| | import streamlit as st |
| | from huggingface_hub import HfApi |
| | import asyncio |
| | import os |
| | import plotly.express as px |
| |
|
| | |
| | api = HfApi() |
| |
|
| | |
| | HTML_DIR = "generated_html_pages" |
| | if not os.path.exists(HTML_DIR): |
| | os.makedirs(HTML_DIR) |
| |
|
| | |
| | default_users = { |
| | "users": [ |
| | "awacke1", "rogerxavier", "jonatasgrosman", "kenshinn", "Csplk", "DavidVivancos", |
| | "cdminix", "Jaward", "TuringsSolutions", "Severian", "Wauplin", |
| | "phosseini", "Malikeh1375", "gokaygokay", "MoritzLaurer", "mrm8488", |
| | "TheBloke", "lhoestq", "xw-eric", "Paul", "Muennighoff", |
| | "ccdv", "haonan-li", "chansung", "lukaemon", "hails", |
| | "pharmapsychotic", "KingNish", "merve", "ameerazam08", "ashleykleynhans" |
| | ] |
| | } |
| |
|
| | |
| | async def fetch_user_content(username): |
| | try: |
| | |
| | models = list(await asyncio.to_thread(api.list_models, author=username)) |
| | datasets = list(await asyncio.to_thread(api.list_datasets, author=username)) |
| | |
| | return { |
| | "username": username, |
| | "models": models, |
| | "datasets": datasets |
| | } |
| | except Exception as e: |
| | |
| | return {"username": username, "error": str(e)} |
| |
|
| | |
| | async def fetch_all_users(usernames): |
| | tasks = [fetch_user_content(username) for username in usernames] |
| | return await asyncio.gather(*tasks) |
| |
|
| | |
| | def generate_html_page(username, models, datasets): |
| | html_content = f""" |
| | <html> |
| | <head> |
| | <title>{username}'s Hugging Face Content</title> |
| | </head> |
| | <body> |
| | <h1>{username}'s Hugging Face Profile</h1> |
| | <p><a href="https://huggingface.co/{username}">π Profile Link</a></p> |
| | <h2>π§ Models</h2> |
| | <ul> |
| | """ |
| | for model in models: |
| | model_name = model.modelId.split("/")[-1] |
| | html_content += f'<li><a href="https://huggingface.co/{model.modelId}">{model_name}</a></li>' |
| | |
| | html_content += """ |
| | </ul> |
| | <h2>π Datasets</h2> |
| | <ul> |
| | """ |
| | for dataset in datasets: |
| | dataset_name = dataset.id.split("/")[-1] |
| | html_content += f'<li><a href="https://huggingface.co/datasets/{dataset.id}">{dataset_name}</a></li>' |
| | |
| | html_content += """ |
| | </ul> |
| | </body> |
| | </html> |
| | """ |
| |
|
| | |
| | html_file_path = os.path.join(HTML_DIR, f"{username}.html") |
| | with open(html_file_path, "w") as html_file: |
| | html_file.write(html_content) |
| |
|
| | return html_file_path |
| |
|
| | |
| | @st.cache_data(show_spinner=False) |
| | def get_cached_html_file(username): |
| | return generate_html_page(username, *get_user_content(username)) |
| |
|
| | |
| | def get_user_content(username): |
| | user_data = asyncio.run(fetch_user_content(username)) |
| | if "error" in user_data: |
| | return None, user_data["error"] |
| | return user_data["models"], user_data["datasets"] |
| |
|
| | |
| | st.title("Hugging Face User Content Display - Let's Automate Some Fun! π") |
| |
|
| | |
| | default_users_str = "\n".join(default_users["users"]) |
| |
|
| | |
| | usernames = st.text_area("Enter Hugging Face usernames (one per line):", value=default_users_str, height=300) |
| |
|
| | |
| | if st.button("Show User Content"): |
| | if usernames: |
| | username_list = [username.strip() for username in usernames.split('\n') if username.strip()] |
| |
|
| | |
| | stats = {"username": [], "models_count": [], "datasets_count": []} |
| |
|
| | st.markdown("### User Content Overview") |
| | for username in username_list: |
| | with st.container(): |
| | |
| | st.markdown(f"**{username}** [π Profile](https://huggingface.co/{username})") |
| |
|
| | |
| | models, datasets = get_user_content(username) |
| | if models is None: |
| | st.warning(f"{username}: {datasets} - Looks like the AI needs a coffee break β") |
| | else: |
| | html_file_path = get_cached_html_file(username) |
| | st.markdown(f"[π Download {username}'s HTML Page]({html_file_path})") |
| |
|
| | |
| | stats["username"].append(username) |
| | stats["models_count"].append(len(models)) |
| | stats["datasets_count"].append(len(datasets)) |
| |
|
| | |
| | with st.expander(f"π§ Models ({len(models)})", expanded=False): |
| | if models: |
| | for model in 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? π΅οΈββοΈ") |
| |
|
| | |
| | with st.expander(f"π Datasets ({len(datasets)})", expanded=False): |
| | if datasets: |
| | for dataset in 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 theyβre still baking in the oven? πͺ") |
| |
|
| | st.markdown("---") |
| |
|
| | |
| | if stats["username"]: |
| | st.markdown("### User Content Statistics") |
| |
|
| | |
| | fig_models = px.bar(x=stats["username"], y=stats["models_count"], labels={'x':'Username', 'y':'Number of Models'}, title="Number of Models per User") |
| | st.plotly_chart(fig_models) |
| |
|
| | |
| | fig_datasets = px.bar(x=stats["username"], y=stats["datasets_count"], labels={'x':'Username', 'y':'Number of Datasets'}, title="Number of Datasets per User") |
| | st.plotly_chart(fig_datasets) |
| |
|
| | else: |
| | st.warning("Please enter at least one username. Don't be shy! π
") |
| |
|
| | |
| | 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 'Show User Content'. |
| | 3. View the user's models and datasets along with a link to their Hugging Face profile. |
| | 4. Download an HTML page for each user to use the absolute links offline! |
| | 5. Check out the statistics visualizations at the end! |
| | """) |
| |
|