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https://github.com/meta-llama/llama-stack.git
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CLI - add back build wizard, configure with name instead of build.yaml (#74)
* add back wizard for build * conda build path move * polish message * run with name only * prompt for build * improve comments * update msgs * add new lines * move build.yaml * address comments * validator for providers * move imports * Please enter -> enter * comments, get started guide * nits * fix cprint import * fix imports
This commit is contained in:
Xi Yan
GitHub
parent
e6fdb9df29
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4 changed files with 134 additions and 30 deletions
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@ -8,43 +8,61 @@ This guides allows you to quickly get started with building and running a Llama
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- Quick 3 line command to build and start a LlamaStack server using our Meta Reference implementation for all API endpoints with `conda` as build type.
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**`llama stack build`**
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- You'll be prompted to enter build information interactively.
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```
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llama stack build ./llama_stack/distribution/example_configs/conda/local-conda-example-build.yaml --name my-local-llama-stack
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...
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...
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Build spec configuration saved at ~/.llama/distributions/conda/my-local-llama-stack-build.yaml
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llama stack build
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> Enter an unique name for identifying your Llama Stack build distribution (e.g. my-local-stack): my-local-llama-stack
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> Enter the image type you want your distribution to be built with (docker or conda): conda
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Llama Stack is composed of several APIs working together. Let's configure the providers (implementations) you want to use for these APIs.
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> Enter the API provider for the inference API: (default=meta-reference): meta-reference
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> Enter the API provider for the safety API: (default=meta-reference): meta-reference
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> Enter the API provider for the agents API: (default=meta-reference): meta-reference
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> Enter the API provider for the memory API: (default=meta-reference): meta-reference
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> Enter the API provider for the telemetry API: (default=meta-reference): meta-reference
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> (Optional) Enter a short description for your Llama Stack distribution:
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Build spec configuration saved at ~/.conda/envs/llamastack-my-local-llama-stack/my-local-llama-stack-build.yaml
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```
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**`llama stack configure`**
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```
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llama stack configure ~/.llama/distributions/conda/my-local-llama-stack-build.yaml
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llama stack configure my-local-llama-stack
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Configuring API: inference (meta-reference)
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Configuring APIs to serve...
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Enter comma-separated list of APIs to serve:
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Configuring API `inference`...
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Configuring provider `meta-reference`...
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Enter value for model (default: Meta-Llama3.1-8B-Instruct) (required):
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Enter value for quantization (optional):
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Do you want to configure quantization? (y/n): n
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Enter value for torch_seed (optional):
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Enter value for max_seq_len (required): 4096
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Enter value for max_batch_size (default: 1) (required):
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Configuring API `safety`...
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Configuring API: memory (meta-reference-faiss)
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Configuring API: safety (meta-reference)
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Configuring provider `meta-reference`...
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Do you want to configure llama_guard_shield? (y/n): n
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Do you want to configure prompt_guard_shield? (y/n): n
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Configuring API `agents`...
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Configuring API: agentic_system (meta-reference)
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Enter value for brave_search_api_key (optional):
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Enter value for bing_search_api_key (optional):
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Enter value for wolfram_api_key (optional):
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Configuring provider `meta-reference`...
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Configuring API `memory`...
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Configuring API: telemetry (console)
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Configuring provider `meta-reference`...
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Configuring API `telemetry`...
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YAML configuration has been written to ~/.llama/builds/conda/my-local-llama-stack-run.yaml
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Configuring provider `meta-reference`...
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> YAML configuration has been written to /home/xiyan/.llama/builds/conda/my-local-llama-stack-run.yaml.
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You can now run `llama stack run my-local-llama-stack --port PORT` or `llama stack run /home/xiyan/.llama/builds/conda/my-local-llama-stack-run.yaml --port PORT
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```
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**`llama stack run`**
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```
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llama stack run ~/.llama/builds/conda/my-local-llama-stack-run.yaml
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llama stack run my-local-llama-stack
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...
