phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-08-12 13:00:39 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

benchmark config

Browse source
This commit is contained in:
Xi Yan 2025-02-12 20:38:21 -08:00
parent 017d24fe65
commit 8759196e29
1 changed files with 7 additions and 24 deletions
Download patch file Download diff file Expand all files Collapse all files

31
llama_stack/apis/eval/eval.py
View file

@ -38,18 +38,7 @@ EvalCandidate = register_schema(
@json_schema_type @json_schema_type
class BenchmarkBenchmarkConfig(BaseModel): class BenchmarkConfig(BaseModel):
type: Literal["benchmark"] = "benchmark"
eval_candidate: EvalCandidate
num_examples: Optional[int] = Field(
description="Number of examples to evaluate (useful for testing), if not provided, all examples in the dataset will be evaluated",
default=None,
)
@json_schema_type
class AppBenchmarkConfig(BaseModel):
type: Literal["app"] = "app"
eval_candidate: EvalCandidate eval_candidate: EvalCandidate
scoring_params: Dict[str, ScoringFnParams] = Field( scoring_params: Dict[str, ScoringFnParams] = Field(
description="Map between scoring function id and parameters for each scoring function you want to run", description="Map between scoring function id and parameters for each scoring function you want to run",
@ -62,12 +51,6 @@ class AppBenchmarkConfig(BaseModel):
# we could optinally add any specific dataset config here # we could optinally add any specific dataset config here
BenchmarkConfig = register_schema(
Annotated[Union[BenchmarkBenchmarkConfig, AppBenchmarkConfig], Field(discriminator="type")],
name="BenchmarkConfig",
)
@json_schema_type @json_schema_type
class EvaluateResponse(BaseModel): class EvaluateResponse(BaseModel):
generations: List[Dict[str, Any]] generations: List[Dict[str, Any]]
@ -76,14 +59,14 @@ class EvaluateResponse(BaseModel):
class Eval(Protocol): class Eval(Protocol):
@webmethod(route="/eval/tasks/{benchmark_id}/jobs", method="POST") @webmethod(route="/eval/benchmarks/{benchmark_id}/jobs", method="POST")
async def run_eval( async def run_eval(
self, self,
benchmark_id: str, benchmark_id: str,
task_config: BenchmarkConfig, task_config: BenchmarkConfig,
) -> Job: ... ) -> Job: ...
@webmethod(route="/eval/tasks/{benchmark_id}/evaluations", method="POST") @webmethod(route="/eval/benchmarks/{benchmark_id}/evaluations", method="POST")
async def evaluate_rows( async def evaluate_rows(
self, self,
benchmark_id: str, benchmark_id: str,
@ -92,11 +75,11 @@ class Eval(Protocol):
task_config: BenchmarkConfig, task_config: BenchmarkConfig,
) -> EvaluateResponse: ... ) -> EvaluateResponse: ...
@webmethod(route="/eval/tasks/{benchmark_id}/jobs/{job_id}", method="GET") @webmethod(route="/eval/benchmarks/{benchmark_id}/jobs/{job_id}", method="GET")
async def job_status(self, benchmark_id: str, job_id: str) -> Optional[JobStatus]: ... async def job_status(self, benchmark_id: str, job_id: str) -> Optional[JobStatus]: ...
@webmethod(route="/eval/tasks/{benchmark_id}/jobs/{job_id}", method="DELETE") @webmethod(route="/eval/benchmarks/{benchmark_id}/jobs/{job_id}", method="DELETE")
async def job_cancel(self, benchmark_id: str, job_id: str) -> None: ... async def job_cancel(self, benchmark_id: str, job_id: str) -> None: ...
@webmethod(route="/eval/tasks/{benchmark_id}/jobs/{job_id}/result", method="GET") @webmethod(route="/eval/benchmarks/{benchmark_id}/jobs/{job_id}/result", method="GET")
async def job_result(self, job_id: str, benchmark_id: str) -> EvaluateResponse: ... async def job_result(self, benchmark_id: str, job_id: str) -> EvaluateResponse: ...