Spaces:
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Update app.py
Browse files
app.py
CHANGED
@@ -1,4 +1,3 @@
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# Imports nécessaires
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import os
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import uuid
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@@ -58,24 +57,20 @@ from dotenv import load_dotenv
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load_dotenv()
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# Chargement des variables d'environnement
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load_dotenv()
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SENDER_EMAIL = os.environ.get('SENDER_EMAIL')
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SENDER_PASSWORD = os.environ.get('SENDER_PASSWORD')
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# Configuration globale
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class Config:
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FASTTEXT_MODEL_PATH = "lid.176.bin"
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# Téléchargement du modèle FastText si nécessaire
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if not os.path.exists(Config.FASTTEXT_MODEL_PATH):
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import urllib.request
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urllib.request.urlretrieve(
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'https://dl.fbaipublicfiles.com/fasttext/supervised-models/lid.176.bin',
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Config.FASTTEXT_MODEL_PATH
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)
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# Classes
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class PDFGenerator:
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@staticmethod
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def create_pdf(content: str, filename: str) -> str:
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fontSize=12,
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leading=14,
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)
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story = []
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title_style = ParagraphStyle(
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'CustomTitle',
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fontSize=16,
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spaceAfter=30,
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)
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story.append(Paragraph("Résumé", title_style))
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story.append(Paragraph(f"Date: {datetime.now().strftime('%d/%m/%Y %H:%M')}", custom_style))
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story.append(Spacer(1, 20))
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for line in content.split('\n'):
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if line.strip():
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if line.startswith('#'):
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story.append(Paragraph(line.strip('# '), styles['Heading2']))
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else:
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story.append(Paragraph(line, custom_style))
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doc.build(story)
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return filename
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class EmailSender:
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def __init__(self, sender_email: str, sender_password: str):
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self.sender_email =
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self.sender_password =
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def send_email(self, recipient_email: str, subject: str, body: str, pdf_path: str) -> bool:
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try:
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msg['To'] = recipient_email
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msg['Subject'] = subject
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msg.attach(MIMEText(body, 'plain'))
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with open(pdf_path, 'rb') as f:
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pdf_attachment = MIMEApplication(f.read(), _subtype='pdf')
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pdf_attachment.add_header('Content-Disposition', 'attachment', filename=os.path.basename(pdf_path))
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msg.attach(pdf_attachment)
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server = smtplib.SMTP('smtp.gmail.com', 587)
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server.starttls()
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server.login(self.sender_email, self.sender_password)
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st.error(f"Erreur d'envoi d'email: {str(e)}")
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return False
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class AudioProcessor:
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def __init__(self, model_name: str, prompt: str = None, chunk_length_ms: int = 300000):
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self.chunk_length_ms = chunk_length_ms
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self.
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self.custom_prompt = prompt
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self.language_detector = fasttext.load_model(Config.FASTTEXT_MODEL_PATH)
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self.text_splitter = RecursiveCharacterTextSplitter(
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def check_language(self, text: str) -> str:
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prediction = self.language_detector.predict(text.replace('\n', ' '))
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return "OUI" if prediction[0][0] == '__label__fr' else "NON"
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def translate_to_french(self, text: str) -> str:
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@limits(calls=5000, period=60)
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def _make_api_call(self, messages):
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return self.llm.generate([messages])
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def chunk_audio(self, file_path: str) -> List[AudioSegment]:
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audio
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def transcribe_chunk(self, audio_chunk: AudioSegment) -> str:
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def generate_summary(self, transcription: str) -> str:
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default_prompt = """
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# Résumé
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[résumé
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# Points Clés
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• [point 1]
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• [point 2]
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# Actions Recommandées
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1. [action 1]
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2. [action 2]
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# Conclusion
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[conclusion
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"""
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class VideoProcessor:
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def __init__(self):
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self.supported_formats = ['.mp4', '.avi', '.mov', '.mkv']
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self.cookie_file_path = "cookies.txt"
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def load_cookies(self):
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dataset = load_dataset("Adjoumani/YoutubeCookiesDataset")
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cookies = dataset["train"]["cookies"][0]
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with open(self.cookie_file_path, "w") as f:
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f.write(cookies)
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def extract_video_id(self, url: str) -> str:
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def get_youtube_transcription(self, video_id: str) -> Optional[str]:
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try:
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return None
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def download_youtube_audio(self, url: str) -> str:
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'preferredcodec': 'mp3',
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'preferredquality': '192',
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}],
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'outtmpl': 'temp_audio.%(ext)s',
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'cookiefile': self.cookie_file_path,
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}
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with yt_dlp.YoutubeDL(ydl_opts) as ydl:
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ydl.download([url])
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return 'temp_audio.mp3'
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class DocumentProcessor:
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def __init__(self, model_name: str, prompt: str = None):
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self.llm = ChatGroq(
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self.custom_prompt = prompt
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self.
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def process_protected_pdf(self, file_path: str, password: str = None) -> str:
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reader = PdfReader(unlocked_pdf_path)
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text = "
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os.remove(unlocked_pdf_path)
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def process_protected_office(self, file, file_type: str, password: str = None) -> str:
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def model_selection_sidebar():
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with st.sidebar:
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st.title("Configuration")
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model = st.selectbox(
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"Sélectionnez un modèle",
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[
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)
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prompt = st.text_area(
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"Instructions personnalisées pour le résumé",
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)
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return model, prompt
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def save_uploaded_file(uploaded_file) -> str:
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with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as tmp_file:
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tmp_file.write(uploaded_file.getvalue())
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return tmp_file.name
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def is_valid_email(email: str) -> bool:
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pattern = r'^[\w\.-]+@[\w\.-]+\.\w+$'
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return bool(re.match(pattern, email))
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def enhance_main():
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if "audio_processor" not in st.session_state:
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model_name, custom_prompt = model_selection_sidebar()
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st.session_state.audio_processor = AudioProcessor(model_name, custom_prompt)
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if "auth_required" not in st.session_state:
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st.session_state.auth_required = False
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source_type = st.radio("Type de source", ["Audio/Vidéo", "Document", "Web"])
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try:
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if source_type == "Audio/Vidéo":
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process_audio_video()
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st.error(f"Une erreur est survenue: {str(e)}")
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st.error("Veuillez réessayer ou contacter le support.")
