Commit
·
4ea6260
1
Parent(s):
1f6e59a
Add atlas-export UV script for HF Jobs
Browse files- README.md +94 -0
- atlas-export.py +432 -0
README.md
ADDED
@@ -0,0 +1,94 @@
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# 🗺️ Atlas Export - One-Click Embedding Visualizations
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Generate and deploy interactive embedding visualizations to HuggingFace Spaces with a single command.
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## Quick Start
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```bash
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# Create a Space from any text dataset
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uv run atlas-export.py stanfordnlp/imdb --space-name my-imdb-viz
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# Your Space will be live at:
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# https://huggingface.co/spaces/YOUR_USERNAME/my-imdb-viz
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```
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## Examples
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### Image Datasets
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```bash
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# Visualize image datasets with CLIP
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uv run atlas-export.py \
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beans \
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--space-name bean-disease-atlas \
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--image-column image \
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--model openai/clip-vit-base-patch32
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```
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### Custom Embeddings
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```bash
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# Use a specific embedding model
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uv run atlas-export.py \
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wikipedia \
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--space-name wiki-viz \
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--model nomic-ai/nomic-embed-text-v1.5 \
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--text-column text \
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--sample 50000
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```
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### Pre-computed Embeddings
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```bash
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# If you already have embeddings in your dataset
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uv run atlas-export.py \
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my-dataset-with-embeddings \
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--space-name my-viz \
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--no-compute-embeddings \
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--x-column umap_x \
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--y-column umap_y
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```
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### GPU Acceleration
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```bash
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# Run on HF Jobs with GPU for faster embedding generation
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hf jobs run --gpu t4 \
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uv run https://huggingface.co/datasets/uv-scripts/build-atlas/raw/main/atlas-export.py \
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stanfordnlp/imdb \
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--space-name imdb-viz \
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--model sentence-transformers/all-mpnet-base-v2 \
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--sample 10000
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```
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## Key Options
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| Option | Description | Default |
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|--------|-------------|---------|
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| `dataset_id` | HuggingFace dataset to visualize | Required |
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| `--space-name` | Name for your Space | Required |
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| `--model` | Embedding model to use | Auto-selected |
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| `--text-column` | Column containing text | Auto-detected |
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| `--image-column` | Column containing images | None |
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| `--sample` | Number of samples to visualize | All |
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| `--local-only` | Generate locally without deploying | False |
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| `--output-dir` | Local output directory | Temp dir |
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Run without arguments to see all options and more examples.
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## How It Works
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1. Loads dataset from HuggingFace Hub
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2. Generates embeddings (or uses pre-computed)
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3. Creates static web app with embedded data
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4. Deploys to HF Space
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The resulting visualization runs entirely in the browser using WebGPU acceleration.
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## Credits
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Built on [Embedding Atlas](https://github.com/apple/embedding-atlas) by Apple.
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---
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Part of the [UV Scripts](https://huggingface.co/uv-scripts) collection 🚀
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atlas-export.py
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# /// script
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# requires-python = ">=3.10"
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# dependencies = [
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# "huggingface-hub[hf_transfer]",
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# "torch", # For GPU detection
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# ]
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# ///
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"""
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Generate static Embedding Atlas visualizations and deploy to HuggingFace Spaces.
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This script creates interactive embedding visualizations that run entirely in the browser,
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using WebGPU acceleration for smooth performance with millions of points.
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Example usage:
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# Basic usage (creates Space from dataset)
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uv run atlas-export.py \
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stanfordnlp/imdb \
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--space-name my-imdb-viz
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# With custom model and configuration
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uv run atlas-export.py \
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beans \
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--space-name bean-disease-atlas \
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--image-column image \
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--model openai/clip-vit-base-patch32 \
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--sample 10000
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# Run on HF Jobs with GPU (if embedding generation benefits)
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hf jobs run --gpu t4 \
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uv run https://huggingface.co/datasets/uv-scripts/build-atlas/raw/main/atlas-export.py \
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my-dataset \
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--space-name my-atlas \
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--model nomic-ai/nomic-embed-text-v1.5
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# Use pre-computed embeddings
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uv run atlas-export.py \
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my-dataset-with-embeddings \
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--space-name my-viz \
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--no-compute-embeddings \
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--x-column umap_x \
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--y-column umap_y
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"""
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import argparse
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import logging
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import os
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import shutil
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import subprocess
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import sys
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import tempfile
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import zipfile
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from pathlib import Path
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from typing import Optional
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from huggingface_hub import HfApi, create_repo, login, upload_folder
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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def check_gpu_available() -> bool:
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"""Check if GPU is available for computation."""
