Ajout de ML pour détecter les G12

main.py

@@ -3,21 +3,81 @@
 __version__ = "under developpement"
 
 import json
-
+import discord
 from discord import Intents
 from discord.ext import commands
-
 from cogs.omega import Omega
 from cogs.moderation import Moderation
 from cogs.fun import Fun, Confession
 from logs.logger import logger
 
 
-# Configuration.
+########################
+from sklearn.feature_extraction.text import CountVectorizer
+from sklearn.naive_bayes import GaussianNB
+from sklearn.svm import SVC
+from sklearn.naive_bayes import MultinomialNB
+from sklearn.tree import DecisionTreeClassifier
+import ast
+
+
+def get_response(message):
+    with open("./save_file.txt", "r", encoding="utf-8") as f:
+        y_train_dict_start = f.read()
+
+        y_train_dict_start = ast.literal_eval(y_train_dict_start)
+
+    corpus_entrainement = y_train_dict_start
+    corpus_test = {"file_test": [message]}
+
+    bigram_vectorizer = CountVectorizer(ngram_range=(1, 2), token_pattern=r'\b\w+\b')
+
+
+    X_train = []
+    y_train = []
+
+    for file, messages_rules in corpus_entrainement.items():
+        for message, rule in messages_rules.items():
+            X_train.append(message)
+            y_train.append(rule)
+
+
+    X_train_transformed = bigram_vectorizer.fit_transform(X_train).toarray()
+    X_test = {filename: bigram_vectorizer.transform(texts).toarray() for filename, texts in corpus_test.items()}
+
+
+    clf = DecisionTreeClassifier()  #Validé
+    #clf = GaussianNB()              #Validé
+    #clf = SVC()                     #Non validé
+    #clf = MultinomialNB()           #Non validé
+
+
+    clf.fit(X_train_transformed, y_train)
+
+
+    predictions = {}
+    for filename, X in X_test.items():
+        predicted = clf.predict(X)
+        predictions[filename] = predicted.tolist()
+
+
+    return [{filename: prediction} for filename, prediction in predictions.items()]
+
+
+#################################
+
+
+
+
+
+
+
+
+
+
 with open("config.json", encoding="utf-8") as file:
     config = json.load(file)
 
-
 class Bot(commands.Bot):
     """Encapsulate a discord bot."""
     extensions = (
@@ -40,21 +100,22 @@ def __init__(self):
 
     async def on_ready(self):
         """Log information about bot launching."""
-        logger.info("Bot %s connected on %s servers",
-                    self.user.name,
-                    len(self.guilds))
-
-    async def on_command(self, msg):
-        """Log each command submitted. Log message provides information
-        about name, author and arguments of the command.
-        """
-        args = msg.args[2:]
-
-        args_info = ', '.join(repr(arg) for arg in args) if args else ""
-
-        log_msg = (f"{msg.command.name} called by {msg.author} with "
-                   f"args {args_info}.")
-        logger.info(log_msg)
+        logger.info("Bot %s connected on %s servers", self.user.name, len(self.guilds))
+
+    async def on_message(self, message):
+        """Handle incoming messages."""
+        if message.author != self.user:
+            logger.info("Received message: %s", message.content)
+            if message.content.startswith('!hello'):
+                await message.channel.send(f'Hello {message.author.name}!')
+
+            response = list(main.get_response(message.content)[0].values())[0][0]
+            logger.info("Response: %s", response)
+
+            if response == "G12":
+                await message.channel.send(f"<@&{discord.utils.get(message.guild.roles, name='Modérateurs').id}>")
+
+        await self.process_commands(message)
 
     def run(self):
         """Start the bot and load one by one available cogs."""
@@ -67,7 +128,6 @@ def run(self):
 
         super().run(self.token)
 
-
 if __name__ == "__main__":
     omega_robot = Bot()
     omega_robot.run()