mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-08-01 16:24:44 +00:00
update build cli
This commit is contained in:
Xi Yan
parent
768ed09dec
commit
d1f0d17644
6 changed files with 109 additions and 117 deletions
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@ -72,65 +72,20 @@ class StackBuild(Subcommand):
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from llama_toolchain.core.package import ApiInput, build_package, ImageType
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from termcolor import cprint
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# expect build to take in a distribution spec file
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api_inputs = []
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if build_config.distribution == "adhoc":
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if not build_config.api_providers:
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self.parser.error(
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"You must specify API providers with (api=provider,...) for building an adhoc distribution"
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)
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return
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parsed = parse_api_provider_tuples(build_config.api_providers, self.parser)
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for api, provider_spec in parsed.items():
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for dep in provider_spec.api_dependencies:
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if dep not in parsed:
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self.parser.error(
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f"API {api} needs dependency {dep} provided also"
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)
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return
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for api, provider_type in build_config.distribution_spec.providers.items():
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api_inputs.append(
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ApiInput(
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api=api,
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provider=provider_spec.provider_type,
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)
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)
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docker_image = None
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else:
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if build_config.api_providers:
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self.parser.error(
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"You cannot specify API providers for pre-registered distributions"
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)
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return
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dist = resolve_distribution_spec(build_config.distribution)
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if dist is None:
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self.parser.error(
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f"Could not find distribution {build_config.distribution}"
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)
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return
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for api, provider_type in dist.providers.items():
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api_inputs.append(
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ApiInput(
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api=api,
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api=Api(api),
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provider=provider_type,
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)
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)
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docker_image = dist.docker_image
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build_package(
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api_inputs,
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image_type=ImageType(build_config.image_type),
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name=build_config.name,
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distribution_type=build_config.distribution,
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docker_image=docker_image,
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)
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build_package(build_config)
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# save build.yaml spec for building same distribution again
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build_dir = (
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DISTRIBS_BASE_DIR / build_config.distribution / build_config.image_type
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)
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build_dir = DISTRIBS_BASE_DIR / build_config.image_type
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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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@ -19,17 +19,15 @@ fi
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set -euo pipefail
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if [ "$#" -ne 4 ]; then
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if [ "$#" -ne 2 ]; then
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echo "Usage: $0 <distribution_type> <build_name> <pip_dependencies>" >&2
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echo "Example: $0 <distribution_type> mybuild 'numpy pandas scipy'" >&2
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exit 1
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fi
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distribution_type="$1"
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build_name="$2"
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build_name="$1"
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env_name="llamastack-$build_name"
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config_file="$3"
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pip_dependencies="$4"
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pip_dependencies="$2"
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# Define color codes
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RED='\033[0;31m'
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@ -151,12 +151,23 @@ def remote_provider_spec(
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@json_schema_type
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class DistributionSpec(BaseModel):
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distribution_type: str
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description: str
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distribution_type: str = Field(
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default="local",
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description="Name of the distribution type. This can used to identify the distribution",
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)
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description: str = Field(
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default="Use code from `llama_toolchain` itself to serve all llama stack APIs",
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description="Description of the distribution",
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)
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docker_image: Optional[str] = None
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providers: Dict[Api, str] = Field(
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default_factory=dict,
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providers: Dict[str, str] = Field(
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default={
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"inference": "meta-reference",
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"memory": "meta-reference-faiss",
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"safety": "meta-reference",
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"agentic_system": "meta-reference",
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"telemetry": "console",
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},
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description="Provider Types for each of the APIs provided by this distribution",
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)
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@ -194,12 +205,8 @@ the dependencies of these providers as well.
