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63 lines
No EOL
2.2 KiB
Python
63 lines
No EOL
2.2 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 logging
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import asyncio
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from typing import TYPE_CHECKING, List, Optional
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if TYPE_CHECKING:
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from sentence_transformers import SentenceTransformer
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from llama_stack.apis.inference import (
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EmbeddingsResponse,
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EmbeddingTaskType,
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InterleavedContentItem,
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ModelStore,
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TextTruncation,
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)
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from llama_stack.providers.utils.inference.prompt_adapter import interleaved_content_as_str
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EMBEDDING_MODELS = {}
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log = logging.getLogger(__name__)
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class SentenceTransformerEmbeddingMixin:
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model_store: ModelStore
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async def embeddings(
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self,
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model_id: str,
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contents: List[str] | List[InterleavedContentItem],
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text_truncation: Optional[TextTruncation] = TextTruncation.none,
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output_dimension: Optional[int] = None,
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task_type: Optional[EmbeddingTaskType] = None,
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) -> EmbeddingsResponse:
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model = await self.model_store.get_model(model_id)
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embedding_model = await self._load_sentence_transformer_model(model.provider_resource_id)
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# Execute the synchronous encode method in an executor
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embeddings = await self._run_in_executor(embedding_model.encode, [interleaved_content_as_str(content) for content in contents], show_progress_bar=False)
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return EmbeddingsResponse(embeddings=embeddings)
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async def _load_sentence_transformer_model(self, model: str) -> "SentenceTransformer":
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global EMBEDDING_MODELS
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loaded_model = EMBEDDING_MODELS.get(model)
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if loaded_model is not None:
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return loaded_model
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log.info(f"Loading sentence transformer for {model}...")
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from sentence_transformers import SentenceTransformer
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# Execute the synchronous SentenceTransformer instantiation in an executor
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loaded_model = await self._run_in_executor(SentenceTransformer, model)
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EMBEDDING_MODELS[model] = loaded_model
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return loaded_model
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async def _run_in_executor(self, func, *args, **kwargs):
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loop = asyncio.get_event_loop()
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return await loop.run_in_executor(None, func, *args, **kwargs) |