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Xi Yan 2025-03-11 21:43:43 -07:00
parent 817331e76e
commit 70fdf6c04b
1 changed files with 44 additions and 10 deletions
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54
llama_stack/apis/scoring_functions/scoring_functions.py
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@ -28,11 +28,37 @@ from llama_stack.schema_utils import json_schema_type, register_schema, webmetho
# with standard metrics so they can be rolled up?
@json_schema_type
class ScoringFnParamsType(Enum):
"""
A type of scoring function parameters.
:cvar llm_as_judge: Provide judge model and prompt template.
:cvar regex_parser: Provide regexes to parse the answer from the generated response.
:cvar basic: Parameters for basic non-parameterized scoring function.
"""
llm_as_judge = "llm_as_judge"
regex_parser = "regex_parser"
basic = "basic"
@json_schema_type
class ScoringFunctionType(Enum):
"""
A type of scoring function. Each type is a criteria for evaluating answers.
:cvar llm_as_judge: Scoring function that uses a judge model to score the answer.
:cvar regex_parser: Scoring function that parses the answer from the generated response using regexes, and checks against the expected answer.
"""
llm_as_judge = "llm_as_judge"
regex_parser = "regex_parser"
# NOTE: add additional scoring function types that can be registered
# equality = "equality"
# subset_of = "subset_of"
# valid_json = "valid_json"
# text_quality = "text_quality"
@json_schema_type
class AggregationFunctionType(Enum):
average = "average"
@ -43,7 +69,7 @@ class AggregationFunctionType(Enum):
@json_schema_type
class LLMAsJudgeScoringFnParams(BaseModel):
type: Literal[ScoringFnParamsType.llm_as_judge.value] = ScoringFnParamsType.llm_as_judge.value
type: Literal["llm_as_judge"] = "llm_as_judge"
judge_model: str
prompt_template: Optional[str] = None
judge_score_regexes: Optional[List[str]] = Field(
@ -58,9 +84,9 @@ class LLMAsJudgeScoringFnParams(BaseModel):
@json_schema_type
class RegexParserScoringFnParams(BaseModel):
type: Literal[ScoringFnParamsType.regex_parser.value] = ScoringFnParamsType.regex_parser.value
type: Literal["regex_parser"] = "regex_parser"
parsing_regexes: Optional[List[str]] = Field(
description="Regex to extract the answer from generated response",
description="Regexes to extract the answer from generated response",
default_factory=list,
)
aggregation_functions: Optional[List[AggregationFunctionType]] = Field(
@ -71,7 +97,7 @@ class RegexParserScoringFnParams(BaseModel):
@json_schema_type
class BasicScoringFnParams(BaseModel):
type: Literal[ScoringFnParamsType.basic.value] = ScoringFnParamsType.basic.value
type: Literal["basic"] = "basic"
aggregation_functions: Optional[List[AggregationFunctionType]] = Field(
description="Aggregation functions to apply to the scores of each row",
default_factory=list,
@ -140,10 +166,18 @@ class ScoringFunctions(Protocol):
@webmethod(route="/scoring-functions", method="POST")
async def register_scoring_function(
self,
scoring_fn_id: str,
description: str,
return_type: ParamType,
provider_scoring_fn_id: Optional[str] = None,
provider_id: Optional[str] = None,
scoring_fn_type: ScoringFunctionType,
params: Optional[ScoringFnParams] = None,
) -> None: ...
scoring_fn_id: Optional[str] = None,
description: Optional[str] = None,
):
"""
Register a new scoring function with given parameters.
Only valid scoring function type that can be parameterized can be registered.
:param scoring_fn_type: The type of scoring function to register. A function type can only be registered if it is a valid type.
:param params: The parameters for the scoring function.
:param scoring_fn_id: (Optional) The ID of the scoring function to register. If not provided, a random ID will be generated.
:param description: (Optional) The description of the scoring function.
"""
...