Update app.py

app.py

@@ -69,7 +69,7 @@ def load_models():
     # Load the text-classification pipeline (acting as our scoring model).
     sentiment_pipe = pipeline("text-classification", model="mixedbread-ai/mxbai-rerank-base-v1")
     # Load the Gemma text generation pipeline.
-    gemma_pipe = pipeline("text-generation", model="google/gemma-3-1b-it", use_auth_token=hf_token)
+    gemma_pipe = pipeline("text-generation", model="google/gemma-3-1b-it")
     return sentiment_pipe, gemma_pipe
 
 sentiment_pipe, gemma_pipe = load_models()
@@ -93,7 +93,7 @@ if uploaded_file is not None:
 else:
     # If no CSV uploaded, split the query text into sentences as candidate documents.
     if query_input.strip():
-        candidate_docs = re.split(r'(?<=[.!?]) +', query_input.strip())
+        candidate_docs = re.split(r'(?<=[.!?])\s+', query_input.strip())
 
 if st.button("Generate Report"):
     if not query_input.strip():