Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import streamlit as st
 from huggingface_hub import HfApi
 import pandas as pd
@@ -6,7 +5,7 @@ import pandas as pd
 # Default list of Hugging Face usernames
 default_users = {
     "users": [
-        "rogerxavier", "jonatasgrosman", "kenshinn", "Csplk", "DavidVivancos",
+        "awacke1", "rogerxavier", "jonatasgrosman", "kenshinn", "Csplk", "DavidVivancos",
         "cdminix", "Jaward", "TuringsSolutions", "Severian", "Wauplin",
         "phosseini", "Malikeh1375", "gokaygokay", "MoritzLaurer", "mrm8488",
         "TheBloke", "lhoestq", "xw-eric", "Paul", "Muennighoff",
@@ -15,24 +14,25 @@ default_users = {
     ]
 }
 
-def get_twitter_link(username):
-    api = HfApi()
+api = HfApi()
+
+def get_user_content(username):
     try:
-        # Fetch the models associated with the user
+        # Fetch models, datasets, and spaces associated with the user
         models = api.list_models(author=username)
-        if models:
-            for model in models:
-                # Try to get the Twitter handle from the first model found
-                twitter = model.cardData.get('social_media', {}).get('twitter')
-                if twitter:
-                    return f"https://twitter.com/{twitter}"
-        else:
-            st.warning(f"No models found for {username}")
+        datasets = api.list_datasets(author=username)
+        spaces = api.list_spaces(author=username)
+        
+        return {
+            "models": models,
+            "datasets": datasets,
+            "spaces": spaces
+        }
     except Exception as e:
-        st.error(f"Error fetching info for {username}: {str(e)}")
-    return None
+        st.error(f"Error fetching content for {username}: {str(e)}")
+        return None
 
-st.title("Hugging Face to Twitter Link Generator")
+st.title("Hugging Face User Content Display")
 
 # Convert the default users list to a string
 default_users_str = "\n".join(default_users["users"])
@@ -40,37 +40,54 @@ default_users_str = "\n".join(default_users["users"])
 # Text area with default list of usernames
 usernames = st.text_area("Enter Hugging Face usernames (one per line):", value=default_users_str, height=300)
 
-if st.button("Generate Twitter Links"):
+if st.button("Show User Content"):
     if usernames:
         username_list = [username.strip() for username in usernames.split('\n') if username.strip()]
         results = []
 
         progress_bar = st.progress(0)
         for i, username in enumerate(username_list):
-            twitter_link = get_twitter_link(username)
-            results.append({"Hugging Face": username, "Twitter Link": twitter_link})
-            progress_bar.progress((i + 1) / len(username_list))
+            content = get_user_content(username)
+            if content:
+                profile_link = f"https://huggingface.co/{username}"
+                profile_emoji = "🔗"
+                
+                models = [f"[{model.modelId}](https://huggingface.co/{model.modelId})" for model in content['models']]
+                datasets = [f"[{dataset.id}](https://huggingface.co/datasets/{dataset.id})" for dataset in content['datasets']]
+                spaces = [f"[{space.id}](https://huggingface.co/spaces/{space.id})" for space in content['spaces']]
 
-        df = pd.DataFrame(results)
-        st.dataframe(df)
+                results.append({
+                    "Hugging Face": username,
+                    "Profile Link": f"[{profile_emoji} Profile]({profile_link})",
+                    "Models": models,
+                    "Datasets": datasets,
+                    "Spaces": spaces
+                })
+            else:
+                results.append({"Hugging Face": username, "Error": "User content not found"})
+            progress_bar.progress((i + 1) / len(username_list))
 
-        # Generate markdown with hyperlinks
-        markdown_links = ""
-        for _, row in df.iterrows():
-            if row['Twitter Link']:
-                markdown_links += f"- [{row['Hugging Face']}]({row['Twitter Link']})\n"
+        st.markdown("### User Content Overview")
+        for result in results:
+            if "Error" not in result:
+                st.markdown(f"**{result['Hugging Face']}** {result['Profile Link']}")
+                st.markdown("**Models:**")
+                st.markdown("\n".join(result["Models"]) if result["Models"] else "No models found")
+                st.markdown("**Datasets:**")
+                st.markdown("\n".join(result["Datasets"]) if result["Datasets"] else "No datasets found")
+                st.markdown("**Spaces:**")
+                st.markdown("\n".join(result["Spaces"]) if result["Spaces"] else "No spaces found")
+                st.markdown("---")
             else:
-                markdown_links += f"- {row['Hugging Face']} (No Twitter link found)\n"
+                st.warning(f"{result['Hugging Face']}: {result['Error']}")
 
-        st.markdown("### Twitter Profile Links")
-        st.markdown(markdown_links)
     else:
         st.warning("Please enter at least one username.")
 
 st.sidebar.markdown("""
 ## How to use:
 1. The text area is pre-filled with a list of Hugging Face usernames. You can edit this list or add more usernames.
-2. Click 'Generate Twitter Links'.
-3. View the results in the table and as clickable links.
-4. The progress bar shows the status of link generation.
+2. Click 'Show User Content'.
+3. View the user's models, datasets, and spaces along with a link to their Hugging Face profile.
+4. The progress bar shows the status of content retrieval.
 """)