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https://github.com/meta-llama/llama-stack.git
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Merge remote-tracking branch 'origin/main' into stores
This commit is contained in:
commit
b72154ce5e
1161 changed files with 609896 additions and 42960 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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|
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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(
|
||||
"--source",
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||||
choices=["meta", "huggingface"],
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||||
default="meta",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--model-id",
|
||||
required=False,
|
||||
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",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--hf-token",
|
||||
type=str,
|
||||
required=False,
|
||||
default=None,
|
||||
help="Hugging Face API token. Needed for gated models like llama2/3. Will also try to read environment variable `HF_TOKEN` as default.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--meta-url",
|
||||
type=str,
|
||||
required=False,
|
||||
help="For source=meta, URL obtained from llama.meta.com after accepting license terms",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--max-parallel",
|
||||
type=int,
|
||||
required=False,
|
||||
default=3,
|
||||
help="Maximum number of concurrent downloads",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--ignore-patterns",
|
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type=str,
|
||||
required=False,
|
||||
default="*.safetensors",
|
||||
help="""For source=huggingface, files matching any of the patterns are not downloaded. Defaults to ignoring
|
||||
safetensors files to avoid downloading duplicate weights.
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||||
""",
|
||||
)
|
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parser.add_argument(
|
||||
"--manifest-file",
|
||||
type=str,
|
||||
help="For source=meta, you can download models from a manifest file containing a file => URL mapping",
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||||
required=False,
|
||||
)
|
||||
parser.set_defaults(func=partial(run_download_cmd, parser=parser))
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|
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|
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@dataclass
|
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class DownloadTask:
|
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url: str
|
||||
output_file: str
|
||||
total_size: int = 0
|
||||
downloaded_size: int = 0
|
||||
task_id: int | None = None
|
||||
retries: int = 0
|
||||
max_retries: int = 3
|
||||
|
||||
|
||||
class DownloadError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class CustomTransferSpeedColumn(TransferSpeedColumn):
|
||||
def render(self, task):
|
||||
if task.finished:
|
||||
return "-"
|
||||
return super().render(task)
|
||||
|
||||
|
||||
class ParallelDownloader:
|
||||
def __init__(
|
||||
self,
|
||||
max_concurrent_downloads: int = 3,
|
||||
buffer_size: int = 1024 * 1024,
|
||||
timeout: int = 30,
|
||||
):
|
||||
self.max_concurrent_downloads = max_concurrent_downloads
|
||||
self.buffer_size = buffer_size
|
||||
self.timeout = timeout
|
||||
self.console = Console()
|
||||
self.progress = Progress(
|
||||
TextColumn("[bold blue]{task.description}"),
|
||||
BarColumn(bar_width=40),
|
||||
"[progress.percentage]{task.percentage:>3.1f}%",
|
||||
DownloadColumn(),
|
||||
CustomTransferSpeedColumn(),
|
||||
TimeRemainingColumn(),
|
||||
console=self.console,
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||||
expand=True,
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||||
)
|
||||
self.client_options = {
|
||||
"timeout": httpx.Timeout(timeout),
|
||||
"follow_redirects": True,
|
||||
}
|
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|
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async def retry_with_exponential_backoff(self, task: DownloadTask, func, *args, **kwargs):
|
||||
last_exception = None
|
||||
for attempt in range(task.max_retries):
|
||||
try:
|
||||
return await func(*args, **kwargs)
|
||||
except Exception as e:
|
||||
last_exception = e
|
||||
if attempt < task.max_retries - 1:
|
||||
wait_time = min(30, 2**attempt) # Cap at 30 seconds
|
||||
self.console.print(
|
||||
f"[yellow]Attempt {attempt + 1}/{task.max_retries} failed, "
|
||||
f"retrying in {wait_time} seconds: {str(e)}[/yellow]"
|
||||
)
|
||||
await asyncio.sleep(wait_time)
|
||||
continue
|
||||
raise last_exception
|
||||
|
||||
async def get_file_info(self, client: httpx.AsyncClient, task: DownloadTask) -> None:
|
||||
if task.total_size > 0:
|
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self.progress.update(task.task_id, total=task.total_size)
|
||||
return
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|
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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)
|
||||
response.raise_for_status()
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return response
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|
||||
try:
|
||||
response = await self.retry_with_exponential_backoff(task, _get_info)
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|
||||
task.url = str(response.url)
|
||||
task.total_size = int(response.headers.get("Content-Length", 0))
|
||||
|
||||
if task.total_size == 0:
|
||||
raise DownloadError(
|
||||
f"Unable to determine file size for {task.output_file}. "
|
||||
"The server might not support range requests."
