mirror of
https://github.com/meta-llama/llama-stack.git
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chore!: remove model mgmt from CLI for Hugging Face CLI (#3700)
This change removes the `llama model` and `llama download` subcommands from the CLI, replacing them with recommendations to use the Hugging Face CLI instead. Rationale for this change: - The model management functionality was largely duplicating what Hugging Face CLI already provides, leading to unnecessary maintenance overhead (except the download source from Meta?) - Maintaining our own implementation required fixing bugs and keeping up with changes in model repositories and download mechanisms - The Hugging Face CLI is more mature, widely adopted, and better maintained - This allows us to focus on the core Llama Stack functionality rather than reimplementing model management tools Changes made: - Removed all model-related CLI commands and their implementations - Updated documentation to recommend using `huggingface-cli` for model downloads - Removed Meta-specific download logic and statements - Simplified the CLI to focus solely on stack management operations Users should now use: - `huggingface-cli download` for downloading models - `huggingface-cli scan-cache` for listing downloaded models This is a breaking change as it removes previously available CLI commands. Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han
GitHub
parent
841d0c3583
commit
7ee0ee7843
21 changed files with 63 additions and 1612 deletions
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@ -1,495 +0,0 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import argparse
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import asyncio
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import json
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import os
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import shutil
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import sys
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from dataclasses import dataclass
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from datetime import UTC, datetime
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from functools import partial
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from pathlib import Path
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import httpx
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from pydantic import BaseModel, ConfigDict
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from rich.console import Console
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from rich.progress import (
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BarColumn,
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DownloadColumn,
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Progress,
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TextColumn,
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TimeRemainingColumn,
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TransferSpeedColumn,
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)
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from termcolor import cprint
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from llama_stack.cli.subcommand import Subcommand
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from llama_stack.models.llama.sku_list import LlamaDownloadInfo
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from llama_stack.models.llama.sku_types import Model
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class Download(Subcommand):
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"""Llama cli for downloading llama toolchain assets"""
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def __init__(self, subparsers: argparse._SubParsersAction):
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super().__init__()
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self.parser = subparsers.add_parser(
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"download",
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prog="llama download",
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description="Download a model from llama.meta.com or Hugging Face Hub",
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formatter_class=argparse.RawTextHelpFormatter,
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)
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setup_download_parser(self.parser)
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def setup_download_parser(parser: argparse.ArgumentParser) -> None:
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parser.add_argument(
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"--source",
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choices=["meta", "huggingface"],
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default="meta",
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)
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parser.add_argument(
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"--model-id",
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required=False,
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help="See `llama model list` or `llama model list --show-all` for the list of available models. Specify multiple model IDs with commas, e.g. --model-id Llama3.2-1B,Llama3.2-3B",
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)
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parser.add_argument(
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"--hf-token",
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type=str,
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required=False,
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default=None,
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help="Hugging Face API token. Needed for gated models like llama2/3. Will also try to read environment variable `HF_TOKEN` as default.",
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)
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parser.add_argument(
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"--meta-url",
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type=str,
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required=False,
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help="For source=meta, URL obtained from llama.meta.com after accepting license terms",
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)
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parser.add_argument(
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"--max-parallel",
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type=int,
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required=False,
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default=3,
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help="Maximum number of concurrent downloads",
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)
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parser.add_argument(
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"--ignore-patterns",
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type=str,
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required=False,
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default="*.safetensors",
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help="""For source=huggingface, files matching any of the patterns are not downloaded. Defaults to ignoring
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safetensors files to avoid downloading duplicate weights.
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""",
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)
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parser.add_argument(
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"--manifest-file",
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type=str,
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help="For source=meta, you can download models from a manifest file containing a file => URL mapping",
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required=False,
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)
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parser.set_defaults(func=partial(run_download_cmd, parser=parser))
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@dataclass
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class DownloadTask:
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url: str
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output_file: str
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total_size: int = 0
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downloaded_size: int = 0
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task_id: int | None = None
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retries: int = 0
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max_retries: int = 3
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class DownloadError(Exception):
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pass
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class CustomTransferSpeedColumn(TransferSpeedColumn):
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def render(self, task):
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if task.finished:
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return "-"
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return super().render(task)
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class ParallelDownloader:
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def __init__(
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self,
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max_concurrent_downloads: int = 3,
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buffer_size: int = 1024 * 1024,
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timeout: int = 30,
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):
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self.max_concurrent_downloads = max_concurrent_downloads
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self.buffer_size = buffer_size
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self.timeout = timeout
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self.console = Console()
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self.progress = Progress(
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TextColumn("[bold blue]{task.description}"),
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BarColumn(bar_width=40),
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"[progress.percentage]{task.percentage:>3.1f}%",
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DownloadColumn(),
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CustomTransferSpeedColumn(),
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TimeRemainingColumn(),
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console=self.console,
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expand=True,
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)
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self.client_options = {
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"timeout": httpx.Timeout(timeout),
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"follow_redirects": True,
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}
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async def retry_with_exponential_backoff(self, task: DownloadTask, func, *args, **kwargs):
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last_exception = None
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for attempt in range(task.max_retries):
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try:
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return await func(*args, **kwargs)
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except Exception as e:
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last_exception = e
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if attempt < task.max_retries - 1:
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wait_time = min(30, 2**attempt) # Cap at 30 seconds
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self.console.print(
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f"[yellow]Attempt {attempt + 1}/{task.max_retries} failed, "
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f"retrying in {wait_time} seconds: {str(e)}[/yellow]"
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)
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await asyncio.sleep(wait_time)
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continue
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raise last_exception
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async def get_file_info(self, client: httpx.AsyncClient, task: DownloadTask) -> None:
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if task.total_size > 0:
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self.progress.update(task.task_id, total=task.total_size)
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return
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async def _get_info():
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response = await client.head(task.url, headers={"Accept-Encoding": "identity"}, **self.client_options)
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response.raise_for_status()
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return response
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try:
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response = await self.retry_with_exponential_backoff(task, _get_info)
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task.url = str(response.url)
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task.total_size = int(response.headers.get("Content-Length", 0))
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if task.total_size == 0:
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raise DownloadError(
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f"Unable to determine file size for {task.output_file}. "
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"The server might not support range requests."
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)
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# Update the progress bar's total size once we know it
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if task.task_id is not None:
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self.progress.update(task.task_id, total=task.total_size)
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except httpx.HTTPError as e:
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self.console.print(f"[red]Error getting file info: {str(e)}[/red]")
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raise
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def verify_file_integrity(self, task: DownloadTask) -> bool:
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if not os.path.exists(task.output_file):
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return False
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return os.path.getsize(task.output_file) == task.total_size
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async def download_chunk(self, client: httpx.AsyncClient, task: DownloadTask, start: int, end: int) -> None:
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async def _download_chunk():
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headers = {"Range": f"bytes={start}-{end}"}
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async with client.stream("GET", task.url, headers=headers, **self.client_options) as response:
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response.raise_for_status()
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with open(task.output_file, "ab") as file:
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file.seek(start)
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async for chunk in response.aiter_bytes(self.buffer_size):
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file.write(chunk)
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task.downloaded_size += len(chunk)
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self.progress.update(
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task.task_id,
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completed=task.downloaded_size,
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)
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try:
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await self.retry_with_exponential_backoff(task, _download_chunk)
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except Exception as e:
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raise DownloadError(
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f"Failed to download chunk {start}-{end} after {task.max_retries} attempts: {str(e)}"
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) from e
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async def prepare_download(self, task: DownloadTask) -> None:
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output_dir = os.path.dirname(task.output_file)
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os.makedirs(output_dir, exist_ok=True)
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if os.path.exists(task.output_file):
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task.downloaded_size = os.path.getsize(task.output_file)
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async def download_file(self, task: DownloadTask) -> None:
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try:
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async with httpx.AsyncClient(**self.client_options) as client:
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await self.get_file_info(client, task)
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# Check if file is already downloaded
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if os.path.exists(task.output_file):
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if self.verify_file_integrity(task):
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self.console.print(f"[green]Already downloaded {task.output_file}[/green]")
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self.progress.update(task.task_id, completed=task.total_size)
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return
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await self.prepare_download(task)
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try:
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# Split the remaining download into chunks
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chunk_size = 27_000_000_000 # Cloudfront max chunk size
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chunks = []
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current_pos = task.downloaded_size
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while current_pos < task.total_size:
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chunk_end = min(current_pos + chunk_size - 1, task.total_size - 1)
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chunks.append((current_pos, chunk_end))
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current_pos = chunk_end + 1
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# Download chunks in sequence
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for chunk_start, chunk_end in chunks:
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await self.download_chunk(client, task, chunk_start, chunk_end)
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except Exception as e:
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raise DownloadError(f"Download failed: {str(e)}") from e
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except Exception as e:
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self.progress.update(task.task_id, description=f"[red]Failed: {task.output_file}[/red]")
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raise DownloadError(f"Download failed for {task.output_file}: {str(e)}") from e
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def has_disk_space(self, tasks: list[DownloadTask]) -> bool:
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try:
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total_remaining_size = sum(task.total_size - task.downloaded_size for task in tasks)
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dir_path = os.path.dirname(os.path.abspath(tasks[0].output_file))
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free_space = shutil.disk_usage(dir_path).free
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# Add 10% buffer for safety
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required_space = int(total_remaining_size * 1.1)
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if free_space < required_space:
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self.console.print(
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f"[red]Not enough disk space. Required: {required_space // (1024 * 1024)} MB, "
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f"Available: {free_space // (1024 * 1024)} MB[/red]"
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)
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return False
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return True
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except Exception as e:
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raise DownloadError(f"Failed to check disk space: {str(e)}") from e
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async def download_all(self, tasks: list[DownloadTask]) -> None:
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if not tasks:
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raise ValueError("No download tasks provided")
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if not os.environ.get("LLAMA_DOWNLOAD_NO_SPACE_CHECK") and not self.has_disk_space(tasks):
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raise DownloadError("Insufficient disk space for downloads")
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failed_tasks = []
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with self.progress:
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for task in tasks:
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desc = f"Downloading {Path(task.output_file).name}"
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task.task_id = self.progress.add_task(desc, total=task.total_size, completed=task.downloaded_size)
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semaphore = asyncio.Semaphore(self.max_concurrent_downloads)
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async def download_with_semaphore(task: DownloadTask):
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async with semaphore:
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try:
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await self.download_file(task)
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except Exception as e:
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failed_tasks.append((task, str(e)))
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await asyncio.gather(*(download_with_semaphore(task) for task in tasks))
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if failed_tasks:
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self.console.print("\n[red]Some downloads failed:[/red]")
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for task, error in failed_tasks:
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self.console.print(f"[red]- {Path(task.output_file).name}: {error}[/red]")
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raise DownloadError(f"{len(failed_tasks)} downloads failed")
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def _hf_download(
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model: "Model",
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hf_token: str,
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ignore_patterns: str,
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parser: argparse.ArgumentParser,
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):
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from huggingface_hub import snapshot_download
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from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
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from llama_stack.core.utils.model_utils import model_local_dir
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repo_id = model.huggingface_repo
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if repo_id is None:
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raise ValueError(f"No repo id found for model {model.descriptor()}")
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output_dir = model_local_dir(model.descriptor())
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os.makedirs(output_dir, exist_ok=True)
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try:
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true_output_dir = snapshot_download(
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repo_id,
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local_dir=output_dir,
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ignore_patterns=ignore_patterns,
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token=hf_token,
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library_name="llama-stack",
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)
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except GatedRepoError:
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parser.error(
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"It looks like you are trying to access a gated repository. Please ensure you "
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"have access to the repository and have provided the proper Hugging Face API token "
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"using the option `--hf-token` or by running `huggingface-cli login`."
