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Commit fbfe2190 authored by Tiravy Amaury's avatar Tiravy Amaury
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function_documentation

parent a6440706
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1 merge request!6Test amau
......@@ -9,12 +9,26 @@ from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
def read_text_file(file_path):
"""
Reads the content of a text file specified by `file_path` and splits it into paragraphs based on double line breaks (`'\n\n'`).
Parameters:
- file_path (str): The path to the text file.
Returns:
- list: A list of non-empty paragraphs from the file.
"""
with open(file_path, 'r', encoding='utf-8') as file:
content = file.read().split('\n\n')
content1 = [item for item in content if item != ""]
return content1
def extract_keywords_textblob_french(sentence):
def extract_keywords_french(sentence):
"""
Tokenizes and filters a given sentence to extract keywords in French. Removes stop words and focuses on meaningful terms.
Parameters:
- sentence (str): The input sentence.
Returns:
- str: A string containing the extracted keywords.
"""
stop_words = set(stopwords.words('french'))
mots_questions = ['qui', 'quoi', '', 'quand', 'pourquoi', 'comment', 'quel', 'quelle', 'quels', 'quelles', 'est-ce que', 'y a-t-il', 'peut-on', 'sont-ils', 'sont-elles', 'combien', 'lequel', 'laquelle', 'lesquels', 'lesquelles', 'est-ce', 'n\'est-ce pas', 'savoir', 'pouvez-vous', 'êtes-vous', 'avez-vous', 'dois-je', 'quelqu\'un', 'quelque chose']
stop_words=stop_words.union(mots_questions)
......@@ -24,6 +38,14 @@ def extract_keywords_textblob_french(sentence):
def create_vectorial_base(text_lines, min_chars=10):
"""
Creates a TF-IDF vectorial base from a list of text lines.
Parameters:
- text_lines (list): List of text lines.
- min_chars (int): Minimum number of characters required for a line to be included (default is 10).
Returns:
- tuple: A tuple containing the TF-IDF vectorizer, the TF-IDF matrix (vectorial base), and the feature names.
"""
filtered_lines = [line for line in text_lines if len(line) >= min_chars]
if not filtered_lines:
......@@ -37,6 +59,16 @@ def create_vectorial_base(text_lines, min_chars=10):
return vectorizer, vectorial_base, feature_names
def get_best_answers(question, text_lines, vectorizer, vectorial_base):
"""
Retrieves the top 3 most similar text lines to a given question based on cosine similarity.
Parameters:
- question (str): The user's question.
- text_lines (list): List of text lines.
- vectorizer: The TF-IDF vectorizer.
- vectorial_base: The TF-IDF matrix (vectorial base).
Returns:
- list: A list of the top 3 most similar text lines as answers.
"""
question_vector = vectorizer.transform([question]).toarray()
# Calculate cosine similarity between the question and each text line
......@@ -50,12 +82,18 @@ def get_best_answers(question, text_lines, vectorizer, vectorial_base):
return best_answers
class WrappingLabel(QLabel):
"""
Subclass of QLabel with word wrapping enabled. Used for displaying text in the GUI.
"""
def __init__(self, text='', parent=None):
super(WrappingLabel, self).__init__(text, parent)
self.setWordWrap(True)
class StyledListWidgetItem(QListWidgetItem):
"""
Subclass of QListWidgetItem with custom styling for the chat history list.
"""
def __init__(self, text='', parent=None):
super(StyledListWidgetItem, self).__init__(parent)
self.setText(text)
......@@ -67,6 +105,9 @@ class StyledListWidgetItem(QListWidgetItem):
self.setData(Qt.UserRole, palette)
class StyledListWidget(QListWidget):
"""
Subclass of QListWidget with custom styling for the chat history list.
"""
def __init__(self, parent=None):
super(StyledListWidget, self).__init__(parent)
self.setAlternatingRowColors(False)
......@@ -79,12 +120,20 @@ class StyledListWidget(QListWidget):
""")
def addStyledItem(self, text):
"""
Adds a styled item to the list widget.
Parameters:
- text (str): The text to be added to the list.
"""
item = StyledListWidgetItem(text)
item.initStyle()
self.addItem(item)
class ChatbotInterface(QWidget):
"""
Main class representing the chatbot interface. Initializes the UI and handles user interactions.
"""
def __init__(self):
super().__init__()
file_path = 'reglementdescolarite-ingegeneraliste2324-1.docx.txt'
......@@ -100,6 +149,9 @@ class ChatbotInterface(QWidget):
self.dico2={}
def init_ui(self):
"""
Initializes the user interface.
"""
# Créer des widgets
self.conversation_text = QTextEdit(self)
self.conversation_text.setFont(QFont("consolas",9))
......@@ -173,7 +225,9 @@ class ChatbotInterface(QWidget):
self.history_list_widget.itemClicked.connect(self.history_item_clicked)
def send_message(self):
"""
Handles the user's input, processes it, and displays the chatbot's response.
"""
user_command = self.user_input_entry.text()
if len(user_command)>0:
self.conversation_text.clear()
......@@ -187,7 +241,7 @@ class ChatbotInterface(QWidget):
self.conversation_text.append(chatbot_response)
# Ajouter la commande à l'historique
user_command1=extract_keywords_textblob_french(user_command)
user_command1=extract_keywords_french(user_command)
self.command_history.append(user_command1)
self.dico2[user_command1]= user_command
self.dico[user_command1]= chatbot_response
......@@ -200,12 +254,20 @@ class ChatbotInterface(QWidget):
pass
def update_history_list(self):
"""
Updates the chat history list in the UI.
"""
self.history_list_widget.clear()
for command in self.command_history:
self.history_list_widget.addStyledItem(command)
def history_item_clicked(self, item):
"""
Displays the chat history when an item is clicked.
Parameters:
- item: The clicked item.
"""
self.conversation_text.clear()
# Réafficher le contenu dans la conversation_text lorsque l'élément de l'historique est cliqué
selected_index = self.history_list_widget.row(item)
......
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