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# What does this PR do? Refactor setting default vector store provider and embedding model to use an optional `vector_stores` config in the `StackRunConfig` and clean up code to do so (had to add back in some pieces of VectorDB). Also added remote Qdrant and Weaviate to starter distro (based on other PR where inference providers were added for UX). New config is simply (default for Starter distro): ```yaml vector_stores: default_provider_id: faiss default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 ``` ## Test Plan CI and Unit tests. --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
454 lines
18 KiB
Python
454 lines
18 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from pathlib import Path
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from typing import Any, Literal
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import jinja2
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import rich
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import yaml
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from pydantic import BaseModel, Field
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from llama_stack.apis.datasets import DatasetPurpose
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from llama_stack.apis.models import ModelType
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from llama_stack.core.datatypes import (
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LLAMA_STACK_RUN_CONFIG_VERSION,
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Api,
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BenchmarkInput,
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BuildConfig,
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BuildProvider,
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DatasetInput,
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DistributionSpec,
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ModelInput,
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Provider,
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ShieldInput,
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TelemetryConfig,
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ToolGroupInput,
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VectorStoresConfig,
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)
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from llama_stack.core.distribution import get_provider_registry
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from llama_stack.core.storage.datatypes import (
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InferenceStoreReference,
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KVStoreReference,
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SqlStoreReference,
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StorageBackendType,
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)
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from llama_stack.core.utils.dynamic import instantiate_class_type
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from llama_stack.core.utils.image_types import LlamaStackImageType
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from llama_stack.providers.utils.inference.model_registry import ProviderModelEntry
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from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
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from llama_stack.providers.utils.kvstore.config import get_pip_packages as get_kv_pip_packages
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from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
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from llama_stack.providers.utils.sqlstore.sqlstore import get_pip_packages as get_sql_pip_packages
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def filter_empty_values(obj: Any) -> Any:
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"""Recursively filter out specific empty values from a dictionary or list.
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This function removes:
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- Empty strings ('') only when they are the 'module' field
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- Empty dictionaries ({}) only when they are the 'config' field
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- None values (always excluded)
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"""
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if obj is None:
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return None
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if isinstance(obj, dict):
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filtered = {}
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for key, value in obj.items():
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# Special handling for specific fields
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if key == "module" and isinstance(value, str) and value == "":
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# Skip empty module strings
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continue
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elif key == "config" and isinstance(value, dict) and not value:
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# Skip empty config dictionaries
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continue
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elif key == "container_image" and not value:
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# Skip empty container_image names
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continue
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else:
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# For all other fields, recursively filter but preserve empty values
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filtered_value = filter_empty_values(value)
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# if filtered_value is not None:
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filtered[key] = filtered_value
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return filtered
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elif isinstance(obj, list):
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filtered = []
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for item in obj:
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filtered_item = filter_empty_values(item)
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if filtered_item is not None:
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filtered.append(filtered_item)
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return filtered
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else:
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# For all other types (including empty strings and dicts that aren't module/config),
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# preserve them as-is
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return obj
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def get_model_registry(
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available_models: dict[str, list[ProviderModelEntry]],
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) -> tuple[list[ModelInput], bool]:
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models = []
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# check for conflicts in model ids
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all_ids = set()
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ids_conflict = False
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for _, entries in available_models.items():
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for entry in entries:
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ids = [entry.provider_model_id] + entry.aliases
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for model_id in ids:
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if model_id in all_ids:
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ids_conflict = True
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rich.print(
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f"[yellow]Model id {model_id} conflicts; all model ids will be prefixed with provider id[/yellow]"
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)
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break
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all_ids.update(ids)
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if ids_conflict:
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break
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if ids_conflict:
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break
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for provider_id, entries in available_models.items():
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for entry in entries:
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ids = [entry.provider_model_id] + entry.aliases
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for model_id in ids:
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identifier = f"{provider_id}/{model_id}" if ids_conflict and provider_id not in model_id else model_id
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models.append(
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ModelInput(
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model_id=identifier,
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provider_model_id=entry.provider_model_id,
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provider_id=provider_id,
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model_type=entry.model_type,
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metadata=entry.metadata,
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)
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)
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return models, ids_conflict
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def get_shield_registry(
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available_safety_models: dict[str, list[ProviderModelEntry]],
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ids_conflict_in_models: bool,
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) -> list[ShieldInput]:
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shields = []
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# check for conflicts in shield ids
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all_ids = set()
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ids_conflict = False
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for _, entries in available_safety_models.items():
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for entry in entries:
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ids = [entry.provider_model_id] + entry.aliases
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for model_id in ids:
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if model_id in all_ids:
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ids_conflict = True
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rich.print(