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"You can find your token by visiting https://huggingface.co/settings/tokens"
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)
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except RepositoryNotFoundError:
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parser.error(f"Repository '{repo_id}' not found on the Hugging Face Hub or incorrect Hugging Face token.")
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except Exception as e:
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parser.error(e)
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print(f"\nSuccessfully downloaded model to {true_output_dir}")
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def _meta_download(
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model: "Model",
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model_id: str,
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meta_url: str,
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info: "LlamaDownloadInfo",
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max_concurrent_downloads: int,
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):
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from llama_stack.core.utils.model_utils import model_local_dir
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output_dir = Path(model_local_dir(model.descriptor()))
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os.makedirs(output_dir, exist_ok=True)
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# Create download tasks for each file
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tasks = []
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for f in info.files:
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output_file = str(output_dir / f)
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url = meta_url.replace("*", f"{info.folder}/{f}")
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total_size = info.pth_size if "consolidated" in f else 0
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tasks.append(DownloadTask(url=url, output_file=output_file, total_size=total_size, max_retries=3))
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# Initialize and run parallel downloader
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downloader = ParallelDownloader(max_concurrent_downloads=max_concurrent_downloads)
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asyncio.run(downloader.download_all(tasks))
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cprint(f"\nSuccessfully downloaded model to {output_dir}", color="green", file=sys.stderr)
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cprint(
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f"\nView MD5 checksum files at: {output_dir / 'checklist.chk'}",
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file=sys.stderr,
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)
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cprint(
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f"\n[Optionally] To run MD5 checksums, use the following command: llama model verify-download --model-id {model_id}",
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color="yellow",
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file=sys.stderr,
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)
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class ModelEntry(BaseModel):
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model_id: str
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files: dict[str, str]
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model_config = ConfigDict(protected_namespaces=())
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class Manifest(BaseModel):
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models: list[ModelEntry]
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expires_on: datetime
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def _download_from_manifest(manifest_file: str, max_concurrent_downloads: int):
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from llama_stack.core.utils.model_utils import model_local_dir
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with open(manifest_file) as f:
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d = json.load(f)
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manifest = Manifest(**d)
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if datetime.now(UTC) > manifest.expires_on.astimezone(UTC):
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raise ValueError(f"Manifest URLs have expired on {manifest.expires_on}")
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console = Console()
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for entry in manifest.models:
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console.print(f"[blue]Downloading model {entry.model_id}...[/blue]")
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output_dir = Path(model_local_dir(entry.model_id))
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os.makedirs(output_dir, exist_ok=True)
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if any(output_dir.iterdir()):
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console.print(f"[yellow]Output directory {output_dir} is not empty.[/yellow]")
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while True:
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resp = input("Do you want to (C)ontinue download or (R)estart completely? (continue/restart): ")
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if resp.lower() in ["restart", "r"]:
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shutil.rmtree(output_dir)
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os.makedirs(output_dir, exist_ok=True)
