llama-stack/llama_stack/cli/stack/build.py
Dinesh Yeduguru a174938fbd
Fix telemetry to work on reinstantiating new lib cli (#761)
# What does this PR do?

Since we maintain global state in our telemetry pipeline,
reinstantiating lib cli will cause us to add duplicate span processors
causing sqlite to lock out because of constraint violations since we now
have two span processor writing to sqlite. This PR changes the telemetry
adapter for otel to only instantiate the provider once and add the span
processsors only once.

Also fixes an issue llama stack build


## Test Plan

tested with notebook at
https://colab.research.google.com/drive/1ck7hXQxRl6UvT-ijNRZ-gMZxH1G3cN2d#scrollTo=9496f75c
2025-01-14 11:31:50 -08:00

327 lines
12 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 importlib.resources
import os
import shutil
from functools import lru_cache
from pathlib import Path
from typing import List, Optional
from llama_stack.cli.subcommand import Subcommand
from llama_stack.distribution.datatypes import (
BuildConfig,
DistributionSpec,
Provider,
StackRunConfig,
)
from llama_stack.distribution.distribution import get_provider_registry
from llama_stack.distribution.resolver import InvalidProviderError
from llama_stack.distribution.utils.dynamic import instantiate_class_type
from llama_stack.providers.datatypes import Api
TEMPLATES_PATH = Path(__file__).parent.parent.parent / "templates"
@lru_cache()
def available_templates_specs() -> List[BuildConfig]:
import yaml
template_specs = []
for p in TEMPLATES_PATH.rglob("*build.yaml"):
with open(p, "r") as f:
build_config = BuildConfig(**yaml.safe_load(f))
template_specs.append(build_config)
return template_specs
class StackBuild(Subcommand):
def __init__(self, subparsers: argparse._SubParsersAction):
super().__init__()
self.parser = subparsers.add_parser(
"build",
prog="llama stack build",
description="Build a Llama stack container",
formatter_class=argparse.RawTextHelpFormatter,
)
self._add_arguments()
self.parser.set_defaults(func=self._run_stack_build_command)
def _add_arguments(self):
self.parser.add_argument(
"--config",
type=str,
default=None,
help="Path to a config file to use for the build. You can find example configs in llama_stack/distribution/**/build.yaml. If this argument is not provided, you will be prompted to enter information interactively",
)
self.parser.add_argument(
"--template",
type=str,
default=None,
help="Name of the example template config to use for build. You may use `llama stack build --list-templates` to check out the available templates",
)
self.parser.add_argument(
"--list-templates",
type=bool,
default=False,
action=argparse.BooleanOptionalAction,
help="Show the available templates for building a Llama Stack distribution",
)
self.parser.add_argument(
"--image-type",
type=str,
help="Image Type to use for the build. This can be either conda or docker. If not specified, will use the image type from the template config.",
choices=["conda", "docker", "venv"],
default="conda",
)
def _run_stack_build_command(self, args: argparse.Namespace) -> None:
import textwrap
import yaml
from prompt_toolkit import prompt
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.validation import Validator
from termcolor import cprint
from llama_stack.distribution.distribution import get_provider_registry
if args.list_templates:
self._run_template_list_cmd(args)
return
if args.template:
available_templates = available_templates_specs()
for build_config in available_templates:
if build_config.name == args.template:
if args.image_type:
build_config.image_type = args.image_type
else:
self.parser.error(
f"Please specify a image-type (docker | conda | venv) for {args.template}"
)
self._run_stack_build_command_from_build_config(
build_config, template_name=args.template
)
return
self.parser.error(
f"Could not find template {args.template}. Please run `llama stack build --list-templates` to check out the available templates"
)
return
if not args.config and not args.template:
name = prompt(
"> Enter a name for your Llama Stack (e.g. my-local-stack): ",
validator=Validator.from_callable(
lambda x: len(x) > 0,
error_message="Name cannot be empty, please enter a name",
),
)
image_type = prompt(
"> Enter the image type you want your Llama Stack to be built as (docker or conda or venv): ",
validator=Validator.from_callable(
lambda x: x in ["docker", "conda", "venv"],
error_message="Invalid image type, please enter conda or docker or venv",
),
default="conda",
)
cprint(
textwrap.dedent(
"""
Llama Stack is composed of several APIs working together. Let's select
the provider types (implementations) you want to use for these APIs.
""",
),
color="green",
)
print("Tip: use <TAB> to see options for the providers.\n")