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||||
)
|
||||
|
||||
# Update the progress bar's total size once we know it
|
||||
if task.task_id is not None:
|
||||
self.progress.update(task.task_id, total=task.total_size)
|
||||
|
||||
except httpx.HTTPError as e:
|
||||
self.console.print(f"[red]Error getting file info: {str(e)}[/red]")
|
||||
raise
|
||||
|
||||
def verify_file_integrity(self, task: DownloadTask) -> bool:
|
||||
if not os.path.exists(task.output_file):
|
||||
return False
|
||||
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:
|
||||
async def _download_chunk():
|
||||
headers = {"Range": f"bytes={start}-{end}"}
|
||||
async with client.stream("GET", task.url, headers=headers, **self.client_options) as response:
|
||||
response.raise_for_status()
|
||||
|
||||
with open(task.output_file, "ab") as file:
|
||||
file.seek(start)
|
||||
async for chunk in response.aiter_bytes(self.buffer_size):
|
||||
file.write(chunk)
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||||
task.downloaded_size += len(chunk)
|
||||
self.progress.update(
|
||||
task.task_id,
|
||||
completed=task.downloaded_size,
|
||||
)
|
||||
|
||||
try:
|
||||
await self.retry_with_exponential_backoff(task, _download_chunk)
|
||||
except Exception as e:
|
||||
raise DownloadError(
|
||||
f"Failed to download chunk {start}-{end} after {task.max_retries} attempts: {str(e)}"
|
||||
) from e
|
||||
|
||||
async def prepare_download(self, task: DownloadTask) -> None:
|
||||
output_dir = os.path.dirname(task.output_file)
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
|
||||
if os.path.exists(task.output_file):
|
||||
task.downloaded_size = os.path.getsize(task.output_file)
|
||||
|
||||
async def download_file(self, task: DownloadTask) -> None:
|
||||
try:
|
||||
async with httpx.AsyncClient(**self.client_options) as client:
|
||||
await self.get_file_info(client, task)
|
||||
|
||||
# Check if file is already downloaded
|
||||
if os.path.exists(task.output_file):
|
||||
if self.verify_file_integrity(task):
|
||||
self.console.print(f"[green]Already downloaded {task.output_file}[/green]")
|
||||
self.progress.update(task.task_id, completed=task.total_size)
|
||||
return
|
||||
|
||||
await self.prepare_download(task)
|
||||
|
||||
try:
|
||||
# Split the remaining download into chunks
|
||||
chunk_size = 27_000_000_000 # Cloudfront max chunk size
|
||||
chunks = []
|
||||
|
||||
current_pos = task.downloaded_size
|
||||
while current_pos < task.total_size:
|
||||
chunk_end = min(current_pos + chunk_size - 1, task.total_size - 1)
|
||||
chunks.append((current_pos, chunk_end))
|
||||
current_pos = chunk_end + 1
|
||||
|
||||
# Download chunks in sequence
|
||||
for chunk_start, chunk_end in chunks:
|
||||
await self.download_chunk(client, task, chunk_start, chunk_end)
|
||||
|
||||
except Exception as e:
|
||||
raise DownloadError(f"Download failed: {str(e)}") from e
|
||||
|
||||
except Exception as e:
|
||||
self.progress.update(task.task_id, description=f"[red]Failed: {task.output_file}[/red]")
|
||||
raise DownloadError(f"Download failed for {task.output_file}: {str(e)}") from e
|
||||
|
||||
def has_disk_space(self, tasks: list[DownloadTask]) -> bool:
|
||||
try:
|
||||
