Add special case for prompt guard

This commit is contained in:
Ashwin Bharambe 2024-10-02 08:38:23 -07:00
parent a80b707ff8
commit cc5029a716
4 changed files with 76 additions and 13 deletions

View file

@ -38,9 +38,6 @@ class Download(Subcommand):
def setup_download_parser(parser: argparse.ArgumentParser) -> None:
from llama_models.sku_list import all_registered_models
models = all_registered_models()
parser.add_argument(
"--source",
choices=["meta", "huggingface"],
@ -123,16 +120,12 @@ def _hf_download(
print(f"\nSuccessfully downloaded model to {true_output_dir}")
def _meta_download(model: "Model", meta_url: str):
from llama_models.sku_list import llama_meta_net_info
def _meta_download(model: "Model", meta_url: str, info: "LlamaDownloadInfo"):
from llama_stack.distribution.utils.model_utils import model_local_dir
output_dir = Path(model_local_dir(model.descriptor()))
os.makedirs(output_dir, exist_ok=True)
info = llama_meta_net_info(model)
# I believe we can use some concurrency here if needed but not sure it is worth it
for f in info.files:
output_file = str(output_dir / f)
@ -147,7 +140,9 @@ def _meta_download(model: "Model", meta_url: str):
def run_download_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser):
from llama_models.sku_list import resolve_model
from llama_models.sku_list import llama_meta_net_info, resolve_model
from .model.safety_models import prompt_guard_download_info, prompt_guard_model_sku
if args.manifest_file:
_download_from_manifest(args.manifest_file)
@ -157,7 +152,14 @@ def run_download_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser):
parser.error("Please provide a model id")
return
prompt_guard = prompt_guard_model_sku()
if args.model_id == prompt_guard.model_id:
model = prompt_guard
info = prompt_guard_download_info()
else:
model = resolve_model(args.model_id)
info = llama_meta_net_info(model)
if model is None:
parser.error(f"Model {args.model_id} not found")
return
@ -171,7 +173,7 @@ def run_download_cmd(args: argparse.Namespace, parser: argparse.ArgumentParser):
"Please provide the signed URL you received via email (e.g., https://llama3-1.llamameta.net/*?Policy...): "
)
assert meta_url is not None and "llamameta.net" in meta_url
_meta_download(model, meta_url)
_meta_download(model, meta_url, info)
class ModelEntry(BaseModel):

View file

@ -39,7 +39,14 @@ class ModelDescribe(Subcommand):
)
def _run_model_describe_cmd(self, args: argparse.Namespace) -> None:
from .safety_models import prompt_guard_model_sku
prompt_guard = prompt_guard_model_sku()
if args.model_id == prompt_guard.model_id:
model = prompt_guard
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."

View file

@ -34,6 +34,8 @@ class ModelList(Subcommand):
)
def _run_model_list_cmd(self, args: argparse.Namespace) -> None:
from .safety_models import prompt_guard_model_sku
headers = [
"Model Descriptor",
"Hugging Face Repo",
@ -41,7 +43,7 @@ class ModelList(Subcommand):
]
rows = []
for model in all_registered_models():
for model in all_registered_models() + [prompt_guard_model_sku()]:
if not args.show_all and not model.is_featured:
continue

View file

@ -0,0 +1,52 @@
# 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, Dict, Optional
from pydantic import BaseModel, ConfigDict, Field
from llama_models.datatypes import * # noqa: F403
from llama_models.sku_list import LlamaDownloadInfo
class PromptGuardModel(BaseModel):
"""Make a 'fake' Model-like object for Prompt Guard. Eventually this will be removed."""
model_id: str = "Prompt-Guard-86M"
description: str = (
"Prompt Guard. NOTE: this model will not be provided via `llama` CLI soon."
)
is_featured: bool = False
huggingface_repo: str = "meta-llama/Prompt-Guard-86M"
max_seq_length: int = 2048
is_instruct_model: bool = False
quantization_format: CheckpointQuantizationFormat = (
CheckpointQuantizationFormat.bf16
)
arch_args: Dict[str, Any] = Field(default_factory=dict)
recommended_sampling_params: Optional[SamplingParams] = None
def descriptor(self) -> str:
return self.model_id
model_config = ConfigDict(protected_namespaces=())
def prompt_guard_model_sku():
return PromptGuardModel()
def prompt_guard_download_info():
return LlamaDownloadInfo(
folder="Prompt-Guard",
files=[
"model.safetensors",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
],
pth_size=1,
)