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try:
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import torch
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return torch.cuda.is_available()
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except ImportError:
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return False
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def build_atlas_command(args) -> list:
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"""Build the embedding-atlas command with all parameters."""
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# Use uvx to run embedding-atlas with required dependencies
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cmd = ["uvx", "--with", "datasets", "embedding-atlas"]
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cmd.append(args.dataset_id)
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# Add all optional parameters
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if args.model:
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cmd.extend(["--model", args.model])
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# Always specify text column to avoid interactive prompt
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text_col = args.text_column or "text" # Default to "text" if not specified
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cmd.extend(["--text", text_col])
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if args.image_column:
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cmd.extend(["--image", args.image_column])
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if args.split:
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cmd.extend(["--split", args.split])
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if args.sample:
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cmd.extend(["--sample", str(args.sample)])
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if args.trust_remote_code:
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cmd.append("--trust-remote-code")
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if not args.compute_embeddings:
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cmd.append("--no-compute-embeddings")
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if args.x_column:
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cmd.extend(["--x", args.x_column])
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if args.y_column:
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cmd.extend(["--y", args.y_column])
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if args.neighbors_column:
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cmd.extend(["--neighbors", args.neighbors_column])
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# Add export flag with output path
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export_path = "atlas_export.zip"
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cmd.extend(["--export-application", export_path])
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return cmd, export_path
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def create_space_readme(args) -> str:
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"""Generate README.md content for the Space."""
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title = args.space_name.replace("-", " ").title()
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readme = f"""---
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title: {title}
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emoji: 🗺️
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colorFrom: blue
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colorTo: purple
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sdk: static
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pinned: false
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license: mit
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---
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129 |
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# 🗺️ {title}
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131 |
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Interactive embedding visualization of [{args.dataset_id}](https://huggingface.co/datasets/{args.dataset_id}) using [Embedding Atlas](https://github.com/apple/embedding-atlas).
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133 |
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## Features
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135 |
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136 |
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- Interactive embedding visualization
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- Real-time search and filtering
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138 |
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- Automatic clustering with labels
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139 |
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- WebGPU-accelerated rendering
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140 |
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"""
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141 |
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if args.model:
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readme += f"\n## Model\n\nEmbeddings generated using: `{args.model}`\n"
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if args.sample:
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readme += f"\n## Data\n\nVisualization includes {args.sample:,} samples from the dataset.\n"
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readme += """
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## How to Use
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150 |
+
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151 |
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- **Click and drag** to navigate
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152 |
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- **Scroll** to zoom in/out
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153 |
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- **Click** on points to see details
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154 |
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- **Search** using the search box
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155 |
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- **Filter** using metadata panels
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156 |
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157 |
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---
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158 |
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159 |
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*Generated with [UV Scripts Atlas Export](https://huggingface.co/uv-scripts)*
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160 |
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"""
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161 |
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162 |
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return readme
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|
164 |
+
|
165 |
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def extract_and_prepare_static_files(zip_path: str, output_dir: Path) -> None:
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166 |
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"""Extract the exported atlas ZIP and prepare for static deployment."""
