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added logging and refactored cause some errors appeared #1

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23fe1e6
added logging and refactored cause some errors appeared
wobkobi Jan 23, 2025
e5c937c
feat: Convert message to lowercase for case-insensitive keyword matching
wobkobi Mar 17, 2025
411d951
chore: Update skip check probability for less messages
wobkobi Apr 7, 2025
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56 changes: 55 additions & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
@@ -1,4 +1,58 @@
/venv
# Python bytecode files
__pycache__/
*.py[cod]

# Distribution / packaging
build/
dist/
*.egg-info/

# Virtual environment
venv/
env/
ENV/
venv.bak/
env.bak/

# IDE and Editor files
.vscode/
.idea/

# macOS system files
.DS_Store

# Windows system files
Thumbs.db
ehthumbs.db

# Logs and temp files
*.log
*.pot
*.pyc
*.swp
*.swo
*.bak

# Jupyter Notebook checkpoints
.ipynb_checkpoints/

# pytest
.cache/

# MyPy
.mypy_cache/

# Coverage reports
.coverage
.coverage.*

# Pycharm
.idea/

# Linux-based IDEs (like Sublime Text)
*.sublime-workspace
*.sublime-project

.env
test_zone.py
training.csv
184 changes: 128 additions & 56 deletions bot.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,10 @@
from interactions import Client, Intents, listen, ContextMenuContext, Message, message_context_menu
import logging
from logging.handlers import RotatingFileHandler
from interactions import (
Client,
Intents,
listen,
)
from interactions.api.events import MessageCreate
from dotenv import load_dotenv
import os
Expand All @@ -7,21 +13,62 @@
import asyncio
import bot_retrainer
import bot_recorder
from pathlib import Path
from datetime import datetime


def load_pickle(file_name):
with open(file_name, 'rb') as file:
with open(file_name, "rb") as file:
return pickle.load(file)


# Setup for logging
log_folder = Path("logs")
log_folder.mkdir(exist_ok=True)

# Get today's date for the log file
current_date = datetime.now().strftime("%Y-%m-%d")
log_file = log_folder / "latest.log" # Current log file as 'latest.log'
log_file_template = (
log_folder / f"{current_date}-%d.log"
) # Rotated log files with date-based naming

log_formatter = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")

# Rotating File Handler: Max 5MB per file, keeps the last 5 rotated files per date
log_handler = RotatingFileHandler(
log_file,
maxBytes=5 * 1024 * 1024, # 5MB
backupCount=5, # Keep last 5 rotated files for each day
)
log_handler.setFormatter(log_formatter)
log_handler.setLevel(logging.DEBUG)

# Console Handler for printing logs to the console
console_handler = logging.StreamHandler()
console_handler.setFormatter(log_formatter)

# Logger setup
logger = logging.getLogger("LisaBotLogger")
logger.setLevel(logging.DEBUG)
logger.addHandler(log_handler)
logger.addHandler(console_handler)

logger.info("Centralized logging initialized with date-based filenames.")

# Loading the serialized components
vectorizer = load_pickle('vectorizer.pkl')
classifier = load_pickle('classifier.pkl')
encoded_to_string = load_pickle('encoded_to_string.pkl')
vectorizer = load_pickle("vectorizer.pkl")
classifier = load_pickle("classifier.pkl")
encoded_to_string = load_pickle("encoded_to_string.pkl")
tfidf_transformer = ""


def get_emoji_back(encoded_number):
return encoded_to_string.get(encoded_number, "Unknown")


def predict_emoji(text, classifier, vectorizer, tfidf_transformer, threshold=0.1):
logger.debug(f"Predicting emojis for text: {text}")
# Preprocess and vectorize the input text
text_vectorized = vectorizer.transform([text])

Expand All @@ -36,19 +83,36 @@ def predict_emoji(text, classifier, vectorizer, tfidf_transformer, threshold=0.1

