forked from phoenix-oss/llama-stack-mirror
e4a1579e63
# What does this PR do? - Configured ruff linter to automatically fix import sorting issues. - Set --exit-non-zero-on-fix to ensure non-zero exit code when fixes are applied. - Enabled the 'I' selection to focus on import-related linting rules. - Ran the linter, and formatted all codebase imports accordingly. - Removed the black dep from the "dev" group since we use ruff Signed-off-by: Sébastien Han <seb@redhat.com> [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan [Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*] [//]: # (## Documentation) [//]: # (- [ ] Added a Changelog entry if the change is significant) Signed-off-by: Sébastien Han <seb@redhat.com>
51 lines
1.5 KiB
Python
51 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 enum import Enum
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from typing import Any, Dict, List, Optional, Protocol, Union
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel
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from llama_stack.apis.inference import Message
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class FilteringFunction(Enum):
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"""The type of filtering function."""
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none = "none"
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random = "random"
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top_k = "top_k"
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top_p = "top_p"
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top_k_top_p = "top_k_top_p"
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sigmoid = "sigmoid"
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@json_schema_type
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class SyntheticDataGenerationRequest(BaseModel):
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"""Request to generate synthetic data. A small batch of prompts and a filtering function"""
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dialogs: List[Message]
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filtering_function: FilteringFunction = FilteringFunction.none
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model: Optional[str] = None
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@json_schema_type
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class SyntheticDataGenerationResponse(BaseModel):
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"""Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold."""
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synthetic_data: List[Dict[str, Any]]
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statistics: Optional[Dict[str, Any]] = None
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class SyntheticDataGeneration(Protocol):
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@webmethod(route="/synthetic-data-generation/generate")
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def synthetic_data_generate(
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self,
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dialogs: List[Message],
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filtering_function: FilteringFunction = FilteringFunction.none,
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model: Optional[str] = None,
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) -> Union[SyntheticDataGenerationResponse]: ...
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