Update app.py

app.py

@@ -58,9 +58,11 @@ def detect_language(text):
 
 @st.cache_data
 def tsne_visualization(embeddings, words):
-    if len(words) < 30:
+    if len(words) < 3:  # Not enough words for t-SNE
         return pd.DataFrame({'word': words})
-    tsne = TSNE(n_components=2, random_state=42, perplexity=min(30, len(words) - 1))
+    
+    perplexity = min(30, len(words) - 1)
+    tsne = TSNE(n_components=2, random_state=42, perplexity=perplexity)
     embeddings_2d = tsne.fit_transform(embeddings)
     df = pd.DataFrame(embeddings_2d, columns=['x', 'y'])
     df['word'] = words
@@ -96,18 +98,21 @@ if st.button("Analyze"):
                 st.write("Word list (not enough words for t-SNE visualization):")
                 st.write(", ".join(words))
 
-        with st.spinner("Extracting topics..."):
-            texts = [user_input, "Another text to improve topic modeling."]
-            topic_distr, vectorizer = topic_modeling_agent.fit_transform(texts, lang)
-            topics = topic_modeling_agent.get_topics(vectorizer)
-            st.subheader("Topics Extracted:")
-            for topic, words in topics.items():
-                st.write(f"Topic {topic}: {', '.join(words)}")
-
-        with st.spinner("Computing similarity..."):
-            text2 = "Otro texto de ejemplo para comparación de similitud." if lang != 'en' else "Another example text for similarity comparison."
-            similarity_score = similarity_agent.compute_similarity(user_input, text2)
-            st.write(f"Similarity Score with example text: {similarity_score:.4f}")
+        if len(words) > 1:
+            with st.spinner("Extracting topics..."):
+                texts = [user_input, "Another text to improve topic modeling."]
+                topic_distr, vectorizer = topic_modeling_agent.fit_transform(texts, lang)
+                topics = topic_modeling_agent.get_topics(vectorizer)
+                st.subheader("Topics Extracted:")
+                for topic, topic_words in topics.items():
+                    st.write(f"Topic {topic}: {', '.join(topic_words)}")
+
+            with st.spinner("Computing similarity..."):
+                text2 = "Otro texto de ejemplo para comparación de similitud." if lang != 'en' else "Another example text for similarity comparison."
+                similarity_score = similarity_agent.compute_similarity(user_input, text2)
+                st.write(f"Similarity Score with example text: {similarity_score:.4f}")
+        else:
+            st.warning("Not enough words for topic modeling and similarity comparison.")
 
     else:
         st.warning("Please enter some text to analyze.")