Update app.py

app.py

@@ -93,10 +93,13 @@ def semantic_compress_text(full_text, compression_rate=0.7, num_topics=5):
 
 
 async def predict(text, word_reduction_factor):
-    if len(text.split()) > 700:
-        return "Text is too long for this demo. Please provide a text with less than 700 words."
+    if len(text.split()) > 5000:
+        return "Text is too long for this demo. Please provide a text with less than 5000 words."
+
+    if word_reduction_factor is None:
+        word_reduction_factor = 0.5
     
-    compressed = semantic_compress_text(text, word_reduction_factor = 1 - word_reduction_factor)
+    compressed = semantic_compress_text(text, compression_rate= 1 - word_reduction_factor)
     perc_reduction = round(100 - (count_tokens_tiktoken(compressed) / count_tokens_tiktoken(text)) * 100, 2)
 
     return f"{compressed}\n\nToken Reduction: {perc_reduction}%"