eval api

llama_stack/apis/eval/eval.py

@@ -14,6 +14,8 @@ 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.scoring_functions import *  # noqa: F403
+from llama_stack.apis.eval_tasks import *  # noqa: F403
 
 
 @json_schema_type
@@ -34,11 +36,27 @@ EvalCandidate = Annotated[
     Union[ModelCandidate, AgentCandidate], Field(discriminator="type")
 ]
 
-# @json_schema_type
-# class EvalTaskDef(BaseModel):
-#     dataset_id: str
-#     candidate: EvalCandidate
-#     scoring_functions: List[str]
+
+@json_schema_type
+class BenchmarkEvalTaskConfig(BaseModel):
+    type: Literal["benchmark"] = "benchmark"
+    eval_candidate: EvalCandidate  # type: ignore
+
+
+@json_schema_type
+class AppEvalTaskConfig(BaseModel):
+    type: Literal["app"] = "app"
+    eval_candidate: EvalCandidate  # type: ignore
+    scoring_functions_config: Dict[str, ScoringFnConfig] = Field(
+        description="Map between scoring function id and parameters",
+        default_factory=dict,
+    )
+    # we could optinally add any GenEval specific dataset config here
+
+
+EvalTaskConfig = Annotated[
+    Union[BenchmarkEvalTaskConfig, AppEvalTaskConfig], Field(discriminator="type")
+]
 
 
 @json_schema_type
@@ -50,6 +68,13 @@ class EvaluateResponse(BaseModel):
 
 
 class Eval(Protocol):
+    @webmethod(route="/eval/evaluate_batch", method="POST")
+    async def evaluate_task(
+        self,
+        eval_task_def: Union[str, EvalTaskDef],  # type: ignore
+        eval_task_config: EvalTaskConfig,  # type: ignore
+    ) -> Job: ...
+
     @webmethod(route="/eval/evaluate_batch", method="POST")
     async def evaluate_batch(
         self,

llama_stack/apis/eval_tasks/eval_tasks.py

@@ -0,0 +1,55 @@
+# 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 enum import Enum
+from typing import (
+    Any,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Protocol,
+    runtime_checkable,
+    Union,
+)
+
+from llama_models.schema_utils import json_schema_type, webmethod
+
+from llama_stack.apis.common.type_system import ParamType
+from pydantic import BaseModel, Field
+from typing_extensions import Annotated
+
+
+@json_schema_type
+class EvalTaskDef(BaseModel):
+    identifier: str
+    dataset_id: str
+    scoring_functions: List[str]
+    metadata: Dict[str, Any] = Field(
+        default_factory=dict,
+        description="Metadata for this evaluation task (e.g. from GECO)",
+    )
+
+
+@json_schema_type
+class EvalTaskDefWithProvider(EvalTaskDef):
+    type: Literal["eval_task"] = "eval_task"
+    provider_id: str = Field(
+        description="ID of the provider which serves this dataset",
+    )
+
+
+@runtime_checkable
+class EvalTasks(Protocol):
+    @webmethod(route="/eval_tasks/list", method="GET")
+    async def list_eval_tasks(self) -> List[EvalTaskDefWithProvider]: ...
+
+    @webmethod(route="/eval_tasks/get", method="GET")
+    async def get_eval_tasks(self, name: str) -> Optional[EvalTaskDefWithProvider]: ...
+
+    @webmethod(route="/eval_tasks/register", method="POST")
+    async def register_eval_tasks(
+        self, function_def: EvalTaskDefWithProvider
+    ) -> None: ...