total_remaining_size = sum(task.total_size - task.downloaded_size for task in tasks)
|
||||
dir_path = os.path.dirname(os.path.abspath(tasks[0].output_file))
|
||||
free_space = shutil.disk_usage(dir_path).free
|
||||
|
||||
# Add 10% buffer for safety
|
||||
required_space = int(total_remaining_size * 1.1)
|
||||
|
||||
if free_space < required_space:
|
||||
self.console.print(
|
||||
f"[red]Not enough disk space. Required: {required_space // (1024 * 1024)} MB, "
|
||||
f"Available: {free_space // (1024 * 1024)} MB[/red]"
|
||||
)
|
||||
return False
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
raise DownloadError(f"Failed to check disk space: {str(e)}") from e
|
||||
|
||||
async def download_all(self, tasks: list[DownloadTask]) -> None:
|
||||
if not tasks:
|
||||
raise ValueError("No download tasks provided")
|
||||
|
||||
if not os.environ.get("LLAMA_DOWNLOAD_NO_SPACE_CHECK") and not self.has_disk_space(tasks):
|
||||
raise DownloadError("Insufficient disk space for downloads")
|
||||
|
||||
failed_tasks = []
|
||||
|
||||
with self.progress:
|
||||
for task in tasks:
|
||||
desc = f"Downloading {Path(task.output_file).name}"
|
||||
task.task_id = self.progress.add_task(desc, total=task.total_size, completed=task.downloaded_size)
|
||||
|
||||
semaphore = asyncio.Semaphore(self.max_concurrent_downloads)
|
||||
|
||||
async def download_with_semaphore(task: DownloadTask):
|
||||
async with semaphore:
|
||||
try:
|
||||
await self.download_file(task)
|
||||
except Exception as e:
|
||||
failed_tasks.append((task, str(e)))
|
||||
|
||||
await asyncio.gather(*(download_with_semaphore(task) for task in tasks))
|
||||
|
||||
if failed_tasks:
|
||||
self.console.print("\n[red]Some downloads failed:[/red]")
|
||||
for task, error in failed_tasks:
|
||||
self.console.print(f"[red]- {Path(task.output_file).name}: {error}[/red]")
|
||||
raise DownloadError(f"{len(failed_tasks)} downloads failed")
|
||||
|
||||
|
||||
def _hf_download(
|
||||
model: "Model",
|
||||
hf_token: str,
|
||||
ignore_patterns: str,
|
||||
parser: argparse.ArgumentParser,
|
||||
):
|
||||
from huggingface_hub import snapshot_download
|
||||
from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
|
||||
|
||||
from llama_stack.core.utils.model_utils import model_local_dir
|
||||
|
||||
repo_id = model.huggingface_repo
|
||||
if repo_id is None:
|
||||
raise ValueError(f"No repo id found for model {model.descriptor()}")
|
||||
|
||||
output_dir = model_local_dir(model.descriptor())
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
try:
|
||||
true_output_dir = snapshot_download(
|
||||
repo_id,
|
||||
local_dir=output_dir,
|
||||
ignore_patterns=ignore_patterns,
|
||||
token=hf_token,
|
||||
library_name="llama-stack",
|
||||
)
|
||||
except GatedRepoError:
|
||||
parser.error(
|
||||
"It looks like you are trying to access a gated repository. Please ensure you "
|
||||
"have access to the repository and have provided the proper Hugging Face API token "
|
||||
"using the option `--hf-token` or by running `huggingface-cli login`."
|
||||
"You can find your token by visiting https://huggingface.co/settings/tokens"
|
||||
)
|
||||
except RepositoryNotFoundError:
|
||||
parser.error(f"Repository '{repo_id}' not found on the Hugging Face Hub or incorrect Hugging Face token.")
