File size: 2,084 Bytes
df455fc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | from __future__ import annotations
from typing import Any, Literal
from openenv.core.env_server.types import Action, Observation
from pydantic import Field
class PptAgentAction(Action):
"""Structured action for the prompt-to-PPT environment skeleton."""
action_type: Literal[
"create_slide",
"update_slide",
"delete_slide",
"save_presentation",
"set_theme",
] = Field(..., description="Macro action to execute")
slide_index: int | None = Field(
default=None,
ge=1,
description="Target slide index using 1-based indexing",
)
payload: dict[str, Any] = Field(
default_factory=dict,
description="Action-specific arguments for the macro action",
)
class PptAgentObservation(Observation):
"""Observation for the prompt-to-PPT environment skeleton."""
task_name: str = Field(default="", description="Current task identifier")
difficulty: str = Field(default="", description="Scenario difficulty label")
slide_count: int = Field(default=0, ge=0, description="Current number of slides")
task_prompt: str = Field(default="", description="Full task prompt from the env")
source_context: str = Field(
default="",
description="Flattened source-pack context available to the agent",
)
last_action_error: str | None = Field(
default=None,
description="Last action validation or execution error",
)
score: float = Field(default=0.0, ge=0.0, le=1.0, description="Normalized score")
prompt_summary: str = Field(default="", description="Current prompt summary")
last_action_result: dict[str, Any] | None = Field(
default=None,
description="Structured result from the last tool-backed action",
)
termination_reason: str | None = Field(
default=None,
description="Episode termination reason when done is true",
)
metadata: dict[str, Any] = Field(
default_factory=dict,
description="Additional debug and reward metadata for the last step",
)
|