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advanced_rag.py

@@ -174,7 +174,7 @@ class ElevatedRagChain:
                         time.sleep(backoff)
                         backoff *= 2  # exponential backoff
                 return response
-            from langchain.llms.base import LLM
+            
             class RemoteLLM(LLM):
                 @property
                 def _llm_type(self) -> str:
@@ -241,7 +241,7 @@ class ElevatedRagChain:
                 device=-1,
                 **extra_kwargs
             )
-            from langchain.llms.base import LLM
+
             class LocalLLM(LLM):
                 @property
                 def _llm_type(self) -> str:
@@ -571,13 +571,15 @@ The response displays the model used, word count, and current context (with conv
     load_button.click(
         load_pdfs_updated, 
         inputs=[pdf_input, model_dropdown, prompt_input, bm25_weight_slider, temperature_slider, top_p_slider],
-        outputs=[response_output, context_output, model_output]
+        outputs=[response_output, context_output, model_output],
+        long_running=True  # Added long_running flag
     )
     
     submit_button.click(
         submit_query_updated, 
         inputs=[query_input],
-        outputs=[response_output, context_output, input_tokens, output_tokens]
+        outputs=[response_output, context_output, input_tokens, output_tokens],
+        long_running=True  # Added long_running flag
     )
     
     reset_button.click(