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def process_audio_video():
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source = st.radio("Choisissez votre source", ["Audio", "Vidéo locale", "YouTube"])
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if source == "Audio":
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handle_audio_input()
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elif source == "Vidéo locale":
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else: # YouTube
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handle_youtube_input()
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def handle_audio_input():
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uploaded_file = st.file_uploader("Fichier audio", type=['mp3', 'wav', 'm4a', 'ogg'])
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audio_bytes = audio_recorder()
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if uploaded_file or audio_bytes:
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process_and_display_results(uploaded_file, audio_bytes)
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def handle_video_input():
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uploaded_video = st.file_uploader("Fichier vidéo", type=['mp4', 'avi', 'mov', 'mkv'])
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if uploaded_video:
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st.video(uploaded_video)
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audio_path = video_processor.extract_audio_from_video(video_path)
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process_and_display_results(audio_path)
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def handle_youtube_input():
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youtube_url = st.text_input("URL YouTube")
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if youtube_url and st.button("Analyser"):
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video_processor = VideoProcessor()
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video_id = video_processor.extract_video_id(youtube_url)
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if video_id:
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st.video(youtube_url)
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with st.spinner("Traitement de la vidéo..."):
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video_processor.load_cookies()
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audio_path = video_processor.download_youtube_audio(youtube_url)
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process_and_display_results(audio_path)
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def process_and_display_results(file_path=None, audio_bytes=None, transcription=None):
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transcriptions = []
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with st.expander("Transcription", expanded=False):
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progress_bar = st.progress(0)
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for i, chunk in enumerate(chunks):
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transcription = st.session_state.audio_processor.transcribe_chunk(chunk)
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if transcription:
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transcriptions.append(transcription)
|
409 |
-
progress_bar.progress((i + 1) / len(chunks))
|
410 |
-
transcription = " ".join(transcriptions) if transcriptions else None
|
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-
|
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-
if transcription:
|
413 |
-
display_transcription_and_summary(transcription)
|
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-
|
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-
|
416 |
-
def save_audio_bytes(audio_bytes: bytes) -> str:
|
417 |
-
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
418 |
-
file_path = f"recording_{timestamp}.wav"
|
419 |
-
with open(file_path, 'wb') as f:
|
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-
f.write(audio_bytes)
|
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-
return file_path
|
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-
|
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|
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-
def
|
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432 |
|
433 |
def get_summary(full_transcription):
|
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if full_transcription is not None:
|
@@ -439,24 +858,237 @@ def get_summary(full_transcription):
|
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439 |
separators=["\n\n", "\n", " ", ""]
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)
|
441 |
chunks = text_splitter.split_text(full_transcription)
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442 |
if len(chunks) > 1:
|
443 |
summary = st.session_state.audio_processor.summarize_long_transcription(full_transcription)
|
444 |
else:
|
445 |
summary = st.session_state.audio_processor.generate_summary(full_transcription)
|
446 |
else:
|
447 |
st.error("La transcription a échoué")
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|
448 |
return None
|
449 |
-
return summary
|
450 |
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|
452 |
def display_summary_and_downloads(summary: str):
|
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|
453 |
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
|
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|
454 |
pdf_filename = f"resume_{timestamp}.pdf"
|
455 |
pdf_path = PDFGenerator.create_pdf(summary, pdf_filename)
|
456 |
-
|
|
|
457 |
docx_filename = f"resume_{timestamp}.docx"
|
458 |
docx_path = generate_docx(summary, docx_filename)
|
459 |
-
|
|
|
460 |
col1, col2 = st.columns(2)
|
461 |
with col1:
|
462 |
with open(pdf_path, "rb") as pdf_file:
|
@@ -466,6 +1098,7 @@ def display_summary_and_downloads(summary: str):
|
|
466 |
file_name=pdf_filename,
|
467 |
mime="application/pdf"
|
468 |
)
|
|
|
469 |
with col2:
|
470 |
with open(docx_path, "rb") as docx_file:
|
471 |
st.download_button(
|
@@ -474,9 +1107,11 @@ def display_summary_and_downloads(summary: str):
|
|
474 |
file_name=docx_filename,
|
475 |
mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
|
476 |
)
|
477 |
-
|
|
|
478 |
st.markdown("### 📧 Recevoir le résumé par email")
|
479 |
recipient_email = st.text_input("Entrez votre adresse email:")
|
|
|
480 |
if st.button("Envoyer par email"):
|
481 |
if not is_valid_email(recipient_email):
|
482 |
st.error("Veuillez entrer une adresse email valide.")
|
@@ -493,30 +1128,14 @@ def display_summary_and_downloads(summary: str):
|
|
493 |
else:
|
494 |
st.error("Échec de l'envoi de l'email.")
|
495 |
|
|
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|
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|
|
|
|
496 |
|
497 |
-
def generate_docx(content: str, filename: str):
|
498 |
-
doc = Document()
|
499 |
-
doc.add_heading('Résumé', 0)
|
500 |
-
doc.add_paragraph(f"Date: {datetime.now().strftime('%d/%m/%Y %H:%M')}")
|
501 |
-
for line in content.split('\n'):
|
502 |
-
if line.strip():
|
503 |
-
if line.startswith('#'):
|
504 |
-
doc.add_heading(line.strip('# '), level=1)
|
505 |
-
else:
|
506 |
-
doc.add_paragraph(line)
|
507 |
-
doc.save(filename)
|
508 |
-
return filename
|
509 |
-
|
510 |
-
def cleanup_temporary_files():
|
511 |
-
temp_files = ['temp_audio.mp3', 'temp_video.mp4']
|
512 |
-
for temp_file in temp_files:
|
513 |
-
if os.path.exists(temp_file):
|
514 |
-
try:
|
515 |
-
os.remove(temp_file)
|
516 |
-
except Exception:
|
517 |
-
pass
|
518 |
-
|
519 |
-
|
520 |
if __name__ == "__main__":
|
521 |
try:
|
522 |
enhance_main()
|
@@ -524,6 +1143,4 @@ if __name__ == "__main__":
|
|
524 |
st.error(f"Une erreur inattendue est survenue: {str(e)}")
|
525 |
st.error("Veuillez réessayer ou contacter le support technique.")
|
526 |
finally:
|
527 |
-
cleanup_temporary_files()
|
528 |
-
|
529 |
-
|
|
|
|
|
1 |
import os
|
2 |
import uuid
|
3 |
|
|
|
57 |
|
58 |
load_dotenv()
|
59 |
|
|
|
|
|
60 |
SENDER_EMAIL = os.environ.get('SENDER_EMAIL')
|
61 |
SENDER_PASSWORD = os.environ.get('SENDER_PASSWORD')
|
62 |
|
|
|
63 |
class Config:
|
64 |
+
"""Centralisation de la configuration"""
|
65 |
+
#GROQ_API_KEY = ""
|
66 |
+
#SENDER_EMAIL = ""
|
67 |
+
#SENDER_PASSWORD = ""
|
68 |
FASTTEXT_MODEL_PATH = "lid.176.bin"
|
69 |
+
import urllib.request
|
70 |
+
urllib.request.urlretrieve('https://dl.fbaipublicfiles.com/fasttext/supervised-models/lid.176.bin', 'lid.176.bin')
|
71 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