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f"[yellow]Shield id {model_id} conflicts; all shield ids will be prefixed with provider id[/yellow]"
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)
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break
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all_ids.update(ids)
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if ids_conflict:
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break
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if ids_conflict:
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break
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for provider_id, entries in available_safety_models.items():
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for entry in entries:
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ids = [entry.provider_model_id] + entry.aliases
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for model_id in ids:
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identifier = f"{provider_id}/{model_id}" if ids_conflict and provider_id not in model_id else model_id
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shields.append(
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ShieldInput(
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shield_id=identifier,
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provider_shield_id=f"{provider_id}/{entry.provider_model_id}"
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if ids_conflict_in_models
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else entry.provider_model_id,
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)
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)
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return shields
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class DefaultModel(BaseModel):
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model_id: str
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doc_string: str
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class RunConfigSettings(BaseModel):
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provider_overrides: dict[str, list[Provider]] = Field(default_factory=dict)
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default_models: list[ModelInput] | None = None
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default_shields: list[ShieldInput] | None = None
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default_tool_groups: list[ToolGroupInput] | None = None
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default_datasets: list[DatasetInput] | None = None
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default_benchmarks: list[BenchmarkInput] | None = None
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vector_stores_config: VectorStoresConfig | None = None
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telemetry: TelemetryConfig = Field(default_factory=lambda: TelemetryConfig(enabled=True))
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storage_backends: dict[str, Any] | None = None
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storage_stores: dict[str, Any] | None = None
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def run_config(
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self,
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name: str,
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providers: dict[str, list[BuildProvider]],
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container_image: str | None = None,
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) -> dict:
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provider_registry = get_provider_registry()
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provider_configs = {}
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for api_str, provider_objs in providers.items():
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if api_providers := self.provider_overrides.get(api_str):
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# Convert Provider objects to dicts for YAML serialization
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provider_configs[api_str] = [p.model_dump(exclude_none=True) for p in api_providers]
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continue
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provider_configs[api_str] = []
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for provider in provider_objs:
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api = Api(api_str)
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if provider.provider_type not in provider_registry[api]:
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raise ValueError(f"Unknown provider type: {provider.provider_type} for API: {api_str}")
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provider_id = provider.provider_type.split("::")[-1]
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config_class = provider_registry[api][provider.provider_type].config_class
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assert config_class is not None, (
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f"No config class for provider type: {provider.provider_type} for API: {api_str}"
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)
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config_class = instantiate_class_type(config_class)
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if hasattr(config_class, "sample_run_config"):
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config = config_class.sample_run_config(__distro_dir__=f"~/.llama/distributions/{name}")
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else:
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config = {}
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# BuildProvider does not have a config attribute; skip assignment
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provider_configs[api_str].append(
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Provider(
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provider_id=provider_id,
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provider_type=provider.provider_type,
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config=config,
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).model_dump(exclude_none=True)
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)
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# Get unique set of APIs from providers
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apis = sorted(providers.keys())
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storage_backends = self.storage_backends or {
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"kv_default": SqliteKVStoreConfig.sample_run_config(
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__distro_dir__=f"~/.llama/distributions/{name}",
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db_name="kvstore.db",
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),
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"sql_default": SqliteSqlStoreConfig.sample_run_config(
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__distro_dir__=f"~/.llama/distributions/{name}",
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db_name="sql_store.db",
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),
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}
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storage_stores = self.storage_stores or {
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"metadata": KVStoreReference(
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backend="kv_default",
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namespace="registry",
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).model_dump(exclude_none=True),
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"inference": InferenceStoreReference(
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backend="sql_default",
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table_name="inference_store",
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).model_dump(exclude_none=True),
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"conversations": SqlStoreReference(
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backend="sql_default",
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table_name="openai_conversations",
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).model_dump(exclude_none=True),
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}
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storage_config = dict(
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backends=storage_backends,
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stores=storage_stores,
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)
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# Return a dict that matches StackRunConfig structure
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config = {
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"version": LLAMA_STACK_RUN_CONFIG_VERSION,
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"image_name": name,
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"container_image": container_image,
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"apis": apis,
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"providers": provider_configs,
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"storage": storage_config,
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"models": [m.model_dump(exclude_none=True) for m in (self.default_models or [])],
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"shields": [s.model_dump(exclude_none=True) for s in (self.default_shields or [])],
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"vector_dbs": [],
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"datasets": [d.model_dump(exclude_none=True) for d in (self.default_datasets or [])],
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"scoring_fns": [],
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"benchmarks": [b.model_dump(exclude_none=True) for b in (self.default_benchmarks or [])],
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"tool_groups": [t.model_dump(exclude_none=True) for t in (self.default_tool_groups or [])],
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"server": {
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"port": 8321,
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},
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"telemetry": self.telemetry.model_dump(exclude_none=True) if self.telemetry else None,
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}
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if self.vector_stores_config:
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config["vector_stores"] = self.vector_stores_config.model_dump(exclude_none=True)
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return config
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class DistributionTemplate(BaseModel):
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"""
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Represents a Llama Stack distribution instance that can generate configuration
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and documentation files.