|
||||
except Exception as e:
|
||||
parser.error(e)
|
||||
|
||||
print(f"\nSuccessfully downloaded model to {true_output_dir}")
|
||||
|
||||
|
||||
def _meta_download(
|
||||
model: "Model",
|
||||
model_id: str,
|
||||
meta_url: str,
|
||||
info: "LlamaDownloadInfo",
|
||||
max_concurrent_downloads: int,
|
||||
):
|
||||
from llama_stack.core.utils.model_utils import model_local_dir
|
||||
|
||||
output_dir = Path(model_local_dir(model.descriptor()))
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
|
||||
# Create download tasks for each file
|
||||
tasks = []
|
||||
for f in info.files:
|
||||
output_file = str(output_dir / f)
|
||||
url = meta_url.replace("*", f"{info.folder}/{f}")
|
||||
total_size = info.pth_size if "consolidated" in f else 0
|
||||
tasks.append(DownloadTask(url=url, output_file=output_file, total_size=total_size, max_retries=3))
|
||||
|
||||
# Initialize and run parallel downloader
|
||||
downloader = ParallelDownloader(max_concurrent_downloads=max_concurrent_downloads)
|
||||
asyncio.run(downloader.download_all(tasks))
|
||||
|
||||
cprint(f"\nSuccessfully downloaded model to {output_dir}", color="green", file=sys.stderr)
|
||||
cprint(
|
||||
f"\nView MD5 checksum files at: {output_dir / 'checklist.chk'}",
|
||||
file=sys.stderr,
|
||||
)
|
||||
cprint(
|
||||
f"\n[Optionally] To run MD5 checksums, use the following command: llama model verify-download --model-id {model_id}",
|
||||
color="yellow",
|
||||
file=sys.stderr,
|
||||
)
|
||||
|
||||
|
||||
class ModelEntry(BaseModel):
|
||||
model_id: str
|
||||
files: dict[str, str]
|
||||
|
||||
model_config = ConfigDict(protected_namespaces=())
|
||||
|
||||
|
||||
class Manifest(BaseModel):
|
||||
models: list[ModelEntry]
|
||||
expires_on: datetime
|
||||
|
||||
|
||||
def _download_from_manifest(manifest_file: str, max_concurrent_downloads: int):
|
||||
from llama_stack.core.utils.model_utils import model_local_dir
|
||||
|
||||
with open(manifest_file) as f:
|
||||
d = json.load(f)
|
||||
manifest = Manifest(**d)
|
||||
|
||||
if datetime.now(UTC) > manifest.expires_on.astimezone(UTC):
|
||||
raise ValueError(f"Manifest URLs have expired on {manifest.expires_on}")
|
||||
|
||||
console = Console()
|
||||
for entry in manifest.models:
|
||||
console.print(f"[blue]Downloading model {entry.model_id}...[/blue]")
|
||||
output_dir = Path(model_local_dir(entry.model_id))
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
|
||||
if any(output_dir.iterdir()):
|
||||
console.print(f"[yellow]Output directory {output_dir} is not empty.[/yellow]")
|
||||
|
||||
while True:
|
||||
resp = input("Do you want to (C)ontinue download or (R)estart completely? (continue/restart): ")
|
||||
if resp.lower() in ["restart", "r"]:
|
||||
shutil.rmtree(output_dir)
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
break
|
||||
elif resp.lower() in ["continue", "c"]:
|
||||
console.print("[blue]Continuing download...[/blue]")
|
||||
break
|
||||
else:
|
||||
console.print("[red]Invalid response. Please try again.[/red]")
|
||||
|
||||
# Create download tasks for all files in the manifest
|
||||
tasks = [
|
||||
DownloadTask(url=url, output_file=str(output_dir / fname), max_retries=3)
|
||||
for fname, url in entry.files.items()
|
||||
]
|
||||
|
||||
# Initialize and run parallel downloader
|
||||
downloader = ParallelDownloader(max_concurrent_downloads=max_concurrent_downloads)
|
||||
asyncio.run(downloader.download_all(tasks))
|
||||
|
||||
|
||||
def run_download_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser):
|
||||
"""Main download command handler"""
|
||||
try:
|
||||
if args.manifest_file:
|
||||
_download_from_manifest(args.manifest_file, args.max_parallel)
|
||||
return
|
||||
|
||||
if args.model_id is None:
|
||||
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)
