Spaces:
Sleeping
Sleeping
File size: 3,480 Bytes
ced8fd0 | 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 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | """
OpenEnv-compliant Pydantic models for the Code Review Environment.
"""
from __future__ import annotations
from typing import Any, Dict, List, Literal, Optional
from pydantic import BaseModel, Field
# ─── Action Space ────────────────────────────────────────────────────────────
class ReviewAction(BaseModel):
"""Agent action: review and optionally patch code."""
action_type: Literal["review", "patch", "comment", "submit"] = Field(
description="Type of action the agent takes."
)
# For 'review': provide a structured analysis
severity: Optional[Literal["critical", "major", "minor", "info"]] = None
issue_type: Optional[str] = Field(
default=None,
description="Category: bug, security, performance, style, logic"
)
line_number: Optional[int] = Field(default=None, ge=1)
description: Optional[str] = Field(default=None, max_length=500)
# For 'patch': provide fixed code
patched_code: Optional[str] = Field(
default=None,
description="Full corrected code (for patch actions)."
)
# For 'comment': free-form annotation
comment: Optional[str] = Field(default=None, max_length=1000)
# For 'submit': final verdict
verdict: Optional[Literal["approve", "request_changes", "reject"]] = None
confidence: Optional[float] = Field(default=None, ge=0.0, le=1.0)
# ─── Observation Space ───────────────────────────────────────────────────────
class CodeFile(BaseModel):
filename: str
language: str
content: str
line_count: int
class ReviewContext(BaseModel):
pull_request_title: str
author: str
description: str
files_changed: List[CodeFile]
test_results: Optional[str] = None
linter_output: Optional[str] = None
class Observation(BaseModel):
"""What the agent sees at each step."""
task_id: str
step: int
max_steps: int
review_context: ReviewContext
previous_actions: List[ReviewAction] = Field(default_factory=list)
feedback: Optional[str] = None
issues_found_so_far: List[Dict[str, Any]] = Field(default_factory=list)
score_so_far: float = 0.0
done: bool = False
# ─── Reward Model ────────────────────────────────────────────────────────────
class StepReward(BaseModel):
"""Reward signal returned at each step."""
value: float = Field(ge=-1.0, le=1.0)
breakdown: Dict[str, float] = Field(default_factory=dict)
explanation: str = ""
# ─── State ───────────────────────────────────────────────────────────────────
class EnvironmentState(BaseModel):
task_id: str
step: int
max_steps: int
review_context: ReviewContext
actions_taken: List[ReviewAction] = Field(default_factory=list)
issues_identified: List[Dict[str, Any]] = Field(default_factory=list)
patch_submitted: Optional[str] = None
verdict_submitted: Optional[str] = None
total_reward: float = 0.0
done: bool = False
terminated_reason: Optional[str] = None
|