| 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! |
| """) |
|
|