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break
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elif resp.lower() in ["continue", "c"]:
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console.print("[blue]Continuing download...[/blue]")
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break
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else:
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console.print("[red]Invalid response. Please try again.[/red]")
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# Create download tasks for all files in the manifest
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tasks = [
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DownloadTask(url=url, output_file=str(output_dir / fname), max_retries=3)
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for fname, url in entry.files.items()
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]
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# Initialize and run parallel downloader
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downloader = ParallelDownloader(max_concurrent_downloads=max_concurrent_downloads)
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asyncio.run(downloader.download_all(tasks))
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|
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def run_download_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser):
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"""Main download command handler"""
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try:
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if args.manifest_file:
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_download_from_manifest(args.manifest_file, args.max_parallel)
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return
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|
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if args.model_id is None:
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parser.error("Please provide a model id")
|
||||
return
|
||||
|
||||
# Handle comma-separated model IDs
|
||||
model_ids = [model_id.strip() for model_id in args.model_id.split(",")]
|
||||
|
||||
from llama_stack.models.llama.sku_list import llama_meta_net_info, resolve_model
|
||||
|
||||
from .model.safety_models import (
|
||||
prompt_guard_download_info_map,
|
||||
prompt_guard_model_sku_map,
|
||||
)
|
||||
|
||||
prompt_guard_model_sku_map = prompt_guard_model_sku_map()
|
||||
prompt_guard_download_info_map = prompt_guard_download_info_map()
|
||||
|
||||
for model_id in model_ids:
|
||||
if model_id in prompt_guard_model_sku_map.keys():
|
||||
model = prompt_guard_model_sku_map[model_id]
|
||||
info = prompt_guard_download_info_map[model_id]
|
||||
else:
|
||||
model = resolve_model(model_id)
|
||||
if model is None:
|
||||
parser.error(f"Model {model_id} not found")
|
||||
continue
|
||||
info = llama_meta_net_info(model)
|
||||
|
||||
if args.source == "huggingface":
|
||||
_hf_download(model, args.hf_token, args.ignore_patterns, parser)
|
||||
else:
|
||||
meta_url = args.meta_url or input(
|
||||
f"Please provide the signed URL for model {model_id} you received via email "
|
||||
f"after visiting https://www.llama.com/llama-downloads/ "
|
||||
f"(e.g., https://llama3-1.llamameta.net/*?Policy...): "
|
||||
)
|
||||
if "llamameta.net" not in meta_url:
|
||||
parser.error("Invalid Meta URL provided")
|
||||
_meta_download(model, model_id, meta_url, info, args.max_parallel)
|
||||
|
||||
except Exception as e:
|
||||
parser.error(f"Download failed: {str(e)}")
|
||||
|
|
@ -6,11 +6,8 @@
|
|||
|
||||
import argparse
|
||||
|
||||
from .download import Download
|
||||
from .model import ModelParser
|
||||
from .stack import StackParser
|
||||
from .stack.utils import print_subcommand_description
|
||||
from .verify_download import VerifyDownload
|
||||
|
||||
|
||||
class LlamaCLIParser:
|
||||
|
|
@ -30,10 +27,7 @@ class LlamaCLIParser:
|
|||
subparsers = self.parser.add_subparsers(title="subcommands")
|
||||
|
||||
# Add sub-commands
|
||||
ModelParser.create(subparsers)
|
||||
StackParser.create(subparsers)
|
||||
Download.create(subparsers)
|
||||
VerifyDownload.create(subparsers)
|
||||
|
||||
print_subcommand_description(self.parser, subparsers)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
from .model import ModelParser # noqa
|
||||
|
|
@ -1,70 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
import json
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
from llama_stack.cli.table import print_table
|
||||
from llama_stack.models.llama.sku_list import resolve_model
|
||||
|
||||
|
||||
class ModelDescribe(Subcommand):
|
||||
"""Show details about a model"""
|
||||
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"describe",
|
||||
prog="llama model describe",
|
||||
description="Show details about a llama model",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
self._add_arguments()
|
||||
self.parser.set_defaults(func=self._run_model_describe_cmd)
|
||||
|
||||
def _add_arguments(self):
|
||||
self.parser.add_argument(
|
||||
"-m",
|
||||
"--model-id",
|
||||
type=str,
|
||||
required=True,
|
||||
help="See `llama model list` or `llama model list --show-all` for the list of available models",
|
||||
)
|
||||
|
||||
def _run_model_describe_cmd(self, args: argparse.Namespace) -> None:
|
||||
from .safety_models import prompt_guard_model_sku_map
|
||||
|
||||
prompt_guard_model_map = prompt_guard_model_sku_map()
|
||||
if args.model_id in prompt_guard_model_map.keys():
|
||||
model = prompt_guard_model_map[args.model_id]
|
||||
else:
|
||||
model = resolve_model(args.model_id)
|
||||
|
||||
if model is None:
|
||||
self.parser.error(
|
||||
f"Model {args.model_id} not found; try 'llama model list' for a list of available models."