72 |
|
73 |
+
# Classes PDFGenerator et EmailSender restent inchangées...
|
74 |
class PDFGenerator:
|
75 |
@staticmethod
|
76 |
def create_pdf(content: str, filename: str) -> str:
|
|
|
84 |
fontSize=12,
|
85 |
leading=14,
|
86 |
)
|
87 |
+
|
88 |
story = []
|
89 |
title_style = ParagraphStyle(
|
90 |
'CustomTitle',
|
|
|
92 |
fontSize=16,
|
93 |
spaceAfter=30,
|
94 |
)
|
95 |
+
story.append(Paragraph("Résumé Audio", title_style))
|
96 |
story.append(Paragraph(f"Date: {datetime.now().strftime('%d/%m/%Y %H:%M')}", custom_style))
|
97 |
story.append(Spacer(1, 20))
|
98 |
+
|
99 |
for line in content.split('\n'):
|
100 |
if line.strip():
|
101 |
if line.startswith('#'):
|
102 |
story.append(Paragraph(line.strip('# '), styles['Heading2']))
|
103 |
else:
|
104 |
story.append(Paragraph(line, custom_style))
|
105 |
+
|
106 |
doc.build(story)
|
107 |
return filename
|
108 |
|
|
|
109 |
class EmailSender:
|
110 |
def __init__(self, sender_email: str, sender_password: str):
|
111 |
+
self.sender_email = SENDER_EMAIL # or Config.SENDER_EMAIL
|
112 |
+
self.sender_password = SENDER_PASSWORD # or Config.SENDER_PASSWORD
|
113 |
|
114 |
def send_email(self, recipient_email: str, subject: str, body: str, pdf_path: str) -> bool:
|
115 |
try:
|
|
|
118 |
msg['To'] = recipient_email
|
119 |
msg['Subject'] = subject
|
120 |
msg.attach(MIMEText(body, 'plain'))
|
121 |
+
|
122 |
with open(pdf_path, 'rb') as f:
|
123 |
pdf_attachment = MIMEApplication(f.read(), _subtype='pdf')
|
124 |
pdf_attachment.add_header('Content-Disposition', 'attachment', filename=os.path.basename(pdf_path))
|
125 |
msg.attach(pdf_attachment)
|
126 |
+
|
127 |
server = smtplib.SMTP('smtp.gmail.com', 587)
|
128 |
server.starttls()
|
129 |
server.login(self.sender_email, self.sender_password)
|
|
|
134 |
st.error(f"Erreur d'envoi d'email: {str(e)}")
|
135 |
return False
|
136 |
|
|
|
137 |
class AudioProcessor:
|
138 |
def __init__(self, model_name: str, prompt: str = None, chunk_length_ms: int = 300000):
|
139 |
self.chunk_length_ms = chunk_length_ms
|
140 |
+
self.groq_client = Groq() #api_key=Config.GROQ_API_KEY
|
141 |
+
self.llm = ChatGroq(
|
142 |
+
model=model_name,
|
143 |
+
temperature=0,
|
144 |
+
#api_key=Config.GROQ_API_KEY
|
145 |
+
)
|
146 |
self.custom_prompt = prompt
|
147 |
self.language_detector = fasttext.load_model(Config.FASTTEXT_MODEL_PATH)
|
148 |
+
self.text_splitter = RecursiveCharacterTextSplitter(
|
149 |
+
chunk_size=4000,
|
150 |
+
chunk_overlap=200
|
151 |
+
)
|
152 |
+
#self.custom_prompt = prompt
|
153 |
+
# Définition des limites de taux : 5000 tokens par minute
|
154 |
+
self.CALLS_PER_MINUTE = 5000
|
155 |
+
self.PERIOD = 60 # 60 secondes = 1 minute
|
156 |
+
# Add language detection model
|
157 |
+
#self.language_detector = fasttext.load_model('lid.176.bin')
|
158 |
|
159 |
def check_language(self, text: str) -> str:
|
160 |
+
"""Vérifie si le texte est en français"""
|
161 |
prediction = self.language_detector.predict(text.replace('\n', ' '))
|
162 |
return "OUI" if prediction[0][0] == '__label__fr' else "NON"
|
163 |
|
164 |
def translate_to_french(self, text: str) -> str:
|
165 |
+
"""Traduit le texte en français si nécessaire"""
|
166 |
+
try:
|
167 |
+
messages = [
|
168 |
+
SystemMessage(content="Vous êtes un traducteur professionnel agréé en Français. Traduisez le texte suivant en français en conservant le format et la structure:"),
|
169 |
+
HumanMessage(content=text)
|
170 |
+
]
|
171 |
+
result = self._make_api_call(messages)
|
172 |
+
return result.generations[0][0].text
|
173 |
+
except Exception as e:
|
174 |
+
if "rate_limit_exceeded" in str(e):
|
175 |
+
time.sleep(60)
|
176 |
+
return self.translate_to_french(text)
|
177 |
+
raise e
|
178 |
|
179 |
+
@sleep_and_retry
|
180 |
@limits(calls=5000, period=60)
|
181 |
def _make_api_call(self, messages):
|
182 |
return self.llm.generate([messages])
|
183 |
|
184 |
def chunk_audio(self, file_path: str) -> List[AudioSegment]:
|
185 |
+
try:
|
186 |
+
audio = AudioSegment.from_file(file_path)
|
187 |
+
if len(audio) < self.chunk_length_ms:
|
188 |
+
return [audio]
|
189 |
+
return [
|
190 |
+
audio[i:i + self.chunk_length_ms]
|
191 |
+
for i in range(0, len(audio), self.chunk_length_ms)
|
192 |
+
]
|
193 |
+
except Exception as e:
|
194 |
+
st.error(f"Error processing audio file: {str(e)}")
|
195 |
+
return []
|
196 |
|
197 |
def transcribe_chunk(self, audio_chunk: AudioSegment) -> str:
|
198 |
+
try:
|
199 |
+
with tempfile.NamedTemporaryFile(suffix='.mp3', delete=False) as temp_file:
|
200 |
+
audio_chunk.export(temp_file.name, format="mp3")
|
201 |
+
with open(temp_file.name, "rb") as audio_file:
|
202 |
+
try:
|
203 |
+
response = self.groq_client.audio.transcriptions.create(
|
204 |
+
file=audio_file,
|
205 |
+
model="whisper-large-v3-turbo",
|
206 |
+
language="fr"
|
207 |
+
)
|
208 |
+
except Exception as e:
|
209 |
+
if "rate_limit_exceeded" in str(e):
|
210 |
+
st.warning("Limite de taux atteinte pendant la transcription. Attente avant nouvelle tentative...")
|
211 |
+
time.sleep(60)
|
212 |
+
return self.transcribe_chunk(audio_chunk)
|
213 |
+
raise e
|
214 |
+
os.unlink(temp_file.name)
|
215 |
+
return response.text
|
216 |
+
except Exception as e:
|
217 |
+
st.error(f"Transcription error: {str(e)}")
|
218 |
+
return ""
|
219 |
+
|
220 |
+
|
221 |
+
# Dans la classe AudioProcessor, ajoutez cette méthode :
|
222 |
+
def split_text(self, text: str, max_tokens: int = 4000) -> List[str]:
|
223 |
+
text_splitter = RecursiveCharacterTextSplitter(
|
224 |
+
chunk_size=max_tokens * 4, # Estimation approximative tokens -> caractères
|
225 |
+
chunk_overlap=200,
|
226 |
+
length_function=len,
|
227 |
+
separators=["\n\n", "\n", " ", ""]
|
228 |
+
)
|
229 |
+
return text_splitter.split_text(text)
|
230 |
|
231 |
def generate_summary(self, transcription: str) -> str:
|
232 |
default_prompt = """
|
233 |
+
Vous êtes un assistant expert spécialisé dans le résumé et l'analyse d'enregistrements audio en langue française.
|
234 |
+
Voici la transcription à analyser:
|
235 |
+
|
236 |
+
{transcript}
|
237 |
+
|
238 |
+
Veuillez fournir:
|
239 |
+
1. Un résumé concis (3-4 phrases)
|
240 |
+
2. Les points clés (maximum 5 points)
|
241 |
+
3. Les actions recommandées (si pertinent)
|
242 |
+
4. Une conclusion brève
|
243 |
+
|
244 |
+
Format souhaité:
|
245 |
# Résumé
|
246 |
+
[votre résumé]
|
247 |
+
|
248 |
# Points Clés
|
249 |
• [point 1]
|
250 |
• [point 2]
|
251 |
+
...
|
252 |
+
|
253 |
# Actions Recommandées
|
254 |
1. [action 1]
|
255 |
2. [action 2]
|
256 |
+
...
|
257 |
+
|
258 |
# Conclusion
|
259 |
+
[votre conclusion]
|
260 |
"""
|
261 |
+
|
262 |
+
prompt_template = self.custom_prompt if self.custom_prompt else default_prompt
|
263 |
+
|
264 |
+
try:
|
265 |
+
chain = LLMChain(
|
266 |
+
llm=self.llm,
|
267 |
+
prompt=PromptTemplate(
|
268 |
+
template=prompt_template,
|
269 |
+
input_variables=["transcript"]
|
270 |
+
)
|
271 |
+
)
|
272 |
+
|
273 |
+
summary = chain.run(transcript=transcription)
|
274 |
+
|
275 |
+
# Vérification de la langue
|
276 |
+
if self.check_language(summary) == "NON":
|
277 |
+
st.warning("Résumé généré dans une autre langue. Traduction en cours...")
|
278 |
+
summary = self.translate_to_french(summary)
|
279 |
+
|
280 |
+
return summary
|
281 |
+
except Exception as e:
|
282 |
+
if "rate_limit_exceeded" in str(e):
|
283 |
+
st.warning("Limite de taux atteinte. Attente avant nouvelle tentative...")
|
284 |
+
time.sleep(60) # Attendre 1 minute
|
285 |
+
return self.generate_summary(transcription)
|
286 |
+
raise e
|
287 |
+
|
288 |
+
# Méthodes existantes inchangées...
|
289 |
+
|
290 |
+
|
291 |
+
|
292 |
+
def summarize_long_transcription(self, transcription: str) -> str:
|
293 |
+
chunks = self.split_text(transcription, max_tokens=4000)
|
294 |
+
partial_summaries = []
|
295 |
+
|
296 |
+
for i, chunk in enumerate(chunks):
|
297 |
+
st.write(f"Traitement du segment {i + 1}/{len(chunks)}...")
|
298 |
+
try:
|
299 |
+
messages = [
|
300 |
+
SystemMessage(content="Vous êtes un assistant expert en résumé de texte en français."),
|
301 |
+
HumanMessage(content=f"Résumez ce texte en français : {chunk}")
|
302 |
+
]
|
303 |
+
result = self._make_api_call(messages)
|
304 |
+
partial_summary = result.generations[0][0].text
|
305 |
+
|
306 |
+
# Vérification de la langue pour chaque segment
|
307 |
+
if self.check_language(partial_summary) == "NON":
|
308 |
+
partial_summary = self.translate_to_french(partial_summary)
|
309 |
+
|
310 |
+
partial_summaries.append(partial_summary)
|
311 |
+
except Exception as e:
|
312 |
+
if "rate_limit_exceeded" in str(e):
|
313 |
+
st.warning(f"Limite de taux atteinte au segment {i+1}. Attente avant nouvelle tentative...")