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"""
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name: str
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description: str
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distro_type: Literal["self_hosted", "remote_hosted", "ondevice"]
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# Now uses BuildProvider for build config, not Provider
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providers: dict[str, list[BuildProvider]]
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run_configs: dict[str, RunConfigSettings]
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template_path: Path | None = None
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# Optional configuration
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run_config_env_vars: dict[str, tuple[str, str]] | None = None
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container_image: str | None = None
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available_models_by_provider: dict[str, list[ProviderModelEntry]] | None = None
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# we may want to specify additional pip packages without necessarily indicating a
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# specific "default" inference store (which is what typically used to dictate additional
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# pip packages)
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additional_pip_packages: list[str] | None = None
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def build_config(self) -> BuildConfig:
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additional_pip_packages: list[str] = []
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for run_config in self.run_configs.values():
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run_config_ = run_config.run_config(self.name, self.providers, self.container_image)
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# TODO: This is a hack to get the dependencies for internal APIs into build
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# We should have a better way to do this by formalizing the concept of "internal" APIs
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# and providers, with a way to specify dependencies for them.
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storage_cfg = run_config_.get("storage", {})
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for backend_cfg in storage_cfg.get("backends", {}).values():
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store_type = backend_cfg.get("type")
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if not store_type:
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continue
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if str(store_type).startswith("kv_"):
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additional_pip_packages.extend(get_kv_pip_packages(backend_cfg))
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elif str(store_type).startswith("sql_"):
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additional_pip_packages.extend(get_sql_pip_packages(backend_cfg))
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if self.additional_pip_packages:
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additional_pip_packages.extend(self.additional_pip_packages)
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# Create minimal providers for build config (without runtime configs)
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build_providers = {}
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for api, providers in self.providers.items():
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build_providers[api] = []
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for provider in providers:
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# Create a minimal build provider object with only essential build information
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build_provider = BuildProvider(
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provider_type=provider.provider_type,
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module=provider.module,
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)
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build_providers[api].append(build_provider)
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return BuildConfig(
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distribution_spec=DistributionSpec(
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description=self.description,
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container_image=self.container_image,
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providers=build_providers,
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),
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image_type=LlamaStackImageType.VENV.value, # default to venv
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additional_pip_packages=sorted(set(additional_pip_packages)),
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)
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def generate_markdown_docs(self) -> str:
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providers_table = "| API | Provider(s) |\n"
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providers_table += "|-----|-------------|\n"
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for api, providers in sorted(self.providers.items()):
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providers_str = ", ".join(f"`{p.provider_type}`" for p in providers)
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providers_table += f"| {api} | {providers_str} |\n"
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if self.template_path is not None:
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template = self.template_path.read_text()
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comment = "<!-- This file was auto-generated by distro_codegen.py, please edit source -->\n"
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orphantext = "---\norphan: true\n---\n"
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if template.startswith(orphantext):
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template = template.replace(orphantext, orphantext + comment)
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else:
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template = comment + template
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# Render template with rich-generated table
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env = jinja2.Environment(
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trim_blocks=True,
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lstrip_blocks=True,
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# NOTE: autoescape is required to prevent XSS attacks
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autoescape=True,
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)
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template = env.from_string(template)
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default_models = []
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if self.available_models_by_provider:
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has_multiple_providers = len(self.available_models_by_provider.keys()) > 1
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for provider_id, model_entries in self.available_models_by_provider.items():
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for model_entry in model_entries:
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doc_parts = []
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if model_entry.aliases:
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doc_parts.append(f"aliases: {', '.join(model_entry.aliases)}")
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if has_multiple_providers:
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doc_parts.append(f"provider: {provider_id}")
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default_models.append(
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DefaultModel(
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model_id=model_entry.provider_model_id,
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doc_string=(f"({' -- '.join(doc_parts)})" if doc_parts else ""),
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)
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)
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return template.render(
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name=self.name,
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description=self.description,
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providers=self.providers,
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providers_table=providers_table,
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run_config_env_vars=self.run_config_env_vars,
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default_models=default_models,
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)
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return ""
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def save_distribution(self, yaml_output_dir: Path, doc_output_dir: Path) -> None:
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def enum_representer(dumper, data):
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return dumper.represent_scalar("tag:yaml.org,2002:str", data.value)
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# Register YAML representer for enums
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yaml.add_representer(ModelType, enum_representer)
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yaml.add_representer(DatasetPurpose, enum_representer)
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yaml.add_representer(StorageBackendType, enum_representer)
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yaml.SafeDumper.add_representer(ModelType, enum_representer)
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yaml.SafeDumper.add_representer(DatasetPurpose, enum_representer)
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yaml.SafeDumper.add_representer(StorageBackendType, enum_representer)
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for output_dir in [yaml_output_dir, doc_output_dir]:
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output_dir.mkdir(parents=True, exist_ok=True)
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build_config = self.build_config()
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with open(yaml_output_dir / "build.yaml", "w") as f:
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yaml.safe_dump(
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filter_empty_values(build_config.model_dump(exclude_none=True)),
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f,
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sort_keys=False,
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)
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for yaml_pth, settings in self.run_configs.items():
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run_config = settings.run_config(self.name, self.providers, self.container_image)
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with open(yaml_output_dir / yaml_pth, "w") as f:
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yaml.safe_dump(
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filter_empty_values(run_config),
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f,
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sort_keys=False,
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)
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if self.template_path:
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docs = self.generate_markdown_docs()
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with open(doc_output_dir / f"{self.name}.md", "w") as f:
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f.write(docs if docs.endswith("\n") else docs + "\n")
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