Update app.py

app.py

@@ -44,11 +44,6 @@ async def fetch_all_users(usernames):
     tasks = [fetch_user_content(username) for username in usernames]
     return await asyncio.gather(*tasks)
 
-# Cache the HTML generation process using Streamlit's caching decorator
-@st.cache_data(show_spinner=False)
-def get_cached_html_page(_username, _models, _datasets):
-    return generate_html_page(_username, _models, _datasets)
-
 # Generate HTML content for a user and save it to a file - because who doesn't love a good download link? 💾
 def generate_html_page(username, models, datasets):
     html_content = f"""
@@ -88,6 +83,14 @@ def generate_html_page(username, models, datasets):
 
     return html_file_path
 
+# Cache the HTML generation process using Streamlit's caching decorator
+@st.cache_data(show_spinner=False)
+def get_cached_html_page(username):
+    user_data = asyncio.run(fetch_user_content(username))
+    if "error" in user_data:
+        return None, user_data["error"]
+    return generate_html_page(username, user_data["models"], user_data["datasets"]), None
+
 # Streamlit app setup - the nerve center of our operation! 🎛️
 st.title("Hugging Face User Content Display - Let's Automate Some Fun! 🎉")
 
@@ -102,47 +105,21 @@ if st.button("Show User Content"):
     if usernames:
         username_list = [username.strip() for username in usernames.split('\n') if username.strip()]
 
-        # Run the asyncio loop to fetch all users - time to unleash the hounds! 🐕
-        results = asyncio.run(fetch_all_users(username_list))
-
         st.markdown("### User Content Overview")
-        for result in results:
-            username = result["username"]
-            if "error" not in result:
-                with st.container():
-                    # Profile link - because everyone deserves their 15 seconds of fame! 🎤
-                    st.markdown(f"**{username}** [🔗 Profile](https://huggingface.co/{username})")
-
-                    # Create columns for models and datasets - divide and conquer! 🏛️
-                    col1, col2 = st.columns(2)
-
-                    # Models section with emoji - 🧠 because AI models are brainy! 🧠
-                    with col1:
-                        st.markdown("**Models:** 🧠")
-                        if result['models']:
-                            for model in result['models']:
-                                model_name = model.modelId.split("/")[-1]
-                                st.markdown(f"- [{model_name}](https://huggingface.co/{model.modelId})")
-                        else:
-                            st.markdown("No models found. Did you check under the rug? 🕵️‍♂️")
-
-                    # Datasets section with emoji - 📚 because data is the foundation of AI! 📚
-                    with col2:
-                        st.markdown("**Datasets:** 📚")
-                        if result['datasets']:
-                            for dataset in result['datasets']:
-                                dataset_name = dataset.id.split("/")[-1]
-                                st.markdown(f"- [{dataset_name}](https://huggingface.co/datasets/{dataset.id})")
-                        else:
-                            st.markdown("No datasets found. Maybe they’re still baking in the oven? 🍪")
-
-                    # Generate HTML page and provide download link - because who wouldn't want a custom webpage? 🌐
-                    html_file_path = get_cached_html_page(username, result['models'], result['datasets'])
+        for username in username_list:
+            with st.container():
+                # Profile link - because everyone deserves their 15 seconds of fame! 🎤
+                st.markdown(f"**{username}** [🔗 Profile](https://huggingface.co/{username})")
+
+                # Generate HTML page and provide download link - because who wouldn't want a custom webpage? 🌐
+                html_file_path, error = get_cached_html_page(username)
+
+                if error:
+                    st.warning(f"{username}: {error} - Looks like the AI needs a coffee break ☕")
+                else:
                     st.markdown(f"[📄 Download {username}'s HTML Page]({html_file_path})")
-                    
-                    st.markdown("---")
-            else:
-                st.warning(f"{username}: {result['error']} - Looks like the AI needs a coffee break ☕")
+
+                st.markdown("---")
 
     else:
         st.warning("Please enter at least one username. Don't be shy! 😅")