mirror of
https://github.com/meta-llama/llama-stack.git
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116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
# 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 json
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import shlex
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from pathlib import Path
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import yaml
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from termcolor import cprint
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from llama_toolchain.cli.subcommand import Subcommand
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from llama_toolchain.common.config_dirs import DISTRIBS_BASE_DIR
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class DistributionConfigure(Subcommand):
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"""Llama cli for configuring llama toolchain configs"""
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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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"configure",
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prog="llama distribution configure",
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description="configure a llama stack distribution",
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formatter_class=argparse.RawTextHelpFormatter,
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)
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self._add_arguments()
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self.parser.set_defaults(func=self._run_distribution_configure_cmd)
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def _add_arguments(self):
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from llama_toolchain.distribution.registry import available_distributions
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self.parser.add_argument(
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"--name",
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type=str,
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help="Name of the distribution to configure",
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default="local-source",
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choices=[d.name for d in available_distributions()],
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)
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def _run_distribution_configure_cmd(self, args: argparse.Namespace) -> None:
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from llama_toolchain.distribution.registry import resolve_distribution
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dist = resolve_distribution(args.name)
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if dist is None:
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self.parser.error(f"Could not find distribution {args.name}")
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return
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env_file = DISTRIBS_BASE_DIR / dist.name / "conda.env"
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# read this file to get the conda env name
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assert env_file.exists(), f"Could not find conda env file {env_file}"
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with open(env_file, "r") as f:
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conda_env = f.read().strip()
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configure_llama_distribution(dist, conda_env)
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def configure_llama_distribution(dist: "Distribution", conda_env: str):
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from llama_toolchain.common.exec import run_command
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from llama_toolchain.common.prompt_for_config import prompt_for_config
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from llama_toolchain.common.serialize import EnumEncoder
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from llama_toolchain.distribution.datatypes import RemoteProviderSpec
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from llama_toolchain.distribution.dynamic import instantiate_class_type
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python_exe = run_command(shlex.split("which python"))
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# simple check
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if conda_env not in python_exe:
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raise ValueError(
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f"Please re-run configure by activating the `{conda_env}` conda environment"
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)
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existing_config = None
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config_path = Path(DISTRIBS_BASE_DIR) / dist.name / "config.yaml"
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if config_path.exists():
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cprint(
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f"Configuration already exists for {dist.name}. Will overwrite...",
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"yellow",
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attrs=["bold"],
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)
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with open(config_path, "r") as fp:
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existing_config = yaml.safe_load(fp)
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provider_configs = {}
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for api, provider_spec in dist.provider_specs.items():
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if isinstance(provider_spec, RemoteProviderSpec):
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provider_configs[api.value] = provider_spec.dict()
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else:
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cprint(f"Configuring API surface: {api.value}", "white", attrs=["bold"])
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config_type = instantiate_class_type(provider_spec.config_class)
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config = prompt_for_config(
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config_type,
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(
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config_type(**existing_config["providers"][api.value])
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if existing_config and api.value in existing_config["providers"]
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else None
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),
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)
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provider_configs[api.value] = {
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"provider_id": provider_spec.provider_id,
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**config.dict(),
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}
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dist_config = {
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"providers": provider_configs,
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"conda_env": conda_env,
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}
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with open(config_path, "w") as fp:
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dist_config = json.loads(json.dumps(dist_config, cls=EnumEncoder))
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fp.write(yaml.dump(dist_config, sort_keys=False))
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print(f"YAML configuration has been written to {config_path}")
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