from prompt import Prompt
from openai import OpenAI
from fuzzywuzzy import fuzz
from fuzzywuzzy import process

import gradio as gr
import pandas as pd
import os

class Backend:
    def __init__(self):
        self.agent = OpenAI()
        self.prompt = Prompt()

    def read_file(self, file):
        # read the file
        if file is not None:
            with open(file.name, 'r') as f:
                text = f.read()
        else:
            raise gr.Error("You need to upload a file first")
        return text
    
    def highlight_text(self, text, highlight_list):
        # Find the original sentences
        # Split the passage into sentences
        sentences_in_passage = text.split('.')
        sentences_in_passage = [i.split('\n') for i in sentences_in_passage]
        new_sentences_in_passage = []
        for i in sentences_in_passage:
            new_sentences_in_passage =new_sentences_in_passage + i

        # hightlight the reference
        for hl in highlight_list:
            # Find the best match using fuzzy matching
            best_match = process.extractOne(hl, new_sentences_in_passage, scorer=fuzz.partial_ratio)
            text = text.replace(best_match[0], f'<mark style="background: #A5D2F1">{best_match[0]}</mark><mark style="background: #FFC0CB"><font color="red"> (match score:{best_match[1]})</font></mark>')

        # add line break
        text = text.replace('\n', f" <br /> ")

        # add scroll bar
        text = f'<div style="height: 500px; overflow: auto;">{text}</div>'

        return text
    
    def process_file(self, file, questions, openai_key):
        # record the questions
        self.questions = questions

        # get the text
        self.text = self.read_file(file)

        # make the prompt
        prompt = self.prompt.get(self.text, questions, 'v3')

        # interact with openai
        res = self.agent(prompt, with_history = False, temperature = 0.1, model = 'gpt-3.5-turbo-16k', api_key = openai_key)
        res = self.prompt.process_result(res, 'v3')

        # for multiple questions
        self.gpt_result = res
        self.curret_question = 0
        self.totel_question = len(res.keys())

        # make a dataframe to record everything
        self.ori_answer_df = pd.DataFrame(res).T
        self.answer_df = pd.DataFrame(res).T

        # default fist question
        res = res['Question 1']
        question = self.questions[self.curret_question]
        self.answer = res['answer']
        self.highlighted_out = res['original sentences']
        highlighted_out_html = self.highlight_text(self.text, self.highlighted_out)
        self.highlighted_out = '\n'.join(self.highlighted_out)
        
        return question, self.answer, self.highlighted_out, highlighted_out_html, self.answer, self.highlighted_out
    
    def process_results(self, answer_correct, correct_answer, reference_correct, correct_reference):
        if not hasattr(self, 'clicked_correct_answer'):
            raise gr.Error("You need to judge whether the generated answer is correct first")

        if not hasattr(self, 'clicked_correct_reference'):
            raise gr.Error("You need to judge whether the highlighted reference is correct first")

        if not hasattr(self, 'answer_df'):
            raise gr.Error("You need to submit the document first")
        
        if self.curret_question >= self.totel_question or self.curret_question < 0:
            raise gr.Error("No more questions, please return back")
                
        # record the answer
        self.answer_df.loc[f'Question {self.curret_question + 1}', 'answer_correct'] = answer_correct
        self.answer_df.loc[f'Question {self.curret_question + 1}', 'reference_correct'] = reference_correct
        
        if self.clicked_correct_answer == True:
            if hasattr(self, 'answer'):
                self.answer_df.loc[f'Question {self.curret_question + 1}', 'correct_answer'] = self.answer
            else:
                raise gr.Error("You need to submit the document first")
        else:
            self.answer_df.loc[f'Question {self.curret_question + 1}', 'correct_answer'] = correct_answer
        
        if self.clicked_correct_reference == True:
            if hasattr(self, 'highlighted_out'):
                self.answer_df.loc[f'Question {self.curret_question + 1}', 'correct_reference'] = self.highlighted_out
            else:
                raise gr.Error("You need to submit the document first")
        else:
            self.answer_df.loc[f'Question {self.curret_question + 1}', 'correct_reference'] = correct_reference
        
        gr.Info('Results saved!')
        return "Results saved!"
    
    def process_next(self):
        self.curret_question += 1
        if hasattr(self, 'clicked_correct_answer'):
            del self.clicked_correct_answer
        if hasattr(self, 'clicked_correct_reference'):
            del self.clicked_correct_reference

        if self.curret_question >= self.totel_question:
            # self.curret_question -= 1
            return "No more questions!", "No more questions!", "No more questions!", "No more questions!", 'No more questions!', 'No more questions!', 'Still need to click the button above to save the results', None, None
        else:
            res = self.gpt_result[f'Question {self.curret_question + 1}']
            question = self.questions[self.curret_question]
            self.answer = res['answer']
            self.highlighted_out = res['original sentences']
            highlighted_out_html = self.highlight_text(self.text, self.highlighted_out)
            self.highlighted_out = '\n'.join(self.highlighted_out)
            return question, self.answer,self.highlighted_out, highlighted_out_html, 'Please judge on the generated answer', 'Please judge on the generated answer', 'Still need to click the button above to save the results', None, None

    def process_last(self):
        self.curret_question -= 1

        if hasattr(self, 'clicked_correct_answer'):
            del self.clicked_correct_answer
        if hasattr(self, 'clicked_correct_reference'):
            del self.clicked_correct_reference
        
        if self.curret_question < 0:
            # self.curret_question += 1
            return "No more questions!", "No more questions!", "No more questions!", "No more questions!", 'No more questions!', 'No more questions!', 'Still need to click the button above to save the results', None, None
        else:
            res = self.gpt_result[f'Question {self.curret_question + 1}']
            question = self.questions[self.curret_question]
            self.answer = res['answer']
            self.highlighted_out = res['original sentences']
            highlighted_out_html = self.highlight_text(self.text, self.highlighted_out)
            self.highlighted_out = '\n'.join(self.highlighted_out)
            return question, self.answer, self.highlighted_out, highlighted_out_html, 'Please judge on the generated answer', 'Please judge on the generated answer', 'Still need to click the button above to save the results', None, None
        
    def download_answer(self, path = './tmp', name = 'answer.xlsx'):
        os.makedirs(path, exist_ok = True)
        path = os.path.join(path, name)
        self.ori_answer_df.to_excel(path, index = False)

        return path
    
    def download_corrected(self, path = './tmp', name = 'corrected_answer.xlsx'):
        os.makedirs(path, exist_ok = True)
        path = os.path.join(path, name)
        self.answer_df.to_excel(path, index = False)

        return path
    
    def change_correct_answer(self, correctness):
        if correctness == "Correct":
            self.clicked_correct_answer = True
            return "No need to change"
        else:
            if hasattr(self, 'answer'):
                self.clicked_correct_answer = False
                return self.answer
            else:
                return "No answer yet, you need to submit the document first"   
        
    def change_correct_reference(self, correctness):
        if correctness == "Correct":
            self.clicked_correct_reference = True
            return "No need to change"
        else:
            if hasattr(self, 'highlighted_out'):
                self.clicked_correct_reference = False
                return self.highlighted_out
            else:
                return "No answer yet, you need to submit the document first"