Update app.py

app.py

@@ -21,8 +21,8 @@ dataset = load_dataset("Namitg02/Test", split='train', streaming=False)
 #Returns a list of dictionaries, each representing a row in the dataset.
 length = len(dataset)
 
-embedding_model = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1")
-#all-MiniLM-L6-v2, BAAI/bge-base-en-v1.5,infgrad/stella-base-en-v2, BAAI/bge-large-en-v1.5 working with default dimensions
+embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
+#all-MiniLM-L6-v2, BAAI/bge-base-en-v1.5,infgrad/stella-base-en-v2, BAAI/bge-large-en-v1.5, mixedbread-ai/mxbai-embed-large-v1 working with default dimensions
 
 df = pd.DataFrame(dataset)
 #print(df.iloc[[1]])
@@ -47,9 +47,9 @@ data = dataset
 d = 384  # vectors dimension
 m = 32  # hnsw parameter. Higher is more accurate but takes more time to index (default is 32, 128 should be ok)
 #index = faiss.IndexHNSWFlat(d, m)
-#index =  faiss.IndexFlatL2(embedding_dim)
-#data.add_faiss_index(embeddings.shape[1], custom_index=index) 
-data.add_faiss_index("embeddings")
+index =  faiss.IndexFlatL2(embedding_dim)
+data.add_faiss_index(embeddings.shape[1], custom_index=index) 
+#data.add_faiss_index("embeddings")
 # adds an index column for the embeddings
 
 print("check1d")