|
||||
|
|
@ -439,12 +439,24 @@ def _run_stack_build_command_from_build_config(
|
|||
|
||||
cprint("Build Successful!", color="green", file=sys.stderr)
|
||||
cprint(f"You can find the newly-built distribution here: {run_config_file}", color="blue", file=sys.stderr)
|
||||
cprint(
|
||||
"You can run the new Llama Stack distro via: "
|
||||
+ colored(f"llama stack run {run_config_file} --image-type {build_config.image_type}", "blue"),
|
||||
color="green",
|
||||
file=sys.stderr,
|
||||
)
|
||||
if build_config.image_type == LlamaStackImageType.VENV:
|
||||
cprint(
|
||||
"You can run the new Llama Stack distro (after activating "
|
||||
+ colored(image_name, "cyan")
|
||||
+ ") via: "
|
||||
+ colored(f"llama stack run {run_config_file}", "blue"),
|
||||
color="green",
|
||||
file=sys.stderr,
|
||||
)
|
||||
elif build_config.image_type == LlamaStackImageType.CONTAINER:
|
||||
cprint(
|
||||
"You can run the container with: "
|
||||
+ colored(
|
||||
f"docker run -p 8321:8321 -v ~/.llama:/root/.llama localhost/{image_name} --port 8321", "blue"
|
||||
),
|
||||
color="green",
|
||||
file=sys.stderr,
|
||||
)
|
||||
return distro_path
|
||||
else:
|
||||
return _generate_run_config(build_config, build_dir, image_name)
|
||||
|
|
|
|||
|
|
@ -6,11 +6,18 @@
|
|||
|
||||
import argparse
|
||||
import os
|
||||
import ssl
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
|
||||
import uvicorn
|
||||
import yaml
|
||||
|
||||
from llama_stack.cli.stack.utils import ImageType
|
||||
from llama_stack.cli.subcommand import Subcommand
|
||||
from llama_stack.core.datatypes import LoggingConfig, StackRunConfig
|
||||
from llama_stack.core.stack import cast_image_name_to_string, replace_env_vars
|
||||
from llama_stack.core.utils.config_resolution import Mode, resolve_config_or_distro
|
||||
from llama_stack.log import get_logger
|
||||
|
||||
REPO_ROOT = Path(__file__).parent.parent.parent.parent
|
||||
|
|
@ -48,18 +55,12 @@ class StackRun(Subcommand):
|
|||
"--image-name",
|
||||
type=str,
|
||||
default=None,
|
||||
help="Name of the image to run. Defaults to the current environment",
|
||||
)
|
||||
self.parser.add_argument(
|
||||
"--env",
|
||||
action="append",
|
||||
help="Environment variables to pass to the server in KEY=VALUE format. Can be specified multiple times.",
|
||||
metavar="KEY=VALUE",
|
||||
help="[DEPRECATED] This flag is no longer supported. Please activate your virtual environment before running.",
|
||||
)
|
||||
self.parser.add_argument(
|
||||
"--image-type",
|
||||
type=str,
|
||||
help="Image Type used during the build. This can be only venv.",
|
||||
help="[DEPRECATED] This flag is no longer supported. Please activate your virtual environment before running.",
|
||||
choices=[e.value for e in ImageType if e.value != ImageType.CONTAINER.value],
|
||||
)
|
||||
self.parser.add_argument(
|
||||
|
|
@ -68,48 +69,22 @@ class StackRun(Subcommand):
|
|||
help="Start the UI server",
|
||||
)
|
||||
|
||||
def _resolve_config_and_distro(self, args: argparse.Namespace) -> tuple[Path | None, str | None]:
|
||||
"""Resolve config file path and distribution name from args.config"""
|
||||
from llama_stack.core.utils.config_dirs import DISTRIBS_BASE_DIR
|
||||
|
||||
if not args.config:
|
||||
return None, None
|
||||
|
||||
config_file = Path(args.config)
|
||||
has_yaml_suffix = args.config.endswith(".yaml")
|
||||
distro_name = None
|
||||
|
||||
if not config_file.exists() and not has_yaml_suffix:
|
||||
# check if this is a distribution
|
||||
config_file = Path(REPO_ROOT) / "llama_stack" / "distributions" / args.config / "run.yaml"
|
||||
if config_file.exists():
|
||||
distro_name = args.config
|
||||
|
||||
if not config_file.exists() and not has_yaml_suffix:
|
||||
# check if it's a build config saved to ~/.llama dir
|
||||
