Update app.py

app.py

@@ -10,10 +10,10 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 # Load the CSV file with embeddings
 df = pd.read_csv('RBDx10kstats.csv')
-df['embedding'] = df['embedding'].apply(json.loads)  # Convert JSON string back to list
+df['Abstract'] = df['Abstract'].apply(json.loads)  # Convert JSON string back to list
 
 # Convert embeddings to tensor for efficient retrieval
-embeddings = torch.tensor(df['embedding'].tolist(), device=device)
+embeddings = torch.tensor(df['Abstract'].tolist(), device=device)
 
 # Load the Sentence Transformer model
 model = SentenceTransformer('all-MiniLM-L6-v2', device=device)