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Create app.py
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app.py
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| 1 |
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from typing import List, Dict
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| 2 |
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import httpx
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| 3 |
+
import gradio as gr
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| 4 |
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import pandas as pd
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+
from huggingface_hub import HfApi, ModelCard, snapshot_download
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import base64
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+
import io
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import zipfile
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import asyncio
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import aiohttp
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from pathlib import Path
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import emoji
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import tempfile
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import shutil
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import os
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| 17 |
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def search_hub(query: str, search_type: str) -> pd.DataFrame:
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| 18 |
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api = HfApi()
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| 19 |
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if search_type == "Models":
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| 20 |
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results = api.list_models(search=query)
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| 21 |
+
data = [{"id": model.modelId, "author": model.author, "downloads": model.downloads, "link": f"https://huggingface.co/{model.modelId}"} for model in results]
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| 22 |
+
elif search_type == "Datasets":
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| 23 |
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results = api.list_datasets(search=query)
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| 24 |
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data = [{"id": dataset.id, "author": dataset.author, "downloads": dataset.downloads, "link": f"https://huggingface.co/datasets/{dataset.id}"} for dataset in results]
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| 25 |
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elif search_type == "Spaces":
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| 26 |
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results = api.list_spaces(search=query)
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| 27 |
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data = [{"id": space.id, "author": space.author, "link": f"https://huggingface.co/spaces/{space.id}"} for space in results]
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| 28 |
+
else:
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data = []
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| 30 |
+
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| 31 |
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for i, item in enumerate(data, 1):
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| 32 |
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item['number'] = i
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| 33 |
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item['formatted_link'] = format_link(item, i, search_type)
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| 34 |
+
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return pd.DataFrame(data)
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| 36 |
+
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| 37 |
+
def format_link(item: Dict, number: int, search_type: str) -> str:
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| 38 |
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link = item['link']
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| 39 |
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readme_link = f"{link}/blob/main/README.md"
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| 40 |
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title = f"{number}. {item['id']}"
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| 41 |
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| 42 |
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metadata = f"Author: {item['author']}"
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if 'downloads' in item:
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| 44 |
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metadata += f", Downloads: {item['downloads']}"
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| 45 |
+
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| 46 |
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html = f"""
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| 47 |
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<div style="margin-bottom: 10px;">
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| 48 |
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<strong>{title}</strong><br>
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| 49 |
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<a href="{link}" target="_blank" style="color: #4a90e2; text-decoration: none;">View {search_type[:-1]}</a> |
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| 50 |
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<a href="{readme_link}" target="_blank" style="color: #4a90e2; text-decoration: none;">View README</a><br>
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| 51 |
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<small>{metadata}</small>
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| 52 |
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</div>
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| 53 |
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"""
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| 54 |
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return html
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| 55 |
+
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| 56 |
+
async def download_readme(session: aiohttp.ClientSession, item: Dict) -> tuple[str, str]:
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| 57 |
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"""Download README.md file for a given item."""
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| 58 |
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item_id = item['id']
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| 59 |
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raw_url = f"https://huggingface.co/{item_id}/raw/main/README.md"
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| 60 |
+
try:
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| 61 |
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async with session.get(raw_url) as response:
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| 62 |
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if response.status == 200:
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| 63 |
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content = await response.text()
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| 64 |
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return item_id.replace('/', '_'), content
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| 65 |
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return item_id.replace('/', '_'), f"# Error downloading README for {item_id}\nStatus code: {response.status}"
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| 66 |
+
except Exception as e:
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| 67 |
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return item_id.replace('/', '_'), f"# Error downloading README for {item_id}\nError: {str(e)}"
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| 68 |
+
|
| 69 |
+
async def download_all_readmes(data: List[Dict]) -> tuple[str, str]:
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| 70 |
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"""Download all README files and create a zip archive."""
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| 71 |
+
if not data:
|
| 72 |
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return "", "No results to download"
|
| 73 |
+
|
| 74 |
+
zip_buffer = io.BytesIO()
|
| 75 |
+
status_message = "Downloading READMEs..."
|
| 76 |
+
|
| 77 |
+
async with aiohttp.ClientSession() as session:
|
| 78 |
+
tasks = [download_readme(session, item) for item in data]
|
| 79 |
+
results = await asyncio.gather(*tasks)
|
| 80 |
+
|
| 81 |
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with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zip_file:
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| 82 |
+
for filename, content in results:
|
| 83 |
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zip_file.writestr(f"{filename}.md", content)
|
| 84 |
+
|
| 85 |
+
zip_buffer.seek(0)
|
| 86 |
+
base64_zip = base64.b64encode(zip_buffer.getvalue()).decode()
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| 87 |
+
|
| 88 |
+
download_link = f"""
|
| 89 |
+
<div style="margin-top: 10px;">
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| 90 |
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<a href="data:application/zip;base64,{base64_zip}"
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| 91 |
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download="readmes.zip"
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| 92 |
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style="display: inline-block; padding: 10px 20px;
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| 93 |
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background-color: #4CAF50; color: white;
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| 94 |
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text-decoration: none; border-radius: 5px;">
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| 95 |
+
📥 Download READMEs Archive
|
| 96 |
+
</a>
|
| 97 |
+
</div>
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| 98 |
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"""
|
| 99 |
+
|
| 100 |
+
return download_link, "READMEs ready for download!"
