change ksize in RAG

RAG/rag_DocumentSearcher.py

@@ -307,20 +307,20 @@ def query_(awsauth,inputs, session_id,search_types):
     for hit in hits[0:5]:
         
         
-        # if(hit["_source"]["raw_element_type"] == 'table'):
-        #     #print("Need to analyse table")
-        #     is_table_in_result = True
-        #     table_res = invoke_models.read_from_table(hit["_source"]["table"],question)
-        #     df.append({'name':hit["_source"]["table"],'text':hit["_source"]["processed_element"]})
-        #     context_tables.append(table_res+"\n\n"+hit["_source"]["processed_element"])
+        if(hit["_source"]["raw_element_type"] == 'table'):
+            #print("Need to analyse table")
+            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(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(invoke_models.generate_image_captions_llm(input_encoded,question))
         else:
-            context.append(hit["_source"]["processed_element"])
+            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(invoke_models.generate_image_captions_llm(input_encoded,question))
+            else:
+                context.append(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

@@ -269,9 +269,10 @@ def render_answer(question,answer,index,res_img):
                             idx = idx+1
                 if(len(answer["table"] )>0):
                     #with st.expander("Table:"):
-                    df = pd.read_csv(answer["table"][0]['name'],skipinitialspace = True, on_bad_lines='skip',delimiter='`')
-                    df.fillna(method='pad', inplace=True)
-                    st.table(df)
+                    for table in answer["table"]:
+                        df = pd.read_csv(table['name'],skipinitialspace = True, on_bad_lines='skip',delimiter='`')
+                        df.fillna(method='pad', inplace=True)
+                        st.table(df)
                 #with st.expander("Raw sources:"):
                 st.write(answer["source"])
     with col_3: