import gradio as gr
import json
from flask import jsonify
from sentence_transformers import SentenceTransformer, InputExample, util
from codeScripts.utils import save_json, load_json, create_file_path, remove
from plentas import Plentas
import pandas as pd
import zipfile
import os
import shutil
from datetime import datetime
import tablib
from pathlib import Path

def Main(uploadedFile, txtFileInput, orthographyPercentage, syntaxPercentage, semanticPercentage, studentsRange):
  
    error = ""
    excelPath = None
    
    copySpanishDictionaries()

    try:        
        if not txtFileInput:
           error="Por favor seleccione un archivo con las preguntas y respuestas"
           return [error, excelPath]
        else:
            txtFileInput = txtFileInput.name

        configuration = readQATextFile(txtFileInput)

        configuration["ortographyPercentage"] = float(orthographyPercentage)
        configuration["syntaxPercentage"] = float(syntaxPercentage)
        configuration["semanticPercentage"] = float(semanticPercentage)

        if studentsRange == "":
            studentsRange = "All"

        configuration["students"] = studentsRange

        if not uploadedFile:
            error="Por favor seleccione el .zip con las respuestas de los alumnos"
            return [error, excelPath]
        else:
            uploadedFilePath = uploadedFile.name
                     
        config_json = load_json("configV2.json")

        answersDict = None
        try:
            answersDict = answersTodict(uploadedFilePath)
        except Exception as ex:
            error = "Error in answersTodict: " + str(ex)
            return [error, excelPath]
        
        teacherJson = None
        try:
            teacherJson = createTeacherJson(configuration)
        except Exception as ex:
            error = "Error in createTeacherJson: " + str(ex)
            return [error, excelPath]
        
        try: 
            # #configuring plentas methodology
            response = Plentas(config_json[0], [answersDict, teacherJson])            
        except Exception as ex:            
            error = "Error configuring: " + str(ex)
            return [error, excelPath]
        
        try:             
            # # #overwriting the custom settings for the settings from the api      
            response.setApiSettings(configuration)
        except Exception as ex:            
            error = "Error setting: " + str(ex)
            return [error, excelPath]

        try:    
            print("Processing!")
            modelResult = response.processApiData()
        except Exception as ex:            
            error = "Error processing: " + str(ex)
            return [error, excelPath]

        # modelJson = json.dumps(modelResult)
        print(modelResult)
        excelPath = exportResultToExcelFile(modelResult)

    except Exception as ex:
        error = "Error exporting to Excel: " + str(ex)
    
    return [error, excelPath]

def exportResultToExcelFile(modelResult):
    try:
        excelData = []

        studentsArray = modelResult[0]
        index = 0
        for item in studentsArray:
            #print("ITEM - " + str(item))
            studentData = item[index]
            excelData.append(studentData)
            index+= 1
    
        #tableResults = tablib.Dataset(headers=('ID', 'SimilitudSpacy', 'SimilitudBert', 'NotaSemanticaSpacy', 'NotaSemanticaBert', 'NotaSintaxis', 'NotaOrtografia','NotaTotalSpacy','NotaTotalBert','Feedback'))    
        tableResults = tablib.Dataset(headers=('ID', 'SumaTotalSpacy', 'SumaTotaldBert', 'NotaSemanticaSpacy', 'NotaSemanticaBert', 'NotaSintaxis', 'NotaOrtografia','NotaTotalSpacy','NotaTotalBert','Feedback'))    

        tableResults.json=json.dumps(excelData)
        tableExport=tableResults.export('xlsx')
        outputFilePath = './output/' + str(datetime.now().microsecond) + '_plentas_output.xlsx'
        # outputFilePath = './output/plentas_output.xlsx'
        with open(outputFilePath, 'wb') as f:  # open the xlsx file
            f.write(tableExport)  # write the dataset to the xlsx file
        f.close()
        
    except Exception as ex:
        print("Error exportando Excel:"+ str(e))
        
    return outputFilePath

def copySpanishDictionaries():
    try:
        shutil.copy("./assets/hunspell_dictionaries/es_ES/es_ES.aff", "/home/user/.local/lib/python3.9/site-packages/hunspell/dictionaries/es_ES.aff")
        shutil.copy("./assets/hunspell_dictionaries/es_ES/es_ES.dic", "/home/user/.local/lib/python3.9/site-packages/hunspell/dictionaries/es_ES.dic")        
    except Exception as ex:
        print("Error copying dictionaries" + str(ex))