# Decode the emojis
emojis = [get_emoji_back(index) for index in high_prob_indices]


logger.debug(f"Predicted emojis: {emojis}")
return emojis


def answer_question(message):
#first check if message is a question directed at lisabot
if message.strip().endswith('?'):
# first check if message is a question directed at lisabot
if message.strip().endswith("?"):
if len(message) > 1:
likert_scale = {
"strong_agree": ["YES", "YESSSS", "Absolutely!"],
"agree": ["yes", "yessir", "ya", "shut up yes", "https://tenor.com/view/kkekekekekkeke-kk-gif-27232250"],
"neutral": ["I actually dont know", "um duh", "period", "not rn", "lol", "I wish I could tell you but I don't want to", "AYO????", "https://cdn.discordapp.com/attachments/1113266262345273428/1213985020901851146/IMG_7578.png?ex=65f776a7&is=65e501a7&hm=20b5210081b1362c97ca5a5fd5dd02dd33f15b2da783cc44aab2fa1a670d6878&"],
"disagree": ["nope", "ewww no", "naurrr", "joever"],
"strong_disagree": ["WHAT NO", "NO", "Absolutely not!!!"]
"strong_agree": ["YES", "YESSSS", "Absolutely!"],
"agree": [
"yes",
"yessir",
"ya",
"shut up yes",
"https://tenor.com/view/kkekekekekkeke-kk-gif-27232250",
],
"neutral": [
"I actually dont know",
"um duh",
"period",
"not rn",
"lol",
"I wish I could tell you but I don't want to",
"AYO????",
"https://cdn.discordapp.com/attachments/1113266262345273428/1213985020901851146/IMG_7578.png?ex=65f776a7&is=65e501a7&hm=20b5210081b1362c97ca5a5fd5dd02dd33f15b2da783cc44aab2fa1a670d6878&",
],
"disagree": ["nope", "ewww no", "naurrr", "joever"],
"strong_disagree": ["WHAT NO", "NO", "Absolutely not!!!"],
}

random_opinion = random.choice(list(likert_scale.keys()))
Expand All @@ -58,27 +122,30 @@ def answer_question(message):
else:
return "?"


# put canned responses
def response_to(message):
reply = ""

message = message.lower()

keywords = {
"erm actually": lambda: "https://tenor.com/view/nerd-dog-nerd-dog-gif-nerd-dog-alen-orbanic-gif-15562966513664309472",
"lisa burger": lambda: "https://media.discordapp.net/attachments/1113266262345273428/1187365137598922802/imageedit_9_9053779888.png?ex=65969ef4&is=658429f4&hm=8ea4ed39282ce942d2556cced752afcc23353607d02a60e7b5119a4ac9c8e43f&=&format=webp&quality=lossless&width=462&height=462",
"in my opinion": lambda: "https://cdn.discordapp.com/attachments/1168400523104358442/1193073645715734578/y147cc9pwqac1.png?ex=65ab636b&is=6598ee6b&hm=c081a2716fbb8415c6a8be0d8ad8fa24fbfa639a5d97d0d673b15c65e2b984ca&",
"erm actually": lambda: "https://tenor.com/view/nerd-dog-nerd-dog-gif-nerd-dog-alen-orbanic-gif-15562966513664309472",
"lisa burger": lambda: "https://media.discordapp.net/attachments/1113266262345273428/1187365137598922802/imageedit_9_9053779888.png?ex=65969ef4&is=658429f4&hm=8ea4ed39282ce942d2556cced752afcc23353607d02a60e7b5119a4ac9c8e43f&=&format=webp&quality=lossless&width=462&height=462",
"in my opinion": lambda: "https://cdn.discordapp.com/attachments/1168400523104358442/1193073645715734578/y147cc9pwqac1.png?ex=65ab636b&is=6598ee6b&hm=c081a2716fbb8415c6a8be0d8ad8fa24fbfa639a5d97d0d673b15c65e2b984ca&",
"are you the real lisa?": lambda: "I am the real Lisa",
"fortnite blake": lambda: "https://tenor.com/view/fortnite-fish-guy-fortnite-wow-gif-27449064",
"ramesh": lambda: "https://tenor.com/view/sleeping-sleep-dog-dawg-eeper-gif-5083970977419902566",
"fortnite blake": lambda: "https://tenor.com/view/fortnite-fish-guy-fortnite-wow-gif-27449064",
"ramesh": lambda: "https://tenor.com/view/sleeping-sleep-dog-dawg-eeper-gif-5083970977419902566",
"too powerful": lambda: "https://cdn.discordapp.com/emojis/853892024879808513.gif?size=128&quality=lossless",
# add here as required
}

for keyword, action in keywords.items():
if keyword in message:
if keyword.lower() in message:
reply = action()

return reply


load_dotenv()
TOKEN = os.getenv("TOKEN")

