llama-stack-mirror/llama_toolchain/cli/api/configure.py
2024-08-30 14:51:40 -07:00

79 lines
2.5 KiB
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.
import argparse
import json
from pathlib import Path
import yaml
from llama_toolchain.cli.subcommand import Subcommand
from llama_toolchain.common.config_dirs import BUILDS_BASE_DIR
from llama_toolchain.core.datatypes import * # noqa: F403
class ApiConfigure(Subcommand):
"""Llama cli for configuring llama toolchain configs"""
def __init__(self, subparsers: argparse._SubParsersAction):
super().__init__()
self.parser = subparsers.add_parser(
"configure",
prog="llama api configure",
description="configure a llama stack API provider",
formatter_class=argparse.RawTextHelpFormatter,
)
self._add_arguments()
self.parser.set_defaults(func=self._run_api_configure_cmd)
def _add_arguments(self):
from llama_toolchain.core.package import BuildType
self.parser.add_argument(
"--build-name",
type=str,
help="Name of the build",
required=True,
)
self.parser.add_argument(
"--build-type",
type=str,
default="conda_env",
choices=[v.value for v in BuildType],
)
def _run_api_configure_cmd(self, args: argparse.Namespace) -> None:
from llama_toolchain.core.package import BuildType
build_type = BuildType(args.build_type)
name = args.build_name
config_file = (
BUILDS_BASE_DIR / "adhoc" / build_type.descriptor() / f"{name}.yaml"
)
if not config_file.exists():
self.parser.error(
f"Could not find {config_file}. Please run `llama api build` first"
)
return
configure_llama_provider(config_file)
def configure_llama_provider(config_file: Path) -> None:
from llama_toolchain.common.serialize import EnumEncoder
from llama_toolchain.core.configure import configure_api_providers
with open(config_file, "r") as f:
config = PackageConfig(**yaml.safe_load(f))
config.providers = configure_api_providers(config.providers)
with open(config_file, "w") as fp:
to_write = json.loads(json.dumps(config.dict(), cls=EnumEncoder))
fp.write(yaml.dump(to_write, sort_keys=False))
print(f"YAML configuration has been written to {config_file}")