def readQATextFile(qaTextFilePath):
    configuration = {}

    f = open(qaTextFilePath, 'r')
    lines = f.readlines()

    count = 0
    qCount=1
    
    q = ""
    a = ""
    while count < len(lines):
        if q == "" or q == "\n":
            q = lines[count]
            count += 1
            continue

        if a == "" or a == "\n":
            a = lines[count]
            count += 1            
            
        if q != "" and a != "":
            configuration["minip" + str(qCount)] = q
            configuration["minir" + str(qCount)] = a
            qCount += 1
            q = ""
            a = ""
    
    return configuration

def createTeacherJson(configuration):
    """
    This function extracts the information about the subquestions and subanswers and puts them in the correct format.
    Inputs:
        config: The configured info from the api.
    Outputs:
        teachersJson: The generated dictionary with the subquestions.
    """
    teachersJson = {"enunciado": "", "minipreguntas":[], "keywords":""}

    #5 is the maximum number of permitted subquestions in the configuration2 page
    
    for i in range(5):
       
        try:
            teachersJson["minipreguntas"].append({
				"minipregunta": configuration["minip" + str(i+1)],
				"minirespuesta": configuration["minir" + str(i+1)]
			})

        except:
            break

    return teachersJson

def extractZipData(ruta_zip):
    """
    This function extracts the students's answers from the zip file (the one the teacher has in the task section).
    Inputs:
        ruta_zip: The path inherited from answersTodict
    """
    #defining the path where the extracted info is to be stored
    ruta_extraccion = create_file_path("StudentAnswers/", doctype= 1)
    #extracting the info
    archivo_zip = zipfile.ZipFile(ruta_zip, "r")
    try:
        archivo_zip.extractall(pwd=None, path=ruta_extraccion)
        #archivo_zip.extract(pwd=None, path=ruta_extraccion)
    except:
        pass
    archivo_zip.close()

def removeHtmlFromString(string):
    """
    This function removes the html tags from the student's response.
    Inputs:
        -string: The student's response
    Outputs:
        -new_string: The filtered response
    """
    string = string.encode('utf-8', 'replace')
    string = string.decode('utf-8', 'replace')
    new_string = ""
    skipChar = 0
    for char in string:
        if char == "<":
            skipChar = 1
        elif char == ">":
            skipChar = 0
        else:
            if not skipChar:        
                new_string = new_string+char

    new_string = new_string.encode('utf-8', 'replace')
    new_string = new_string.decode('utf-8', 'replace')
    return new_string

def answersTodict(zip_path):
    """
    This function extracts the students's answers and stacks them in one specific format so that it can be processed next.
    Inputs:
        ruta_zip: The path where the zip file is stored
    Outputs:
        studentAnswersDict: The dictionary with all the responses
    """
  
    # path
    remove('api/StudentAnswers/')

    #extracting the data
    extractZipData(zip_path)
    
    
    
    studentAnswersDict = []
    indx2=0

    #stacking the information of each extracted folder
    for work_folder in os.listdir(create_file_path("StudentAnswers/", doctype= 1)):
        #print("work_folder: " + work_folder)

        for student, indx in zip(os.listdir(create_file_path("StudentAnswers/" + work_folder, doctype= 1)), range(len(os.listdir(create_file_path("StudentAnswers/" + work_folder, doctype= 1))))):
            student_name = student.split("(")
            student_name = student_name[0]

            print("student: " + str(student) + " - index: " + str(indx))

            try:
                #opening the file
               
                #fichero1 = create_file_path("StudentAnswers/" + work_folder + "/" + student+ "/" + 'Adjuntos del envio/', doctype= 1)
                fichero1 = create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + student+'_submissionText.html', doctype= 1)
                