|
314 |
+
time.sleep(60)
|
315 |
+
i -= 1
|
316 |
+
continue
|
317 |
+
raise e
|
318 |
+
|
319 |
+
try:
|
320 |
+
final_prompt = f"""Combinez ces résumés partiels en un résumé global cohérent en langue française :
|
321 |
+
|
322 |
+
{' '.join(partial_summaries)}
|
323 |
+
"""
|
324 |
+
messages = [
|
325 |
+
SystemMessage(content="Vous êtes un assistant expert en résumé de texte en français."),
|
326 |
+
HumanMessage(content=final_prompt)
|
327 |
+
]
|
328 |
+
final_result = self._make_api_call(messages)
|
329 |
+
final_summary = final_result.generations[0][0].text
|
330 |
+
|
331 |
+
# Vérification finale de la langue
|
332 |
+
if self.check_language(final_summary) == "NON":
|
333 |
+
st.warning("Résumé final dans une autre langue. Traduction en cours...")
|
334 |
+
final_summary = self.translate_to_french(final_summary)
|
335 |
+
|
336 |
+
return final_summary
|
337 |
+
|
338 |
+
except Exception as e:
|
339 |
+
if "rate_limit_exceeded" in str(e):
|
340 |
+
st.warning("Limite de taux atteinte lors de la génération du résumé final. Attente avant nouvelle tentative...")
|
341 |
+
time.sleep(60)
|
342 |
+
return self.summarize_long_transcription(transcription)
|
343 |
+
raise e
|
344 |
+
|
345 |
class VideoProcessor:
|
346 |
def __init__(self):
|
347 |
self.supported_formats = ['.mp4', '.avi', '.mov', '.mkv']
|
348 |
+
self.cookie_file_path = "cookies.txt" # Chemin du fichier cookies
|
349 |
+
self.ydl_opts = {
|
350 |
+
'format': 'bestaudio/best',
|
351 |
+
'postprocessors': [{
|
352 |
+
'key': 'FFmpegExtractAudio',
|
353 |
+
'preferredcodec': 'mp3',
|
354 |
+
'preferredquality': '192',
|
355 |
+
}],
|
356 |
+
'outtmpl': 'temp_audio.%(ext)s'
|
357 |
+
}
|
358 |
+
|
359 |
+
|
360 |
def load_cookies(self):
|
361 |
+
"""Charge les cookies depuis Hugging Face et les enregistre localement."""
|
362 |
dataset = load_dataset("Adjoumani/YoutubeCookiesDataset")
|
363 |
cookies = dataset["train"]["cookies"][0]
|
364 |
with open(self.cookie_file_path, "w") as f:
|
365 |
f.write(cookies)
|
366 |
+
print(f"Cookies enregistrés dans {self.cookie_file_path}")
|
367 |
|
368 |
+
|
369 |
def extract_video_id(self, url: str) -> str:
|
370 |
+
try:
|
371 |
+
parsed_url = urlparse(url)
|
372 |
+
if parsed_url.hostname in ['www.youtube.com', 'youtube.com']:
|
373 |
+
return parse_qs(parsed_url.query)['v'][0]
|
374 |
+
elif parsed_url.hostname == 'youtu.be':
|
375 |
+
return parsed_url.path[1:]
|
376 |
+
return None
|
377 |
+
except Exception:
|
378 |
+
return None
|
379 |
|
380 |
def get_youtube_transcription(self, video_id: str) -> Optional[str]:
|
381 |
try:
|
|
|
385 |
return None
|
386 |
|
387 |
def download_youtube_audio(self, url: str) -> str:
|
388 |
+
try:
|
389 |
+
# Ajoutez le fichier cookies dans les options
|
390 |
+
ydl_opts = self.ydl_opts.copy()
|
391 |
+
ydl_opts['cookiefile'] = self.cookie_file_path
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
392 |
|
393 |
+
# Téléchargement
|
394 |
+
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
|
395 |
+
ydl.download([url])
|
396 |
+
|
397 |
+
# Vérifier si le fichier audio existe
|
398 |
+
audio_path = 'temp_audio.mp3'
|
399 |
+
if not os.path.exists(audio_path):
|
400 |
+
raise FileNotFoundError(f"Le fichier {audio_path} n'a pas été généré.")
|
401 |
|
402 |
+
return audio_path
|
403 |
+
except Exception as e:
|
404 |
+
raise RuntimeError(f"Erreur lors du téléchargement : {str(e)}")
|
405 |
+
|
406 |
+
def extract_audio_from_video(self, video_path: str) -> str:
|
407 |
+
try:
|
408 |
+
audio_path = f"{os.path.splitext(video_path)[0]}.mp3"
|
409 |
+
with VideoFileClip(video_path) as video:
|
410 |
+
video.audio.write_audiofile(audio_path)
|
411 |
+
return audio_path
|
412 |
+
except Exception as e:
|
413 |
+
st.error(f"Erreur lors de l'extraction audio: {str(e)}")
|
414 |
+
raise
|
415 |
|
416 |
class DocumentProcessor:
|
417 |
def __init__(self, model_name: str, prompt: str = None):
|
418 |
+
self.llm = ChatGroq(
|
419 |
+
model=model_name,
|
420 |
+
temperature=0,
|
421 |
+
#api_key=Config.GROQ_API_KEY
|
422 |
+
)
|
423 |
self.custom_prompt = prompt
|
424 |
+
#self.text_splitter = RecursiveCharacterTextSplitter(
|
425 |
+
# chunk_size=4000,
|
426 |
+
# chunk_overlap=200
|
427 |
+
#)
|
428 |
+
self.language_detector = fasttext.load_model('lid.176.bin')
|
429 |
+
|
430 |
+
def split_text(self, text: str, max_tokens: int = 4000) -> List[str]:
|
431 |
+
text_splitter = RecursiveCharacterTextSplitter(
|
432 |
+
chunk_size=max_tokens * 4, # Estimation approximative tokens -> caractères
|
433 |
+
chunk_overlap=200,
|
434 |
+
length_function=len,
|
435 |
+
separators=["\n\n", "\n", " ", ""]
|
436 |
+
)
|
437 |
+
return text_splitter.split_text(text)
|
438 |
+
|
439 |
+
def check_language(self, text: str) -> str:
|
440 |
+
"""Vérifie si le texte est en français"""
|
441 |
+
prediction = self.language_detector.predict(text.replace('\n', ' '))
|
442 |
+
return "OUI" if prediction[0][0] == '__label__fr' else "NON"
|
443 |
+
|
444 |
+
def translate_to_french(self, text: str) -> str:
|
445 |
+
"""Traduit le texte en français si nécessaire"""
|
446 |
+
try:
|
447 |
+
messages = [
|
448 |
+
SystemMessage(content="Vous êtes un traducteur professionnel agrée en Français. Traduisez le texte suivant en français en conservant le format et la structure:"),
|
449 |
+
HumanMessage(content=text)
|
450 |
+
]
|
451 |
+
result = self._make_api_call(messages)
|
452 |
+
return result.generations[0][0].text
|
453 |
+
except Exception as e:
|
454 |
+
if "rate_limit_exceeded" in str(e):
|
455 |
+
time.sleep(60)
|
456 |
+
return self.translate_to_french(text)
|
457 |
+
raise e
|
458 |
+
|
459 |
+
# Méthodes existantes de DocumentProcessor inchangées...
|
460 |
+
@sleep_and_retry
|
461 |
+
@limits(calls=5000, period=60)
|
462 |
+
def _make_api_call(self, messages):
|
463 |
+
return self.llm.generate([messages])
|
464 |
+
|
465 |
+
|
466 |
|
467 |
def process_protected_pdf(self, file_path: str, password: str = None) -> str:
|
468 |
+
"""
|
469 |
+
Traite un PDF, avec ou sans mot de passe, et extrait le texte.
|
470 |
+
|
471 |
+
:param file_path: Chemin vers le fichier PDF.
|
472 |
+
:param password: Mot de passe du fichier PDF (si nécessaire).
|
473 |
+
:return: Texte extrait du PDF.
|
474 |
+
"""
|
475 |
+
try:
|
476 |
+
# Si un mot de passe est fourni, tenter de déverrouiller le PDF
|
477 |
+
if password:
|
478 |
+
with pikepdf.open(file_path, password=password) as pdf:
|
479 |
+
unlocked_pdf_path = "unlocked_temp.pdf"
|
480 |
+
pdf.save(unlocked_pdf_path)
|
481 |
+
|
482 |
+
# Utiliser le fichier temporaire déverrouillé
|
483 |
reader = PdfReader(unlocked_pdf_path)
|
484 |
+
text = ""
|
485 |
+
for page in reader.pages:
|
486 |
+
text += page.extract_text()
|
487 |
+
|
488 |
+
# Supprimer le fichier temporaire
|
489 |
os.remove(unlocked_pdf_path)
|
490 |
+
|
491 |
+
else:
|
492 |
+
# Si aucun mot de passe, traiter directement le PDF
|
493 |
+
reader = PdfReader(file_path)
|
494 |
+
text = ""
|
495 |
+
for page in reader.pages:
|
496 |
+
text += page.extract_text()
|
497 |
+
|
498 |
+
return text
|
499 |
+
|
500 |
+
except pikepdf.PasswordError:
|
501 |
+
raise ValueError("Mot de passe PDF incorrect")
|
502 |
+
except Exception as e:
|
503 |
+
raise RuntimeError(f"Erreur lors du traitement du PDF : {e}")
|
504 |
|
505 |
def process_protected_office(self, file, file_type: str, password: str = None) -> str:
|
506 |
+
"""
|
507 |
+
Traite un fichier Office (protégé ou non) et extrait le texte.
|
508 |
+
|
509 |
+
:param file: Le fichier Office à traiter.
|
510 |
+
:param password: Mot de passe du fichier (si nécessaire, sinon None).
|
511 |
+
:param file_type: Type du fichier ('docx' ou 'pptx').
|
512 |
+
:return: Texte extrait du fichier.
|
513 |
+
"""
|
514 |
+
try:
|
515 |
+
if password:
|
516 |
+
# Cas où un mot de passe est fourni, tenter de déverrouiller le fichier
|
517 |
+
office_file = msoffcrypto.OfficeFile(file)
|
518 |
+
office_file.load_key(password=password)
|
519 |
+
|
520 |
+
decrypted = io.BytesIO()
|
521 |
+
office_file.decrypt(decrypted)
|
522 |
+
|
523 |
+
if file_type == 'docx':
|
524 |
+
doc = docx.Document(decrypted)
|
525 |
+
return "\n".join([p.text for p in doc.paragraphs])
|
526 |
+
elif file_type == 'pptx':
|
527 |
+
ppt = pptx.Presentation(decrypted)
|
528 |
+
return "\n".join([shape.text for slide in ppt.slides
|
529 |
+
for shape in slide.shapes if hasattr(shape, "text")])
|
530 |
+
else:
|
531 |
+
# Cas où aucun mot de passe n'est fourni, traiter directement le fichier
|
532 |
+
if file_type == 'docx':
|
533 |
+
doc = docx.Document(file) # Charger le fichier sans décryptage
|
534 |
+
return "\n".join([p.text for p in doc.paragraphs])
|
535 |
+
elif file_type == 'pptx':
|
536 |
+
ppt = pptx.Presentation(file)
|
537 |
+
return "\n".join([shape.text for slide in ppt.slides
|
538 |
+
for shape in slide.shapes if hasattr(shape, "text")])
|
539 |
+
|
540 |
+
raise ValueError("Type de fichier non supporté. Utilisez 'docx' ou 'pptx'.")
|
541 |
+
|
542 |
+
except msoffcrypto.exceptions.InvalidKeyError:
|
543 |
+
raise ValueError("Mot de passe incorrect ou fichier non valide.")
|
544 |
+
except Exception as e:
|
545 |
+
raise RuntimeError(f"Erreur lors du traitement du fichier Office : {e}")
|
546 |
+
|
547 |
+
|
548 |
+
|
549 |
+
def scrape_web_content(self, url: str, auth: Dict[str, str] = None) -> str:
|
550 |
+
try:
|
551 |
+
if auth:
|
552 |
+
session = requests.Session()
|
553 |
+
session.auth = HTTPBasicAuth(auth['username'], auth['password'])
|
554 |
+
response = session.get(url, timeout=30)
|
555 |
+
else:
|
556 |
+
response = requests.get(url, timeout=30)
|
557 |
+
|
558 |
+
response.raise_for_status()
|
559 |
+
downloaded = trafilatura.extract(response.text)
|
560 |
+
|
561 |
+
if not downloaded:
|
562 |
+
raise ValueError("Impossible d'extraire le contenu de cette page")
|
563 |
+
return downloaded
|
564 |
+
|
565 |
+
except requests.exceptions.HTTPError as e:
|
566 |
+
if e.response.status_code == 401:
|
567 |
+
raise ValueError("Authentification requise pour accéder à cette page")
|
568 |
+
elif e.response.status_code == 404:
|
569 |
+
raise ValueError("Page introuvable")
|
570 |
+
else:
|
571 |
+
raise ValueError(f"Erreur HTTP: {e.response.status_code}")
|
572 |
+
except requests.exceptions.RequestException:
|
573 |
+
raise ValueError("URL invalide ou inaccessible")
|
574 |
+
|
575 |
+
def summarize_text(self, transcription: str) -> str:
|
576 |
+
chunks = self.split_text(transcription, max_tokens=4000)
|
577 |
+
partial_summaries = []
|
578 |
+
|
579 |
+
for i, chunk in enumerate(chunks):
|
580 |
+
st.write(f"Traitement du segment {i + 1}/{len(chunks)}...")
|
581 |
+
try:
|
582 |
+
messages = [
|
583 |
+
SystemMessage(content="Vous êtes un assistant expert en résumé de texte en français."),
|
584 |
+
HumanMessage(content=f"Résumez ce texte en français : {chunk}")
|
585 |
+
]
|
586 |
+
result = self._make_api_call(messages)
|
587 |
+
partial_summary = result.generations[0][0].text
|
588 |
+
|
589 |
+
# Vérification de la langue pour chaque segment
|
590 |
+
if self.check_language(partial_summary) == "NON":
|
591 |
+
partial_summary = self.translate_to_french(partial_summary)
|
592 |
+
|
593 |
+
partial_summaries.append(partial_summary)
|
594 |
+
except Exception as e:
|
595 |
+
if "rate_limit_exceeded" in str(e):
|
596 |
+
st.warning(f"Limite de taux atteinte au segment {i+1}. Attente avant nouvelle tentative...")
|
597 |
+
time.sleep(60)
|
598 |
+
i -= 1
|
599 |
+
continue
|
600 |
+
raise e
|
601 |
+
|
602 |
+
try:
|
603 |
+
final_prompt = f"""Combinez ces résumés partiels en un résumé global cohérent en langue française :
|
604 |
+
|
605 |
+
{' '.join(partial_summaries)}
|
606 |
+
"""
|
607 |
+
messages = [
|
608 |
+
SystemMessage(content="Vous êtes un assistant expert en résumé de texte en français."),
|
609 |
+
HumanMessage(content=final_prompt)
|
610 |
+
]
|
611 |
+
final_result = self._make_api_call(messages)
|
612 |
+
final_summary = final_result.generations[0][0].text
|
613 |
+
|
614 |
+
# Vérification finale de la langue
|
615 |
+
if self.check_language(final_summary) == "NON":
|
616 |
+
st.warning("Résumé final dans une autre langue. Traduction en cours...")
|
617 |
+
final_summary = self.translate_to_french(final_summary)
|
618 |
+
|
619 |
+
return final_summary
|
620 |
+
|
621 |
+
except Exception as e:
|
622 |
+
if "rate_limit_exceeded" in str(e):
|
623 |
+
st.warning("Limite de taux atteinte lors de la génération du résumé final. Attente avant nouvelle tentative...")
