		temp.append('open_bracket_here')
		main_format_data.append(temp)
		temp = []
		temp.append(str(i)+'.1')
		temp.append(str(i-1))
		temp.append(str(i))
		temp.append(inp[i-1])
		main_format_data.append(temp)
	
	# Morph analyser is run here and output is store in 
	# "output" variable.
	output=	morph_analyser.main(inp)
	
	# output is stored in "main_format_data" from "output"
	# variable 
	j=0
	for i in range(len(output)):
		while main_format_data[j][1]=='open_bracket_here':
			j+=1
		main_format_data[j].append(output[i][0][2])
		main_format_data[j].append(output[i][0][1])
		main_format_data[j].append('')
		main_format_data[j].append(output[i][0][3])
		main_format_data[j].append(output[i][0][4])
		main_format_data[j].append(output[i][0][5])
		main_format_data[j].append(output[i][0][6])
		main_format_data[j].append(output[i][0][7])
		main_format_data[j].append('')
		main_format_data[j].append('')			
		j+=1
	
	# output from morph analyser is stored in file
	# main_format.txt
	main_format_writer(main_format_data)
	
	ssf_converter.out_temp_file.write('\t\t***Output after Morph Analyser***\n\n')
	
	# this function converts the data from main_format.txt
	# to SSF and stored in SSF.txt
	ssf_converter.func()
	
	# Input is written in sentinput.txt file in POS_Tagger
	# directory in the order word , pos , gender , number, 
	# person, case ,tam
	pos_tagger_input = open(pos_tagger_input_file, 'w', encoding='utf-8')
	
	for j in range(len(main_format_data)):
		if main_format_data[j][1]=='open_bracket_here':
			continue
		temp=main_format_data[j][3]
		for k in range(7,12):
			temp+='\t'+main_format_data[j][k]
		temp+='\n'
		pos_tagger_input.write(temp)
	pos_tagger_input.flush()
	pos_tagger_input.close()
	
	# POS tagger module is run here and output is taken in
	# in "output" variable
	ssf_converter.out_temp_file.write('\t\t***Output after POS Tagger***\n\n')	
	output = pos_tagger.pos_main()
	
	# output is stored in "main_format_data" from "output"
	# variable
	i=0
	for j in range(len(main_format_data)):
		if main_format_data[j][1]=='open_bracket_here':
			continue
		main_format_data[j][4]=output[0][i]
		i+=1
	
	# POS tagger output is written in main_format.txt
	main_format_writer(main_format_data)
	
	# output is converted in SSF and stored in SSF.txt
	ssf_converter.func()

	# Input is written in input.txt file in chunking
	# directory in the order word , pos , gender , number, 
	# person, case ,tam
	chunker_input = open(chunker_input_file, 'w', encoding='utf-8')
	
	for j in range(len(main_format_data)):
		if main_format_data[j][1]=='open_bracket_here':
			continue
		temp=main_format_data[j][3]
		temp+='\t'+main_format_data[j][4]
		for k in range(7,12):
			temp+='\t'+main_format_data[j][k]
		temp+='\n'
		chunker_input.write(temp)
	chunker_input.flush()
	chunker_input.close()

	# chunker module is run here and output is taken in
	# in "output" variable
	ssf_converter.out_temp_file.write('\t\t***Output after Chunker***\n\n')	
	output = chunker.main_chunker()
	
	i=0
	for j in range(len(main_format_data)):
		if main_format_data[j][1]=='open_bracket_here':
			continue
		main_format_data[j][12]=output[0][i]
		i+=1

	# Chunker output is written in main_format.txt

	main_format_writer(main_format_data)
	
	# output is converted in SSF with the help of second 
	# type of converter and stored in SSF.txt	
	ssf_converter2.func()

	# ssf_converter.out_temp_file.write('\t\t***Output after Morph Inflection Generator***\n\n')	
	# output = morph_generator.main()

	temp_list = ['यी','एशियी','का','सबसे','बड़ी','मस्जिद','में','से','एक','हैं','।']

	i=0
	for j in range(len(main_format_data)):
		if main_format_data[j][1]=='open_bracket_here':
			continue
		main_format_data[j][5] = lexical.convert(main_format_data[j][5],'noun')
		main_format_data[j][5]=temp_list[i]
		i+=1

	# print(main_format_data)
	ssf_converter.out_temp_file.write('\t\t***Output after Lexical Generator***\n\n') 
	
	main_format_writer(main_format_data)

	ssf_converter2.func()

	output = morph_generator.pred() 
 
	ssf_converter.out_temp_file.write('Final Output = '+' '.join(output)+'\n\n')

	block_maker()