                #where the actual response is 
              

                if os.path.exists(fichero1):
                    print("Fichero: "+str(fichero1))    
                    #fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'Adjuntos del envio/Respuesta enviada', doctype= 1), encoding='utf-8')                
                    #fichero = create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'Adjuntos del envio/Respuesta enviada', doctype= 1)
                    #if os.path.exists(fichero):
                    #    fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + 'Adjuntos del envio/Respuesta enviada', doctype= 1), encoding='utf-8')                
                    #else:
                    fichero = open(create_file_path("StudentAnswers/" + work_folder + "/" + student + "/" + student+'_submissionText.html', doctype= 1), encoding='utf-8')                
                    
                    print("fichero abierto")
                    #reading it
                    lineas = fichero.readlines()

                    textoFichero = ""

                    if (len(lineas) > 0):
                        textoFichero = lineas[0]

                    print("texto: " + textoFichero)

                    #removing html                
                    textoFichero = removeHtmlFromString(textoFichero)           
                                
                    #saving it                                
                    studentAnswersDict.append({"respuesta":textoFichero, "hashed_id":student_name, "TableIndex":indx})
                    print("fichero procesado")

                elif os.path.exists(create_file_path("StudentAnswers/" + work_folder, doctype= 1)) :                     
                    #print("Entra por acá2")
                    student_name2 = work_folder.split("_")
                    student_name = student_name2[0]
                    student_id2=student_name2[1]
                    student_assingsubmission = student_name2[2]
                    student_response = student_name2[3]
                    #print("Sigue acá2")
                    #print("StudentResponse"+str(student_response))
                    if student_response=='onlinetext':

                      #  print("Fichero: " + "StudentAnswers/" + work_folder+"/onlinetext.html")
                        fichero = open(create_file_path("StudentAnswers/" + work_folder+"/onlinetext.html", doctype= 1), encoding='utf-8')                
                                                                        
                        lineas = fichero.readlines()

                        #removing html                
                        lineas[0] = removeHtmlFromString(lineas[0]) 
                                                       
                        #saving it         
                        indx2+=1                                               
                        studentAnswersDict.append({"respuesta":lineas[0], "hashed_id":student_name, "TableIndex":indx2})
                        #break
                    #elif student_response!='file' or None:
                       # print("Fichero no encontrado")
                     #   studentAnswersDict.append({"respuesta":'', "hashed_id":student_name, "TableIndex":indx2})

            except:
                #studentAnswersDict.append({"respuesta":"", "hashed_id":student_name, "TableIndex":indx})
                print("Error buscando ficheros:"+fichero)

    #print("DICT" + json.dumps(studentAnswersDict))

    #saving the final dictionary
    save_json(create_file_path('ApiStudentsDict.json', doctype= 1),studentAnswersDict)
    return studentAnswersDict

    
zipFileInput = gr.inputs.File(label="1. Selecciona el .ZIP con las respuestas de los alumnos")
txtFileInput = gr.inputs.File(label="2. Selecciona el .txt con las preguntas y respuestas correctas. Escriba una pregunta en una sola línea y debajo la respuesta en la línea siguiente.")
orthographyPercentage = gr.inputs.Textbox(label="Ortografía",lines=1, placeholder="0",default=0.1, numeric=1)
syntaxPercentage = gr.inputs.Textbox(label="Sintaxis",lines=1, placeholder="0",default=0.1,numeric=1)
semanticPercentage = gr.inputs.Textbox(label="Semántica",lines=1, placeholder="0",default=0.8, numeric=1)
studentsRange = gr.inputs.Textbox(label="Estudiantes a evaluar",lines=1, placeholder="Dejar vacío para evaluar todos")
        #dataFrameOutput = gr.outputs.Dataframe(headers=["Resultados"], max_rows=20, max_cols=None, overflow_row_behaviour="paginate", type="pandas", label="Resultado")

labelOutput = gr.outputs.Label(num_top_classes=None, type="auto", label="Output")
labelError = gr.outputs.Label(num_top_classes=None, type="auto", label="Errores")
downloadExcelButton = gr.outputs.File('Resultados')

iface = gr.Interface(fn=Main
    , inputs=[zipFileInput, txtFileInput, orthographyPercentage, syntaxPercentage, semanticPercentage, studentsRange]
    , outputs=[labelError, downloadExcelButton]
    , title = "PLENTAS"
    
)

#iface.launch(share = False,enable_queue=True, show_error =True, server_port= 7861)
iface.launch(share = False,enable_queue=True, show_error =True)