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167 |
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logger.info(f"Extracting {zip_path} to {output_dir}")
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+
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169 |
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with zipfile.ZipFile(zip_path, 'r') as zip_ref:
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170 |
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zip_ref.extractall(output_dir)
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171 |
+
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172 |
+
# The ZIP should contain index.html and associated files
|
173 |
+
if not (output_dir / "index.html").exists():
|
174 |
+
raise FileNotFoundError("index.html not found in exported atlas")
|
175 |
+
|
176 |
+
logger.info(f"Extracted {len(list(output_dir.iterdir()))} items")
|
177 |
+
|
178 |
+
|
179 |
+
def deploy_to_space(
|
180 |
+
output_dir: Path,
|
181 |
+
space_name: str,
|
182 |
+
organization: Optional[str] = None,
|
183 |
+
private: bool = False,
|
184 |
+
hf_token: Optional[str] = None
|
185 |
+
) -> str:
|
186 |
+
"""Deploy the static files to a HuggingFace Space."""
|
187 |
+
api = HfApi(token=hf_token)
|
188 |
+
|
189 |
+
# Construct full repo ID
|
190 |
+
if organization:
|
191 |
+
repo_id = f"{organization}/{space_name}"
|
192 |
+
else:
|
193 |
+
# Get username from API
|
194 |
+
user_info = api.whoami()
|
195 |
+
username = user_info["name"]
|
196 |
+
repo_id = f"{username}/{space_name}"
|
197 |
+
|
198 |
+
logger.info(f"Creating Space: {repo_id}")
|
199 |
+
|
200 |
+
# Create the Space repository
|
201 |
+
try:
|
202 |
+
create_repo(
|
203 |
+
repo_id,
|
204 |
+
repo_type="space",
|
205 |
+
space_sdk="static",
|
206 |
+
private=private,
|
207 |
+
token=hf_token
|
208 |
+
)
|
209 |
+
logger.info(f"Created new Space: {repo_id}")
|
210 |
+
except Exception as e:
|
211 |
+
if "already exists" in str(e):
|
212 |
+
logger.info(f"Space {repo_id} already exists, updating...")
|
213 |
+
else:
|
214 |
+
raise
|
215 |
+
|
216 |
+
# Upload all files
|
217 |
+
logger.info("Uploading files to Space...")
|
218 |
+
upload_folder(
|
219 |
+
folder_path=str(output_dir),
|
220 |
+
repo_id=repo_id,
|
221 |
+
repo_type="space",
|
222 |
+
token=hf_token
|
223 |
+
)
|
224 |
+
|
225 |
+
space_url = f"https://huggingface.co/spaces/{repo_id}"
|
226 |
+
logger.info(f"✅ Space deployed successfully: {space_url}")
|
227 |
+
|
228 |
+
return space_url
|
229 |
+
|
230 |
+
|
231 |
+
def main():
|
232 |
+
# Enable HF Transfer for faster downloads if available
|
233 |
+
os.environ.setdefault("HF_HUB_ENABLE_HF_TRANSFER", "1")
|
234 |
+
|
235 |
+
parser = argparse.ArgumentParser(
|
236 |
+
description="Generate and deploy static Embedding Atlas visualizations",
|
237 |
+
formatter_class=argparse.RawDescriptionHelpFormatter,
|
238 |
+
epilog=__doc__,
|
239 |
+
)
|
240 |
+
|
241 |
+
# Required arguments
|
242 |
+
parser.add_argument(
|
243 |
+
"dataset_id",
|
244 |
+
type=str,
|
245 |
+
help="HuggingFace dataset ID to visualize",
|
246 |
+
)
|
247 |
+
|
248 |
+
# Space configuration
|
249 |
+
parser.add_argument(
|
250 |
+
"--space-name",
|
251 |
+
type=str,
|
252 |
