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80d58ab519
# What does this PR do? Converts openai(_chat)_completions params to pydantic BaseModel to reduce code duplication across all providers. ## Test Plan CI --- [//]: # (BEGIN SAPLING FOOTER) Stack created with [Sapling](https://sapling-scm.com). Best reviewed with [ReviewStack](https://reviewstack.dev/llamastack/llama-stack/pull/3761). * #3777 * __->__ #3761
44 lines
1.5 KiB
Python
44 lines
1.5 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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from collections.abc import Iterable
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from databricks.sdk import WorkspaceClient
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from llama_stack.apis.inference import OpenAICompletion, OpenAICompletionRequest
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from llama_stack.log import get_logger
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from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
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from .config import DatabricksImplConfig
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logger = get_logger(name=__name__, category="inference::databricks")
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class DatabricksInferenceAdapter(OpenAIMixin):
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config: DatabricksImplConfig
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# source: https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models
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embedding_model_metadata: dict[str, dict[str, int]] = {
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"databricks-gte-large-en": {"embedding_dimension": 1024, "context_length": 8192},
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"databricks-bge-large-en": {"embedding_dimension": 1024, "context_length": 512},
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}
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def get_base_url(self) -> str:
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return f"{self.config.url}/serving-endpoints"
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async def list_provider_model_ids(self) -> Iterable[str]:
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return [
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endpoint.name
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for endpoint in WorkspaceClient(
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host=self.config.url, token=self.get_api_key()
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).serving_endpoints.list() # TODO: this is not async
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]
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async def openai_completion(
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self,
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params: OpenAICompletionRequest,
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) -> OpenAICompletion:
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raise NotImplementedError()
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