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implement embedding generation in supported inference providers (#589)

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This PR adds the ability to generate embeddings in all supported
inference providers.

```
pytest -v -s llama_stack/providers/tests/inference/test_embeddings.py -k "bedrock" --inference-model="amazon.titan-embed-text-v2:0"  --env EMBEDDING_DIMENSION=1024

 pytest -v -s -k "vllm"  --inferrence-model="intfloat/e5-mistral-7b-instruct"  llama_stack/providers/tests/inference/test_embeddings.py --env EMBEDDING_DIMENSION=4096  --env VLLM_URL="http://localhost:9798/v1"

pytest -v -s --inference-model="nomic-ai/nomic-embed-text-v1.5"  llama_stack/providers/tests/inference/test_embeddings.py  -k "fireworks"  --env FIREWORKS_API_KEY=<API_KEY>--env EMBEDDING_DIMENSION=128

pytest -v -s --inference-model="togethercomputer/m2-bert-80M-2k-retrieval"  llama_stack/providers/tests/inference/test_embeddings.py  -k "together"  --env TOGETHER_API_KEY=<API_KEY>--env EMBEDDING_DIMENSION=768

pytest -v -s -k "ollama"  --inference-model="all-minilm:v8"  llama_stack/providers/tests/inference/test_embeddings.py --env EMBEDDING_DIMENSION=384

 torchrun $CONDA_PREFIX/bin/pytest -v -s -k "meta_reference" --inference-model="sentence-transformers/all-MiniLM-L6-v2"  llama_stack/providers/tests/inference/test_embeddings.py --env EMBEDDING_DIMENSION=384

```
This commit is contained in:
Dinesh Yeduguru 2024-12-12 11:17:39 -08:00
parent 6a23f24ee0
commit d362d2d740
32 changed files with 597 additions and 143 deletions
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22
llama_stack/providers/remote/inference/bedrock/bedrock.py
View file

@ -5,6 +5,7 @@
# the root directory of this source tree.
from typing import * # noqa: F403
import json
from botocore.client import BaseClient
from llama_models.datatypes import CoreModelId
@ -19,8 +20,10 @@ from llama_stack.providers.utils.inference.model_registry import (
from llama_stack.apis.inference import * # noqa: F403
from llama_stack.providers.remote.inference.bedrock.config import BedrockConfig
from llama_stack.providers.utils.bedrock.client import create_bedrock_client
from llama_stack.providers.utils.inference.prompt_adapter import content_has_media
model_aliases = [
@ -448,4 +451,21 @@ class BedrockInferenceAdapter(ModelRegistryHelper, Inference):
model_id: str,
contents: List[InterleavedTextMedia],
) -> EmbeddingsResponse:
raise NotImplementedError()
model = await self.model_store.get_model(model_id)
embeddings = []
for content in contents:
assert not content_has_media(
content
), "Bedrock does not support media for embeddings"
input_text = interleaved_text_media_as_str(content)
input_body = {"inputText": input_text}
body = json.dumps(input_body)
response = self.client.invoke_model(
body=body,
modelId=model.provider_resource_id,
accept="application/json",
contentType="application/json",
)
response_body = json.loads(response.get("body").read())
embeddings.append(response_body.get("embedding"))
return EmbeddingsResponse(embeddings=embeddings)