+
required=True,
|
253 |
+
help="Name for the HuggingFace Space",
|
254 |
+
)
|
255 |
+
parser.add_argument(
|
256 |
+
"--organization",
|
257 |
+
type=str,
|
258 |
+
help="HuggingFace organization (default: your username)",
|
259 |
+
)
|
260 |
+
parser.add_argument(
|
261 |
+
"--private",
|
262 |
+
action="store_true",
|
263 |
+
help="Make the Space private",
|
264 |
+
)
|
265 |
+
|
266 |
+
# Atlas configuration
|
267 |
+
parser.add_argument(
|
268 |
+
"--model",
|
269 |
+
type=str,
|
270 |
+
help="Embedding model to use (e.g., sentence-transformers/all-MiniLM-L6-v2)",
|
271 |
+
)
|
272 |
+
parser.add_argument(
|
273 |
+
"--text-column",
|
274 |
+
type=str,
|
275 |
+
help="Name of text column (default: auto-detect)",
|
276 |
+
)
|
277 |
+
parser.add_argument(
|
278 |
+
"--image-column",
|
279 |
+
type=str,
|
280 |
+
help="Name of image column for image datasets",
|
281 |
+
)
|
282 |
+
parser.add_argument(
|
283 |
+
"--split",
|
284 |
+
type=str,
|
285 |
+
default="train",
|
286 |
+
help="Dataset split to use (default: train)",
|
287 |
+
)
|
288 |
+
parser.add_argument(
|
289 |
+
"--sample",
|
290 |
+
type=int,
|
291 |
+
help="Number of samples to visualize (default: all)",
|
292 |
+
)
|
293 |
+
parser.add_argument(
|
294 |
+
"--trust-remote-code",
|
295 |
+
action="store_true",
|
296 |
+
help="Trust remote code in dataset/model",
|
297 |
+
)
|
298 |
+
|
299 |
+
# Pre-computed embeddings
|
300 |
+
parser.add_argument(
|
301 |
+
"--no-compute-embeddings",
|
302 |
+
action="store_false",
|
303 |
+
dest="compute_embeddings",
|
304 |
+
help="Use pre-computed embeddings from dataset",
|
305 |
+
)
|
306 |
+
parser.add_argument(
|
307 |
+
"--x-column",
|
308 |
+
type=str,
|
309 |
+
help="Column with X coordinates (for pre-computed projections)",
|
310 |
+
)
|
311 |
+
parser.add_argument(
|
312 |
+
"--y-column",
|
313 |
+
type=str,
|
314 |
+
help="Column with Y coordinates (for pre-computed projections)",
|
315 |
+
)
|
316 |
+
parser.add_argument(
|
317 |
+
"--neighbors-column",
|
318 |
+
type=str,
|
319 |
+
help="Column with neighbor indices (for pre-computed)",
|
320 |
+
)
|
321 |
+
|
322 |
+
# Additional options
|
323 |
+
parser.add_argument(
|
324 |
+
"--hf-token",
|
325 |
+
type=str,
|
326 |
+
help="HuggingFace API token (or set HF_TOKEN env var)",
|
327 |
+
)
|
328 |
+
parser.add_argument(
|
329 |
+
"--local-only",
|
330 |
+
action="store_true",
|
331 |
+
help="Only generate locally, don't deploy to Space",
|
332 |
+
)
|
333 |
+
parser.add_argument(
|
334 |
+
"--output-dir",
|
335 |
+
type=str,
|
336 |
+
help="Local directory for output (default: temp directory)",
|
337 |
+
)
|
338 |
+
|
339 |
+
args = parser.parse_args()
|
340 |
+
|
341 |
+
# Check GPU availability
|
342 |
+
if check_gpu_available():
|
343 |
+
logger.info("🚀 GPU detected - may accelerate embedding generation")
|
344 |
+
else:
|
345 |
+
logger.info("💻 Running on CPU - embedding generation may be slower")
|
346 |
+
|
347 |
+
# Login to HuggingFace if needed
|
348 |
+
if not args.local_only:
|
349 |
+
hf_token = args.hf_token or os.environ.get("HF_TOKEN")
|
350 |
+
if hf_token:
|
351 |
+
login(token=hf_token)
|
352 |
+
else:
|
353 |
+
logger.warning("No HF token provided. You may not be able to push to the Hub.")
