diff --git a/App_Function_Libraries/Gradio_UI/RAG_QA_Chat_tab.py b/App_Function_Libraries/Gradio_UI/RAG_QA_Chat_tab.py
index 8da14328..6fe74be1 100644
--- a/App_Function_Libraries/Gradio_UI/RAG_QA_Chat_tab.py
+++ b/App_Function_Libraries/Gradio_UI/RAG_QA_Chat_tab.py
@@ -73,6 +73,7 @@ def update_conversation_list():
                 top_k_input = gr.Number(value=10, label="Maximum amount of results to use (Default: 10)", minimum=1, maximum=50, step=1, precision=0, interactive=True)
                 keywords_input = gr.Textbox(label="Keywords (comma-separated) to filter results by)", visible=True)
                 use_query_rewriting = gr.Checkbox(label="Use Query Rewriting", value=True)
+                use_re_ranking = gr.Checkbox(label="Use Re-ranking", value=True)
                 # with gr.Row():
                 #     page_number = gr.Number(value=1, label="Page", precision=0)
                 #     page_size = gr.Number(value=20, label="Items per page", precision=0)
@@ -385,7 +386,7 @@ def rephrase_question(history, latest_question, api_choice):
 
         def rag_qa_chat_wrapper(message, history, context_source, existing_file, search_results, file_upload,
                                 convert_to_text, keywords, api_choice, use_query_rewriting, state_value,
-                                keywords_input, top_k_input):
+                                keywords_input, top_k_input, use_re_ranking):
             try:
                 logging.info(f"Starting rag_qa_chat_wrapper with message: {message}")
                 logging.info(f"Context source: {context_source}")
@@ -421,8 +422,8 @@ def rag_qa_chat_wrapper(message, history, context_source, existing_file, search_
 
                 if context_source == "All Files in the Database":
                     # Use the enhanced_rag_pipeline to search the entire database
-                    context = enhanced_rag_pipeline(rephrased_question, api_choice, keywords=keywords_input,
-                                                    top_k=int(top_k_input))
+                    context = enhanced_rag_pipeline(rephrased_question, api_choice, keywords_input, top_k_input,
+                                                    use_re_ranking)
                     logging.info(f"Using enhanced_rag_pipeline for database search")
                 elif context_source == "Search Database":
                     context = f"media_id:{search_results.split('(ID: ')[1][:-1]}"
diff --git a/App_Function_Libraries/RAG/RAG_Library_2.py b/App_Function_Libraries/RAG/RAG_Library_2.py
index 956523ea..9e3fad3b 100644
--- a/App_Function_Libraries/RAG/RAG_Library_2.py
+++ b/App_Function_Libraries/RAG/RAG_Library_2.py
@@ -336,14 +336,15 @@ def generate_answer(api_choice: str, context: str, query: str) -> str:
         logging.error(f"Error in generate_answer: {str(e)}")
         return "An error occurred while generating the answer."
 
-def perform_vector_search(query: str, relevant_media_ids: List[str] = None) -> List[Dict[str, Any]]:
+def perform_vector_search(query: str, relevant_media_ids: List[str] = None, top_k=10) -> List[Dict[str, Any]]:
     log_counter("perform_vector_search_attempt")
     start_time = time.time()
     all_collections = chroma_client.list_collections()
     vector_results = []
     try:
         for collection in all_collections:
-            collection_results = vector_search(collection.name, query, k=5)
+            k = top_k
+            collection_results = vector_search(collection.name, query, k)
             filtered_results = [
                 result for result in collection_results
                 if relevant_media_ids is None or result['metadata'].get('media_id') in relevant_media_ids
@@ -358,11 +359,11 @@ def perform_vector_search(query: str, relevant_media_ids: List[str] = None) -> L
         logging.error(f"Error in perform_vector_search: {str(e)}")
         raise
 
-def perform_full_text_search(query: str, relevant_media_ids: List[str] = None) -> List[Dict[str, Any]]:
+def perform_full_text_search(query: str, relevant_media_ids: List[str] = None, fts_top_k=None) -> List[Dict[str, Any]]:
     log_counter("perform_full_text_search_attempt")
     start_time = time.time()
     try:
-        fts_results = search_db(query, ["content"], "", page=1, results_per_page=5)
+        fts_results = search_db(query, ["content"], "", page=1, results_per_page=fts_top_k or 10)
         filtered_fts_results = [
             {
                 "content": result['content'],
@@ -381,7 +382,7 @@ def perform_full_text_search(query: str, relevant_media_ids: List[str] = None) -
         raise
 
 
-def fetch_relevant_media_ids(keywords: List[str]) -> List[int]:
+def fetch_relevant_media_ids(keywords: List[str], top_k=10) -> List[int]:
     log_counter("fetch_relevant_media_ids_attempt", labels={"keyword_count": len(keywords)})
     start_time = time.time()
     relevant_ids = set()