llama-stack/llama_stack/cli/stack/build.py
Dalton Flanagan b007b062f3
Fix llama stack build in 0.0.54 (#505)
# What does this PR do?

Safety provider `inline::meta-reference` is now deprecated. However, we 

* aren't checking / printing the deprecation message in `llama stack
build`
* make the deprecated (unusable) provider

So I (1) added checking and (2) made `inline::llama-guard` the default

## Test Plan

Before

```
Traceback (most recent call last):
  File "/home/dalton/.conda/envs/nov22/bin/llama", line 8, in <module>
    sys.exit(main())
  File "/home/dalton/all/llama-stack/llama_stack/cli/llama.py", line 46, in main
    parser.run(args)
  File "/home/dalton/all/llama-stack/llama_stack/cli/llama.py", line 40, in run
    args.func(args)
  File "/home/dalton/all/llama-stack/llama_stack/cli/stack/build.py", line 177, in _run_stack_build_command
    self._run_stack_build_command_from_build_config(build_config)
  File "/home/dalton/all/llama-stack/llama_stack/cli/stack/build.py", line 305, in _run_stack_build_command_from_build_config
    self._generate_run_config(build_config, build_dir)
  File "/home/dalton/all/llama-stack/llama_stack/cli/stack/build.py", line 226, in _generate_run_config
    config_type = instantiate_class_type(
  File "/home/dalton/all/llama-stack/llama_stack/distribution/utils/dynamic.py", line 12, in instantiate_class_type
    module = importlib.import_module(module_name)
  File "/home/dalton/.conda/envs/nov22/lib/python3.10/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1004, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'llama_stack.providers.inline.safety.meta_reference'
```

After

```
Traceback (most recent call last):
  File "/home/dalton/.conda/envs/nov22/bin/llama", line 8, in <module>
    sys.exit(main())
  File "/home/dalton/all/llama-stack/llama_stack/cli/llama.py", line 46, in main
    parser.run(args)
  File "/home/dalton/all/llama-stack/llama_stack/cli/llama.py", line 40, in run
    args.func(args)
  File "/home/dalton/all/llama-stack/llama_stack/cli/stack/build.py", line 177, in _run_stack_build_command
    self._run_stack_build_command_from_build_config(build_config)
  File "/home/dalton/all/llama-stack/llama_stack/cli/stack/build.py", line 309, in _run_stack_build_command_from_build_config
    self._generate_run_config(build_config, build_dir)
  File "/home/dalton/all/llama-stack/llama_stack/cli/stack/build.py", line 228, in _generate_run_config
    raise InvalidProviderError(p.deprecation_error)
llama_stack.distribution.resolver.InvalidProviderError: 
Provider `inline::meta-reference` for API `safety` does not work with the latest Llama Stack.
- if you are using Llama Guard v3, please use the `inline::llama-guard` provider instead.
- if you are using Prompt Guard, please use the `inline::prompt-guard` provider instead.
- if you are using Code Scanner, please use the `inline::code-scanner` provider instead.
```

<img width="469" alt="Screenshot 2024-11-22 at 4 10 24 PM"
src="https://github.com/user-attachments/assets/8c2e09fe-379a-4504-b246-7925f80a6ed6">

## Sources

Please link relevant resources if necessary.


## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
2024-11-22 16:23:44 -05:00

336 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
from llama_stack.cli.subcommand import Subcommand
from llama_stack.distribution.datatypes import * # noqa: F403
import os
import shutil
from functools import lru_cache
from pathlib import Path
import pkg_resources
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
TEMPLATES_PATH = Path(os.path.relpath(__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/example_configs. 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"],
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) 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): ",
validator=Validator.from_callable(
lambda x: x in ["docker", "conda"],
error_message="Invalid image type, please enter conda or docker",
),
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 re
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 = pkg_resources.resource_filename(
"llama_stack", f"templates/{template_name}/run.yaml"
)
os.makedirs(build_dir, exist_ok=True)
run_config_file = build_dir / f"{build_config.name}-run.yaml"
shutil.copy(template_path, run_config_file)
with open(template_path, "r") as f:
yaml_content = f.read()
# Find all ${env.VARIABLE} patterns
env_vars = set(re.findall(r"\${env\.([A-Za-z0-9_]+)}", yaml_content))
cprint("Build Successful! Next steps: ", color="green")
cprint(
f" 1. Set the environment variables: {list(env_vars)}",
color="green",
)
cprint(
f" 2. Run: `llama stack run {template_name}`",
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,
)