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Make embedding generation go through inference (#606)

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This PR does the following:
1) adds the ability to generate embeddings in all supported inference
providers.
2) Moves all the memory providers to use the inference API and improved
the memory tests to setup the inference stack correctly and use the
embedding models

This is a merge from #589 and #598
This commit is contained in:
Dinesh Yeduguru 2024-12-12 11:47:50 -08:00 • committed by GitHub
parent a14785af46
commit 96e158eaac
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37 changed files with 677 additions and 156 deletions
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9
llama_stack/providers/utils/inference/model_registry.py
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@ -9,6 +9,7 @@ from typing import List, Optional
from llama_models.sku_list import all_registered_models
from llama_stack.apis.models.models import ModelType
from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
from llama_stack.providers.utils.inference import (
@ -77,7 +78,13 @@ class ModelRegistryHelper(ModelsProtocolPrivate):
return None
async def register_model(self, model: Model) -> Model:
provider_resource_id = self.get_provider_model_id(model.provider_resource_id)
if model.model_type == ModelType.embedding_model:
# 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: