app.py

import streamlit as st
import requests
import base64
import os
import asyncio
from huggingface_hub import HfApi, snapshot_download
import plotly.express as px
import zipfile
import tempfile
import shutil

# Initialize the Hugging Face API
api = HfApi()

# Directories for saving files
HTML_DIR = "generated_html_pages"
ZIP_DIR = "generated_zips"
SNAPSHOT_DIR = "snapshot_downloads"

for directory in [HTML_DIR, ZIP_DIR, SNAPSHOT_DIR]:
    if not os.path.exists(directory):
        os.makedirs(directory)

# Default list of Hugging Face usernames
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)}

def download_user_page(username):
    url = f"https://huggingface.co/{username}"
    try:
        response = requests.get(url)
        response.raise_for_status()
        html_content = response.text
        html_file_path = os.path.join(HTML_DIR, f"{username}.html")
        with open(html_file_path, "w", encoding='utf-8') as html_file:
            html_file.write(html_content)
        return html_file_path, None
    except Exception as e:
        return None, str(e)

@st.cache_resource
def create_zip_of_files(files, zip_name):
    zip_file_path = os.path.join(ZIP_DIR, zip_name)
    with zipfile.ZipFile(zip_file_path, 'w') as zipf:
        for file in files:
            zipf.write(file, arcname=os.path.basename(file))
    return zip_file_path

@st.cache_resource
def get_download_link(file_path, link_text):
    with open(file_path, 'rb') as f:
        data = f.read()
    b64 = base64.b64encode(data).decode()
    return f'<a href="data:application/zip;base64,{b64}" download="{os.path.basename(file_path)}">{link_text}</a>'

async def fetch_all_users(usernames):
    tasks = [fetch_user_content(username) for username in usernames]
    return await asyncio.gather(*tasks)

def get_all_html_files(usernames):
    html_files = []
    errors = {}
    for username in usernames:
        html_file, error = download_user_page(username)
        if html_file:
            html_files.append(html_file)
        else:
            errors[username] = error
    return html_files, errors

def perform_snapshot_download(repo_id, repo_type):
    try:
        temp_dir = tempfile.mkdtemp()
        snapshot_download(repo_id=repo_id, repo_type=repo_type, local_dir=temp_dir)
        zip_name = f"{repo_id.replace('/', '_')}_{repo_type}.zip"
        zip_path = os.path.join(SNAPSHOT_DIR, zip_name)
        shutil.make_archive(zip_path[:-4], 'zip', temp_dir)
        shutil.rmtree(temp_dir)
        return zip_path
    except Exception as e:
        return str(e)

st.title("Hugging Face User Page Downloader & Zipper 📄➕📦")

user_input = st.text_area(
    "Enter Hugging Face usernames (one per line):",
    value="\n".join(default_users["users"]),
    height=300
)

if st.button("Show User Content and Download Snapshots"):
    if user_input:
        username_list = [username.strip() for username in user_input.split('\n') if username.strip()]
        
        user_data_list = asyncio.run(fetch_all_users(username_list))
        
        stats = {"username": [], "models_count": [], "datasets_count": []}
        successful_html_files = []
        snapshot_downloads = []
        
        st.markdown("### User Content Overview")
        for user_data in user_data_list:
            username = user_data["username"]
            with st.container():
                st.markdown(f"**{username}** [🔗 Profile](https://huggingface.co/{username})")
                
                if "error" in user_data:
                    st.warning(f"{username}: {user_data['error']} - Something went wrong! ⚠️")
                else:
                    models = user_data["models"]
                    datasets = user_data["datasets"]
                    
                    html_file_path, download_error = download_user_page(username)
                    if html_file_path:
                        successful_html_files.append(html_file_path)
                        st.success(f"✅ Successfully downloaded {username}'s page.")
                    else:
                        st.error(f"❌ Failed to download {username}'s page: {download_error}")
                    
                    stats["username"].append(username)
                    stats["models_count"].append(len(models))
                    stats["datasets_count"].append(len(datasets))
                    
                    with st.expander(f"🧠 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})")
                                if st.button(f"Download Snapshot: {model_name}", key=f"model_{model.modelId}"):
                                    with st.spinner(f"Downloading snapshot for {model_name}..."):
                                        result = perform_snapshot_download(model.modelId, "model")
                                        if isinstance(result, str):
                                            st.error(f"Failed to download {model_name}: {result}")
                                        else:
                                            snapshot_downloads.append(result)
                                            st.success(f"Successfully downloaded snapshot for {model_name}")
                        else:
                            st.markdown("No models found. 🤷‍♂️")
                    
                    with st.expander(f"📚 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})")
                                if st.button(f"Download Snapshot: {dataset_name}", key=f"dataset_{dataset.id}"):
                                    with st.spinner(f"Downloading snapshot for {dataset_name}..."):
                                        result = perform_snapshot_download(dataset.id, "dataset")
                                        if isinstance(result, str):
                                            st.error(f"Failed to download {dataset_name}: {result}")
                                        else:
                                            snapshot_downloads.append(result)
                                            st.success(f"Successfully downloaded snapshot for {dataset_name}")
                        else:
                            st.markdown("No datasets found. 🤷‍♀️")
                
                st.markdown("---")
        
        if successful_html_files:
            html_zip_path = create_zip_of_files(successful_html_files, "HuggingFace_User_Pages.zip")
            html_download_link = get_download_link(html_zip_path, "📥 Download All HTML Pages as ZIP")
            st.markdown(html_download_link, unsafe_allow_html=True)
        else:
            st.warning("No HTML files were successfully downloaded to create a ZIP archive.")
        
        if snapshot_downloads:
            snapshot_zip_path = create_zip_of_files(snapshot_downloads, "HuggingFace_Snapshots.zip")
            snapshot_download_link = get_download_link(snapshot_zip_path, "📥 Download All Snapshots as ZIP")
            st.markdown(snapshot_download_link, unsafe_allow_html=True)
        
        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! 😅")

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 and Download Snapshots'**.
3. View each user's models and datasets along with a link to their Hugging Face profile.
4. For each model or dataset, you can click the "Download Snapshot" button to download a snapshot.
5. **Download ZIP archives** containing all the HTML pages and snapshots by clicking the download links.
6. Check out the statistics visualizations below!
""")