config_file = Path(DISTRIBS_BASE_DIR / f"llamastack-{args.config}" / f"{args.config}-run.yaml")
|
||||
|
||||
if not config_file.exists():
|
||||
self.parser.error(
|
||||
f"File {str(config_file)} does not exist.\n\nPlease run `llama stack build` to generate (and optionally edit) a run.yaml file"
|
||||
)
|
||||
|
||||
if not config_file.is_file():
|
||||
self.parser.error(
|
||||
f"Config file must be a valid file path, '{config_file}' is not a file: type={type(config_file)}"
|
||||
)
|
||||
|
||||
return config_file, distro_name
|
||||
|
||||
def _run_stack_run_cmd(self, args: argparse.Namespace) -> None:
|
||||
import yaml
|
||||
|
||||
from llama_stack.core.configure import parse_and_maybe_upgrade_config
|
||||
from llama_stack.core.utils.exec import formulate_run_args, run_command
|
||||
|
||||
if args.image_type or args.image_name:
|
||||
self.parser.error(
|
||||
"The --image-type and --image-name flags are no longer supported.\n\n"
|
||||
"Please activate your virtual environment manually before running `llama stack run`.\n\n"
|
||||
"For example:\n"
|
||||
" source /path/to/venv/bin/activate\n"
|
||||
" llama stack run <config>\n"
|
||||
)
|
||||
|
||||
if args.enable_ui:
|
||||
self._start_ui_development_server(args.port)
|
||||
image_type, image_name = args.image_type, args.image_name
|
||||
|
||||
if args.config:
|
||||
try:
|
||||
|
|
@ -121,10 +96,6 @@ class StackRun(Subcommand):
|
|||
else:
|
||||
config_file = None
|
||||
|
||||
# Check if config is required based on image type
|
||||
if image_type == ImageType.VENV.value and not config_file:
|
||||
self.parser.error("Config file is required for venv environment")
|
||||
|
||||
if config_file:
|
||||
logger.info(f"Using run configuration: {config_file}")
|
||||
|
||||
|
|
@ -139,50 +110,67 @@ class StackRun(Subcommand):
|
|||
os.makedirs(str(config.external_providers_dir), exist_ok=True)
|
||||
except AttributeError as e:
|
||||
self.parser.error(f"failed to parse config file '{config_file}':\n {e}")
|
||||
|
||||
self._uvicorn_run(config_file, args)
|
||||
|
||||
def _uvicorn_run(self, config_file: Path | None, args: argparse.Namespace) -> None:
|
||||
if not config_file:
|
||||
self.parser.error("Config file is required")
|
||||
|
||||
config_file = resolve_config_or_distro(str(config_file), Mode.RUN)
|
||||
with open(config_file) as fp:
|
||||
config_contents = yaml.safe_load(fp)
|
||||
if isinstance(config_contents, dict) and (cfg := config_contents.get("logging_config")):
|
||||
logger_config = LoggingConfig(**cfg)
|
||||
else:
|
||||
logger_config = None
|
||||
config = StackRunConfig(**cast_image_name_to_string(replace_env_vars(config_contents)))
|
||||
|
||||
port = args.port or config.server.port
|
||||
host = config.server.host or ["::", "0.0.0.0"]
|
||||
|
||||
# Set the config file in environment so create_app can find it
|
||||
os.environ["LLAMA_STACK_CONFIG"] = str(config_file)
|
||||
|
||||
uvicorn_config = {
|
||||
"factory": True,
|
||||
"host": host,
|
||||
"port": port,
|
||||
"lifespan": "on",
|
||||
"log_level": logger.getEffectiveLevel(),
|
||||
"log_config": logger_config,
|
||||
}
|
||||
|
||||
keyfile = config.server.tls_keyfile
|
||||
certfile = config.server.tls_certfile
|
||||
if keyfile and certfile:
|
||||
uvicorn_config["ssl_keyfile"] = config.server.tls_keyfile
|
||||
uvicorn_config["ssl_certfile"] = config.server.tls_certfile
|
||||
if config.server.tls_cafile:
|
||||
uvicorn_config["ssl_ca_certs"] = config.server.tls_cafile
|
||||
uvicorn_config["ssl_cert_reqs"] = ssl.CERT_REQUIRED
|
||||
|
||||
logger.info(
|
||||
f"HTTPS enabled with certificates:\n Key: {keyfile}\n Cert: {certfile}\n CA: {config.server.tls_cafile}"
|
||||
)
|
||||
else:
|
||||
config = None
|
||||
logger.info(f"HTTPS enabled with certificates:\n Key: {keyfile}\n Cert: {certfile}")
