Update app.py

app.py

@@ -46,7 +46,7 @@ if 'whisper_model' not in st.session_state:
 markdown_text = """  
 # 👋🏻Welcome to [Team](https://huggingface.co/TeamTonic) [Tonic](https://huggingface.co/Tonic) 's Patentable Claims Extractor.   
 Here you can input audio and text and extract patentable claims from these conversational inputs using [LegalBert](nlpaueb/legal-bert-base-uncased).   
-- Save time and effort when ideating for your future business.  
+- Save time and effort when ideating for your future business.  Expect latency upwards of 2.5 hours !
 """  
   
 # Render the Markdown content  
@@ -181,7 +181,7 @@ else:
 # Process each chunk with the BERT-based model  
 summaries = []  
 for chunk in chunks:  
-    summary = bert_legal_model(chunk, min_length=8, ratio=0.05)  
+    summary = bert_legal_model(chunk, min_length=20, ratio=0.9)  
     summaries.append(summary)  
   
 # Now you have a list of summaries for each chunk