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CodeSensei — Typed Models for the CodeDebug OpenEnv Environment.
Defines the Action, Observation, and State Pydantic models that form the
typed contract between the training client and the environment server.
"""
from __future__ import annotations
from typing import List, Optional, Any
from pydantic import BaseModel, Field
class CodeDebugAction(BaseModel):
"""Action sent by the LLM agent to the environment.
Attributes:
proposed_fix: The corrected Python function body proposed by the LLM.
session_id: Unique session identifier for this training episode.
"""
proposed_fix: str
session_id: str = ""
class TestResult(BaseModel):
"""Result of a single test case execution.
Attributes:
test_name: Human-readable name / description of the test.
passed: Whether the test passed.
error_message: Error message if the test failed, empty string otherwise.
"""
test_name: str
passed: bool
error_message: str = ""
class CodeDebugObservation(BaseModel):
"""Observation returned by the environment after each step.
Attributes:
buggy_code: The original buggy Python function source.
current_code: The current version of the code (after applying fix).
error_output: Stderr/exception output from the most recent execution.
test_results: Detailed per-test results.
tests_passed: Number of tests that passed.
tests_total: Total number of tests.
reward: Aggregated reward signal for this step.
done: Whether the episode is complete (all tests pass or max attempts).
attempt: Current attempt number (1-indexed).
max_attempts: Maximum allowed attempts per episode.
feedback: Human-readable feedback string for the LLM's context window.
"""
buggy_code: str
current_code: str
error_output: str
test_results: List[TestResult] = Field(default_factory=list)
tests_passed: int = 0
tests_total: int = 0
reward: float = 0.0
done: bool = False
attempt: int = 0
max_attempts: int = 6
feedback: str = ""
class CodeDebugState(BaseModel):
"""Internal state of the environment for a single episode.
Attributes:
episode_id: Unique identifier for this episode.
session_id: WebSocket session identifier.
attempt: Current attempt number (1-indexed).
max_attempts: Maximum allowed attempts.
original_bug: The original buggy code string.
current_code: The latest version of the code.
bug_description: Short description of the intentional bug.
function_name: Name of the function being debugged.
tests_passed_history: List of tests_passed counts per attempt.
fix_hashes: Set of SHA-256 hashes of previously proposed fixes.
solved: Whether the bug has been successfully fixed.
"""
class Config:
arbitrary_types_allowed = True
episode_id: str = ""
session_id: str = ""
attempt: int = 0
max_attempts: int = 6
original_bug: str = ""
current_code: str = ""
bug_description: str = ""
function_name: str = ""
tests_passed_history: List[int] = Field(default_factory=list)
fix_hashes: List[str] = Field(default_factory=list)
solved: bool = False
# Not using Field for internal _bug_data to avoid pydantic issues with raw dicts
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