|
||||
)
|
||||
return
|
||||
|
||||
headers = [
|
||||
"Model",
|
||||
model.descriptor(),
|
||||
]
|
||||
|
||||
rows = [
|
||||
("Hugging Face ID", model.huggingface_repo or "<Not Available>"),
|
||||
("Description", model.description),
|
||||
("Context Length", f"{model.max_seq_length // 1024}K tokens"),
|
||||
("Weights format", model.quantization_format.value),
|
||||
("Model params.json", json.dumps(model.arch_args, indent=4)),
|
||||
]
|
||||
|
||||
print_table(
|
||||
rows,
|
||||
headers,
|
||||
separate_rows=True,
|
||||
)
|
||||
|
|
@ -1,24 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
|
||||
|
||||
class ModelDownload(Subcommand):
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"download",
|
||||
prog="llama model download",
|
||||
description="Download a model from llama.meta.com or Hugging Face Hub",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
|
||||
from llama_stack.cli.download import setup_download_parser
|
||||
|
||||
setup_download_parser(self.parser)
|
||||
|
|
@ -1,119 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
import os
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
from llama_stack.cli.table import print_table
|
||||
from llama_stack.core.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
|
||||
from llama_stack.models.llama.sku_list import all_registered_models
|
||||
|
||||
|
||||
def _get_model_size(model_dir):
|
||||
return sum(f.stat().st_size for f in Path(model_dir).rglob("*") if f.is_file())
|
||||
|
||||
|
||||
def _convert_to_model_descriptor(model):
|
||||
for m in all_registered_models():
|
||||
if model == m.descriptor().replace(":", "-"):
|
||||
return str(m.descriptor())
|
||||
return str(model)
|
||||
|
||||
|
||||
def _run_model_list_downloaded_cmd() -> None:
|
||||
headers = ["Model", "Size", "Modified Time"]
|
||||
|
||||
rows = []
|
||||
for model in os.listdir(DEFAULT_CHECKPOINT_DIR):
|
||||
abs_path = os.path.join(DEFAULT_CHECKPOINT_DIR, model)
|
||||
space_usage = _get_model_size(abs_path)
|
||||
model_size = f"{space_usage / (1024**3):.2f} GB"
|
||||
modified_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(os.path.getmtime(abs_path)))
|
||||
rows.append(
|
||||
[
|
||||
_convert_to_model_descriptor(model),
|
||||
model_size,
|
||||
modified_time,
|
||||
]
|
||||
)
|
||||
|
||||
print_table(
|
||||
rows,
|
||||
headers,
|
||||
separate_rows=True,
|
||||
)
|
||||
|
||||
|
||||
class ModelList(Subcommand):
|
||||
"""List available llama models"""
|
||||
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"list",
|
||||
prog="llama model list",
|
||||
description="Show available llama models",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
self._add_arguments()
|
||||
self.parser.set_defaults(func=self._run_model_list_cmd)
|
||||
|
||||
def _add_arguments(self):
|
||||
self.parser.add_argument(
|
||||
"--show-all",
|
||||
action="store_true",
|
||||
help="Show all models (not just defaults)",
|
||||
)
|
||||
self.parser.add_argument(
|
||||
"--downloaded",
|
||||
action="store_true",
|
||||
help="List the downloaded models",
|
||||
)
|
||||
self.parser.add_argument(
|
||||
"-s",
|
||||
"--search",
|
||||
type=str,
|
||||
required=False,
|
||||
help="Search for the input string as a substring in the model descriptor(ID)",
|
||||
)
|
||||
|
||||
def _run_model_list_cmd(self, args: argparse.Namespace) -> None:
|
||||
from .safety_models import prompt_guard_model_skus
|
||||
|
||||
if args.downloaded:
|
||||
return _run_model_list_downloaded_cmd()
|
||||
|
||||
headers = [
|
||||
"Model Descriptor(ID)",
|
||||
"Hugging Face Repo",
|
||||
"Context Length",
|
||||
]
|
||||
|
||||
rows = []
|
||||
for model in all_registered_models() + prompt_guard_model_skus():
|
||||
if not args.show_all and not model.is_featured:
|
||||
continue
|
||||
|
||||
descriptor = model.descriptor()
|
||||
if not args.search or args.search.lower() in descriptor.lower():
|
||||
rows.append(
|
||||
[
|
||||
descriptor,
|
||||
model.huggingface_repo,
|
||||
f"{model.max_seq_length // 1024}K",
|
||||
]
|
||||
)
|
||||
if len(rows) == 0:
|
||||
print(f"Did not find any model matching `{args.search}`.")
|
||||
else:
|
||||
print_table(
|
||||
rows,
|
||||
headers,
|
||||
separate_rows=True,
|
||||
)
|
||||
|
|
@ -1,43 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
|
||||
from llama_stack.cli.model.describe import ModelDescribe
|
||||
from llama_stack.cli.model.download import ModelDownload
|
||||
from llama_stack.cli.model.list import ModelList
|
||||
from llama_stack.cli.model.prompt_format import ModelPromptFormat
|
||||
from llama_stack.cli.model.remove import ModelRemove
|
||||
from llama_stack.cli.model.verify_download import ModelVerifyDownload
|
||||
from llama_stack.cli.stack.utils import print_subcommand_description
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
|
||||
|
||||
class ModelParser(Subcommand):
|
||||
"""Llama cli for model interface apis"""
|
||||
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"model",
|
||||
prog="llama model",
|
||||
description="Work with llama models",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
|
||||
self.parser.set_defaults(func=lambda args: self.parser.print_help())
|
||||
|
||||
subparsers = self.parser.add_subparsers(title="model_subcommands")
|
||||
|
||||
# Add sub-commands
|
||||
ModelDownload.create(subparsers)
|
||||
ModelList.create(subparsers)
|
||||
ModelPromptFormat.create(subparsers)
|
||||
ModelDescribe.create(subparsers)
|
||||
ModelVerifyDownload.create(subparsers)
|
||||
ModelRemove.create(subparsers)
|
||||
|
||||
print_subcommand_description(self.parser, subparsers)
|
||||
|
|
@ -1,133 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
import textwrap
|
||||
from io import StringIO
|
||||
from pathlib import Path
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