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| 101 |
+
|
| 102 |
+
def download_repository(repo_id: str, repo_type: str, temp_dir: str) -> str:
|
| 103 |
+
"""Download a single repository."""
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| 104 |
+
try:
|
| 105 |
+
repo_path = snapshot_download(
|
| 106 |
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repo_id=repo_id,
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| 107 |
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repo_type=repo_type.lower()[:-1], # Remove 's' from 'Models'/'Datasets'/'Spaces'
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| 108 |
+
local_dir=os.path.join(temp_dir, repo_id.replace('/', '_')),
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| 109 |
+
ignore_patterns=["*.bin", "*.pt", "*.pth", "*.ckpt", "*.safetensors"] # Ignore large binary files
|
| 110 |
+
)
|
| 111 |
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return repo_path
|
| 112 |
+
except Exception as e:
|
| 113 |
+
print(f"Error downloading {repo_id}: {str(e)}")
|
| 114 |
+
return None
|
| 115 |
+
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| 116 |
+
def create_repo_zip(data: List[Dict], search_type: str) -> tuple[str, str]:
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| 117 |
+
"""Download repositories and create a zip archive."""
|
| 118 |
+
if not data:
|
| 119 |
+
return "", "No repositories to download"
|
| 120 |
+
|
| 121 |
+
# Create temporary directory
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| 122 |
+
with tempfile.TemporaryDirectory() as temp_dir:
|
| 123 |
+
successful_downloads = []
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| 124 |
+
|
| 125 |
+
# Download each repository
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| 126 |
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for item in data:
|
| 127 |
+
repo_path = download_repository(item['id'], search_type, temp_dir)
|
| 128 |
+
if repo_path:
|
| 129 |
+
successful_downloads.append(repo_path)
|
| 130 |
+
|
| 131 |
+
if not successful_downloads:
|
| 132 |
+
return "", "No repositories were successfully downloaded"
|
| 133 |
+
|
| 134 |
+
# Create zip file in memory
|
| 135 |
+
zip_buffer = io.BytesIO()
|
| 136 |
+
with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zip_file:
|
| 137 |
+
for repo_path in successful_downloads:
|
| 138 |
+
repo_name = os.path.basename(repo_path)
|
| 139 |
+
for root, _, files in os.walk(repo_path):
|
| 140 |
+
for file in files:
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| 141 |
+
file_path = os.path.join(root, file)
|
| 142 |
+
arcname = os.path.join(repo_name, os.path.relpath(file_path, repo_path))
|
| 143 |
+
zip_file.write(file_path, arcname)
|
| 144 |
+
|
| 145 |
+
# Convert to base64
|
| 146 |
+
zip_buffer.seek(0)
|
| 147 |
+
base64_zip = base64.b64encode(zip_buffer.getvalue()).decode()
|
| 148 |
+
|
| 149 |
+
download_link = f"""
|
| 150 |
+
<div style="margin-top: 10px;">
|
| 151 |
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<a href="data:application/zip;base64,{base64_zip}"
|
| 152 |
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download="repositories.zip"
|
| 153 |
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style="display: inline-block; padding: 10px 20px;
|
| 154 |
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background-color: #4CAF50; color: white;
|
| 155 |
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text-decoration: none; border-radius: 5px;">
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| 156 |
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📥 Download Repositories Archive
|
| 157 |
+
</a>
|
| 158 |
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</div>
|
| 159 |
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"""
|
| 160 |
+
|
| 161 |
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return download_link, f"Successfully downloaded {len(successful_downloads)} repositories"
|
| 162 |
+
|
| 163 |
+
def display_results(df: pd.DataFrame):
|
| 164 |
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if df is not None and not df.empty:
|
| 165 |
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html = "<div style='max-height: 400px; overflow-y: auto;'>"
|
| 166 |
+
for _, row in df.iterrows():
|
| 167 |
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html += row['formatted_link']
|
| 168 |
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html += "</div>"
|
| 169 |
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return html
|
| 170 |
+
else:
|
| 171 |
+
return "<p>No results found.</p>"
|
| 172 |
+
|
| 173 |
+
def SwarmyTime(data: List[Dict]) -> Dict:
|
| 174 |
+
"""Aggregates all content from the given data."""
