Update app.py

app.py

@@ -23,6 +23,45 @@ from sentence_transformers import SentenceTransformer #import model
 
 embedder = SentenceTransformer("nomic-ai/nomic-embed-text-v1.5",trust_remote_code=True)
 
+def search(query):
+  # return the first 15 results ranked by similarity.
+  n = 15
+
+  # Embedding the query.
+  query_embedding = embedder.encode(query)
+
+  # Generate the similarity column.
+  df_with_embedding2["similarity"] = (df_with_embedding2.embedding_summary.apply(lambda x: cosine_similarity(x, query_embedding.reshape(768,-1)))+df_with_embedding2.embedding_reviews.apply(lambda x: cosine_similarity(x, query_embedding.reshape(768,-1))))/2
+
+
+  results = (
+      df_with_embedding2.sort_values("similarity", ascending=False)
+      .head(n))
+
+  resultlist = []
+
+
+  hlist = []
+  for r in results.index:
+      if results.hotel_name[r] not in hlist:
+          smalldf = results.loc[results.hotel_name == results.hotel_name[r]]
+          if smalldf.shape[1] > 3:
+            smalldf = smalldf[:3]
+
+          resultlist.append(
+          {
+            "name":results.hotel_name[r],
+            "score": smalldf.similarity[r][0],
+            "rating": smalldf.rating_value[r],
+            "review_count": smalldf.review_count[r],
+            "street_address": smalldf.street_address[r],
+            "city": smalldf.locality[r],
+            "country": smalldf.country[r],
+            "hotel_image":smalldf.hotel_image[r]
+          })
+          hlist.append(results.hotel_name[r])
+  return resultlist
+
 import gradio as gr
 import json