llama-stack-mirror/llama_stack/cli/stack/configure.py
Ashwin Bharambe ec4fc800cc
[API Updates] Model / shield / memory-bank routing + agent persistence + support for private headers (#92)
This is yet another of those large PRs (hopefully we will have less and less of them as things mature fast). This one introduces substantial improvements and some simplifications to the stack.

Most important bits:

* Agents reference implementation now has support for session / turn persistence. The default implementation uses sqlite but there's also support for using Redis.

* We have re-architected the structure of the Stack APIs to allow for more flexible routing. The motivating use cases are:
  - routing model A to ollama and model B to a remote provider like Together
  - routing shield A to local impl while shield B to a remote provider like Bedrock
  - routing a vector memory bank to Weaviate while routing a keyvalue memory bank to Redis

* Support for provider specific parameters to be passed from the clients. A client can pass data using `x_llamastack_provider_data` parameter which can be type-checked and provided to the Adapter implementations.
2024-09-23 14:22:22 -07:00

170 lines
6 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
from llama_stack.cli.subcommand import Subcommand
from llama_stack.distribution.utils.config_dirs import BUILDS_BASE_DIR
from llama_stack.distribution.datatypes import * # noqa: F403
class StackConfigure(Subcommand):
"""Llama cli for configuring llama toolchain configs"""
def __init__(self, subparsers: argparse._SubParsersAction):
super().__init__()
self.parser = subparsers.add_parser(
"configure",
prog="llama stack configure",
description="configure a llama stack distribution",
formatter_class=argparse.RawTextHelpFormatter,
)
self._add_arguments()
self.parser.set_defaults(func=self._run_stack_configure_cmd)
def _add_arguments(self):
self.parser.add_argument(
"config",
type=str,
help="Path to the build config file (e.g. ~/.llama/builds/<image_type>/<name>-build.yaml). For docker, this could also be the name of the docker image. ",
)
self.parser.add_argument(
"--output-dir",
type=str,
help="Path to the output directory to store generated run.yaml config file. If not specified, will use ~/.llama/build/<image_type>/<name>-run.yaml",
)
def _run_stack_configure_cmd(self, args: argparse.Namespace) -> None:
import os
from pathlib import Path
import pkg_resources
import yaml
from termcolor import cprint
from llama_stack.distribution.build import ImageType
from llama_stack.distribution.utils.exec import run_with_pty
docker_image = None
build_config_file = Path(args.config)
if build_config_file.exists():
with open(build_config_file, "r") as f:
build_config = BuildConfig(**yaml.safe_load(f))
self._configure_llama_distribution(build_config, args.output_dir)
return
# if we get here, we need to try to find the conda build config file
cprint(
f"Could not find {build_config_file}. Trying conda build name instead...",
color="green",
)
if os.getenv("CONDA_PREFIX"):
conda_dir = (
Path(os.getenv("CONDA_PREFIX")).parent / f"llamastack-{args.config}"
)
build_config_file = Path(conda_dir) / f"{args.config}-build.yaml"
if build_config_file.exists():
with open(build_config_file, "r") as f:
build_config = BuildConfig(**yaml.safe_load(f))
self._configure_llama_distribution(build_config, args.output_dir)
return
# if we get here, we need to try to find the docker image
cprint(
f"Could not find {build_config_file}. Trying docker image name instead...",
color="green",
)
docker_image = args.config
builds_dir = BUILDS_BASE_DIR / ImageType.docker.value
if args.output_dir:
builds_dir = Path(output_dir)
os.makedirs(builds_dir, exist_ok=True)
script = pkg_resources.resource_filename(
"llama_stack", "distribution/configure_container.sh"
)
script_args = [script, docker_image, str(builds_dir)]
return_code = run_with_pty(script_args)
# we have regenerated the build config file with script, now check if it exists
if return_code != 0:
self.parser.error(
f"Failed to configure container {docker_image} with return code {return_code}. Please run `llama stack build first`. "
)
return
build_name = docker_image.removeprefix("llamastack-")
saved_file = str(builds_dir / f"{build_name}-run.yaml")
cprint(
f"YAML configuration has been written to {saved_file}. You can now run `llama stack run {saved_file}`",
color="green",
)
return
def _configure_llama_distribution(
self,
build_config: BuildConfig,
output_dir: Optional[str] = None,
):
import json
import os
from pathlib import Path
import yaml
from termcolor import cprint
from llama_stack.distribution.configure import configure_api_providers
from llama_stack.distribution.utils.serialize import EnumEncoder
builds_dir = BUILDS_BASE_DIR / build_config.image_type
if output_dir:
builds_dir = Path(output_dir)
os.makedirs(builds_dir, exist_ok=True)
image_name = build_config.name.replace("::", "-")
run_config_file = builds_dir / f"{image_name}-run.yaml"
if run_config_file.exists():
cprint(
f"Configuration already exists at `{str(run_config_file)}`. Will overwrite...",
"yellow",
attrs=["bold"],
)
config = StackRunConfig(**yaml.safe_load(run_config_file.read_text()))
else:
config = StackRunConfig(
built_at=datetime.now(),
image_name=image_name,
apis_to_serve=[],
api_providers={},
)
config = configure_api_providers(config, build_config.distribution_spec)
config.docker_image = (
image_name if build_config.image_type == "docker" else None
)
config.conda_env = image_name if build_config.image_type == "conda" else None
with open(run_config_file, "w") as f:
to_write = json.loads(json.dumps(config.dict(), cls=EnumEncoder))
f.write(yaml.dump(to_write, sort_keys=False))
cprint(
f"> YAML configuration has been written to {run_config_file}.",
color="blue",
)
cprint(
f"You can now run `llama stack run {image_name} --port PORT`",
color="green",
)