Update app.py

app.py

@@ -7,7 +7,7 @@ from datasets import load_dataset
 import pandas as pd
 
 # Charger les embeddings sauvegardés
-dataset = load_dataset("ayouubelb/embeddings",split = 'train')
+dataset = load_dataset("ayouubelb/embeddings")
 data = pd.DataFrame(dataset)
 embeddings = np.array(data['embedding']).astype('float32')
 texts = data['metadata']
@@ -19,7 +19,7 @@ index.add(embeddings)
 
 genai.configure(api_key="AIzaSyBLlaGtxtzHmVgMfOC02AfgvOoKTwXGGIc")
 model_gene = genai.GenerativeModel("gemini-2.0-flash")
-model =  SentenceTransformer("dangvantuan/sentence-camembert-base",device = 'cuda')
+model =  SentenceTransformer("dangvantuan/sentence-camembert-base")
 
 def rag_legal_bot(user_input):
     # Générer l'embedding de la requête