Commit
ยท
31ad4fe
1
Parent(s):
ab2fedd
Refactor atlas-export.py for improved readability and maintainability
Browse files- atlas-export.py +93 -75
atlas-export.py
CHANGED
@@ -65,6 +65,7 @@ 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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@@ -74,52 +75,58 @@ 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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# Include hf-transfer for faster downloads when HF_HUB_ENABLE_HF_TRANSFER is set
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-
cmd = [
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-
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-
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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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-
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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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-
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if args.image_column:
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cmd.extend(["--image", args.image_column])
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-
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if args.split:
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cmd.extend(["--split", args.split])
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-
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if args.sample:
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cmd.extend(["--sample", str(args.sample)])
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-
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if args.trust_remote_code:
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cmd.append("--trust-remote-code")
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-
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if not args.compute_embeddings:
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cmd.append("--no-compute-embeddings")
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-
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if args.x_column:
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cmd.extend(["--x", args.x_column])
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-
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if args.y_column:
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cmd.extend(["--y", args.y_column])
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-
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if args.neighbors_column:
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cmd.extend(["--neighbors", args.neighbors_column])
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-
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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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-
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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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-
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readme = f"""---
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title: {title}
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emoji: ๐บ๏ธ
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@@ -141,13 +148,13 @@ Interactive embedding visualization of [{args.dataset_id}](https://huggingface.c
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- Automatic clustering with labels
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- WebGPU-accelerated rendering
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"""
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-
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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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-
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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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-
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readme += """
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## How to Use
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@@ -161,21 +168,21 @@ Interactive embedding visualization of [{args.dataset_id}](https://huggingface.c
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*Generated with [UV Scripts Atlas Export](https://huggingface.co/uv-scripts)*
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"""
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-
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return readme
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def extract_and_prepare_static_files(zip_path: str, output_dir: Path) -> None:
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"""Extract the exported atlas ZIP and prepare for static deployment."""
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logger.info(f"Extracting {zip_path} to {output_dir}")
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-
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with zipfile.ZipFile(zip_path,
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zip_ref.extractall(output_dir)
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-
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# The ZIP should contain index.html and associated files
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if not (output_dir / "index.html").exists():
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raise FileNotFoundError("index.html not found in exported atlas")
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-
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logger.info(f"Extracted {len(list(output_dir.iterdir()))} items")
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@@ -184,11 +191,11 @@ def deploy_to_space(
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space_name: str,
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organization: Optional[str] = None,
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private: bool = False,
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-
hf_token: Optional[str] = None
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) -> str:
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"""Deploy the static files to a HuggingFace Space."""
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api = HfApi(token=hf_token)
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-
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# Construct full repo ID
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if organization:
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repo_id = f"{organization}/{space_name}"
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@@ -197,9 +204,9 @@ def deploy_to_space(
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user_info = api.whoami()
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username = user_info["name"]
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repo_id = f"{username}/{space_name}"
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-
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logger.info(f"Creating Space: {repo_id}")
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-
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# Create the Space repository
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try:
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create_repo(
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@@ -207,7 +214,7 @@ def deploy_to_space(
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repo_type="space",
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space_sdk="static",
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private=private,
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-
token=hf_token
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)
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logger.info(f"Created new Space: {repo_id}")
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except Exception as e:
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@@ -215,39 +222,36 @@ def deploy_to_space(
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logger.info(f"Space {repo_id} already exists, updating...")
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else:
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raise
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-
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# Upload all files
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logger.info("Uploading files to Space...")
