add embedding model by default to distribution templates (#617)

# What does this PR do?
Adds the sentence transformer provider and the `all-MiniLM-L6-v2`
embedding model to the default models to register in the run.yaml for
all providers.

## Test Plan
llama stack build --template together --image-type conda
llama stack run
~/.llama/distributions/llamastack-together/together-run.yaml
This commit is contained in:
Dinesh Yeduguru 2024-12-13 12:48:00 -08:00 committed by GitHub
parent e893b22868
commit 516e1a3e59
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41 changed files with 473 additions and 64 deletions

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@ -4,7 +4,11 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.models.models import ModelType
from llama_stack.distribution.datatypes import ModelInput, Provider
from llama_stack.providers.inline.inference.sentence_transformers import (
SentenceTransformersInferenceConfig,
)
from llama_stack.providers.inline.inference.vllm import VLLMConfig
from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@ -32,11 +36,24 @@ def get_distribution_template() -> DistributionTemplate:
provider_type="inline::faiss",
config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
)
embedding_provider = Provider(
provider_id="sentence-transformers",
provider_type="inline::sentence-transformers",
config=SentenceTransformersInferenceConfig.sample_run_config(),
)
inference_model = ModelInput(
model_id="${env.INFERENCE_MODEL}",
provider_id="vllm",
)
embedding_model = ModelInput(
model_id="all-MiniLM-L6-v2",
provider_id="sentence-transformers",
model_type=ModelType.embedding,
metadata={
"embedding_dimension": 384,
},
)
return DistributionTemplate(
name=name,
@ -49,10 +66,10 @@ def get_distribution_template() -> DistributionTemplate:
run_configs={
"run.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"inference": [inference_provider, embedding_provider],
"memory": [memory_provider],
},
default_models=[inference_model],
default_models=[inference_model, embedding_model],
),
},
run_config_env_vars={