from llama_stack.cli.table import print_table
|
||||
from llama_stack.models.llama.sku_types import CoreModelId, ModelFamily, is_multimodal, model_family
|
||||
|
||||
ROOT_DIR = Path(__file__).parent.parent.parent
|
||||
|
||||
|
||||
class ModelPromptFormat(Subcommand):
|
||||
"""Llama model cli for describe a model prompt format (message formats)"""
|
||||
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"prompt-format",
|
||||
prog="llama model prompt-format",
|
||||
description="Show llama model message formats",
|
||||
epilog=textwrap.dedent(
|
||||
"""
|
||||
Example:
|
||||
llama model prompt-format <options>
|
||||
"""
|
||||
),
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
self._add_arguments()
|
||||
self.parser.set_defaults(func=self._run_model_template_cmd)
|
||||
|
||||
def _add_arguments(self):
|
||||
self.parser.add_argument(
|
||||
"-m",
|
||||
"--model-name",
|
||||
type=str,
|
||||
help="Example: Llama3.1-8B or Llama3.2-11B-Vision, etc\n"
|
||||
"(Run `llama model list` to see a list of valid model names)",
|
||||
)
|
||||
self.parser.add_argument(
|
||||
"-l",
|
||||
"--list",
|
||||
action="store_true",
|
||||
help="List all available models",
|
||||
)
|
||||
|
||||
def _run_model_template_cmd(self, args: argparse.Namespace) -> None:
|
||||
import importlib.resources
|
||||
|
||||
# Only Llama 3.1 and 3.2 are supported
|
||||
supported_model_ids = [
|
||||
m for m in CoreModelId if model_family(m) in {ModelFamily.llama3_1, ModelFamily.llama3_2}
|
||||
]
|
||||
|
||||
model_list = [m.value for m in supported_model_ids]
|
||||
|
||||
if args.list:
|
||||
headers = ["Model(s)"]
|
||||
rows = []
|
||||
for m in model_list:
|
||||
rows.append(
|
||||
[
|
||||
m,
|
||||
]
|
||||
)
|
||||
print_table(
|
||||
rows,
|
||||
headers,
|
||||
separate_rows=True,
|
||||
)
|
||||
return
|
||||
|
||||
try:
|
||||
model_id = CoreModelId(args.model_name)
|
||||
except ValueError:
|
||||
self.parser.error(
|
||||
f"{args.model_name} is not a valid Model. Choose one from the list of valid models. "
|
||||
f"Run `llama model list` to see the valid model names."
|
||||
)
|
||||
|
||||
if model_id not in supported_model_ids:
|
||||
self.parser.error(
|
||||
f"{model_id} is not a valid Model. Choose one from the list of valid models. "
|
||||
f"Run `llama model list` to see the valid model names."
|
||||
)
|
||||
|
||||
llama_3_1_file = ROOT_DIR / "models" / "llama" / "llama3_1" / "prompt_format.md"
|
||||
llama_3_2_text_file = ROOT_DIR / "models" / "llama" / "llama3_2" / "text_prompt_format.md"
|
||||
llama_3_2_vision_file = ROOT_DIR / "models" / "llama" / "llama3_2" / "vision_prompt_format.md"
|
||||
if model_family(model_id) == ModelFamily.llama3_1:
|
||||
with importlib.resources.as_file(llama_3_1_file) as f:
|
||||
content = f.open("r").read()
|
||||
elif model_family(model_id) == ModelFamily.llama3_2:
|
||||
if is_multimodal(model_id):
|
||||
with importlib.resources.as_file(llama_3_2_vision_file) as f:
|
||||
content = f.open("r").read()
|
||||
else:
|
||||
with importlib.resources.as_file(llama_3_2_text_file) as f:
|
||||
content = f.open("r").read()
|
||||
|
||||
render_markdown_to_pager(content)
|
||||
|
||||
|
||||
def render_markdown_to_pager(markdown_content: str):
|
||||
from rich.console import Console
|
||||
from rich.markdown import Markdown
|
||||
from rich.style import Style
|
||||
from rich.text import Text
|
||||
|
||||
class LeftAlignedHeaderMarkdown(Markdown):
|
||||
def parse_header(self, token):
|
||||
level = token.type.count("h")
|
||||
content = Text(token.content)
|
||||
header_style = Style(color="bright_blue", bold=True)
|
||||
header = Text(f"{'#' * level} ", style=header_style) + content
|
||||
self.add_text(header)
|
||||
|
||||
# Render the Markdown
|
||||
md = LeftAlignedHeaderMarkdown(markdown_content)
|
||||
|
||||
# Capture the rendered output
|
||||
output = StringIO()
|
||||
console = Console(file=output, force_terminal=True, width=100) # Set a fixed width
|
||||
console.print(md)
|
||||
rendered_content = output.getvalue()
|
||||
print(rendered_content)
|
||||
|
|
@ -1,68 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
import os
|
||||
import shutil
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
from llama_stack.core.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
|
||||
from llama_stack.models.llama.sku_list import resolve_model
|
||||
|
||||
|
||||
class ModelRemove(Subcommand):
|
||||
"""Remove the downloaded llama model"""
|
||||
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"remove",
|
||||
prog="llama model remove",
|
||||
description="Remove the downloaded llama model",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
self._add_arguments()
|
||||
self.parser.set_defaults(func=self._run_model_remove_cmd)
|
||||
|
||||
def _add_arguments(self):
|
||||
self.parser.add_argument(
|
||||
"-m",
|
||||
"--model",
|
||||
required=True,
|
||||
help="Specify the llama downloaded model name, see `llama model list --downloaded`",
|
||||
)
|
||||
self.parser.add_argument(
|
||||
"-f",
|
||||
"--force",
|
||||
action="store_true",
|
||||
help="Used to forcefully remove the llama model from the storage without further confirmation",
|
||||
)
|
||||
|
||||
def _run_model_remove_cmd(self, args: argparse.Namespace) -> None:
|
||||
from .safety_models import prompt_guard_model_sku_map
|
||||
|
||||
prompt_guard_model_map = prompt_guard_model_sku_map()
|
||||
|
||||
if args.model in prompt_guard_model_map.keys():
|
||||
model = prompt_guard_model_map[args.model]
|
||||
else:
|
||||
model = resolve_model(args.model)
|
||||
|
||||
model_path = os.path.join(DEFAULT_CHECKPOINT_DIR, args.model.replace(":", "-"))
|
||||
|
||||
if model is None or not os.path.isdir(model_path):
|
||||
print(f"'{args.model}' is not a valid llama model or does not exist.")
