Make embedding generation go through inference (#606)

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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GPG key ID: B5690EEEBB952194
37 changed files with 677 additions and 156 deletions

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@ -4,6 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from enum import Enum
from typing import Any, Dict, List, Literal, Optional, Protocol, runtime_checkable
from llama_models.schema_utils import json_schema_type, webmethod
@ -20,6 +21,11 @@ class CommonModelFields(BaseModel):
)
class ModelType(Enum):
llm = "llm"
embedding_model = "embedding"
@json_schema_type
class Model(CommonModelFields, Resource):
type: Literal[ResourceType.model.value] = ResourceType.model.value
@ -34,12 +40,14 @@ class Model(CommonModelFields, Resource):
model_config = ConfigDict(protected_namespaces=())
model_type: ModelType = Field(default=ModelType.llm)
class ModelInput(CommonModelFields):
model_id: str
provider_id: Optional[str] = None
provider_model_id: Optional[str] = None
model_type: Optional[ModelType] = ModelType.llm
model_config = ConfigDict(protected_namespaces=())
@ -59,6 +67,7 @@ class Models(Protocol):
provider_model_id: Optional[str] = None,
provider_id: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
model_type: Optional[ModelType] = None,
) -> Model: ...
@webmethod(route="/models/unregister", method="POST")