|
354 |
+
response = input("Continue anyway? (y/n): ")
|
355 |
+
if response.lower() != 'y':
|
356 |
+
sys.exit(0)
|
357 |
+
|
358 |
+
# Set up output directory
|
359 |
+
if args.output_dir:
|
360 |
+
output_dir = Path(args.output_dir)
|
361 |
+
output_dir.mkdir(parents=True, exist_ok=True)
|
362 |
+
temp_dir = None
|
363 |
+
else:
|
364 |
+
temp_dir = tempfile.mkdtemp(prefix="atlas_export_")
|
365 |
+
output_dir = Path(temp_dir)
|
366 |
+
logger.info(f"Using temporary directory: {output_dir}")
|
367 |
+
|
368 |
+
try:
|
369 |
+
# Build and run embedding-atlas command
|
370 |
+
cmd, export_path = build_atlas_command(args)
|
371 |
+
logger.info(f"Running command: {' '.join(cmd)}")
|
372 |
+
|
373 |
+
# Run the command
|
374 |
+
result = subprocess.run(cmd, capture_output=True, text=True)
|
375 |
+
|
376 |
+
if result.returncode != 0:
|
377 |
+
logger.error(f"Atlas export failed with return code {result.returncode}")
|
378 |
+
logger.error(f"STDOUT: {result.stdout}")
|
379 |
+
logger.error(f"STDERR: {result.stderr}")
|
380 |
+
sys.exit(1)
|
381 |
+
|
382 |
+
logger.info("✅ Atlas export completed successfully")
|
383 |
+
|
384 |
+
# Extract the exported files
|
385 |
+
extract_and_prepare_static_files(export_path, output_dir)
|
386 |
+
|
387 |
+
# Create README for the Space
|
388 |
+
readme_content = create_space_readme(args)
|
389 |
+
(output_dir / "README.md").write_text(readme_content)
|
390 |
+
|
391 |
+
if args.local_only:
|
392 |
+
logger.info(f"✅ Static files prepared in: {output_dir}")
|
393 |
+
logger.info("To deploy manually, upload the contents to a HuggingFace Space with sdk: static")
|
394 |
+
else:
|
395 |
+
# Deploy to HuggingFace Space
|
396 |
+
space_url = deploy_to_space(
|
397 |
+
output_dir,
|
398 |
+
args.space_name,
|
399 |
+
args.organization,
|
400 |
+
args.private,
|
401 |
+
hf_token
|
402 |
+
)
|
403 |
+
|
404 |
+
logger.info(f"\n🎉 Success! Your atlas is live at: {space_url}")
|
405 |
+
logger.info(f"The visualization will be available in a few moments.")
|
406 |
+
|
407 |
+
# Clean up the ZIP file
|
408 |
+
if Path(export_path).exists():
|
409 |
+
os.remove(export_path)
|
410 |
+
|
411 |
+
finally:
|
412 |
+
# Clean up temp directory if used
|
413 |
+
if temp_dir and not args.local_only:
|
414 |
+
shutil.rmtree(temp_dir)
|
415 |
+
logger.info("Cleaned up temporary files")
|
416 |
+
|
417 |
+
|
418 |
+
if __name__ == "__main__":
|
419 |
+
# Show example commands if no args provided
|
420 |
+
if len(sys.argv) == 1:
|
421 |
+
print("Example commands:\n")
|
422 |
+
print("# Basic usage:")
|
423 |
+
print("uv run atlas-export.py stanfordnlp/imdb --space-name imdb-atlas\n")
|
424 |
+
print("# With custom model and sampling:")
|
425 |
+
print("uv run atlas-export.py my-dataset --space-name my-viz --model nomic-ai/nomic-embed-text-v1.5 --sample 10000\n")
|
426 |
+
print("# For HF Jobs with GPU:")
|
427 |
+
print("hf jobs run --gpu t4 uv run https://huggingface.co/datasets/uv-scripts/build-atlas/raw/main/atlas-export.py dataset --space-name viz --model sentence-transformers/all-mpnet-base-v2\n")
|
428 |
+
print("# Local generation only:")
|
429 |
+
print("uv run atlas-export.py dataset --space-name test --local-only --output-dir ./atlas-output")
|
430 |
+
sys.exit(0)
|
431 |
+
|
432 |
+
main()
|