|
||||
return
|
||||
|
||||
if args.force:
|
||||
shutil.rmtree(model_path)
|
||||
print(f"{args.model} removed.")
|
||||
else:
|
||||
if input(f"Are you sure you want to remove {args.model}? (y/n): ").strip().lower() == "y":
|
||||
shutil.rmtree(model_path)
|
||||
print(f"{args.model} removed.")
|
||||
else:
|
||||
print("Removal aborted.")
|
||||
|
|
@ -1,64 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
from typing import Any
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field
|
||||
|
||||
from llama_stack.models.llama.sku_list import LlamaDownloadInfo
|
||||
from llama_stack.models.llama.sku_types import CheckpointQuantizationFormat
|
||||
|
||||
|
||||
class PromptGuardModel(BaseModel):
|
||||
"""Make a 'fake' Model-like object for Prompt Guard. Eventually this will be removed."""
|
||||
|
||||
model_id: str
|
||||
huggingface_repo: str
|
||||
description: str = "Prompt Guard. NOTE: this model will not be provided via `llama` CLI soon."
|
||||
is_featured: bool = False
|
||||
max_seq_length: int = 512
|
||||
is_instruct_model: bool = False
|
||||
quantization_format: CheckpointQuantizationFormat = CheckpointQuantizationFormat.bf16
|
||||
arch_args: dict[str, Any] = Field(default_factory=dict)
|
||||
|
||||
def descriptor(self) -> str:
|
||||
return self.model_id
|
||||
|
||||
model_config = ConfigDict(protected_namespaces=())
|
||||
|
||||
|
||||
def prompt_guard_model_skus():
|
||||
return [
|
||||
PromptGuardModel(model_id="Prompt-Guard-86M", huggingface_repo="meta-llama/Prompt-Guard-86M"),
|
||||
PromptGuardModel(
|
||||
model_id="Llama-Prompt-Guard-2-86M",
|
||||
huggingface_repo="meta-llama/Llama-Prompt-Guard-2-86M",
|
||||
),
|
||||
PromptGuardModel(
|
||||
model_id="Llama-Prompt-Guard-2-22M",
|
||||
huggingface_repo="meta-llama/Llama-Prompt-Guard-2-22M",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
def prompt_guard_model_sku_map() -> dict[str, Any]:
|
||||
return {model.model_id: model for model in prompt_guard_model_skus()}
|
||||
|
||||
|
||||
def prompt_guard_download_info_map() -> dict[str, LlamaDownloadInfo]:
|
||||
return {
|
||||
model.model_id: LlamaDownloadInfo(
|
||||
folder="Prompt-Guard" if model.model_id == "Prompt-Guard-86M" else model.model_id,
|
||||
files=[
|
||||
"model.safetensors",
|
||||
"special_tokens_map.json",
|
||||
"tokenizer.json",
|
||||
"tokenizer_config.json",
|
||||
],
|
||||
pth_size=1,
|
||||
)
|
||||
for model in prompt_guard_model_skus()
|
||||
}
|
||||
|
|
@ -1,24 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
|
||||
|
||||
class ModelVerifyDownload(Subcommand):
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"verify-download",
|
||||
prog="llama model verify-download",
|
||||
description="Verify the downloaded checkpoints' checksums for models downloaded from Meta",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
|
||||
from llama_stack.cli.verify_download import setup_verify_download_parser
|
||||
|
||||
setup_verify_download_parser(self.parser)
|
||||
|
|
@ -1,141 +0,0 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import argparse
|
||||
import hashlib
|
||||
from dataclasses import dataclass
|
||||
from functools import partial
|
||||
from pathlib import Path
|
||||
|
||||
from rich.console import Console
|
||||
from rich.progress import Progress, SpinnerColumn, TextColumn
|
||||
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
|
||||
|
||||
@dataclass
|
||||
class VerificationResult:
|
||||
filename: str
|
||||
expected_hash: str
|
||||
actual_hash: str | None
|
||||
exists: bool
|
||||
matches: bool
|
||||
|
||||
|
||||
class VerifyDownload(Subcommand):
|
||||
"""Llama cli for verifying downloaded model files"""
|
||||
|
||||
def __init__(self, subparsers: argparse._SubParsersAction):
|
||||
super().__init__()
|
||||
self.parser = subparsers.add_parser(
|
||||
"verify-download",
|
||||
prog="llama verify-download",
|
||||
description="Verify integrity of downloaded model files",
|
||||
formatter_class=argparse.RawTextHelpFormatter,
|
||||
)
|
||||
setup_verify_download_parser(self.parser)
|
||||
|
||||
|
||||
def setup_verify_download_parser(parser: argparse.ArgumentParser) -> None:
|
||||
parser.add_argument(
|
||||
"--model-id",
|
||||
required=True,
|
||||
help="Model ID to verify (only for models downloaded from Meta)",
|
||||
)
|
||||
parser.set_defaults(func=partial(run_verify_cmd, parser=parser))
|
||||
|
||||
|
||||
def calculate_sha256(filepath: Path, chunk_size: int = 8192) -> str:
|
||||
sha256_hash = hashlib.sha256()
|
||||
with open(filepath, "rb") as f:
|
||||
for chunk in iter(lambda: f.read(chunk_size), b""):
|
||||
sha256_hash.update(chunk)
|
||||
