change ksize in RAG

RAG/rag_DocumentSearcher.py

@@ -312,15 +312,15 @@ def query_(awsauth,inputs, session_id,search_types):
             is_table_in_result = True
             #table_res = invoke_models.read_from_table(hit["_source"]["table"],question) # use for complex analytical dataframe questions (uses panda at the background))
             df.append({'name':hit["_source"]["table"],'text':hit["_source"]["processed_element"]})
-            context_tables.append(str(id) + " : Reference from a table :" + hit["_source"]["processed_element"])#table_res+"\n\n"+
+            context_tables.append(str(id+1) + " : Reference from a table :" + hit["_source"]["processed_element"])#table_res+"\n\n"+
             
         else:
             if(hit["_source"]["image"]!="None"):
                 with open(parent_dirname+'/figures/'+st.session_state.input_index+"/"+hit["_source"]["raw_element_type"].split("_")[1].replace(".jpg","")+"-resized.jpg", "rb") as read_img:
                     input_encoded = base64.b64encode(read_img.read()).decode("utf8")
-                context.append(str(id) + " : Reference from a image :" + invoke_models.generate_image_captions_llm(input_encoded,question))
+                context.append(str(id+1) + " : Reference from a image :" + invoke_models.generate_image_captions_llm(input_encoded,question))
             else:
-                context.append(str(id) + " : Reference from a text chunk :" + hit["_source"]["processed_element"])
+                context.append(str(id+1) + " : Reference from a text chunk :" + hit["_source"]["processed_element"])
             
         if(hit["_source"]["image"]!="None"):
             images_2.append({'file':hit["_source"]["image"],'caption':hit["_source"]["processed_element"]})

pages/Multimodal_Conversational_Search.py

@@ -436,7 +436,7 @@ with st.sidebar:
     #st.button("Show similarity map",key="input_sim_map",on_click=handle_input,args=('colpali_show_similarity_map',True))
        
     with st.expander("Sample questions for Colpali retriever:"):
-        st.write("1. Proportion of female new hires 2021-2023? \n\n 2. First-half 2021 return on unlisted real estate investments? \n\n 3. Trend of the fund's expected absolute volatility between January 2014 and January 2016? \n\n 4. Fund return percentage in 2017? \n\n 5. Annualized gross return of the fund from 1997 to 2008?")
+        st.write("1. Proportion of female new hires 2021-2023? \n\n 2. hula hoop kid \n\n 3. First-half 2021 return on unlisted real estate investments? \n\n 4. Trend of the fund's expected absolute volatility between January 2014 and January 2016? \n\n 5. Fund return percentage in 2017? \n\n 6. Annualized gross return of the fund from 1997 to 2008?")
     
         
     

semantic_search/all_search_execute.py

@@ -151,7 +151,7 @@ def handler(input_,session_id):
     ######### Create the queries for hybrid search #########
     
     
-    path = "demostore-search-index/_search"
+    path = "demostore-search-index-reindex/_search"
     
     url = host + path
     
@@ -412,7 +412,7 @@ def handler(input_,session_id):
             del hybrid_payload["query"]["hybrid"]
             hybrid_payload["query"] = single_query
             if(st.session_state.re_ranker == 'true' and st.session_state.input_reranker == 'Cohere Rerank'):
-                path = "demostore-search-index/_search?search_pipeline=rerank_pipeline" 
+                path = "demostore-search-index-reindex/_search?search_pipeline=rerank_pipeline" 
                 url = host + path
                 hybrid_payload["ext"] = {"rerank": {
                                             "query_context": {