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upload_folder(
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-
folder_path=str(output_dir),
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-
repo_id=repo_id,
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-
repo_type="space",
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-
token=hf_token
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)
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-
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space_url = f"https://huggingface.co/spaces/{repo_id}"
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logger.info(f"โ
Space deployed successfully: {space_url}")
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-
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return space_url
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def main():
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# Enable HF Transfer for faster downloads if available
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os.environ.setdefault("HF_HUB_ENABLE_HF_TRANSFER", "1")
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-
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parser = argparse.ArgumentParser(
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description="Generate and deploy static Embedding Atlas visualizations",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog=__doc__,
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)
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-
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# Required arguments
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parser.add_argument(
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"dataset_id",
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type=str,
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help="HuggingFace dataset ID to visualize",
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)
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-
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# Space configuration
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parser.add_argument(
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"--space-name",
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@@ -265,7 +269,7 @@ def main():
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action="store_true",
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help="Make the Space private",
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)
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-
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# Atlas configuration
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parser.add_argument(
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"--model",
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@@ -298,7 +302,7 @@ def main():
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action="store_true",
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help="Trust remote code in dataset/model",
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)
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-
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# Pre-computed embeddings
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parser.add_argument(
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"--no-compute-embeddings",
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@@ -321,7 +325,7 @@ def main():
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type=str,
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help="Column with neighbor indices (for pre-computed)",
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)
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-
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# Additional options
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parser.add_argument(
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"--hf-token",
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@@ -338,44 +342,52 @@ def main():
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type=str,
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help="Local directory for output (default: temp directory)",
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)
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-
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args = parser.parse_args()
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-
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# Check GPU availability
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if check_gpu_available():
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logger.info("๐ GPU detected - may accelerate embedding generation")
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else:
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logger.info("๐ป Running on CPU - embedding generation may be slower")
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-
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# Login to HuggingFace if needed
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if not args.local_only:
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# Try to get token from various sources
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hf_token = (
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-
args.hf_token
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or os.environ.get("HF_TOKEN")
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or os.environ.get("HUGGING_FACE_HUB_TOKEN")
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or get_token() # This will check HF CLI login
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)
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-
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if hf_token:
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login(token=hf_token)
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logger.info("โ
Authenticated with Hugging Face")
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else:
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# Check if running in non-interactive environment (HF Jobs, CI, etc.)
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is_interactive = sys.stdin.isatty()
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-
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if is_interactive:
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-
logger.warning(
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response = input("Continue anyway? (y/n): ")
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-
if response.lower() !=
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sys.exit(0)
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else:
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# In non-interactive environments, fail immediately if no token
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-
logger.error(
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-
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-
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sys.exit(1)
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-
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# Set up output directory
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if args.output_dir:
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output_dir = Path(args.output_dir)
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@@ -385,50 +397,48 @@ def main():
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temp_dir = tempfile.mkdtemp(prefix="atlas_export_")
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output_dir = Path(temp_dir)
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logger.info(f"Using temporary directory: {output_dir}")
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-
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try:
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# Build and run embedding-atlas command
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cmd, export_path = build_atlas_command(args)
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logger.info(f"Running command: {' '.join(cmd)}")
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-
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# Run the command
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result = subprocess.run(cmd, capture_output=True, text=True)
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-
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if result.returncode != 0:
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logger.error(f"Atlas export failed with return code {result.returncode}")
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logger.error(f"STDOUT: {result.stdout}")
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logger.error(f"STDERR: {result.stderr}")
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sys.exit(1)
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-
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logger.info("โ
Atlas export completed successfully")
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-
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# Extract the exported files
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extract_and_prepare_static_files(export_path, output_dir)
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-
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# Create README for the Space
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readme_content = create_space_readme(args)
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(output_dir / "README.md").write_text(readme_content)
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-
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if args.local_only:
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logger.info(f"โ
Static files prepared in: {output_dir}")
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-
logger.info(
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else:
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# Deploy to HuggingFace Space
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space_url = deploy_to_space(
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-
output_dir,
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-
args.space_name,
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-
args.organization,
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-
args.private,
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-
hf_token
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)
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-
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logger.info(f"\n๐ Success! Your atlas is live at: {space_url}")
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logger.info(f"The visualization will be available in a few moments.")
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-
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# Clean up the ZIP file
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if Path(export_path).exists():
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os.remove(export_path)
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-
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finally:
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# Clean up temp directory if used
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if temp_dir and not args.local_only:
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@@ -443,12 +453,20 @@ if __name__ == "__main__":
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print("# Basic usage:")
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print("uv run atlas-export.py stanfordnlp/imdb --space-name imdb-atlas\n")
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print("# With custom model and sampling:")
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-
print(
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print("# For HF Jobs with GPU (experimental UV support):")
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448 |
-
print(
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-
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print("# Local generation only:")
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-
print(
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sys.exit(0)
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-
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-
main()
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"""Check if GPU is available for computation."""