return sha256_hash.hexdigest()
|
||||
|
||||
|
||||
def load_checksums(checklist_path: Path) -> dict[str, str]:
|
||||
checksums = {}
|
||||
with open(checklist_path) as f:
|
||||
for line in f:
|
||||
if line.strip():
|
||||
sha256sum, filepath = line.strip().split(" ", 1)
|
||||
# Remove leading './' if present
|
||||
filepath = filepath.lstrip("./")
|
||||
checksums[filepath] = sha256sum
|
||||
return checksums
|
||||
|
||||
|
||||
def verify_files(model_dir: Path, checksums: dict[str, str], console: Console) -> list[VerificationResult]:
|
||||
results = []
|
||||
|
||||
with Progress(
|
||||
SpinnerColumn(),
|
||||
TextColumn("[progress.description]{task.description}"),
|
||||
console=console,
|
||||
) as progress:
|
||||
for filepath, expected_hash in checksums.items():
|
||||
full_path = model_dir / filepath
|
||||
task_id = progress.add_task(f"Verifying {filepath}...", total=None)
|
||||
|
||||
exists = full_path.exists()
|
||||
actual_hash = None
|
||||
matches = False
|
||||
|
||||
if exists:
|
||||
actual_hash = calculate_sha256(full_path)
|
||||
matches = actual_hash == expected_hash
|
||||
|
||||
results.append(
|
||||
VerificationResult(
|
||||
filename=filepath,
|
||||
expected_hash=expected_hash,
|
||||
actual_hash=actual_hash,
|
||||
exists=exists,
|
||||
matches=matches,
|
||||
)
|
||||
)
|
||||
|
||||
progress.remove_task(task_id)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def run_verify_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser):
|
||||
from llama_stack.core.utils.model_utils import model_local_dir
|
||||
|
||||
console = Console()
|
||||
model_dir = Path(model_local_dir(args.model_id))
|
||||
checklist_path = model_dir / "checklist.chk"
|
||||
|
||||
if not model_dir.exists():
|
||||
parser.error(f"Model directory not found: {model_dir}")
|
||||
|
||||
if not checklist_path.exists():
|
||||
parser.error(f"Checklist file not found: {checklist_path}")
|
||||
|
||||
checksums = load_checksums(checklist_path)
|
||||
results = verify_files(model_dir, checksums, console)
|
||||
|
||||
# Print results
|
||||
console.print("\nVerification Results:")
|
||||
|
||||
all_good = True
|
||||
for result in results:
|
||||
if not result.exists:
|
||||
console.print(f"[red]❌ {result.filename}: File not found[/red]")
|
||||
all_good = False
|
||||
elif not result.matches:
|
||||
console.print(
|
||||
f"[red]❌ {result.filename}: Hash mismatch[/red]\n"
|
||||
f" Expected: {result.expected_hash}\n"
|
||||
f" Got: {result.actual_hash}"
|
||||
)
|
||||
all_good = False
|
||||
else:
|
||||
console.print(f"[green]✓ {result.filename}: Verified[/green]")
|
||||
|
||||
if all_good:
|
||||
console.print("\n[green]All files verified successfully![/green]")
|
||||
|
|
@ -29,31 +29,7 @@ The following environment variables can be configured:
|
|||
|
||||
## Prerequisite: Downloading Models
|
||||
|
||||
Please use `llama model list --downloaded` to check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](../../references/llama_cli_reference/download_models.md) here to download the models. Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints.
|
||||
|
||||
```
|
||||
$ llama model list --downloaded
|
||||
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
|
||||
┃ Model ┃ Size ┃ Modified Time ┃
|
||||
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
|
||||
│ Llama3.2-1B-Instruct:int4-qlora-eo8 │ 1.53 GB │ 2025-02-26 11:22:28 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama3.2-1B │ 2.31 GB │ 2025-02-18 21:48:52 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Prompt-Guard-86M │ 0.02 GB │ 2025-02-26 11:29:28 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama3.2-3B-Instruct:int4-spinquant-eo8 │ 3.69 GB │ 2025-02-26 11:37:41 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama3.2-3B │ 5.99 GB │ 2025-02-18 21:51:26 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama3.1-8B │ 14.97 GB │ 2025-02-16 10:36:37 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama3.2-1B-Instruct:int4-spinquant-eo8 │ 1.51 GB │ 2025-02-26 11:35:02 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama-Guard-3-1B │ 2.80 GB │ 2025-02-26 11:20:46 │
|
||||
├─────────────────────────────────────────┼──────────┼─────────────────────┤
|
||||
│ Llama-Guard-3-1B:int4 │ 0.43 GB │ 2025-02-26 11:33:33 │
|
||||
└─────────────────────────────────────────┴──────────┴─────────────────────┘
|
||||
Please check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](../../references/llama_cli_reference/download_models.md) here to download the models using the Hugging Face CLI.
|
||||
```
|
||||
|
||||
## Running the Distribution
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue