New approach for warning to load dataset

app.py

@@ -85,77 +85,80 @@ def main():
     st.text(f'The smaller the dataset the faster the search will work.')
     st.text('Please click Load Dataset to finalize selection for search')
     
-    # Load dataset with limit only if not already loaded
-    if st.button("Load Dataset", key="load_dataset"):
-        try:
-            loading_dataset_text = st.empty()
-            loading_dataset_text.text("Loading Dataset...")
-            loading_dataset_bar = st.progress(0)
-            
-            # Simulate dataset loading progress
-            for i in range(0, 100, 25):
-                time.sleep(0.2)  # Simulate work being done
-                loading_dataset_bar.progress(i + 25)
+    
+    #Loading Dataset
+    loading_dataset_text = st.empty()
+    loading_dataset_text.text("Loading Dataset...")
+    loading_dataset_bar = st.progress(0)
+    
+    # Simulate dataset loading progress
+    for i in range(0, 100, 25):
+        time.sleep(0.2)  # Simulate work being done
+        loading_dataset_bar.progress(i + 25)
 
-            # Load dataset
-            df, total_rows = load_dataset_with_limit(dataset_name, st.session_state.dataset_number, st.session_state.search_in_small_objects, limit=dataset_limit)
-            
-            # Store loaded dataset in session state
-            st.session_state.df = df
-            loading_dataset_bar.progress(100)
-            loading_dataset_text.text("Dataset loaded successfully!")
-            st.success(f"Dataset loaded successfully with {len(df)} rows.")
+    # Load dataset
+    df, total_rows = load_dataset_with_limit(dataset_name, st.session_state.dataset_number, st.session_state.search_in_small_objects, limit=dataset_limit)
+    
+    # Store loaded dataset in session state
+    st.session_state.df = df
+    loading_dataset_bar.progress(100)
+    loading_dataset_text.text("Dataset loaded successfully!")
+    st.success(f"Dataset loaded successfully with {len(df)} rows.")
             
-            # After dataset is loaded, show search options
-            query = st.text_input("Enter your search query", key="search_query")
-            st.text(f"Example Queries for your Dataset: {example_queries[dataset_name]}")
-            # Number of results to display
-            limit = st.number_input("Number of results to display", min_value=1, max_value=10, value=10, key="result_limit")
+    # After dataset is loaded, show search options
+    query = st.text_input("Enter your search query")
+    st.text(f"Example Queries for your Dataset: {example_queries[dataset_name]}")
+    # Number of results to display
+    limit = st.number_input("Number of results to display", min_value=1, max_value=100, value=10)
             
-            # Search button
-            if st.button("Search", key="search_button"):
-                # Validate input
-                if not query:
-                    st.warning("Please enter a search query.")
+    # Search button
+    if st.button("Search"):
+        # Validate input
+        if not query:
+            st.warning("Please enter a search query.")
+        else:
+            try:
+                # Progress bar for search
+                search_loading_text = st.empty()
+                search_loading_text.text("Searching...")
+                search_progress_bar = st.progress(0)
+
+                # Perform search on the loaded dataset from session state
+                df = st.session_state.df
+                if st.session_state.search_in_small_objects:
+                    results = search(query, df, limit)
+                    top_k_paths = get_file_paths(df, results)
+                    top_k_cordinates = get_cordinates(df, results)
+                    search_type = 'Splits'
                 else:
-                    try:
-                        # Progress bar for search
-                        search_loading_text = st.empty()
-                        search_loading_text.text("Searching...")
-                        search_progress_bar = st.progress(0)
-
-                        # Perform search on the loaded dataset from session state
-                        df = st.session_state.df
-                        if st.session_state.search_in_small_objects:
-                            results = search(query, df, limit)
-                            top_k_paths = get_file_paths(df, results)
-                            top_k_cordinates = get_cordinates(df, results)
-                            search_type = 'Splits'
-                        else:
-                            # Normal Search
-                            results = search(query, df, limit)
-                            top_k_paths = get_file_paths(df, results)
-                            search_type = 'Main'
-
-                        # Complete the search progress
-                        search_progress_bar.progress(100)
-                        search_loading_text.text(f"Search completed among {dataset_limit} rows for {dataset_name} in {search_type} {st.session_state.dataset_number}")
-
-                        # Load Images with Bounding Boxes if applicable
-                        if st.session_state.search_in_small_objects and top_k_paths and top_k_cordinates:
-                            get_images_with_bounding_boxes_from_s3(bucket_name, top_k_paths, top_k_cordinates, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
-                        elif not st.session_state.search_in_small_objects and top_k_paths:
-                            st.write(f"Displaying top {len(top_k_paths)} results for query '{query}':")
-                            get_images_from_s3_to_display(bucket_name, top_k_paths, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
+                    # Normal Search
+                    results = search(query, df, limit)
+                    top_k_paths = get_file_paths(df, results)
+                    search_type = 'Main'
+
+                    # Complete the search progress
+                    search_progress_bar.progress(100)
+                    search_loading_text.text(f"Search completed among {dataset_limit} rows for {dataset_name} in {search_type} {st.session_state.dataset_number}")
+
+                    # Load Images with Bounding Boxes if applicable
+                    if st.session_state.search_in_small_objects and top_k_paths and top_k_cordinates:
+                        get_images_with_bounding_boxes_from_s3(bucket_name, top_k_paths, top_k_cordinates, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
+                    elif not st.session_state.search_in_small_objects and top_k_paths:
+                        st.write(f"Displaying top {len(top_k_paths)} results for query '{query}':")
+                        get_images_from_s3_to_display(bucket_name, top_k_paths, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
                             
-                        else:
-                            st.write("No results found.")
+                    else:
+                        st.write("No results found.")
 
-                    except Exception as e:
-                        st.error(f"Search failed: {e}")
+                except Exception as e:
+                    st.error(f"Search failed: {e}")
 
         except Exception as e:
-            st.error(f"Failed to load dataset: {e}")
+            if 'None' in e:
+                st.warning("Please Click Load Dataset")
+            else:
+                st.error(f"Failed to load dataset: {e}")
+            
 
 if __name__ == "__main__":
     main()