|
624 |
+
time.sleep(60)
|
625 |
+
return self.summarize_long_transcription(transcription)
|
626 |
+
raise e
|
627 |
+
|
628 |
+
|
629 |
+
def generate_docx(content: str, filename: str):
|
630 |
+
doc = Document()
|
631 |
+
doc.add_heading('Résumé Audio', 0)
|
632 |
+
doc.add_paragraph(f"Date: {datetime.now().strftime('%d/%m/%Y %H:%M')}")
|
633 |
+
|
634 |
+
for line in content.split('\n'):
|
635 |
+
if line.strip():
|
636 |
+
if line.startswith('#'):
|
637 |
+
doc.add_heading(line.strip('# '), level=1)
|
638 |
+
else:
|
639 |
+
doc.add_paragraph(line)
|
640 |
+
|
641 |
+
doc.save(filename)
|
642 |
+
return filename
|
643 |
|
644 |
|
645 |
def model_selection_sidebar():
|
646 |
+
"""Configuration du modèle dans la barre latérale"""
|
647 |
with st.sidebar:
|
648 |
st.title("Configuration")
|
649 |
model = st.selectbox(
|
650 |
"Sélectionnez un modèle",
|
651 |
+
[
|
652 |
+
"mixtral-8x7b-32768",
|
653 |
+
"llama-3.3-70b-versatile",
|
654 |
+
"gemma2-9b-i",
|
655 |
+
"llama3-70b-8192"
|
656 |
+
]
|
657 |
)
|
658 |
prompt = st.text_area(
|
659 |
"Instructions personnalisées pour le résumé",
|
|
|
661 |
)
|
662 |
return model, prompt
|
663 |
|
|
|
664 |
def save_uploaded_file(uploaded_file) -> str:
|
665 |
+
"""Sauvegarde un fichier uploadé et retourne son chemin"""
|
666 |
with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[1]) as tmp_file:
|
667 |
tmp_file.write(uploaded_file.getvalue())
|
668 |
return tmp_file.name
|
669 |
|
|
|
670 |
def is_valid_email(email: str) -> bool:
|
671 |
+
"""Valide le format d'une adresse email"""
|
672 |
pattern = r'^[\w\.-]+@[\w\.-]+\.\w+$'
|
673 |
return bool(re.match(pattern, email))
|
674 |
|
|
|
675 |
def enhance_main():
|
676 |
+
|
677 |
+
|
678 |
+
# Titre de l'application
|
679 |
+
st.title("🧠 **MultiModal Genius - Résumé Intelligent de Contenus Multimédias**")
|
680 |
+
st.subheader("Transformez vidéos, audios, textes, pages webs et plus en résumés clairs et percutants grâce à la puissance de l'IA")
|
681 |
+
|
682 |
+
with st.expander("Notice d'utilisation 📜"):
|
683 |
+
st.markdown("""
|
684 |
+
## **Bienvenue dans l'application MultiModal Genius !** 🎉
|
685 |
+
Cette application exploite la puissance de l'IA pour résumer des contenus multimédias variés, tels que des **documents**, **vidéos YouTube**, **audios**, **pages web**, et bien plus encore ! 🧠✨
|
686 |
+
|
687 |
+
### **Comment utiliser l'application ?**
|
688 |
+
1. **Documents** 📄 :
|
689 |
+
- **Formats supportés** : `.pdf`, `.docx`, `.pptx`, `.txt`
|
690 |
+
- Chargez un document via le bouton **"Télécharger un fichier"**.
|
691 |
+
- ⚠️ **Remarque** : Les documents contenant plus de **10 pages** peuvent entraîner des résultats imprécis en raison des limitations des modèles d'IA.
|
692 |
+
|
693 |
+
2. **Vidéos YouTube** 📹 :
|
694 |
+
- Collez simplement l'URL de la vidéo.
|
695 |
+
- La vidéo est automatiquement découpée en segments pour une analyse et un résumé précis.
|
696 |
+
- **Durée du traitement** : Plus la vidéo est longue, plus le traitement peut prendre du temps.
|
697 |
+
|
698 |
+
3. **Audios** 🎵 :
|
699 |
+
- Téléchargez un fichier audio au format `.mp3`.
|
700 |
+
- L'audio sera transcrit par blocs (chunks) avant d'être résumé.
|
701 |
+
- ⚠️ **Remarque** : Les fichiers audio de grande taille peuvent rallonger le processus.
|
702 |
+
|
703 |
+
4. **Pages Web** 🌐 :
|
704 |
+
- Fournissez l'URL de la page.
|
705 |
+
- Le contenu textuel sera extrait, découpé en blocs, puis résumé.
|
706 |
+
|
707 |
+
### **Pourquoi le résumé peut être long ?**
|
708 |
+
- **Traitement volumineux** : Les contenus trop longs ou complexes nécessitent un découpage en plusieurs blocs (chunks). Ces blocs sont analysés et traduits avant d'être rassemblés pour un résumé final.
|
709 |
+
- **Limites des modèles IA** : Certains contenus trop volumineux peuvent provoquer des hallucinations du modèle (résultats incohérents ou incorrects).
|
710 |
+
|
711 |
+
### **Fonctionnalités à venir 🚀**
|
712 |
+
- **Description d'images** 🖼️ : Transformez vos images en descriptions riches et détaillées.
|
713 |
+
- **Extraction de données** 📊 : Convertissez vos contenus en **format JSON** structuré.
|
714 |
+
- **Amélioration des résumés longs** : Réduction des hallucinations grâce à des optimisations.
|
715 |
+
- Et bien plus encore ! 🎯
|
716 |
+
|
717 |
+
### **Astuce pour une meilleure expérience**
|
718 |
+
- **Préférez des contenus courts ou moyennement volumineux** pour des résultats optimaux.
|
719 |
+
- En cas de traitement long, un indicateur de progression vous tiendra informé. ⏳
|
720 |
+
|
721 |
+
### **Nous sommes là pour vous aider !**
|
722 |
+
Si vous rencontrez un problème ou avez une suggestion pour améliorer l'application, n'hésitez pas à nous contacter. 🙌
|
723 |
+
""")
|
724 |
+
|
725 |
+
|
726 |
if "audio_processor" not in st.session_state:
|
727 |
model_name, custom_prompt = model_selection_sidebar()
|
728 |
st.session_state.audio_processor = AudioProcessor(model_name, custom_prompt)
|
729 |
+
|
730 |
if "auth_required" not in st.session_state:
|
731 |
st.session_state.auth_required = False
|
732 |
+
|
733 |
+
# Interface principale
|
734 |
source_type = st.radio("Type de source", ["Audio/Vidéo", "Document", "Web"])
|
735 |
+
|
736 |
try:
|
737 |
if source_type == "Audio/Vidéo":
|
738 |
process_audio_video()
|
|
|
744 |
st.error(f"Une erreur est survenue: {str(e)}")
|
745 |
st.error("Veuillez réessayer ou contacter le support.")
|
746 |
|
|
|
747 |
def process_audio_video():
|
748 |
+
"""Traitement des sources audio et vidéo"""
|
749 |
source = st.radio("Choisissez votre source", ["Audio", "Vidéo locale", "YouTube"])
|
750 |
+
|
751 |
if source == "Audio":
|
752 |
handle_audio_input()
|
753 |
elif source == "Vidéo locale":
|
|
|
755 |
else: # YouTube
|
756 |
handle_youtube_input()
|
757 |
|
|
|
758 |
def handle_audio_input():
|
759 |
+
"""Gestion des entrées audio"""
|
760 |
uploaded_file = st.file_uploader("Fichier audio", type=['mp3', 'wav', 'm4a', 'ogg'])
|
761 |
audio_bytes = audio_recorder()
|
762 |
+
|
763 |
if uploaded_file or audio_bytes:
|
764 |
process_and_display_results(uploaded_file, audio_bytes)
|
765 |
|
|
|
766 |
def handle_video_input():
|
767 |
+
"""Gestion des entrées vidéo"""
|
768 |
uploaded_video = st.file_uploader("Fichier vidéo", type=['mp4', 'avi', 'mov', 'mkv'])
|
769 |
if uploaded_video:
|
770 |
st.video(uploaded_video)
|
|
|
774 |
audio_path = video_processor.extract_audio_from_video(video_path)
|
775 |
process_and_display_results(audio_path)
|
776 |
|
|
|
777 |
def handle_youtube_input():
|
778 |
+
"""Gestion des entrées YouTube"""
|
779 |
+
|
780 |
youtube_url = st.text_input("URL YouTube")
|
781 |
if youtube_url and st.button("Analyser"):
|
782 |
video_processor = VideoProcessor()
|
783 |
video_id = video_processor.extract_video_id(youtube_url)
|
784 |
+
|
785 |
if video_id:
|
786 |
st.video(youtube_url)
|
787 |
with st.spinner("Traitement de la vidéo..."):
|
|
|
792 |
video_processor.load_cookies()
|
793 |
audio_path = video_processor.download_youtube_audio(youtube_url)
|
794 |
process_and_display_results(audio_path)
|
795 |
+
|
796 |
+
#if youtube_url and st.button("Analyser"):