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@json_schema_type
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class BuildConfig(BaseModel):
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name: str
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distribution: str = Field(
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default="local", description="Type of distribution to build (adhoc | {})"
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)
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api_providers: Optional[str] = Field(
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default_factory=list,
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description="List of API provider names to build",
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distribution_spec: DistributionSpec = Field(
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description="The distribution spec to build including API providers. "
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)
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image_type: str = Field(
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default="conda",
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@ -31,14 +31,14 @@ SERVER_DEPENDENCIES = [
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]
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def distribution_dependencies(distribution: DistributionSpec) -> List[str]:
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# only consider InlineProviderSpecs when calculating dependencies
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return [
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dep
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for provider_spec in distribution.provider_specs.values()
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if isinstance(provider_spec, InlineProviderSpec)
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for dep in provider_spec.pip_packages
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] + SERVER_DEPENDENCIES
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# def distribution_dependencies(distribution: DistributionSpec) -> List[str]:
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# # only consider InlineProviderSpecs when calculating dependencies
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# return [
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# dep
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# for provider_spec in distribution.provider_specs.values()
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# if isinstance(provider_spec, InlineProviderSpec)
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# for dep in provider_spec.pip_packages
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# ] + SERVER_DEPENDENCIES
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def stack_apis() -> List[Api]:
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@ -17,62 +17,43 @@ def available_distribution_specs() -> List[DistributionSpec]:
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distribution_type="local",
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description="Use code from `llama_toolchain` itself to serve all llama stack APIs",
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providers={
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Api.inference: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.telemetry: "console",
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},
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),
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DistributionSpec(
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distribution_type="remote",
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description="Point to remote services for all llama stack APIs",
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providers={
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**{x: "remote" for x in Api},
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Api.telemetry: "console",
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"inference": "meta-reference",
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"memory": "meta-reference-faiss",
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"safety": "meta-reference",
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"agentic_system": "meta-reference",
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"telemetry": "console",
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},
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),
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DistributionSpec(
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distribution_type="local-ollama",
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description="Like local, but use ollama for running LLM inference",
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providers={
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Api.inference: remote_provider_type("ollama"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.telemetry: "console",
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"inference": remote_provider_type("ollama"),
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"safety": "meta-reference",
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"agentic_system": "meta-reference",
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"memory": "meta-reference-faiss",
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"telemetry": "console",
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},
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),
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DistributionSpec(
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distribution_type="local-plus-fireworks-inference",
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description="Use Fireworks.ai for running LLM inference",
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providers={
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Api.inference: remote_provider_type("fireworks"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.telemetry: "console",
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},
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),
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DistributionSpec(
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distribution_type="local-plus-together-inference",
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description="Use Together.ai for running LLM inference",
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providers={
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Api.inference: remote_provider_type("together"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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Api.telemetry: "console",
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"inference": remote_provider_type("fireworks"),
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"safety": "meta-reference",
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"agentic_system": "meta-reference",
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"memory": "meta-reference-faiss",
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"telemetry": "console",
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},
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),
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DistributionSpec(
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distribution_type="local-plus-tgi-inference",
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description="Use TGI for running LLM inference",
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providers={
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Api.inference: remote_provider_type("tgi"),
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Api.safety: "meta-reference",
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Api.agentic_system: "meta-reference",
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Api.memory: "meta-reference-faiss",
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"inference": remote_provider_type("tgi"),
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"safety": "meta-reference",
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"agentic_system": "meta-reference",
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"memory": "meta-reference-faiss",
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},
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),
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]
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@ -39,7 +39,58 @@ class ApiInput(BaseModel):
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provider: str
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def build_package(
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def build_package(build_config: BuildConfig):
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package_deps = Dependencies(
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docker_image=build_config.distribution_spec.docker_image or "python:3.10-slim",
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pip_packages=SERVER_DEPENDENCIES,
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)
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# extend package dependencies based on providers spec
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all_providers = api_providers()
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for api_str, provider in build_config.distribution_spec.providers.items():
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providers_for_api = all_providers[Api(api_str)]
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if provider not in providers_for_api:
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raise ValueError(
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f"Provider `{provider}` is not available for API `{api_str}`"
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)
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provider_spec = providers_for_api[provider]
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package_deps.pip_packages.extend(provider_spec.pip_packages)
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if provider_spec.docker_image:
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raise ValueError("A stack's dependencies cannot have a docker image")
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if build_config.image_type == ImageType.docker.value:
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script = pkg_resources.resource_filename(
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"llama_toolchain", "core/build_container.sh"
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)
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args = [
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script,
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distribution_type,
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package_name,
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package_deps.docker_image,
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str(package_file),
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" ".join(package_deps.pip_packages),
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]
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else:
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script = pkg_resources.resource_filename(
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"llama_toolchain", "core/build_conda_env.sh"
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)
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args = [
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script,
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build_config.name,
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" ".join(package_deps.pip_packages),
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]
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return_code = run_with_pty(args)
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if return_code != 0:
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cprint(
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f"Failed to build target {build_config.name} with return code {return_code}",
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color="red",
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)
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return
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def build_package_deprecated(
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api_inputs: List[ApiInput],
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image_type: ImageType,
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name: str,
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