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https://github.com/meta-llama/llama-stack.git
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68a2dfbad7
For self-hosted providers like Ollama (or vLLM), the backing server is running a set of models. That server should be treated as the source of truth and the Stack registry should just be a cache for those models. Of course, in production environments, you may not want this (because you know what model you are running statically) hence there's a config boolean to control this behavior. _This is part of a series of PRs aimed at removing the requirement of needing to set `INFERENCE_MODEL` env variables for running Llama Stack server._ ## Test Plan Copy and modify the starter.yaml template / config and enable `refresh_models: true, refresh_models_interval: 10` for the ollama provider. Then, run: ``` LLAMA_STACK_LOGGING=all=debug \ ENABLE_OLLAMA=ollama uv run llama stack run --image-type venv /tmp/starter.yaml ``` See a gargantuan amount of logs, but verify that the provider is periodically refreshing models. Stop and prune a model from ollama server, restart the server. Verify that the model goes away when I call `uv run llama-stack-client models list`
113 lines
4.3 KiB
Python
113 lines
4.3 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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import time
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from typing import Any
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from llama_stack.apis.models import ListModelsResponse, Model, Models, ModelType, OpenAIListModelsResponse, OpenAIModel
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from llama_stack.distribution.datatypes import (
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ModelWithOwner,
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)
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from llama_stack.log import get_logger
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from .common import CommonRoutingTableImpl
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logger = get_logger(name=__name__, category="core")
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class ModelsRoutingTable(CommonRoutingTableImpl, Models):
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async def list_models(self) -> ListModelsResponse:
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return ListModelsResponse(data=await self.get_all_with_type("model"))
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async def openai_list_models(self) -> OpenAIListModelsResponse:
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models = await self.get_all_with_type("model")
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openai_models = [
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OpenAIModel(
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id=model.identifier,
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object="model",
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created=int(time.time()),
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owned_by="llama_stack",
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)
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for model in models
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]
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return OpenAIListModelsResponse(data=openai_models)
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async def get_model(self, model_id: str) -> Model:
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model = await self.get_object_by_identifier("model", model_id)
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if model is None:
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raise ValueError(f"Model '{model_id}' not found")
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return model
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async def register_model(
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self,
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model_id: str,
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provider_model_id: str | None = None,
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provider_id: str | None = None,
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metadata: dict[str, Any] | None = None,
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model_type: ModelType | None = None,
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) -> Model:
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if provider_model_id is None:
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provider_model_id = model_id
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if provider_id is None:
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# If provider_id not specified, use the only provider if it supports this model
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if len(self.impls_by_provider_id) == 1:
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provider_id = list(self.impls_by_provider_id.keys())[0]
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else:
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raise ValueError(
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f"No provider specified and multiple providers available. Please specify a provider_id. Available providers: {self.impls_by_provider_id.keys()}"
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)
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if metadata is None:
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metadata = {}
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if model_type is None:
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model_type = ModelType.llm
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if "embedding_dimension" not in metadata and model_type == ModelType.embedding:
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raise ValueError("Embedding model must have an embedding dimension in its metadata")
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model = ModelWithOwner(
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identifier=model_id,
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provider_resource_id=provider_model_id,
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provider_id=provider_id,
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metadata=metadata,
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model_type=model_type,
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)
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registered_model = await self.register_object(model)
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return registered_model
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async def unregister_model(self, model_id: str) -> None:
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existing_model = await self.get_model(model_id)
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if existing_model is None:
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raise ValueError(f"Model {model_id} not found")
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await self.unregister_object(existing_model)
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async def update_registered_models(
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self,
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provider_id: str,
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models: list[Model],
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) -> None:
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existing_models = await self.get_all_with_type("model")
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# we may have an alias for the model registered by the user (or during initialization
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# from run.yaml) that we need to keep track of
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model_ids = {}
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for model in existing_models:
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if model.provider_id == provider_id:
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model_ids[model.provider_resource_id] = model.identifier
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logger.debug(f"unregistering model {model.identifier}")
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await self.unregister_object(model)
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for model in models:
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if model.provider_resource_id in model_ids:
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model.identifier = model_ids[model.provider_resource_id]
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logger.debug(f"registering model {model.identifier} ({model.provider_resource_id})")
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await self.register_object(
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ModelWithOwner(
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identifier=model.identifier,
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provider_resource_id=model.provider_resource_id,
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provider_id=provider_id,
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metadata=model.metadata,
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model_type=model.model_type,
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)
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)
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