|
| 175 |
+
aggregated = {
|
| 176 |
+
"total_items": len(data),
|
| 177 |
+
"unique_authors": set(),
|
| 178 |
+
"total_downloads": 0,
|
| 179 |
+
"item_types": {"Models": 0, "Datasets": 0, "Spaces": 0}
|
| 180 |
+
}
|
| 181 |
+
|
| 182 |
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for item in data:
|
| 183 |
+
aggregated["unique_authors"].add(item.get("author", "Unknown"))
|
| 184 |
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aggregated["total_downloads"] += item.get("downloads", 0)
|
| 185 |
+
|
| 186 |
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if "modelId" in item:
|
| 187 |
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aggregated["item_types"]["Models"] += 1
|
| 188 |
+
elif "dataset" in item.get("id", ""):
|
| 189 |
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aggregated["item_types"]["Datasets"] += 1
|
| 190 |
+
else:
|
| 191 |
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aggregated["item_types"]["Spaces"] += 1
|
| 192 |
+
|
| 193 |
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aggregated["unique_authors"] = len(aggregated["unique_authors"])
|
| 194 |
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return aggregated
|
| 195 |
+
|
| 196 |
+
with gr.Blocks() as demo:
|
| 197 |
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gr.Markdown("## Search the Hugging Face Hub")
|
| 198 |
+
with gr.Row():
|
| 199 |
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search_query = gr.Textbox(label="Search Query", value="awacke1")
|
| 200 |
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search_type = gr.Radio(["Models", "Datasets", "Spaces"], label="Search Type", value="Models")
|
| 201 |
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search_button = gr.Button("Search")
|
| 202 |
+
|
| 203 |
+
results_html = gr.HTML(label="Search Results")
|
| 204 |
+
|
| 205 |
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with gr.Row():
|
| 206 |
+
download_readme_button = gr.Button("📚 Download READMEs", visible=False)
|
| 207 |
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download_repo_button = gr.Button("📦 Download Repositories", visible=False)
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| 208 |
+
|
| 209 |
+
download_status = gr.Markdown("", label="Download Status")
|
| 210 |
+
download_area = gr.HTML("", label="Download Link")
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| 211 |
+
metadata_output = gr.Textbox(label="Metadata", lines=10)
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| 212 |
+
aggregated_output = gr.JSON(label="Aggregated Content")
|
| 213 |
+
|
| 214 |
+
search_type_state = gr.State("")
|
| 215 |
+
current_results = gr.State([])
|
| 216 |
+
|
| 217 |
+
def search_and_aggregate(query, search_type):
|
| 218 |
+
df = search_hub(query, search_type)
|
| 219 |
+
data = df.to_dict('records')
|
| 220 |
+
aggregated = SwarmyTime(data)
|
| 221 |
+
html_results = display_results(df)
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| 222 |
+
show_download = len(data) > 0
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| 223 |
+
return [
|
| 224 |
+
html_results, # results_html
|
| 225 |
+
show_download, # download_readme_button visible
|
| 226 |
+
show_download, # download_repo_button visible
|
| 227 |
+
"", # download_status
|
| 228 |
+
"", # download_area
|
| 229 |
+
aggregated, # aggregated_output
|
| 230 |
+
search_type, # search_type_state
|
| 231 |
+
data # current_results
|
| 232 |
+
]
|
| 233 |
+
|
| 234 |
+
async def handle_readme_download(data):
|
| 235 |
+
if not data:
|
| 236 |
+
return ["No results to download", ""]
|
| 237 |
+
download_link, status = await download_all_readmes(data)
|
| 238 |
+
return [status, download_link]
|
| 239 |
+
|
| 240 |
+
def handle_repo_download(data, search_type):
|
| 241 |
+
if not data:
|
| 242 |
+
return ["No results to download", ""]
|
| 243 |
+
download_link, status = create_repo_zip(data, search_type)
|
| 244 |
+
return [status, download_link]
|
| 245 |
+
|
| 246 |
+
search_button.click(
|
| 247 |
+
search_and_aggregate,
|
| 248 |
+
inputs=[search_query, search_type],
|
| 249 |
+
outputs=[
|
| 250 |
+
results_html,
|
| 251 |
+
download_readme_button,
|
| 252 |
+
download_repo_button,
|
| 253 |
+
download_status,
|
| 254 |
+
download_area,
|
| 255 |
+
aggregated_output,
|
| 256 |
+
search_type_state,
|
| 257 |
+
current_results
|
| 258 |
+
]
|
| 259 |
+
)
|
| 260 |
+
|
| 261 |
+
download_readme_button.click(
|
| 262 |
+
handle_readme_download,
|
| 263 |
+
inputs=[current_results],
|
| 264 |
+
outputs=[download_status, download_area]
|
| 265 |
+
)
|
| 266 |
+
|
| 267 |
+
download_repo_button.click(
|
| 268 |
+
handle_repo_download,
|
| 269 |
+
inputs=[current_results, search_type_state],
|
| 270 |
+
outputs=[download_status, download_area]
|
| 271 |
+
)
|
| 272 |
+
|
| 273 |
+
demo.launch(debug=True)
|