providers = dict()
for api, providers_for_api in get_provider_registry().items():
available_providers = [
x
for x in providers_for_api.keys()
if x not in ("remote", "remote::sample")
]
api_provider = prompt(
"> Enter provider for API {}: ".format(api.value),
completer=WordCompleter(available_providers),
complete_while_typing=True,
validator=Validator.from_callable(
lambda x: x in available_providers,
error_message="Invalid provider, use <TAB> to see options",
),
)
providers[api.value] = api_provider
description = prompt(
"\n > (Optional) Enter a short description for your Llama Stack: ",
default="",
)
distribution_spec = DistributionSpec(
providers=providers,
description=description,
)
build_config = BuildConfig(
name=name, image_type=image_type, distribution_spec=distribution_spec
)
self._run_stack_build_command_from_build_config(build_config)
return
with open(args.config, "r") as f:
try:
build_config = BuildConfig(**yaml.safe_load(f))
except Exception as e:
self.parser.error(f"Could not parse config file {args.config}: {e}")
return
self._run_stack_build_command_from_build_config(build_config)
def _generate_run_config(self, build_config: BuildConfig, build_dir: Path) -> None:
"""
Generate a run.yaml template file for user to edit from a build.yaml file
"""
import json
import yaml
from termcolor import cprint
from llama_stack.distribution.build import ImageType
apis = list(build_config.distribution_spec.providers.keys())
run_config = StackRunConfig(
docker_image=(
build_config.name
if build_config.image_type == ImageType.docker.value
else None
),
image_name=build_config.name,
conda_env=(
build_config.name
if build_config.image_type == ImageType.conda.value
else None
),
apis=apis,
providers={},
)
# build providers dict
provider_registry = get_provider_registry()
for api in apis:
run_config.providers[api] = []
provider_types = build_config.distribution_spec.providers[api]
if isinstance(provider_types, str):
provider_types = [provider_types]
for i, provider_type in enumerate(provider_types):
pid = provider_type.split("::")[-1]
p = provider_registry[Api(api)][provider_type]
if p.deprecation_error:
raise InvalidProviderError(p.deprecation_error)
config_type = instantiate_class_type(
provider_registry[Api(api)][provider_type].config_class
)
if hasattr(config_type, "sample_run_config"):
config = config_type.sample_run_config(
__distro_dir__=f"distributions/{build_config.name}"
)
else:
config = {}
p_spec = Provider(
provider_id=f"{pid}-{i}" if len(provider_types) > 1 else pid,
provider_type=provider_type,
config=config,
)
run_config.providers[api].append(p_spec)
os.makedirs(build_dir, exist_ok=True)
run_config_file = build_dir / f"{build_config.name}-run.yaml"
with open(run_config_file, "w") as f:
to_write = json.loads(run_config.model_dump_json())
f.write(yaml.dump(to_write, sort_keys=False))
cprint(
f"You can now edit {run_config_file} and run `llama stack run {run_config_file}`",
color="green",
)
def _run_stack_build_command_from_build_config(
self, build_config: BuildConfig, template_name: Optional[str] = None
) -> None:
import json
import os
import yaml
from termcolor import cprint
from llama_stack.distribution.build import build_image
from llama_stack.distribution.utils.config_dirs import DISTRIBS_BASE_DIR
# save build.yaml spec for building same distribution again
build_dir = DISTRIBS_BASE_DIR / f"llamastack-{build_config.name}"
os.makedirs(build_dir, exist_ok=True)
build_file_path = build_dir / f"{build_config.name}-build.yaml"
with open(build_file_path, "w") as f:
to_write = json.loads(build_config.model_dump_json())
f.write(yaml.dump(to_write, sort_keys=False))
return_code = build_image(build_config, build_file_path)
if return_code != 0:
return
if template_name:
# copy run.yaml from template to build_dir instead of generating it again
template_path = (
importlib.resources.files("llama_stack")
/ f"templates/{template_name}/run.yaml"
)
with importlib.resources.as_file(template_path) as path:
run_config_file = build_dir / f"{build_config.name}-run.yaml"
shutil.copy(path, run_config_file)
# Find all ${env.VARIABLE} patterns
cprint("Build Successful!", color="green")
else:
self._generate_run_config(build_config, build_dir)
def _run_template_list_cmd(self, args: argparse.Namespace) -> None:
import json
from llama_stack.cli.table import print_table
# eventually, this should query a registry at llama.meta.com/llamastack/distributions
headers = [
"Template Name",
"Providers",
"Description",
]
rows = []
for spec in available_templates_specs():
rows.append(
[
spec.name,
json.dumps(spec.distribution_spec.providers, indent=2),
spec.distribution_spec.description,
]
)
print_table(
rows,
headers,
separate_rows=True,
)