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66 |
try:
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67 |
import torch
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68 |
+
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69 |
return torch.cuda.is_available()
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70 |
except ImportError:
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71 |
return False
|
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"""Build the embedding-atlas command with all parameters."""
|
76 |
# Use uvx to run embedding-atlas with required dependencies
|
77 |
# Include hf-transfer for faster downloads when HF_HUB_ENABLE_HF_TRANSFER is set
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78 |
+
cmd = [
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+
"uvx",
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80 |
+
"--with",
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81 |
+
"datasets",
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82 |
+
"--with",
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83 |
+
"hf-transfer",
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84 |
+
"embedding-atlas",
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85 |
+
args.dataset_id,
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86 |
+
]
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87 |
# Add all optional parameters
|
88 |
if args.model:
|
89 |
cmd.extend(["--model", args.model])
|
90 |
+
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91 |
# Always specify text column to avoid interactive prompt
|
92 |
text_col = args.text_column or "text" # Default to "text" if not specified
|
93 |
cmd.extend(["--text", text_col])
|
94 |
+
|
95 |
if args.image_column:
|
96 |
cmd.extend(["--image", args.image_column])
|
97 |
+
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98 |
if args.split:
|
99 |
cmd.extend(["--split", args.split])
|
100 |
+
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101 |
if args.sample:
|
102 |
cmd.extend(["--sample", str(args.sample)])
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103 |
+
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104 |
if args.trust_remote_code:
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105 |
cmd.append("--trust-remote-code")
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106 |
+
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107 |
if not args.compute_embeddings:
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108 |
cmd.append("--no-compute-embeddings")
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109 |
+
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110 |
if args.x_column:
|
111 |
cmd.extend(["--x", args.x_column])
|
112 |
+
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113 |
if args.y_column:
|
114 |
cmd.extend(["--y", args.y_column])
|
115 |
+
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116 |
if args.neighbors_column:
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117 |
cmd.extend(["--neighbors", args.neighbors_column])
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118 |
+
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119 |
# Add export flag with output path
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120 |
export_path = "atlas_export.zip"
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121 |
cmd.extend(["--export-application", export_path])
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122 |
+
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123 |
return cmd, export_path
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124 |
|
125 |
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126 |
def create_space_readme(args) -> str:
|
127 |
"""Generate README.md content for the Space."""
|
128 |
title = args.space_name.replace("-", " ").title()
|
129 |
+
|
130 |
readme = f"""---
|
131 |
title: {title}
|
132 |
emoji: ๐บ๏ธ
|
|
|
148 |
- Automatic clustering with labels
|
149 |
- WebGPU-accelerated rendering
|
150 |
"""
|
151 |
+
|
152 |
if args.model:
|
153 |
readme += f"\n## Model\n\nEmbeddings generated using: `{args.model}`\n"
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154 |
+
|
155 |
if args.sample:
|
156 |
readme += f"\n## Data\n\nVisualization includes {args.sample:,} samples from the dataset.\n"
|
157 |
+
|
158 |
readme += """
|
159 |
## How to Use
|
160 |
|
|
|
168 |
|
169 |
*Generated with [UV Scripts Atlas Export](https://huggingface.co/uv-scripts)*
|
170 |
"""
|
171 |
+
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172 |
return readme
|
173 |
|
174 |
|
175 |
def extract_and_prepare_static_files(zip_path: str, output_dir: Path) -> None:
|
176 |
"""Extract the exported atlas ZIP and prepare for static deployment."""
|
177 |
logger.info(f"Extracting {zip_path} to {output_dir}")
|
178 |
+
|
179 |
+
with zipfile.ZipFile(zip_path, "r") as zip_ref:
|
180 |
zip_ref.extractall(output_dir)
|
181 |
+
|
182 |
# The ZIP should contain index.html and associated files
|
183 |
if not (output_dir / "index.html").exists():
|
184 |
raise FileNotFoundError("index.html not found in exported atlas")
|
185 |
+
|
186 |
logger.info(f"Extracted {len(list(output_dir.iterdir()))} items")
|
187 |
|
188 |
|
|
|
191 |
space_name: str,
|
192 |
organization: Optional[str] = None,
|
193 |
private: bool = False,
|
194 |
+
hf_token: Optional[str] = None,
|
195 |
) -> str:
|
196 |
"""Deploy the static files to a HuggingFace Space."""
