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60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any, Dict, List, Literal, Optional, Protocol, runtime_checkable
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel, Field
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from llama_stack.apis.resource import Resource, ResourceType
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class CommonEvalTaskFields(BaseModel):
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dataset_id: str
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scoring_functions: List[str]
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metadata: Dict[str, Any] = Field(
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default_factory=dict,
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description="Metadata for this evaluation task",
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)
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@json_schema_type
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class EvalTask(CommonEvalTaskFields, Resource):
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type: Literal[ResourceType.eval_task.value] = ResourceType.eval_task.value
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@property
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def eval_task_id(self) -> str:
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return self.identifier
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@property
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def provider_eval_task_id(self) -> str:
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return self.provider_resource_id
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class EvalTaskInput(CommonEvalTaskFields, BaseModel):
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eval_task_id: str
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provider_id: Optional[str] = None
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provider_eval_task_id: Optional[str] = None
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@runtime_checkable
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class EvalTasks(Protocol):
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@webmethod(route="/eval_tasks/list", method="GET")
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async def list_eval_tasks(self) -> List[EvalTask]: ...
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@webmethod(route="/eval_tasks/get", method="GET")
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async def get_eval_task(self, name: str) -> Optional[EvalTask]: ...
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@webmethod(route="/eval_tasks/register", method="POST")
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async def register_eval_task(
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self,
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eval_task_id: str,
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dataset_id: str,
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scoring_functions: List[str],
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provider_eval_task_id: Optional[str] = None,
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provider_id: Optional[str] = None,
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metadata: Optional[Dict[str, Any]] = None,
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) -> None: ...
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