Update app.py

app.py

@@ -2,19 +2,20 @@ import gradio as gr
 import pandas as pd
 import requests
 
-CHUNK_SIZE = 1000
+# Endpoints
 DATA_URL = "https://erkhov.com/huggingspace_data"
 TIME_URL = "https://erkhov.com/huggingspace_time"
-
-def fetch_time():
-    response = requests.get(TIME_URL)
-    return response.text.strip()  # assume the endpoint returns a raw timestamp or numeric value as string
+CHUNK_SIZE = 1000
 
 def fetch_data():
     response = requests.get(DATA_URL)
     data = response.json()
     return data
 
+def fetch_time():
+    response = requests.get(TIME_URL)
+    return response.text.strip()
+
 def clickable(x, which_one):
     if x in ["Not Found", "Unknown"]:
         return "Not Found"
@@ -110,33 +111,8 @@ def filter_authors(authors_df, author_search_query, min_author_downloads, min_au
     filtered_authors = apply_author_filters(authors_df, author_search_query, min_author_downloads, min_author_likes)
     return filtered_authors
 
-def refresh_data(last_time, models_df_state, authors_df_state, stats_markdown, model_table, author_table):
-    # Check if time changed
-    current_time = fetch_time()
-    if current_time != last_time and current_time != 0:
-        # Time changed, re-fetch data
-        data = fetch_data()
-        models_df, authors_df = create_dataframes(data)
-        
-        total_models_count = data["total_models"]
-        total_downloads = data["total_downloads"]
-        total_likes = models_df["Likes"].sum() if "Likes" in models_df.columns else 0
-        
-        # Update stats markdown
-        new_stats_markdown = f"""
-        # GGUF Models and Authors Leaderboard
-        **Total Models:** {total_models_count} | **Total Downloads (30d):** {total_downloads} | **Total Likes:** {total_likes}  
-        **Last Updated:** {current_time}
-        """
-        
-        # Update states
-        return current_time, models_df, authors_df, gr.update(value=new_stats_markdown), gr.update(value=models_df.iloc[:CHUNK_SIZE]), gr.update(value=authors_df)
-    else:
-        # No change
-        return last_time, models_df_state, authors_df_state, stats_markdown, model_table, author_table
-
-# Initial fetch
-initial_time = fetch_time()
+# Fetch data once at start
+last_updated = fetch_time()
 data = fetch_data()
 all_models_df, authors_df = create_dataframes(data)
 
@@ -144,24 +120,22 @@ total_models_count = data["total_models"]
 total_downloads = data["total_downloads"]
 total_likes = all_models_df["Likes"].sum() if "Likes" in all_models_df.columns else 0
 
-initial_stats_markdown = f"""
-# GGUF Models and Authors Leaderboard
-**Total Models:** {total_models_count} | **Total Downloads (30d):** {total_downloads} | **Total Likes:** {total_likes}  
-**Last Updated:** {initial_time}
-"""
-
 with gr.Blocks() as demo:
     gr.Markdown(f"""
     # 🚀GGUF Tracker🚀
     Welcome to 🚀**GGUF Tracker**🚀, a live-updating leaderboard for all things GGUF on 🚀Hugging Face.  
-    Stats refresh every hour on the backend, but this interface checks every 5 minutes for updates.
+    Data is fetched once upon startup. To get new data, please restart the space.
 
     By the way, I’m 🚀Richard Erkhov, and you can check out more of what I’m working on at my [🌟**github**](https://github.com/RichardErkhov), 
     [🌟**huggingface**](https://huggingface.co/RichardErkhov) or [🌟**erkhov.com**](https://erkhov.com). Go take a look—I think you’ll like what you find.
     """)
 
-    stats_markdown = gr.Markdown(initial_stats_markdown)
-    
+    gr.Markdown(f"""
+    # GGUF Models and Authors Leaderboard
+    **Total Models:** {total_models_count} | **Total Downloads (30d):** {total_downloads} | **Total Likes:** {total_likes}  
+    **Last Updated:** {last_updated}
+    """)
+
     with gr.Tabs():
         with gr.TabItem("Models"):
             with gr.Row():
@@ -179,7 +153,7 @@ with gr.Blocks() as demo:
             )
             load_more_button = gr.Button("Load More Models")
             
-            # States for models
+            # States
             start_idx = gr.State(value=CHUNK_SIZE)
             filtered_df_state = gr.State(value=all_models_df)
 
@@ -211,26 +185,4 @@ with gr.Blocks() as demo:
                 outputs=author_table
             )
 
-    # States for refresh
-    last_hf_time_state = gr.State(value=initial_time)
-    models_df_state = gr.State(value=all_models_df)
-    authors_df_state = gr.State(value=authors_df)
-
-    # Timer to check every 5 minutes = 300 seconds
-    timer = gr.Timer(interval=300, fn=refresh_data, inputs=[
-        last_hf_time_state,
-        models_df_state,
-        authors_df_state,
-        stats_markdown,
-        model_table,
-        author_table
-    ], outputs=[
-        last_hf_time_state,
-        models_df_state,
-        authors_df_state,
-        stats_markdown,
-        model_table,
-        author_table
-    ])
-
     demo.launch()