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chore(api): remove deprecated embeddings impls (#3301)
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# What does this PR do?

remove deprecated embeddings implementations
This commit is contained in:
Matthew Farrellee 2025-09-29 14:45:09 -04:00 • committed by GitHub
parent aab22dc759
commit 975ead1d6a
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19 changed files with 3 additions and 632 deletions
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31
llama_stack/providers/remote/inference/fireworks/fireworks.py
View file

@ -10,22 +10,18 @@ from fireworks.client import Fireworks
from llama_stack.apis.common.content_types import (
InterleavedContent,
InterleavedContentItem,
)
from llama_stack.apis.inference import (
ChatCompletionRequest,
ChatCompletionResponse,
CompletionRequest,
CompletionResponse,
EmbeddingsResponse,
EmbeddingTaskType,
Inference,
LogProbConfig,
Message,
ResponseFormat,
ResponseFormatType,
SamplingParams,
TextTruncation,
ToolChoice,
ToolConfig,
ToolDefinition,
@ -48,8 +44,6 @@ from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
from llama_stack.providers.utils.inference.prompt_adapter import (
chat_completion_request_to_prompt,
completion_request_to_prompt,
content_has_media,
interleaved_content_as_str,
request_has_media,
)
@ -259,28 +253,3 @@ class FireworksInferenceAdapter(OpenAIMixin, ModelRegistryHelper, Inference, Nee
logger.debug(f"params to fireworks: {params}")
return params
async def embeddings(
self,
model_id: str,
contents: list[str] | list[InterleavedContentItem],
text_truncation: TextTruncation | None = TextTruncation.none,
output_dimension: int | None = None,
task_type: EmbeddingTaskType | None = None,
) -> EmbeddingsResponse:
model = await self.model_store.get_model(model_id)
kwargs = {}
if model.metadata.get("embedding_dimension"):
kwargs["dimensions"] = model.metadata.get("embedding_dimension")
assert all(not content_has_media(content) for content in contents), (
"Fireworks does not support media for embeddings"
)
response = self._get_client().embeddings.create(
model=model.provider_resource_id,
input=[interleaved_content_as_str(content) for content in contents],
**kwargs,
)
embeddings = [data.embedding for data in response.data]
return EmbeddingsResponse(embeddings=embeddings)