forked from phoenix-oss/llama-stack-mirror
4253cfcd7f
# What does this PR do? - local persistence for HF dataset provider - follow https://github.com/meta-llama/llama-stack/pull/375 ## Test Plan **e2e** 1. fresh llama stack run w/ yaml 2. kill server 3. restart llama stack run w/ yaml ```yaml datasets: - dataset_id: mmlu provider_id: huggingface-0 url: uri: https://huggingface.co/datasets/llamastack/evals metadata: path: llamastack/evals name: evals__mmlu__details split: train dataset_schema: input_query: type: string expected_answer: type: string ``` <img width="686" alt="image" src="https://github.com/user-attachments/assets/d7737931-6a7d-400a-a17d-fef6cbd97eea"> ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests.
17 lines
629 B
Python
17 lines
629 B
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 llama_stack.distribution.utils.config_dirs import RUNTIME_BASE_DIR
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from llama_stack.providers.utils.kvstore.config import (
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KVStoreConfig,
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SqliteKVStoreConfig,
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)
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from pydantic import BaseModel
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class HuggingfaceDatasetIOConfig(BaseModel):
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kvstore: KVStoreConfig = SqliteKVStoreConfig(
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db_path=(RUNTIME_BASE_DIR / "huggingface_datasetio.db").as_posix()
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) # Uses SQLite config specific to HF storage
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