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| import joblib | |
| import os | |
| import os.path | |
| from os import path | |
| import discord | |
| import pandas as pd | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
| from transformers import pipeline | |
| from discord.ext import commands | |
| from discord.ext import commands | |
| positive = ['admiration', 'surprise','curiosity','desire','amusement', 'approval', 'caring', 'excitement','gratitude','joy', 'love', 'optimism', 'pride', 'relief'] | |
| negative = ['anger', 'annoyance', 'confusion','disappointment', 'disapproval', 'disgust', 'embarrassment', 'fear', 'grief', 'nervousness', 'realization', 'remorse', 'sadness'] | |
| emotions=["admiration", "amusement", "anger", "annoyance", "approval", "caring", "confusion", "curiosity", "desire", "disappointment", "disapproval", "disgust", "embarrassment", "excitement", "fear", "gratitude", "grief", "joy", "love", "nervousness", "optimism", "pride", "realization", "relief", "remorse", "sadness", "surprise"] | |
| admiration_list=[] | |
| admiration_idx=0 | |
| admiration_val=0 | |
| amusement_list=[] | |
| amusement_idx=0 | |
| amusement_val=0 | |
| anger_list=[] | |
| anger_idx=0 | |
| anger_val=0 | |
| annoyance_list=[] | |
| annoyance_idx=0 | |
| annoyance_val=0 | |
| approval_list=[] | |
| approval_idx=0 | |
| approval_val=0 | |
| caring_list=[] | |
| caring_idx=0 | |
| caring_val=0 | |
| confusion_list=[] | |
| confusion_idx=0 | |
| confusion_val=0 | |
| curiosity_list=[] | |
| curiosity_idx=0 | |
| curiosity_val=0 | |
| desire_list=[] | |
| desire_idx=0 | |
| desire_val=0 | |
| disappointment_list=[] | |
| disappointment_idx=0 | |
| disappointment_val=0 | |
| disapproval_list=[] | |
| disapproval_idx=0 | |
| disapproval_val=0 | |
| disgust_list=[] | |
| disgust_idx=0 | |
| disgust_val=0 | |
| embarrassment_list=[] | |
| embarrassment_idx=0 | |
| embrassment_val=0 | |
| excitement_list=[] | |
| excitement_idx=0 | |
| excitement_val=0 | |
| fear_list=[] | |
| fear_idx=0 | |
| fear_val=0 | |
| gratitude_list=[] | |
| gratitude_idx=0 | |
| gratitude_val=0 | |
| grief_list=[] | |
| grief_idx=0 | |
| grief_val=0 | |
| joy_list=[] | |
| joy_idx=0 | |
| joy_val=0 | |
| love_list=[] | |
| love_idx=0 | |
| love_val=0 | |
| nervousness_list=[] | |
| nervousness_idx=0 | |
| nervousness_val=0 | |
| optimism_list=[] | |
| optimism_idx=0 | |
| optimism_val=0 | |
| pride_list=[] | |
| pride_idx=0 | |
| pride_val=0 | |
| realization_list=[] | |
| realization_idx=0 | |
| realization_val=0 | |
| relief_list=[] | |
| relief_idx=0 | |
| relief_val=0 | |
| remorse_list=[] | |
| remorse_idx=0 | |
| remorse_val=0 | |
| sadness_list=[] | |
| sadness_idx=0 | |
| sadness_val=0 | |
| surprise_list=[] | |
| surprise_idx=0 | |
| surprise_val=0 | |
| neutral_list=[] | |
| neutral_idx=0 | |
| neutral_val=0 | |
| basepath="/content/drive/MyDrive/raahee_activity_recommendations/" | |
| t=0 | |
| for emotion in emotions: | |
| filepath=basepath+emotion | |
| responsepath=filepath+"_responses.xlsx" | |
| if(os.path.exists(responsepath)): | |
| df=pd.read_excel(responsepath) | |
| emotion+="_list" | |
| for i in df['Unnamed: 0']: | |
| globals()[emotion].append(i) | |
| else: | |
| gifpath=filepath+"_gifs.xlsx" | |
| if(os.path.exists(gifpath)): | |
| df=pd.read_excel(gifpath) | |
| emotion+="_list" | |
| for i in df['Unnamed: 0']: | |
| globals()[emotion].append(i) | |
| else: | |
| moviepath=filepath+"_movies.xlsx" | |
| if(os.path.exists(moviepath)): | |
| df=pd.read_excel(moviepath) | |
| emotion+="_list" | |
| val=emotion | |
| val+="_val" | |
| globals()[val]=1 | |
| t=1 | |
| for i in df['Unnamed: 0']: | |
| globals()[emotion].append(i) | |
| else: | |
| bookpath=filepath+"_books.xlsx" | |
| t=2 | |
| val=emotion | |
| val+="_val" | |
| globals()[val]=2 | |
| if(os.path.exists(bookpath)): | |
| df=pd.read_excel(bookpath) | |
| emotion+="_list" | |
| for i in df['Unnamed: 0']: | |
| globals()[emotion].append(i) | |
| client = discord.Client() | |
| bot = commands.Bot(command_prefix='!') | |
| #classifier = pipeline("text-classification",model='bhadresh-savani/bert-base-go-emotion') | |
| def getEmotion(message): | |
| return classifier(message)[0]["label"] | |
| async def on_ready(): | |
| print('We have logged in as {0.user}'.format(client)) | |
| async def on_message(message): | |
| if message.author == client.user: | |
| return | |
| if message.content.startswith('$hello'): | |
| await message.channel.send('Hello!') | |
| elif message.content.startswith('!pm'): | |
| await message.channel.send('') | |
| else: | |
| print(message.author) | |
| t=0 | |
| msg = message.content | |
| print(msg) | |
| response = getEmotion(msg) | |
| print(response) | |
| ans="" | |
| greeting="" | |
| val=response+"_list" | |
| idx=response+"_idx" | |
| temp=response+"_val" | |
| print(idx) | |
| print(temp) | |
| print(globals()[temp]) | |
| if response in positive: | |
| greeting = "Great to hear that <@{0.author.id}> !!!\n".format(message) | |
| elif response in negative: | |
| greeting = "<@{0.author.id}> I can completely understand what you're going through\n".format(message) | |
| if(globals()[temp]==1): | |
| greeting+="This movie made my day, hope it turns out the same for you too !\n" | |
| if(globals()[temp]==2): | |
| greeting+="I really enjoyed reading this book, I guess you must read it too!\n" | |
| t=0 | |
| if(globals()[idx]<len(globals()[val])): | |
| ans=globals()[val][globals()[idx]] | |
| globals()[idx]+=1 | |
| else: | |
| globals()[idx]=0 | |
| if(len(globals()[val])!=0): | |
| ans=globals()[val][0] | |
| globals()[idx]+=1 | |
| await message.channel.send(greeting+ans) | |
| client.run(os.getenv("TOKEN")) | |