translate

app.py

@@ -1,9 +1,158 @@
-from fastapi import FastAPI
+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import JSONResponse, RedirectResponse
 from fastapi.staticfiles import StaticFiles
-from fastapi.responses import RedirectResponse
+from fastapi.middleware.cors import CORSMiddleware
+from transformers import pipeline, M2M100ForConditionalGeneration, M2M100Tokenizer, MarianMTModel, MarianTokenizer
+import shutil
+#
+import os
+import logging
+from PyPDF2 import PdfReader
+import docx
+from PIL import Image
+import openpyxl  # 📌 Pour lire les fichiers Excel (.xlsx)
+from pptx import Presentation
+import fitz  # PyMuPDF
+import io
+from docx import Document
+import matplotlib.pyplot as plt
+import seaborn as sns
+import torch
+import re
+import pandas as pd
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from fastapi.responses import FileResponse
+import os
+from fastapi.middleware.cors import CORSMiddleware
+import matplotlib
+matplotlib.use('Agg')
+
+import re
+import torch
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import FileResponse
+import os
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import JSONResponse, RedirectResponse
+from fastapi.staticfiles import StaticFiles
+from transformers import pipeline, M2M100ForConditionalGeneration, M2M100Tokenizer
+import shutil
+import os
+import logging
+from fastapi.middleware.cors import CORSMiddleware
+from PyPDF2 import PdfReader
+import docx
+from PIL import Image  # Pour ouvrir les images avant analyse
+from transformers import MarianMTModel, MarianTokenizer
+import os
+import fitz 
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+import logging
+import openpyxl
+
+
+# Configuration du logging
+logging.basicConfig(level=logging.INFO)
 
 app = FastAPI()
 
+# Configuration CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+UPLOAD_DIR = "uploads"
+os.makedirs(UPLOAD_DIR, exist_ok=True)
+
+#traduction-----------------------------------------------------------------------------------------------------------
+
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+model_name = "facebook/m2m100_418M"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+
+# Fonction pour extraire le texte
+def extract_text_from_pdf(file):
+    doc = fitz.open(stream=file.file.read(), filetype="pdf")
+    return "\n".join([page.get_text() for page in doc]).strip()
+
+def extract_text_from_docx(file):
+    doc = Document(io.BytesIO(file.file.read()))
+    return "\n".join([para.text for para in doc.paragraphs]).strip()
+
+def extract_text_from_pptx(file):
+    prs = Presentation(io.BytesIO(file.file.read()))
+    return "\n".join([shape.text for slide in prs.slides for shape in slide.shapes if hasattr(shape, "text")]).strip()
+
+def extract_text_from_excel(file):
+    wb = openpyxl.load_workbook(io.BytesIO(file.file.read()), data_only=True)
+    text = [str(cell) for sheet in wb.worksheets for row in sheet.iter_rows(values_only=True) for cell in row if cell]
+    return "\n".join(text).strip()
+
+@app.post("/translate/")
+async def translate_document(file: UploadFile = File(...), target_lang: str = Form(...)):
+    """API pour traduire un document."""
+    try:
+        logging.info(f"📥 Fichier reçu : {file.filename}")
+        logging.info(f"🌍 Langue cible reçue : {target_lang}")
+
+        if model is None or tokenizer is None:
+            return JSONResponse(status_code=500, content={"error": "Modèle de traduction non chargé"})
+
+        # Extraction du texte
+        if file.filename.endswith(".pdf"):
+            text = extract_text_from_pdf(file)
+        elif file.filename.endswith(".docx"):
+            text = extract_text_from_docx(file)
+        elif file.filename.endswith(".pptx"):
+            text = extract_text_from_pptx(file)
+        elif file.filename.endswith(".xlsx"):
+            text = extract_text_from_excel(file)
+        else:
+            return JSONResponse(status_code=400, content={"error": "Format non supporté"})
+
+        logging.info(f"📜 Texte extrait : {text[:50]}...")
+
+        if not text:
+            return JSONResponse(status_code=400, content={"error": "Aucun texte trouvé dans le document"})
+
+        # Vérifier si la langue cible est supportée
+        target_lang_id = tokenizer.get_lang_id(target_lang)
+
+        if target_lang_id is None:
+            return JSONResponse(
+                status_code=400,
+                content={"error": f"Langue cible '{target_lang}' non supportée. Langues disponibles : {list(tokenizer.lang_code_to_id.keys())}"}
+            )
+
+        # Traduction
+        tokenizer.src_lang = "fr"
+        encoded_text = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+
+        logging.info(f"🔍 ID de la langue cible : {target_lang_id}")
+
+        generated_tokens = model.generate(**encoded_text, forced_bos_token_id=target_lang_id)
+
+        translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+
+        logging.info(f"✅ Traduction réussie : {translated_text[:50]}...")
+        return {"translated_text": translated_text}
+
+    except Exception as e:
+        logging.error(f"❌ Erreur lors de la traduction : {e}")
+        return JSONResponse(status_code=500, content={"error": "Échec de la traduction"})
+
 # Servir les fichiers statiques (HTML, CSS, JS)
 app.mount("/static", StaticFiles(directory="static", html=True), name="static")