Update app.py

app.py

@@ -101,8 +101,12 @@ def process_files(model_name, split_strategy, chunk_size, overlap_size, max_toke
 
 def search_embeddings(query, model_name, top_k):
     model = HuggingFaceEmbeddings(model_name=MODELS[model_name])
-    embeddings = model.embed_query(query)
-
+    #embeddings = model.embed_query(query)
+    embeddings = model.similarity_search(query)
+    print(embeddings[0])
+    #query = "What did the president say about Ketanji Brown Jackson"
+    #docs = db.similarity_search(query)
+    #print(docs[0].page_content)
     # Perform FAISS or other similarity-based search over embeddings
     # This part requires you to build and search a FAISS index with embeddings