|
197 |
api = HfApi(token=hf_token)
|
198 |
+
|
199 |
# Construct full repo ID
|
200 |
if organization:
|
201 |
repo_id = f"{organization}/{space_name}"
|
|
|
204 |
user_info = api.whoami()
|
205 |
username = user_info["name"]
|
206 |
repo_id = f"{username}/{space_name}"
|
207 |
+
|
208 |
logger.info(f"Creating Space: {repo_id}")
|
209 |
+
|
210 |
# Create the Space repository
|
211 |
try:
|
212 |
create_repo(
|
|
|
214 |
repo_type="space",
|
215 |
space_sdk="static",
|
216 |
private=private,
|
217 |
+
token=hf_token,
|
218 |
)
|
219 |
logger.info(f"Created new Space: {repo_id}")
|
220 |
except Exception as e:
|
|
|
222 |
logger.info(f"Space {repo_id} already exists, updating...")
|
223 |
else:
|
224 |
raise
|
225 |
+
|
226 |
# Upload all files
|
227 |
logger.info("Uploading files to Space...")
|
228 |
upload_folder(
|
229 |
+
folder_path=str(output_dir), repo_id=repo_id, repo_type="space", token=hf_token
|
|
|
|
|
|
|
230 |
)
|
231 |
+
|
232 |
space_url = f"https://huggingface.co/spaces/{repo_id}"
|
233 |
logger.info(f"โ
Space deployed successfully: {space_url}")
|
234 |
+
|
235 |
return space_url
|
236 |
|
237 |
|
238 |
def main():
|
239 |
# Enable HF Transfer for faster downloads if available
|
240 |
os.environ.setdefault("HF_HUB_ENABLE_HF_TRANSFER", "1")
|
241 |
+
|
242 |
parser = argparse.ArgumentParser(
|
243 |
description="Generate and deploy static Embedding Atlas visualizations",
|
244 |
formatter_class=argparse.RawDescriptionHelpFormatter,
|
245 |
epilog=__doc__,
|
246 |
)
|
247 |
+
|
248 |
# Required arguments
|
249 |
parser.add_argument(
|
250 |
"dataset_id",
|
251 |
type=str,
|
252 |
help="HuggingFace dataset ID to visualize",
|
253 |
)
|
254 |
+
|
255 |
# Space configuration
|
256 |
parser.add_argument(
|
257 |
"--space-name",
|
|
|
269 |
action="store_true",
|
270 |
help="Make the Space private",
|
271 |
)
|
272 |
+
|
273 |
# Atlas configuration
|
274 |
parser.add_argument(
|
275 |
"--model",
|
|
|
302 |
action="store_true",
|
303 |
help="Trust remote code in dataset/model",
|
304 |
)
|
305 |
+
|
306 |
# Pre-computed embeddings
|
307 |
parser.add_argument(
|
308 |
"--no-compute-embeddings",
|
|
|
325 |
type=str,
|
326 |
help="Column with neighbor indices (for pre-computed)",
|
327 |
)
|
328 |
+
|
329 |
# Additional options
|
330 |
parser.add_argument(
|
331 |
"--hf-token",
|
|
|
342 |
type=str,
|
343 |
help="Local directory for output (default: temp directory)",
|
344 |
)
|
345 |
+
|
346 |
args = parser.parse_args()
|
347 |
+
|
348 |
# Check GPU availability
|
349 |
if check_gpu_available():
|
350 |
logger.info("๐ GPU detected - may accelerate embedding generation")
|
351 |
else:
|
352 |
logger.info("๐ป Running on CPU - embedding generation may be slower")
|
353 |
+
|
354 |
# Login to HuggingFace if needed
|
355 |
if not args.local_only:
|
356 |
# Try to get token from various sources
|
357 |
hf_token = (
|
358 |
+
args.hf_token
|
359 |
or os.environ.get("HF_TOKEN")
|
360 |
or os.environ.get("HUGGING_FACE_HUB_TOKEN")
|
361 |
or get_token() # This will check HF CLI login
|
362 |
)
|
363 |
+
|
364 |
if hf_token:
|
365 |
login(token=hf_token)
|
366 |
logger.info("โ
Authenticated with Hugging Face")
|
367 |
else:
|
368 |
# Check if running in non-interactive environment (HF Jobs, CI, etc.)
|
369 |
is_interactive = sys.stdin.isatty()
|
370 |
+
|
371 |
if is_interactive:
|
372 |
+
logger.warning(
|
373 |
+
"No HF token provided. You may not be able to push to the Hub."
