Adding in model choice

app.py

@@ -47,15 +47,24 @@ text = st.text_area('Enter sentences:', value="The sun is hotter than the moon.\
 
 nc = st.slider('Select a number of clusters', min_value=1, max_value=15, value=3)
 
+model_type = st.radio("Choose model", ('Sentence Transformer', 'Universal Sentence Encoder'), index=0)
+
 # Model setup
-model = SentenceTransformer('paraphrase-distilroberta-base-v1')
+if model_type == "Sentence Transformer":
+    model = SentenceTransformer('paraphrase-distilroberta-base-v1')
+elif model_type == "Universal Sentence Encoder":
+    model_url = "https://tfhub.dev/google/universal-sentence-encoder-large/5"
+    model = hub.load(model_url)
+
 nltk.download('punkt')
 
 # Run model
 if text:
     sentences = nltk.tokenize.sent_tokenize(text)
-    embed = model.encode(sentences)
-    
+    if model_type == "Sentence Transformer":
+        embed = model.encode(sentences)
+    elif model_type == "Universal Sentence Encoder":
+        embed = model(sentences).numpy()
     sim = np.zeros([len(embed), len(embed)])
     for i,em in enumerate(embed):
         for j,ea in enumerate(embed):

requirements.txt

@@ -7,3 +7,5 @@ numpy
 seaborn
 matplotlib
 sklearn
+tensorflow_hub
+tensorflow