Update app.py

app.py

@@ -16,7 +16,7 @@ from nltk.corpus import stopwords
 model = SentenceTransformer('sentence-transformers/multi-qa-distilbert-cos-v1')
 russian_stopwords = stopwords.words('russian') + ['ВАШ']
 
-with open("data/symptom_checker/top_150_symps_by_spec.json", 'r') as f:
+with open("top_150_symps_by_spec.json", 'r') as f:
     symps = json.load(f)
 
 with open("embeddings.npy", 'rb') as f:
@@ -40,7 +40,6 @@ def get_symptomps_v2(text, treshold = 0.7):
             text = [text]
             
         X = vectorizer.fit_transform(text)
-        # print(vectorizer.get_feature_names_out())
         text_emb = model.encode(vectorizer.get_feature_names_out(), batch_size=64)
         cos_sim_m = util.cos_sim(text_emb, embs).numpy()
         cos_sim_m = np.where(cos_sim_m > treshold, cos_sim_m, -1)