Add application file

app.py

@@ -3,11 +3,21 @@ import fitz  # PyMuPDF
 from sentence_transformers import SentenceTransformer, util
 import faiss
 from transformers import pipeline
+import os
+from pathlib import Path
 
 st.title("Évaluation Stagiaire Data Scientist")
 
 uploaded_file = st.file_uploader("Choisissez un fichier PDF", type="pdf")
 
+def save_uploaded_file(uploaded_file, directory):
+    directory = Path(directory)
+    directory.mkdir(parents=True, exist_ok=True)
+    file_path = directory / uploaded_file.name
+    with open(file_path, "wb") as f:
+        f.write(uploaded_file.getbuffer())
+    return file_path
+
 def extract_text_from_pdf(pdf_path):
     text = ""
     pdf_document = fitz.open(pdf_path)
@@ -55,10 +65,10 @@ def generate_training_plan(scores, threshold=0.7):
     return plan
 
 if uploaded_file is not None:
-    with open("uploaded_document.pdf", "wb") as f:
-        f.write(uploaded_file.getbuffer())
-    document_text = extract_text_from_pdf("uploaded_document.pdf")
-    
+    file_path = save_uploaded_file(uploaded_file, "uploaded_documents")
+    st.write(f"Fichier téléchargé et sauvegardé sous : {file_path}")
+
+    document_text = extract_text_from_pdf(file_path)
     st.write("Texte extrait du document PDF:")
     st.write(document_text[:1000])  # Affiche les 1000 premiers caractères du texte extrait
 

requirements.txt

@@ -4,3 +4,4 @@ sentence-transformers
 faiss-cpu
 transformers
 torch
+sentencepiece