mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-15 14:43:48 +00:00
96 lines
2.9 KiB
Python
96 lines
2.9 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 Literal, Optional, Protocol, Union
|
|
|
|
from typing_extensions import Annotated
|
|
|
|
from llama_models.llama3.api.datatypes import * # noqa: F403
|
|
from llama_models.schema_utils import json_schema_type, webmethod
|
|
from llama_stack.apis.scoring_functions import * # noqa: F403
|
|
from llama_stack.apis.agents import AgentConfig
|
|
from llama_stack.apis.common.job_types import Job, JobStatus
|
|
from llama_stack.apis.scoring import * # noqa: F403
|
|
from llama_stack.apis.eval_tasks import * # noqa: F403
|
|
|
|
|
|
@json_schema_type
|
|
class ModelCandidate(BaseModel):
|
|
type: Literal["model"] = "model"
|
|
model: str
|
|
sampling_params: SamplingParams
|
|
system_message: Optional[SystemMessage] = None
|
|
|
|
|
|
@json_schema_type
|
|
class AgentCandidate(BaseModel):
|
|
type: Literal["agent"] = "agent"
|
|
config: AgentConfig
|
|
|
|
|
|
EvalCandidate = Annotated[
|
|
Union[ModelCandidate, AgentCandidate], Field(discriminator="type")
|
|
]
|
|
|
|
|
|
@json_schema_type
|
|
class BenchmarkEvalTaskConfig(BaseModel):
|
|
eval_candidate: EvalCandidate # type: ignore
|
|
|
|
|
|
@json_schema_type
|
|
class AppEvalTaskConfig(BaseModel):
|
|
eval_candidate: EvalCandidate # type: ignore
|
|
scoring_functions_params: Dict[str, ScoringFnParams] = Field( # type: ignore
|
|
description="Map between scoring function id and parameters",
|
|
default_factory=dict,
|
|
)
|
|
# we could optinally add any specific dataset config here
|
|
|
|
|
|
EvalTaskConfig = Annotated[
|
|
Union[BenchmarkEvalTaskConfig, AppEvalTaskConfig], Field(discriminator="type")
|
|
]
|
|
|
|
|
|
@json_schema_type
|
|
class EvaluateResponse(BaseModel):
|
|
generations: List[Dict[str, Any]]
|
|
# each key in the dict is a scoring function name
|
|
scores: Dict[str, ScoringResult]
|
|
|
|
|
|
class Eval(Protocol):
|
|
@webmethod(route="/eval/run_benchmark_eval", method="POST")
|
|
async def run_benchmark_eval(
|
|
self,
|
|
benchmark_id: str,
|
|
eval_task_config: BenchmarkEvalTaskConfig, # type: ignore
|
|
) -> Job: ...
|
|
|
|
@webmethod(route="/eval/run_eval", method="POST")
|
|
async def run_eval(
|
|
self,
|
|
eval_task_def: EvalTaskDef, # type: ignore
|
|
eval_task_config: EvalTaskConfig, # type: ignore
|
|
) -> Job: ...
|
|
|
|
@webmethod(route="/eval/evaluate_rows", method="POST")
|
|
async def evaluate_rows(
|
|
self,
|
|
input_rows: List[Dict[str, Any]],
|
|
scoring_functions: List[str],
|
|
eval_task_config: EvalTaskConfig, # type: ignore
|
|
) -> EvaluateResponse: ...
|
|
|
|
@webmethod(route="/eval/job/status", method="GET")
|
|
async def job_status(self, job_id: str) -> Optional[JobStatus]: ...
|
|
|
|
@webmethod(route="/eval/job/cancel", method="POST")
|
|
async def job_cancel(self, job_id: str) -> None: ...
|
|
|
|
@webmethod(route="/eval/job/result", method="GET")
|
|
async def job_result(self, job_id: str) -> EvaluateResponse: ...
|