import streamlit as st
import pandas as pd
from datetime import datetime
def render_home():
"""Render the home page with model overview and statistics"""
st.title("🤗 Hugging Face Model Manager")
st.markdown(
"""
Welcome to your personal Hugging Face model management dashboard.
From here, you can view, create, and manage your machine learning models.
"""
)
# Check if we have models loaded
if not st.session_state.get("models"):
with st.spinner("Loading your models..."):
try:
st.session_state.models = st.session_state.client.get_user_models()
except Exception as e:
st.error(f"Error loading models: {str(e)}")
# Model Statistics Dashboard
st.markdown("### 📊 Model Statistics")
# Key statistics in cards
col1, col2, col3 = st.columns([1, 1, 1])
with col1:
# Total models count
total_models = len(st.session_state.models)
st.markdown(
f"""
<div class="tooltip" style="width: 100%;">
<div style="padding: 20px; background-color: #F9FAFB; border-radius: 10px; border: 1px solid #E5E7EB; text-align: center; box-shadow: 0 2px 4px rgba(0,0,0,0.05); transition: all 0.3s;">
<div style="font-size: 36px; color: #6366F1; font-weight: bold;">
{total_models}
</div>
<div style="color: #6B7280; font-weight: 500;">
Total Models
</div>
</div>
<span class="tooltip-text">Total number of models you've created</span>
</div>
""",
unsafe_allow_html=True,
)
with col2:
# Total downloads (sum from all models)
total_downloads = sum(
getattr(model, "downloads", 0) for model in st.session_state.models
)
st.markdown(
f"""
<div class="tooltip" style="width: 100%;">
<div style="padding: 20px; background-color: #F9FAFB; border-radius: 10px; border: 1px solid #E5E7EB; text-align: center; box-shadow: 0 2px 4px rgba(0,0,0,0.05); transition: all 0.3s;">
<div style="font-size: 36px; color: #10B981; font-weight: bold;">
{total_downloads:,}
</div>
<div style="color: #6B7280; font-weight: 500;">
Total Downloads
</div>
</div>
<span class="tooltip-text">Cumulative downloads across all your models</span>
</div>
""",
unsafe_allow_html=True,
)
with col3:
# Calculate total likes
total_likes = sum(
getattr(model, "likes", 0) for model in st.session_state.models
)
st.markdown(
f"""
<div class="tooltip" style="width: 100%;">
<div style="padding: 20px; background-color: #F9FAFB; border-radius: 10px; border: 1px solid #E5E7EB; text-align: center; box-shadow: 0 2px 4px rgba(0,0,0,0.05); transition: all 0.3s;">
<div style="font-size: 36px; color: #FF9D96; font-weight: bold;">
{total_likes}
</div>
<div style="color: #6B7280; font-weight: 500;">
Total Likes
</div>
</div>
<span class="tooltip-text">Cumulative likes across all your models</span>
</div>
""",
unsafe_allow_html=True,
)
# Quick Actions with improved styling
st.markdown("### 🚀 Quick Actions")
quick_actions_col1, quick_actions_col2 = st.columns([1, 1])
with quick_actions_col1:
if st.button(
"➕ Create New Repository", key="create_repo_home", use_container_width=True
):
st.session_state.page = "repository_management"
st.experimental_rerun()
with quick_actions_col2:
if st.button(
"🔄 Refresh Models", key="refresh_models_home", use_container_width=True
):
with st.spinner("Refreshing models..."):
try:
st.session_state.models = st.session_state.client.get_user_models()
st.success("Models refreshed!")
except Exception as e:
st.error(f"Error refreshing models: {str(e)}")
# Your Models section
st.markdown("### 📚 Your Models")
if not st.session_state.models:
st.info(
"You don't have any models yet. Click 'Create New Repository' to get started!"
)
else:
# Create dataframe from models list for display
models_data = []
for model in st.session_state.models:
try:
# Extract key data
last_modified = (
datetime.fromisoformat(model.lastModified.replace("Z", "+00:00"))
if hasattr(model, "lastModified")
else None
)
model_data = {
"Model Name": model.modelId.split("/")[-1],
"Full ID": model.modelId,
"Downloads": getattr(model, "downloads", 0),
"Likes": getattr(model, "likes", 0),
"Last Modified": last_modified,
"Private": getattr(model, "private", False),
}
models_data.append(model_data)
except Exception as e:
st.warning(f"Error processing model {getattr(model, 'modelId', 'unknown')}: {str(e)}")
# Sorting
sort_options = ["Last Modified", "Downloads", "Likes", "Model Name"]
sort_by = st.selectbox("Sort by", sort_options, index=0)
# Create DataFrame and sort
if models_data:
df = pd.DataFrame(models_data)
if sort_by == "Last Modified":
df = df.sort_values(by=sort_by, ascending=False)
elif sort_by in ["Downloads", "Likes"]:
df = df.sort_values(by=sort_by, ascending=False)
else:
df = df.sort_values(by=sort_by)
# Format the Last Modified date
df["Last Modified"] = df["Last Modified"].apply(
lambda x: x.strftime("%b %d, %Y") if pd.notnull(x) else "N/A"
)
# Display models as cards
for i, row in df.iterrows():
with st.container():
col1, col2 = st.columns([3, 1])
with col1:
st.markdown(
f"""
<div style="padding: 16px; background-color: #F9FAFB; border-radius: 8px; border: 1px solid #E5E7EB; margin-bottom: 16px; cursor: pointer; transition: all 0.3s;"
onclick="window.open('https://huggingface.co/{row['Full ID']}', '_blank')">
<div style="display: flex; justify-content: space-between; align-items: center;">
<div>
<h3 style="margin: 0; color: #111827;">{row['Model Name']}</h3>
<p style="margin: 4px 0 0 0; color: #6B7280; font-size: 14px;">{row['Full ID']}</p>
</div>
<div style="display: flex; align-items: center;">
<div style="margin-right: 16px; text-align: center;">
<div style="font-weight: bold; color: #10B981;">{row['Downloads']:,}</div>
<div style="font-size: 12px; color: #6B7280;">downloads</div>
</div>
<div style="margin-right: 16px; text-align: center;">
<div style="font-weight: bold; color: #FF9D96;">{row['Likes']}</div>
<div style="font-size: 12px; color: #6B7280;">likes</div>
</div>
<div style="text-align: center;">
<div style="font-weight: bold; color: #6366F1;">{row['Last Modified']}</div>
<div style="font-size: 12px; color: #6B7280;">updated</div>
</div>
</div>
</div>
</div>
""",
unsafe_allow_html=True,
)
with col2:
if st.button(
"📝 Manage",
key=f"manage_{row['Full ID']}",
use_container_width=True
):
st.session_state.selected_model = row["Full ID"]
st.session_state.page = "model_details"
st.experimental_rerun()