llama-stack-mirror/scripts/generate_prompt_format.py
Charlie Doern 2e5d1c8881 refactor: enforce top-level imports for llama-stack-api
Enforce that all imports from llama-stack-api use the form:

from llama_stack_api import <symbol>

 This prevents external code from accessing internal package structure
 (e.g., llama_stack_api.agents, llama_stack_api.common.*) and establishes
 a clear public API boundary.

 Changes:
 - Export 400+ symbols from llama_stack_api/__init__.py
 - Include all API types, common utilities, and strong_typing helpers
 - Update files across src/llama_stack, docs/, tests/, scripts/
 - Convert all submodule imports to top-level imports
 - ensure docs use the proper importing structure

 Addresses PR review feedback requiring explicit __all__ definition to
 prevent "peeking inside" the API package.

Signed-off-by: Charlie Doern <cdoern@redhat.com>
2025-11-13 14:14:52 -05:00

68 lines
1.8 KiB
Python
Executable file

#!/usr/bin/env python
# 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.
# Run this script:
# torchrun --nproc_per_node=8 scripts/generate_prompt_format.py meta-llama/Llama-4-17B-Omni-Instruct-BF16-16E ~/.llama/checkpoints/Llama-4-17B-Omni-Instruct-BF16-16E/ llama_stack.models.llama.llama4.prompts llama_stack/models/llama/llama4/prompt_format.md
import importlib
import os
from pathlib import Path
import fire
from llama_stack_api import ModelNotFoundError
from llama_stack.models.llama.llama3.generation import Llama3
from llama_stack.models.llama.llama4.generation import Llama4
from llama_stack.models.llama.sku_list import resolve_model
THIS_DIR = Path(__file__).parent.resolve()
def run_main(
model_id: str,
checkpoint_dir: str,
module_name: str,
output_path: str,
llama4: bool = True,
):
module = importlib.import_module(module_name)
assert hasattr(module, "usecases"), f"Module {module_name} missing usecases function"
llama_model = resolve_model(model_id)
if not llama_model:
raise ModelNotFoundError(model_id)
cls = Llama4 if llama4 else Llama3
generator = cls.build(
ckpt_dir=checkpoint_dir,
max_seq_len=4096,
max_batch_size=1,
)
use_cases = module.usecases()
text = ""
for u in use_cases:
if isinstance(u, str):
use_case_text = f"\n{u}\n"
else:
use_case_text = u.to_text(generator)
text += use_case_text
print(use_case_text)
os.makedirs(os.path.dirname(output_path), exist_ok=True)
with open(output_path, "w") as f:
f.write(text)
def main():
fire.Fire(run_main)
if __name__ == "__main__":
main()