|
797 |
+
# if not re.match(r'^https?://(?:www\.)?youtube\.com/watch\?v=[\w-]+|^https?://youtu\.be/[\w-]+', youtube_url):
|
798 |
+
# st.error("URL YouTube invalide")
|
799 |
+
# else:
|
800 |
+
# video_processor = VideoProcessor()
|
801 |
+
# video_id = video_processor.extract_video_id(youtube_url)
|
802 |
+
# if video_id:
|
803 |
+
# st.video(youtube_url)
|
804 |
+
|
805 |
+
# with st.spinner("Récupération du contenu de la vidéo..."):
|
806 |
+
# Essayer d'abord d'obtenir la transcription
|
807 |
+
# transcription = video_processor.get_youtube_transcription(video_id)
|
808 |
+
|
809 |
+
# if transcription:
|
810 |
+
# st.success("Transcription YouTube trouvée!")
|
811 |
+
# process_and_display_results(None, None, transcription)
|
812 |
+
# else:
|
813 |
+
# st.info("Pas de transcription disponible. Extraction de l'audio...")
|
814 |
+
# video_processor.load_cookies()
|
815 |
+
# audio_path = video_processor.download_youtube_audio(youtube_url)
|
816 |
+
# process_and_display_results(audio_path)
|
817 |
|
818 |
|
819 |
def process_and_display_results(file_path=None, audio_bytes=None, transcription=None):
|
820 |
+
"""Traitement et affichage des résultats"""
|
821 |
+
try:
|
822 |
+
if transcription is None:
|
823 |
+
transcription = get_transcription(file_path, audio_bytes)
|
824 |
+
|
825 |
+
if transcription:
|
826 |
+
display_transcription_and_summary(transcription)
|
827 |
+
finally:
|
828 |
+
cleanup_temporary_files()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
829 |
|
830 |
+
def get_transcription(file_path=None, audio_bytes=None) -> str:
|
831 |
+
"""Obtention de la transcription"""
|
832 |
+
if file_path:
|
833 |
+
path = file_path if isinstance(file_path, str) else save_uploaded_file(file_path)
|
834 |
+
elif audio_bytes:
|
835 |
+
path = save_audio_bytes(audio_bytes)
|
836 |
+
else:
|
837 |
+
return None
|
838 |
|
839 |
+
chunks = st.session_state.audio_processor.chunk_audio(path)
|
840 |
+
transcriptions = []
|
841 |
+
|
842 |
+
with st.expander("Transcription", expanded=False):
|
843 |
+
progress_bar = st.progress(0)
|
844 |
+
for i, chunk in enumerate(chunks):
|
845 |
+
transcription = st.session_state.audio_processor.transcribe_chunk(chunk)
|
846 |
+
if transcription:
|
847 |
+
transcriptions.append(transcription)
|
848 |
+
progress_bar.progress((i + 1) / len(chunks))
|
849 |
+
|
850 |
+
return " ".join(transcriptions) if transcriptions else None
|
851 |
|
852 |
def get_summary(full_transcription):
|
853 |
if full_transcription is not None:
|
|
|
858 |
separators=["\n\n", "\n", " ", ""]
|
859 |
)
|
860 |
chunks = text_splitter.split_text(full_transcription)
|
861 |
+
|
862 |
+
# Résumé basé sur le nombre de morceaux
|
863 |
if len(chunks) > 1:
|
864 |
summary = st.session_state.audio_processor.summarize_long_transcription(full_transcription)
|
865 |
else:
|
866 |
summary = st.session_state.audio_processor.generate_summary(full_transcription)
|
867 |
else:
|
868 |
st.error("La transcription a échoué")
|
869 |
+
return None # Retourne None si la transcription est invalide
|
870 |
+
|
871 |
+
return summary # Retourne le résumé
|
872 |
+
|
873 |
+
def generate_and_download_documents(summary: str):
|
874 |
+
"""Génération et téléchargement des documents"""
|
875 |
+
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
|
876 |
+
|
877 |
+
# Génération PDF
|
878 |
+
pdf_filename = f"resume_{timestamp}.pdf"
|
879 |
+
pdf_path = PDFGenerator.create_pdf(summary, pdf_filename)
|
880 |
+
|
881 |
+
# Génération DOCX
|
882 |
+
docx_filename = f"resume_{timestamp}.docx"
|
883 |
+
docx_path = generate_docx(summary, docx_filename)
|
884 |
+
|
885 |
+
# Boutons de téléchargement avec des clés uniques
|
886 |
+
col1, col2 = st.columns(2)
|
887 |
+
with col1:
|
888 |
+
with open(pdf_path, "rb") as pdf_file:
|
889 |
+
st.download_button(
|
890 |
+
"📥 Télécharger PDF",
|
891 |
+
pdf_file,
|
892 |
+
file_name=pdf_filename,
|
893 |
+
mime="application/pdf",
|
894 |
+
key=f"download_pdf_{uuid.uuid4()}" # Utilisation d'un UUID
|
895 |
+
)
|
896 |
+
|
897 |
+
with col2:
|
898 |
+
with open(docx_path, "rb") as docx_file:
|
899 |
+
st.download_button(
|
900 |
+
"📥 Télécharger DOCX",
|
901 |
+
docx_file,
|
902 |
+
file_name=docx_filename,
|
903 |
+
mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
|
904 |
+
key=f"download_docx_{uuid.uuid4()}" # Utilisation d'un UUID
|
905 |
+
)
|
906 |
+
|
907 |
+
return pdf_path
|
908 |
+
|
909 |
+
|
910 |
+
def display_transcription_and_summary(transcription: str):
|
911 |
+
"""Affichage de la transcription et du résumé"""
|
912 |
+
st.subheader("Transcription")
|
913 |
+
st.text_area("Texte transcrit:", value=transcription, height=200)
|
914 |
+
|
915 |
+
st.subheader("Résumé et Analyse")
|
916 |
+
summary = get_summary(transcription)
|
917 |
+
st.markdown(summary)
|
918 |
+
|
919 |
+
# Génération et téléchargement des documents
|
920 |
+
#generate_and_download_documents(summary)
|
921 |
+
display_summary_and_downloads(summary)
|
922 |
+
# Option d'envoi par email
|
923 |
+
#handle_email_sending(summary)
|
924 |
+
|
925 |
+
|
926 |
+
|
927 |
+
|
928 |
+
def handle_email_sending(summary: str):
|
929 |
+
"""Gestion de l'envoi par email"""
|
930 |
+
st.subheader("📧 Recevoir le résumé par email")
|
931 |
+
recipient_email = st.text_input("Entrez votre adresse email:")
|
932 |
+
|
933 |
+
if st.button("Envoyer par email"):
|
934 |
+
if not is_valid_email(recipient_email):
|
935 |
+
st.error("Veuillez entrer une adresse email valide.")
|
936 |
+
return
|
937 |
+
|
938 |
+
with st.spinner("Envoi de l'email en cours..."):
|
939 |
+
pdf_path = generate_and_download_documents(summary)
|
940 |
+
email_sender = EmailSender(SENDER_EMAIL, SENDER_PASSWORD)
|
941 |
+
|
942 |
+
if email_sender.send_email(
|
943 |
+
recipient_email,
|
944 |
+
"Résumé de votre contenu audio/vidéo",
|
945 |
+
"Veuillez trouver ci-joint le résumé de votre contenu.",
|
946 |
+
pdf_path
|
947 |
+
):
|
948 |
+
st.success("Email envoyé avec succès!")
|
949 |
+
else:
|
950 |
+
st.error("Échec de l'envoi de l'email.")
