Update app.py

app.py

@@ -59,21 +59,9 @@ def find_sentences(query):
     query_embedding = model.encode(query)
     hits = util.semantic_search(query_embedding, corpus_embeddings, top_k=5)
     hit = hits[0][0]
-
     
     corpus_id = hit['corpus_id']
-    # print(corpus[corpus_id], "(Score: {:.4f})".format(hit['score']))
-    # Find source document based on sentence index
-    count = 0
-    for idx, c in enumerate(sentence_count):
-        count+=c
-        if (corpus_id > count-1):
-            continue
-        else:
-            doc = corpus[idx]
-            return doc
-            #print(f"Document: {doc}, {count}")
-            break
+
     return corpus[corpus_id]