Spaces:
Sleeping
Sleeping
File size: 1,720 Bytes
cacd58c | 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 | # models.py
from __future__ import annotations
from pydantic import BaseModel, Field
from typing import Optional
import uuid
class Action(BaseModel):
"""Agent's action: submit a code patch to fix the buggy function."""
patch: str = Field(
description="Full replacement of the function body (valid Python source code)."
)
task_id: str = Field(
description="Which task this patch targets. Must match a task from /tasks."
)
think: Optional[str] = Field(
default=None,
description="Optional chain-of-thought reasoning. Providing this earns r_cot bonus."
)
class TestResult(BaseModel):
name: str
passed: bool
error: Optional[str] = None
class Observation(BaseModel):
"""What the agent sees after reset() or step()."""
task_id: str
buggy_code: str = Field(description="Current version of the code (may be patched).")
task_description: str
test_results: list[TestResult] = Field(default_factory=list)
passed: int = 0
total: int = 0
score: float = 0.0
done: bool = False
reward: float = Field(default=0.0, exclude=True) # Required by openenv 0.2 serialization
error: Optional[str] = None
class State(BaseModel):
"""Episode metadata — returned by state() endpoint."""
episode_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
task_id: str = ""
step_count: int = 0
max_steps: int = 10
current_score: float = 0.0
best_score: float = 0.0
class TaskInfo(BaseModel):
"""Returned by /tasks endpoint."""
task_id: str
difficulty: str # "easy" | "medium" | "hard"
description: str
action_schema: dict # JSON schema of Action for this task
|