forked from phoenix-oss/llama-stack-mirror
* Add distribution CLI scaffolding * More progress towards `llama distribution install` * getting closer to a distro definition, distro install + configure works * Distribution server now functioning * read existing configuration, save enums properly * Remove inference uvicorn server entrypoint and llama inference CLI command * updated dependency and client model name * Improved exception handling * local imports for faster cli * undo a typo, add a passthrough distribution * implement full-passthrough in the server * add safety adapters, configuration handling, server + clients * cleanup, moving stuff to common, nuke utils * Add a Path() wrapper at the earliest place * fixes * Bring agentic system api to toolchain Add adapter dependencies and resolve adapters using a topological sort * refactor to reduce size of `agentic_system` * move straggler files and fix some important existing bugs * ApiSurface -> Api * refactor a method out * Adapter -> Provider * Make each inference provider into its own subdirectory * installation fixes * Rename Distribution -> DistributionSpec, simplify RemoteProviders * dict key instead of attr * update inference config to take model and not model_dir * Fix passthrough streaming, send headers properly not part of body :facepalm * update safety to use model sku ids and not model dirs * Update cli_reference.md * minor fixes * add DistributionConfig, fix a bug in model download * Make install + start scripts do proper configuration automatically * Update CLI_reference * Nuke fp8_requirements, fold fbgemm into common requirements * Update README, add newline between API surface configurations * Refactor download functionality out of the Command so can be reused * Add `llama model download` alias for `llama download` * Show message about checksum file so users can check themselves * Simpler intro statements * get ollama working * Reduce a bunch of dependencies from toolchain Some improvements to the distribution install script * Avoid using `conda run` since it buffers everything * update dependencies and rely on LLAMA_TOOLCHAIN_DIR for dev purposes * add validation for configuration input * resort imports * make optional subclasses default to yes for configuration * Remove additional_pip_packages; move deps to providers * for inline make 8b model the default * Add scripts to MANIFEST * allow installing from test.pypi.org * Fix #2 to help with testing packages * Must install llama-models at that same version first * fix PIP_ARGS --------- Co-authored-by: Hardik Shah <hjshah@fb.com> Co-authored-by: Hardik Shah <hjshah@meta.com>
106 lines
3.7 KiB
Python
106 lines
3.7 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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import yaml
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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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from termcolor import cprint
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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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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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required=True,
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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.datatypes import DistributionConfig
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from llama_toolchain.distribution.registry import resolve_distribution_spec
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config_file = DISTRIBS_BASE_DIR / args.name / "config.yaml"
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if not config_file.exists():
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self.parser.error(
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f"Could not find {config_file}. Please run `llama distribution install` first"
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)
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return
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# we need to find the spec from the name
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with open(config_file, "r") as f:
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config = DistributionConfig(**yaml.safe_load(f))
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dist = resolve_distribution_spec(config.spec)
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if dist is None:
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raise ValueError(f"Could not find any registered spec `{config.spec}`")
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configure_llama_distribution(dist, config)
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def configure_llama_distribution(dist: "Distribution", config: "DistributionConfig"):
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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.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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conda_env = config.conda_env
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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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if config.providers:
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cprint(
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f"Configuration already exists for {config.name}. Will overwrite...",
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"yellow",
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attrs=["bold"],
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)
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for api, provider_spec in dist.provider_specs.items():
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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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provider_config = prompt_for_config(
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config_type,
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(
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config_type(**config.providers[api.value])
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if api.value in config.providers
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else None
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),
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)
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print("")
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config.providers[api.value] = {
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"provider_id": provider_spec.provider_id,
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**provider_config.dict(),
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}
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config_path = DISTRIBS_BASE_DIR / config.name / "config.yaml"
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with open(config_path, "w") as fp:
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dist_config = json.loads(json.dumps(config.dict(), 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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