llama-stack/llama_stack/apis/scoring/scoring.py
Dinesh Yeduguru 7fb2c1c48d
More idiomatic REST API (#765)
# What does this PR do?

This PR changes our API to follow more idiomatic REST API approaches of
having paths being resources and methods indicating the action being
performed.

Changes made to generator:
1) removed the prefix check of "get" as its not required and is actually
needed for other method types too
2) removed _ check on path since variables can have "_"



## Test Plan

LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v
tests/client-sdk/agents/test_agents.py
2025-01-15 13:20:09 -08:00

58 lines
1.6 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
from llama_models.schema_utils import json_schema_type, webmethod
from pydantic import BaseModel
from llama_stack.apis.scoring_functions import ScoringFn, ScoringFnParams
# mapping of metric to value
ScoringResultRow = Dict[str, Any]
@json_schema_type
class ScoringResult(BaseModel):
score_rows: List[ScoringResultRow]
# aggregated metrics to value
aggregated_results: Dict[str, Any]
@json_schema_type
class ScoreBatchResponse(BaseModel):
dataset_id: Optional[str] = None
results: Dict[str, ScoringResult]
@json_schema_type
class ScoreResponse(BaseModel):
# each key in the dict is a scoring function name
results: Dict[str, ScoringResult]
class ScoringFunctionStore(Protocol):
def get_scoring_function(self, scoring_fn_id: str) -> ScoringFn: ...
@runtime_checkable
class Scoring(Protocol):
scoring_function_store: ScoringFunctionStore
@webmethod(route="/scoring/score-batch", method="POST")
async def score_batch(
self,
dataset_id: str,
scoring_functions: Dict[str, Optional[ScoringFnParams]],
save_results_dataset: bool = False,
) -> ScoreBatchResponse: ...
@webmethod(route="/scoring/score", method="POST")
async def score(
self,
input_rows: List[Dict[str, Any]],
scoring_functions: Dict[str, Optional[ScoringFnParams]],
) -> ScoreResponse: ...