Expand All @@ -90,32 +157,39 @@ def response_to(message):
# count of how many replies the bot has before it stops.
count = 10


async def run_every_2_hours():
global count, vectorizer, tfidf_transformer, classifier, encoded_to_string
while True:
count += 3
logger.info("Retraining bot...")
vectorizer, tfidf_transformer, classifier, encoded_to_string = (
bot_retrainer.retrain_bot()
)
logger.info("Bot retrained successfully.")
await asyncio.sleep(3 * 60 * 60)

vectorizer, tfidf_transformer, classifier, encoded_to_string = bot_retrainer.retrain_bot()

await asyncio.sleep(3 * 60 * 60) # 3 hours in seconds

@listen()
async def on_ready():
print(f"This bot is owned by {bot.owner}.")
logger.info("Bot is ready and connected.")
asyncio.create_task(run_every_2_hours())


@listen()
async def on_message_create(event: MessageCreate):
global count
msg = event.message
guild_emojis = await msg.guild.fetch_all_custom_emojis()
logger.debug(f"Message received: {msg.content} by {msg.author}")

if msg.author.bot: # Check if the message is from a bot
logger.debug("Message is from a bot. Ignoring.")
return

#lisa38
# lisa38
if msg.author == "lisa38":
#print("lisa spoke")
# print("lisa spoke")
bot_recorder.record_msg(msg, guild_emojis)

# follow along if everyone is posting the same thing.
Expand All @@ -124,67 +198,65 @@ async def on_message_create(event: MessageCreate):
if isinstance(previous_msg, str):
previous_msg = msg
if msg.content == previous_msg.content and msg.author != previous_msg.author:
logger.info(f"Echoing message: {msg.content}")
await msg.channel.send(msg.content)
previous_msg.content = "lisabot"
return
previous_msg = msg

likert_answer = ""

#checks for trigger word and sends hardcoded reply
# checks for trigger word and sends hardcoded reply
trigger = response_to(msg.content)
if trigger != "":
logger.info(f"Triggered response for keyword. Replying with: {trigger}")
await msg.reply(trigger)
return

# Check if the bot is mentioned
# checks if the bot is mentioned
bot_mentioned = (
f"@{bot.user.id}" in msg.content or
f"<@{bot.user.id}>" in msg.content
f"@{bot.user.id}" in msg.content or f"<@{bot.user.id}>" in msg.content
)
if bot_mentioned:
#gets rid of bot's name before running through the classifier
# gets rid of bot's name before running through the classifier
text = msg.content.replace(f"<@{bot.user.id}>", "").strip()

#wakes the bot up for a bit
count = count+3

#now check if the message is a question for lisa
# wakes the bot for a bit
count += 3
likert_answer = answer_question(text)

else:
else:
text = msg.content

text = str(msg.author)[1:] + " " + text

# Determine whether to skip the count and random chance check
skip_check = bot_mentioned or (count > 0 and random.randint(1, 15) == 1)

skip_check = bot_mentioned or (count > 0 and random.randint(1, 30) == 1)
if not skip_check:
return #print(f"Check not passed. Exiting function. {bot_mentioned}, {count}")

emoji_list = predict_emoji(text, classifier, vectorizer, tfidf_transformer,threshold=0.1)
logger.debug("Check not passed. Exiting function.")
return # print(f"Check not passed. Exiting function. {bot_mentioned}, {count}")

if emoji_list: # This is equivalent to checking if len(emoji_list) > 0
emoji_list = predict_emoji(
text, classifier, vectorizer, tfidf_transformer, threshold=0.1
)
if emoji_list:
emojis_to_send = ""

for emoji_name in emoji_list:
for guild_emoji in guild_emojis:
if guild_emoji.name == emoji_name.replace(":",""):
for guild_emoji in await msg.guild.fetch_all_custom_emojis():
if guild_emoji.name == emoji_name.replace(":", ""):
emojis_to_send += str(guild_emoji)

if emojis_to_send or likert_answer:
response = likert_answer + " " + emojis_to_send
if random.randint(1, 2) == 1:
await msg.reply(likert_answer + " " + emojis_to_send)
logger.info(f"Replying to message: {response}")
await msg.reply(response)
else:
await msg.channel.send(likert_answer + " " + emojis_to_send)
logger.info(f"Sending message: {response}")
await msg.channel.send(response)
else:
r = random.randint(1, 4)
if r == 1:
await msg.channel.send("HUH")
elif r == 2:
await msg.channel.send("??")
fallback_response = random.choice(["HUH", "??"])
logger.info(f"Fallback response: {fallback_response}")
await msg.channel.send(fallback_response)

count -= 1

count = count-1

bot.start(TOKEN)
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