# 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. from typing import List, Optional from pydantic import BaseModel, Field from llama_stack.apis.models.models import ModelType from llama_stack.models.llama.sku_list import all_registered_models from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate from llama_stack.providers.utils.inference import ( ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR, ) # TODO: this class is more confusing than useful right now. We need to make it # more closer to the Model class. class ModelAlias(BaseModel): provider_model_id: str aliases: List[str] = Field(default_factory=list) llama_model: Optional[str] = None model_type: ModelType = ModelType.llm def get_huggingface_repo(model_descriptor: str) -> Optional[str]: for model in all_registered_models(): if model.descriptor() == model_descriptor: return model.huggingface_repo return None def build_model_alias(provider_model_id: str, model_descriptor: str) -> ModelAlias: return ModelAlias( provider_model_id=provider_model_id, aliases=[ get_huggingface_repo(model_descriptor), ], llama_model=model_descriptor, ) def build_model_alias_with_just_provider_model_id(provider_model_id: str, model_descriptor: str) -> ModelAlias: return ModelAlias( provider_model_id=provider_model_id, aliases=[], llama_model=model_descriptor, ) class ModelRegistryHelper(ModelsProtocolPrivate): def __init__(self, model_aliases: List[ModelAlias]): self.alias_to_provider_id_map = {} self.provider_id_to_llama_model_map = {} for alias_obj in model_aliases: for alias in alias_obj.aliases: self.alias_to_provider_id_map[alias] = alias_obj.provider_model_id # also add a mapping from provider model id to itself for easy lookup self.alias_to_provider_id_map[alias_obj.provider_model_id] = alias_obj.provider_model_id # ensure we can go from llama model to provider model id self.alias_to_provider_id_map[alias_obj.llama_model] = alias_obj.provider_model_id self.provider_id_to_llama_model_map[alias_obj.provider_model_id] = alias_obj.llama_model def get_provider_model_id(self, identifier: str) -> Optional[str]: return self.alias_to_provider_id_map.get(identifier, None) def get_llama_model(self, provider_model_id: str) -> Optional[str]: return self.provider_id_to_llama_model_map.get(provider_model_id, None) async def register_model(self, model: Model) -> Model: if model.model_type == ModelType.embedding: # embedding models are always registered by their provider model id and does not need to be mapped to a llama model provider_resource_id = model.provider_resource_id else: provider_resource_id = self.get_provider_model_id(model.provider_resource_id) if provider_resource_id: model.provider_resource_id = provider_resource_id else: if model.metadata.get("llama_model") is None: raise ValueError( f"Model '{model.provider_resource_id}' is not available and no llama_model was specified in metadata. " "Please specify a llama_model in metadata or use a supported model identifier" ) existing_llama_model = self.get_llama_model(model.provider_resource_id) if existing_llama_model: if existing_llama_model != model.metadata["llama_model"]: raise ValueError( f"Provider model id '{model.provider_resource_id}' is already registered to a different llama model: '{existing_llama_model}'" ) else: if model.metadata["llama_model"] not in ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR: raise ValueError( f"Invalid llama_model '{model.metadata['llama_model']}' specified in metadata. " f"Must be one of: {', '.join(ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR.keys())}" ) self.provider_id_to_llama_model_map[model.provider_resource_id] = ( ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR[model.metadata["llama_model"]] ) return model