llama-stack-mirror/llama_stack/providers/impls/meta_reference/evals/evals.py
2024-10-15 10:14:35 -07:00

56 lines
1.8 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.
import json
from termcolor import cprint
from llama_stack.apis.inference import * # noqa: F403
from llama_stack.apis.evals import * # noqa: F403
from llama_stack.apis.datasets import * # noqa: F403
from .config import MetaReferenceEvalsImplConfig
from .tasks.run_eval_task import RunEvalTask
from .tasks.run_scoring_task import RunScoringTask
class MetaReferenceEvalsImpl(Evals):
def __init__(self, config: MetaReferenceEvalsImplConfig, inference_api: Inference):
self.inference_api = inference_api
async def initialize(self) -> None:
pass
async def shutdown(self) -> None:
pass
async def run_eval_task(
self,
eval_task_config: EvaluateTaskConfig,
) -> EvaluateResponse:
cprint(f"run_eval_task: on {eval_task_config}", "green")
run_task = RunEvalTask()
eval_result = await run_task.run(eval_task_config, self.inference_api)
return EvaluateResponse(
eval_result=eval_result,
formatted_report=json.dumps(eval_result.json(), indent=4),
)
async def run_scorer(
self,
dataset_config: EvaluateDatasetConfig,
eval_scoring_config: EvaluateScoringConfig,
) -> EvaluateResponse:
cprint(f"run_scorer: on {dataset_config} with {eval_scoring_config}", "green")
run_task = RunScoringTask()
eval_result = await run_task.run(dataset_config, eval_scoring_config)
return EvaluateResponse(
eval_result=eval_result,
formatted_report=json.dumps(eval_result.json(), indent=4),
)