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Adam 2023-03-03 13:49:19 -05:00
parent 51e20ae01e
commit 0bc9a6ec82
5 changed files with 78 additions and 43 deletions
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3
.gitignore vendored
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@ -1,2 +1,5 @@
.sekrit
__pycache__
bin/
lib/
pyvenv.cfg

59
lulzbot.py
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@ -1,11 +1,21 @@
motd ='''
_ _ ____ ___ _
| | _ _| | ___| __ ) / _ \| |_
| | | | | | | |_ / _ \| | | | __|
| |__| |_| | |___ / /| |_) | |_| | |_
|_____\__,_|_____/___|____/ \___/ \__|
import datetime
import discord
from src.flan import flan_speak
from src.cartman import cartman_speak
from src.twitter import get_tweet
from fortune import fortune
import numpy as np
motd = '''
_ _ ____ ___ _
| | _ _| | ___| __ ) / _ \| |_
| | | | | | | |_ / _ \| | | | __|
| |__| |_| | |___ / /| |_) | |_| | |_
|_____\__,_|_____/___|____/ \___/ \__|
'''
menu ='''```
menu = '''```
Commands:
fortune: tell a fortune
chuck: give a Chuck Norris quote
@ -18,40 +28,41 @@ Commands:
Contribute!
https://github.com/adoyle0/lulzbot```'''
import discord, datetime
import numpy as np
from fortune import fortune
from src.twitter import get_tweet
from src.cartman import cartman_speak
from src.flan import flan_speak
chuck_quotes = open('data/chuck_quotes').read().split('\n%\n')
ligma_list = open('data/ligma_list').read().split('\n')
limericks = open('data/limericks').read().split('\n%\n')
aclist = open('data/aclist').read().split('\n')
def show_menu():
return menu
def musk():
return get_tweet(44196397)
def ligma():
return np.random.choice(ligma_list)
def limerick():
return np.random.choice(limericks)
def prost():
return 'https://tenor.com/view/prost-christoph-waltz-django-bier-zum-wohle-gif-11041516'
def chuck():
return np.random.choice(chuck_quotes)
def ac():
return np.random.choice(aclist)
triggers = {'lulzbot': show_menu, # these need to be functions
triggers = {'lulzbot': show_menu, # these need to be functions
'musk': musk,
'deez': ligma,
'ligma': ligma,
@ -63,18 +74,22 @@ triggers = {'lulzbot': show_menu, # these need to be functions
'fortune': fortune,
'chuck': chuck,
'ac': ac,
}
}
TOKEN = open('.sekrit/discord_token').read()
intents = discord.Intents.default()
# intents.message_content = True
client = discord.Client(activity=discord.Game(name='with myself'), intents=intents)
intents.message_content = True
client = discord.Client(activity=discord.Game(
name='with myself'), intents=intents)
@client.event
async def on_ready():
print(motd+'\n'+datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')+'\nLogged in as {0.user}'.format(client))
print(motd+'\n'+datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S') +
'\nLogged in as {0.user}'.format(client))
return
@client.event
async def on_message(message):
username = str(message.author).split('#')[0]
@ -87,14 +102,14 @@ async def on_message(message):
elif message.channel.name == 'cartman':
await message.channel.send(cartman_speak(user_message))
#await message.channel.send("I'm broken, come back later.")
# await message.channel.send("I'm broken, come back later.")
elif message.channel.name == 'flan':
await message.channel.send(flan_speak(user_message))
# await message.channel.send('GPU is busy, come back later')
await message.channel.send(flan_speak(user_message))
# await message.channel.send('GPU is busy, come back later')
elif message.channel.name == 'shitposting':
if user_message.lower() in triggers:
if user_message.lower() in triggers:
await message.channel.send(triggers[user_message.lower()]())
return

6
requirements.txt Normal file
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@ -0,0 +1,6 @@
discord
numpy
fortune-python
tweepy
transformers
torch

7
run Executable file
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#!/bin/bash
source bin/activate &&
pip install --upgrade pip &&
pip install --upgrade -r requirements.txt &&
clear &&
python lulzbot.py

46
src/cartman.py
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@ -1,36 +1,40 @@
from transformers.models.auto.modeling_auto import AutoModelForCausalLM
from transformers.models.auto.tokenization_auto import AutoTokenizer
import requests
import json
url = 'https://doordesk.net/chat'
def cartman_respond(user_message):
message = {'Message': user_message}
response = requests.post(url,json.dumps(message))
response = requests.post(url, json.dumps(message))
return response.json().get('Cartman')
from transformers.models.auto.modeling_auto import AutoModelForCausalLM
from transformers.models.auto.tokenization_auto import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
model = AutoModelForCausalLM.from_pretrained("../cartman/train/cartman/models/output-medium")
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained(
"../cartman/train/cartman/models/output-medium-3ep")
def cartman_speak(input_text):
input_ids = tokenizer(input_text + tokenizer.eos_token, return_tensors="pt").input_ids
input_ids = tokenizer(input_text + tokenizer.eos_token,
return_tensors="pt").input_ids
outputs = model.generate(
input_ids,
pad_token_id=tokenizer.eos_token_id,
max_new_tokens = 200,
num_beams = 8,
num_beam_groups = 4,
no_repeat_ngram_size=3,
length_penalty = 1.4,
diversity_penalty = 0,
repetition_penalty = 2.1,
early_stopping = True,
input_ids,
pad_token_id=tokenizer.eos_token_id,
max_new_tokens=200,
num_beams=8,
num_beam_groups=4,
no_repeat_ngram_size=3,
length_penalty=1.4,
diversity_penalty=0,
repetition_penalty=2.1,
early_stopping=True,
# do_sample = True,
# top_k = 100,
# top_p = 0.7,
# temperature = 0.8,
)
# do_sample = True,
# top_k = 100,
# top_p = 0.7,
# temperature = 0.8,
)
return tokenizer.decode(outputs[:, input_ids.shape[-1]:][0], skip_special_tokens=True)