Update app.py

app.py

@@ -28,7 +28,7 @@ def search(query):
     query_vector = model.encode([query])[0].astype('float32')
     
     # Search the FAISS index
-    distances, indices = index.search(np.array([query_vector]), k=5)  # Search for top 5 closest vectors
+    distances, indices = index.search(np.array([query_vector]), k=1)  # Search for top 5 closest vectors
     
     # Return corresponding content for the top results using the indices
     results = [f"Content: {content_column[i]}\nDistance: {d:.4f}" for i, d in zip(indices[0], distances[0])]