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feat(api): Add options for supporting various embedding models (#1192)

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We need to support:
- asymmetric embedding models (#934)
- truncation policies (#933)
- varying dimensional output (#932) 

## Test Plan

```bash
$ cd llama_stack/providers/tests/inference
$ pytest -s -v -k fireworks test_embeddings.py \
   --inference-model nomic-ai/nomic-embed-text-v1.5 --env EMBEDDING_DIMENSION=784
$  pytest -s -v -k together test_embeddings.py \
   --inference-model togethercomputer/m2-bert-80M-8k-retrieval --env EMBEDDING_DIMENSION=784
$ pytest -s -v -k ollama test_embeddings.py \
   --inference-model all-minilm:latest --env EMBEDDING_DIMENSION=784
```
This commit is contained in:
Ashwin Bharambe 2025-02-20 22:27:12 -08:00 • committed by GitHub
parent 6f9d622340
commit 81ce39a607
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19 changed files with 202 additions and 11 deletions
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7
llama_stack/providers/utils/inference/embedding_mixin.py
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@ -5,12 +5,14 @@
# the root directory of this source tree.
import logging
from typing import List
from typing import List, Optional
from llama_stack.apis.inference import (
EmbeddingsResponse,
EmbeddingTaskType,
InterleavedContentItem,
ModelStore,
TextTruncation,
)
EMBEDDING_MODELS = {}
@ -26,6 +28,9 @@ class SentenceTransformerEmbeddingMixin:
self,
model_id: str,
contents: List[str] | List[InterleavedContentItem],
text_truncation: Optional[TextTruncation] = TextTruncation.none,
output_dimension: Optional[int] = None,
task_type: Optional[EmbeddingTaskType] = None,
) -> EmbeddingsResponse:
model = await self.model_store.get_model(model_id)
embedding_model = self._load_sentence_transformer_model(model.provider_resource_id)