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> initializing model parallel with size 1
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@ -29,7 +29,9 @@ class StackBuild(Subcommand):
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self.parser.add_argument(
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"config",
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type=str,
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help="Path to a config file to use for the build. You may find example configs in llama_stack/distribution/example_configs",
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default=None,
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nargs="*",
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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",
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)
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self.parser.add_argument(
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@ -44,9 +46,10 @@ class StackBuild(Subcommand):
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import json
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import os
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from llama_stack.distribution.build import ApiInput, build_image, ImageType
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from llama_stack.distribution.utils.config_dirs import DISTRIBS_BASE_DIR
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from llama_stack.distribution.utils.serialize import EnumEncoder
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from llama_stack.distribution.build import ApiInput, build_image, ImageType
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from termcolor import cprint
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# save build.yaml spec for building same distribution again
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@ -57,7 +60,10 @@ class StackBuild(Subcommand):
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llama_stack_path / "configs/distributions" / build_config.image_type
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)
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else:
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build_dir = DISTRIBS_BASE_DIR / build_config.image_type
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build_dir = (
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Path(os.getenv("CONDA_PREFIX")).parent
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/ f"llamastack-{build_config.name}"
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)
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os.makedirs(build_dir, exist_ok=True)
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build_file_path = build_dir / f"{build_config.name}-build.yaml"
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@ -70,17 +76,76 @@ class StackBuild(Subcommand):
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cprint(
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f"Build spec configuration saved at {str(build_file_path)}",
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color="blue",
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)
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cprint(
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f"You may now run `llama stack configure {build_config.name}` or `llama stack configure {str(build_file_path)}`",
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color="green",
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)
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def _run_stack_build_command(self, args: argparse.Namespace) -> None:
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from llama_stack.distribution.utils.prompt_for_config import prompt_for_config
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from llama_stack.distribution.distribution import Api, api_providers
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from llama_stack.distribution.utils.dynamic import instantiate_class_type
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from prompt_toolkit import prompt
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from prompt_toolkit.validation import Validator
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from termcolor import cprint
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if not args.config:
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self.parser.error(
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"No config file specified. Please use `llama stack build /path/to/*-build.yaml`. Example config files can be found in llama_stack/distribution/example_configs"
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name = prompt(
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"> Enter a unique name for identifying your Llama Stack build (e.g. my-local-stack): "
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)
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image_type = prompt(
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"> Enter the image type you want your Llama Stack to be built as (docker or conda): ",
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validator=Validator.from_callable(
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lambda x: x in ["docker", "conda"],
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error_message="Invalid image type, please enter conda or docker",
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),
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default="conda",
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)
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cprint(
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f"\n Llama Stack is composed of several APIs working together. Let's configure the providers (implementations) you want to use for these APIs.",
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color="green",
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)
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providers = dict()
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for api in Api:
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all_providers = api_providers()
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providers_for_api = all_providers[api]
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api_provider = prompt(
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"> Enter the API provider for the {} API: (default=meta-reference): ".format(
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api.value
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),
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validator=Validator.from_callable(
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lambda x: x in providers_for_api,
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error_message="Invalid provider, please enter one of the following: {}".format(
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providers_for_api.keys()
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),
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),
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default=(
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"meta-reference"
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if "meta-reference" in providers_for_api
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else list(providers_for_api.keys())[0]
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),
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)
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providers[api.value] = api_provider
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description = prompt(
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"\n > (Optional) Enter a short description for your Llama Stack: ",
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default="",
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)
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distribution_spec = DistributionSpec(
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providers=providers,
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description=description,
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)
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build_config = BuildConfig(
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name=name, image_type=image_type, distribution_spec=distribution_spec
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)
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self._run_stack_build_command_from_build_config(build_config)
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return
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with open(args.config, "r") as f:
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@ -9,7 +9,6 @@ import json
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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_stack.cli.subcommand import Subcommand
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from llama_stack.distribution.utils.config_dirs import BUILDS_BASE_DIR
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@ -50,9 +49,12 @@ class StackConfigure(Subcommand):
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import pkg_resources
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from llama_stack.distribution.build import ImageType
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from termcolor import cprint
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docker_image = None
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build_config_file = Path(args.config)
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conda_dir = Path(os.getenv("CONDA_PREFIX")).parent / f"llamastack-{args.config}"
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build_config_file = Path(conda_dir) / f"{args.config}-build.yaml"
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if not build_config_file.exists():
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cprint(
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f"Could not find {build_config_file}. Trying docker image name instead...",
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@ -79,8 +81,9 @@ class StackConfigure(Subcommand):
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)
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build_name = docker_image.removeprefix("llamastack-")
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saved_file = str(builds_dir / f"{build_name}-run.yaml")
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cprint(
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f"YAML configuration has been written to {builds_dir / f'{build_name}-run.yaml'}",
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f"YAML configuration has been written to {saved_file}. You can now run `llama stack run {saved_file}`",
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color="green",
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)
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return
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@ -97,6 +100,7 @@ class StackConfigure(Subcommand):
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):
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from llama_stack.distribution.configure import configure_api_providers
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from llama_stack.distribution.utils.serialize import EnumEncoder
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from termcolor import cprint
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builds_dir = BUILDS_BASE_DIR / build_config.image_type
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if output_dir:
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@ -132,6 +136,11 @@ class StackConfigure(Subcommand):
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f.write(yaml.dump(to_write, sort_keys=False))
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cprint(
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f"> YAML configuration has been written to {run_config_file}",
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f"> YAML configuration has been written to {run_config_file}.",
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color="blue",
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)
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cprint(
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f"You can now run `llama stack run {image_name} --port PORT` or `llama stack run {run_config_file} --port PORT`",
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color="green",
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)
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@ -47,6 +47,8 @@ class StackRun(Subcommand):
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def _run_stack_run_cmd(self, args: argparse.Namespace) -> None:
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import pkg_resources
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from llama_stack.distribution.build import ImageType
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from llama_stack.distribution.utils.config_dirs import BUILDS_BASE_DIR
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from llama_stack.distribution.utils.exec import run_with_pty
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@ -54,12 +56,22 @@ class StackRun(Subcommand):
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self.parser.error("Must specify a config file to run")
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return
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path = args.config
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config_file = Path(path)
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config_file = Path(args.config)
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if not config_file.exists() and not args.config.endswith(".yaml"):
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# check if it's a build config saved to conda dir
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config_file = Path(
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BUILDS_BASE_DIR / ImageType.conda.value / f"{args.config}-run.yaml"
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)
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if not config_file.exists() and not args.config.endswith(".yaml"):
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# check if it's a build config saved to docker dir
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config_file = Path(
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BUILDS_BASE_DIR / ImageType.docker.value / f"{args.config}-run.yaml"
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)
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if not config_file.exists():
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self.parser.error(
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f"File {str(config_file)} does not exist. Did you run `llama stack build`?"
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f"File {str(config_file)} does not exist. Please run `llama stack build` and `llama stack configure <name>` to generate a run.yaml file"
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)
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return
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