|
951 |
+
|
952 |
+
|
953 |
+
|
954 |
+
def cleanup_temporary_files():
|
955 |
+
"""Nettoyage des fichiers temporaires"""
|
956 |
+
temp_files = ['temp_audio.mp3', 'temp_video.mp4']
|
957 |
+
for temp_file in temp_files:
|
958 |
+
if os.path.exists(temp_file):
|
959 |
+
try:
|
960 |
+
os.remove(temp_file)
|
961 |
+
except Exception:
|
962 |
+
pass
|
963 |
+
|
964 |
+
def process_document():
|
965 |
+
"""Traitement des documents"""
|
966 |
+
file = st.file_uploader("Chargez votre document", type=['pdf', 'docx', 'pptx', 'txt'])
|
967 |
+
password = st.text_input("Mot de passe (si protégé)", type="password")
|
968 |
+
|
969 |
+
if file:
|
970 |
+
try:
|
971 |
+
doc_processor = DocumentProcessor(
|
972 |
+
st.session_state.audio_processor.llm.model_name,
|
973 |
+
st.session_state.audio_processor.custom_prompt
|
974 |
+
)
|
975 |
+
text = process_document_with_password(file, password, doc_processor)
|
976 |
+
if text:
|
977 |
+
summary = doc_processor.summarize_text(text)
|
978 |
+
st.markdown("### 📝 Résumé et Analyse")
|
979 |
+
st.markdown(summary)
|
980 |
+
display_summary_and_downloads(summary)
|
981 |
+
except ValueError as e:
|
982 |
+
st.error(str(e))
|
983 |
+
|
984 |
+
def process_document_with_password(file, password: str, doc_processor: DocumentProcessor) -> Optional[str]:
|
985 |
+
"""Traitement des documents protégés par mot de passe"""
|
986 |
+
file_extension = os.path.splitext(file.name)[1].lower()
|
987 |
+
|
988 |
+
try:
|
989 |
+
if file_extension == '.pdf':
|
990 |
+
return doc_processor.process_protected_pdf(file, password)
|
991 |
+
elif file_extension in ['.docx', '.pptx']:
|
992 |
+
return doc_processor.process_protected_office(file, file_extension[1:], password)
|
993 |
+
elif file_extension == '.txt':
|
994 |
+
return file.read().decode('utf-8')
|
995 |
+
else:
|
996 |
+
st.error("Format de fichier non supporté")
|
997 |
+
return None
|
998 |
+
except ValueError as e:
|
999 |
+
st.error(str(e))
|
1000 |
return None
|
|
|
1001 |
|
1002 |
|
1003 |
+
|
1004 |
+
|
1005 |
+
def is_text_content(url):
|
1006 |
+
try:
|
1007 |
+
# Utiliser Selenium ou Playwright pour le rendu JavaScript
|
1008 |
+
response = requests.get(url)
|
1009 |
+
return ('text' in response.headers.get('content-type', '').lower()
|
1010 |
+
or 'html' in response.headers.get('content-type', '').lower()
|
1011 |
+
or 'application/json' in response.headers.get('content-type', '').lower())
|
1012 |
+
except:
|
1013 |
+
return False
|
1014 |
+
|
1015 |
+
def is_valid_content_url(url):
|
1016 |
+
"""Vérifie si l'URL est valide pour l'extraction de contenu"""
|
1017 |
+
parsed = urlparse(url)
|
1018 |
+
|
1019 |
+
excluded_domains = [
|
1020 |
+
'youtube.com', 'vimeo.com', 'dailymotion.com',
|
1021 |
+
'imgur.com', 'flickr.com', 'instagram.com',
|
1022 |
+
'facebook.com', 'fb.com', 'twitter.com', 'x.com',
|
1023 |
+
'tiktok.com', 'linkedin.com', 'pinterest.com',
|
1024 |
+
'snapchat.com', 'reddit.com', 'tumblr.com',
|
1025 |
+
'whatsapp.com', 'telegram.org', 'discord.com'
|
1026 |
+
]
|
1027 |
+
|
1028 |
+
excluded_extensions = ['.jpg', '.jpeg', '.png', '.gif', '.mp4', '.mp3', '.pdf']
|
1029 |
+
|
1030 |
+
domain = parsed.netloc.lower()
|
1031 |
+
path = parsed.path.lower()
|
1032 |
+
|
1033 |
+
return not (
|
1034 |
+
any(exc in domain for exc in excluded_domains) or
|
1035 |
+
any(path.endswith(ext) for ext in excluded_extensions)
|
1036 |
+
)
|
1037 |
+
|
1038 |
+
def process_web():
|
1039 |
+
"""Traitement des contenus web"""
|
1040 |
+
url = st.text_input("URL du site web")
|
1041 |
+
auth_required = st.checkbox("Authentification requise")
|
1042 |
+
|
1043 |
+
auth = None
|
1044 |
+
if auth_required:
|
1045 |
+
username = st.text_input("Nom d'utilisateur")
|
1046 |
+
password = st.text_input("Mot de passe", type="password")
|
1047 |
+
auth = {"username": username, "password": password}
|
1048 |
+
|
1049 |
+
if url and st.button("Analyser"):
|
1050 |
+
if not url.startswith(('http://', 'https://')):
|
1051 |
+
st.error("L'URL doit commencer par 'http://' ou 'https://'")
|
1052 |
+
return
|
1053 |
+
|
1054 |
+
if not is_valid_content_url(url):
|
1055 |
+
st.error(f"Cette URL ({url}) ne peut pas être traitée (vidéo, image ou autre contenu non supporté)")
|
1056 |
+
return
|
1057 |
+
|
1058 |
+
if not is_text_content(url):
|
1059 |
+
st.error(f"Cette URL ({url}) ne contient pas de contenu textuel analysable")
|
1060 |
+
return
|
1061 |
+
|
1062 |
+
try:
|
1063 |
+
doc_processor = DocumentProcessor(
|
1064 |
+
st.session_state.audio_processor.llm.model_name,
|
1065 |
+
st.session_state.audio_processor.custom_prompt
|
1066 |
+
)
|
1067 |
+
text = doc_processor.scrape_web_content(url, auth)
|
1068 |
+
if text:
|
1069 |
+
summary = doc_processor.summarize_text(text)
|
1070 |
+
st.markdown("### 📝 Résumé et Analyse")
|
1071 |
+
st.markdown(summary)
|
1072 |
+
display_summary_and_downloads(summary)
|
1073 |
+
except ValueError as e:
|
1074 |
+
st.error(str(e))
|
1075 |
+
|
1076 |
def display_summary_and_downloads(summary: str):
|
1077 |
+
"""Affichage du résumé et options de téléchargement"""
|
1078 |
+
#st.markdown("### 📝 Résumé et Analyse")
|
1079 |
+
#st.markdown(summary)
|
1080 |
+
|
1081 |
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
|
1082 |
+
|
1083 |
+
# Génération PDF
|
1084 |
pdf_filename = f"resume_{timestamp}.pdf"
|
1085 |
pdf_path = PDFGenerator.create_pdf(summary, pdf_filename)
|
1086 |
+
|
1087 |
+
# Génération DOCX
|
1088 |
docx_filename = f"resume_{timestamp}.docx"
|
1089 |
docx_path = generate_docx(summary, docx_filename)
|
1090 |
+
|
1091 |
+
# Boutons de téléchargement
|
1092 |
col1, col2 = st.columns(2)
|
1093 |
with col1:
|
1094 |
with open(pdf_path, "rb") as pdf_file:
|
|
|
1098 |
file_name=pdf_filename,
|
1099 |
mime="application/pdf"
|
1100 |
)
|
1101 |
+
|
1102 |
with col2:
|
1103 |
with open(docx_path, "rb") as docx_file:
|
1104 |
st.download_button(
|
|
|
1107 |
file_name=docx_filename,
|
1108 |
mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
|
1109 |
)
|
1110 |
+
|
1111 |
+
# Option d'envoi par email
|
1112 |
st.markdown("### 📧 Recevoir le résumé par email")
|
1113 |
recipient_email = st.text_input("Entrez votre adresse email:")
|
1114 |
+
|
1115 |
if st.button("Envoyer par email"):
|
1116 |
if not is_valid_email(recipient_email):
|
1117 |
st.error("Veuillez entrer une adresse email valide.")
|
|
|
1128 |
else:
|
1129 |
st.error("Échec de l'envoi de l'email.")
|
1130 |
|
1131 |
+
def save_audio_bytes(audio_bytes: bytes) -> str:
|
1132 |
+
"""Sauvegarde les bytes audio dans un fichier temporaire"""
|
1133 |
+
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
1134 |
+
file_path = f"recording_{timestamp}.wav"
|
1135 |
+
with open(file_path, 'wb') as f:
|
1136 |
+
f.write(audio_bytes)
|
1137 |
+
return file_path
|
1138 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1139 |
if __name__ == "__main__":
|
1140 |
try:
|
1141 |
enhance_main()
|
|
|
1143 |
st.error(f"Une erreur inattendue est survenue: {str(e)}")
|
1144 |
st.error("Veuillez réessayer ou contacter le support technique.")
|
1145 |
finally:
|
1146 |
+
cleanup_temporary_files()
|
|
|
|