|
374 |
+
)
|
375 |
response = input("Continue anyway? (y/n): ")
|
376 |
+
if response.lower() != "y":
|
377 |
sys.exit(0)
|
378 |
else:
|
379 |
# In non-interactive environments, fail immediately if no token
|
380 |
+
logger.error(
|
381 |
+
"No HF token found. Cannot deploy to Space in non-interactive environment."
|
382 |
+
)
|
383 |
+
logger.error(
|
384 |
+
"Please set HF_TOKEN environment variable or use --hf-token argument."
|
385 |
+
)
|
386 |
+
logger.error(
|
387 |
+
"Checked: HF_TOKEN, HUGGING_FACE_HUB_TOKEN, and HF CLI login"
|
388 |
+
)
|
389 |
sys.exit(1)
|
390 |
+
|
391 |
# Set up output directory
|
392 |
if args.output_dir:
|
393 |
output_dir = Path(args.output_dir)
|
|
|
397 |
temp_dir = tempfile.mkdtemp(prefix="atlas_export_")
|
398 |
output_dir = Path(temp_dir)
|
399 |
logger.info(f"Using temporary directory: {output_dir}")
|
400 |
+
|
401 |
try:
|
402 |
# Build and run embedding-atlas command
|
403 |
cmd, export_path = build_atlas_command(args)
|
404 |
logger.info(f"Running command: {' '.join(cmd)}")
|
405 |
+
|
406 |
# Run the command
|
407 |
result = subprocess.run(cmd, capture_output=True, text=True)
|
408 |
+
|
409 |
if result.returncode != 0:
|
410 |
logger.error(f"Atlas export failed with return code {result.returncode}")
|
411 |
logger.error(f"STDOUT: {result.stdout}")
|
412 |
logger.error(f"STDERR: {result.stderr}")
|
413 |
sys.exit(1)
|
414 |
+
|
415 |
logger.info("โ
Atlas export completed successfully")
|
416 |
+
|
417 |
# Extract the exported files
|
418 |
extract_and_prepare_static_files(export_path, output_dir)
|
419 |
+
|
420 |
# Create README for the Space
|
421 |
readme_content = create_space_readme(args)
|
422 |
(output_dir / "README.md").write_text(readme_content)
|
423 |
+
|
424 |
if args.local_only:
|
425 |
logger.info(f"โ
Static files prepared in: {output_dir}")
|
426 |
+
logger.info(
|
427 |
+
"To deploy manually, upload the contents to a HuggingFace Space with sdk: static"
|
428 |
+
)
|
429 |
else:
|
430 |
# Deploy to HuggingFace Space
|
431 |
space_url = deploy_to_space(
|
432 |
+
output_dir, args.space_name, args.organization, args.private, hf_token
|
|
|
|
|
|
|
|
|
433 |
)
|
434 |
+
|
435 |
logger.info(f"\n๐ Success! Your atlas is live at: {space_url}")
|
436 |
logger.info(f"The visualization will be available in a few moments.")
|
437 |
+
|
438 |
# Clean up the ZIP file
|
439 |
if Path(export_path).exists():
|
440 |
os.remove(export_path)
|
441 |
+
|
442 |
finally:
|
443 |
# Clean up temp directory if used
|
444 |
if temp_dir and not args.local_only:
|
|
|
453 |
print("# Basic usage:")
|
454 |
print("uv run atlas-export.py stanfordnlp/imdb --space-name imdb-atlas\n")
|
455 |
print("# With custom model and sampling:")
|
456 |
+
print(
|
457 |
+
"uv run atlas-export.py my-dataset --space-name my-viz --model nomic-ai/nomic-embed-text-v1.5 --sample 10000\n"
|
458 |
+
)
|
459 |
print("# For HF Jobs with GPU (experimental UV support):")
|
460 |
+
print(
|
461 |
+
'# First get your token: python -c "from huggingface_hub import get_token; print(get_token())"'
|
462 |
+
)
|
463 |
+
print(
|
464 |
+
"hf jobs uv run --flavor t4-small -s HF_TOKEN=your-token-here 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"
|
465 |
+
)
|
466 |
print("# Local generation only:")
|
467 |
+
print(
|
468 |
+
"uv run atlas-export.py dataset --space-name test --local-only --output-dir ./atlas-output"
|
469 |
+
)
|
470 |
sys.exit(0)
|
471 |
+
|
472 |
+
main()
|