Update api.py

api.py

@@ -80,8 +80,10 @@ class MovieRecommender:
         return np.array(ids)[None,:]
 
     def recommend(self, prompt, topk=10):
-        q_ids = self._encode(prompt)
-        query_vec = np.sum(self.embeddings[q_ids], axis=1)
+        q_ids = self.tokenizer.texts_to_sequences([prompt])[0]
+        q_ids = [i for i in q_ids if 0 <= i < len(self.embeddings)]
+        q_ids = np.array(q_ids, dtype=np.int64)
+        query_vec = self.embeddings[q_ids].mean(axis=0, keepdims=True)
         sims = cosine_similarity(query_vec, self.embeddings).flatten()
         idx = sims.argsort()[::-1][:topk]
         return self.movies.iloc[idx][["title","release_date","vote_average","vote_count","status"]]