forked from phoenix-oss/llama-stack-mirror
e45f121c77
* type system api * datasets api * fix * datasetio api * kill reward scoring * scoring functions + evals * move jobs, fix errors
46 lines
1.3 KiB
Python
46 lines
1.3 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 typing import Any, Dict, List, Protocol, runtime_checkable
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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_models.llama3.api.datatypes import * # noqa: F403
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from llama_stack.apis.scoring_functions import * # noqa: F403
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ScoringResult = Dict[str, Any]
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@json_schema_type
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class ScoreBatchResponse(BaseModel):
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dataset_id: str
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@json_schema_type
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class ScoreResponse(BaseModel):
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# each key in the dict is a scoring function name
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results: List[Dict[str, ScoringResult]]
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class ScoringFunctionStore(Protocol):
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def get_scoring_function(self, name: str) -> ScoringFunctionDefWithProvider: ...
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@runtime_checkable
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class Scoring(Protocol):
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scoring_function_store: ScoringFunctionStore
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@webmethod(route="/scoring/score_batch")
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async def score_batch(
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self, dataset_id: str, scoring_functions: List[str]
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) -> ScoreBatchResponse: ...
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@webmethod(route="/scoring/score")
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async def score(
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self, input_rows: List[Dict[str, Any]], scoring_functions: List[str]
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) -> ScoreResponse: ...
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