|
||||
|
||||
# If neither image type nor image name is provided, assume the server should be run directly
|
||||
# using the current environment packages.
|
||||
if not image_type and not image_name:
|
||||
logger.info("No image type or image name provided. Assuming environment packages.")
|
||||
from llama_stack.core.server.server import main as server_main
|
||||
logger.info(f"Listening on {host}:{port}")
|
||||
|
||||
# Build the server args from the current args passed to the CLI
|
||||
server_args = argparse.Namespace()
|
||||
for arg in vars(args):
|
||||
# If this is a function, avoid passing it
|
||||
# "args" contains:
|
||||
# func=<bound method StackRun._run_stack_run_cmd of <llama_stack.cli.stack.run.StackRun object at 0x10484b010>>
|
||||
if callable(getattr(args, arg)):
|
||||
continue
|
||||
if arg == "config":
|
||||
server_args.config = str(config_file)
|
||||
else:
|
||||
setattr(server_args, arg, getattr(args, arg))
|
||||
|
||||
# Run the server
|
||||
server_main(server_args)
|
||||
else:
|
||||
run_args = formulate_run_args(image_type, image_name)
|
||||
|
||||
run_args.extend([str(args.port)])
|
||||
|
||||
if config_file:
|
||||
run_args.extend(["--config", str(config_file)])
|
||||
|
||||
if args.env:
|
||||
for env_var in args.env:
|
||||
if "=" not in env_var:
|
||||
self.parser.error(f"Environment variable '{env_var}' must be in KEY=VALUE format")
|
||||
return
|
||||
key, value = env_var.split("=", 1) # split on first = only
|
||||
if not key:
|
||||
self.parser.error(f"Environment variable '{env_var}' has empty key")
|
||||
return
|
||||
run_args.extend(["--env", f"{key}={value}"])
|
||||
|
||||
run_command(run_args)
|
||||
# We need to catch KeyboardInterrupt because uvicorn's signal handling
|
||||
# re-raises SIGINT signals using signal.raise_signal(), which Python
|
||||
# converts to KeyboardInterrupt. Without this catch, we'd get a confusing
|
||||
# stack trace when using Ctrl+C or kill -2 (SIGINT).
|
||||
# SIGTERM (kill -15) works fine without this because Python doesn't
|
||||
# have a default handler for it.
|
||||
#
|
||||
# Another approach would be to ignore SIGINT entirely - let uvicorn handle it through its own
|
||||
# signal handling but this is quite intrusive and not worth the effort.
|
||||
try:
|
||||
uvicorn.run("llama_stack.core.server.server:create_app", **uvicorn_config)
|
||||
except (KeyboardInterrupt, SystemExit):
|
||||
logger.info("Received interrupt signal, shutting down gracefully...")
|
||||
|
||||
def _start_ui_development_server(self, stack_server_port: int):
|
||||
logger.info("Attempting to start UI development server...")
|
||||
|
|
|
|||
|
|
@ -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]")
|
||||
Loading…
Add table
Add a link
Reference in a new issue