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cf05092 899a7c7 cf05092 babc153 cf05092 899a7c7 cf05092 899a7c7 cf05092 86c3e08 cf05092 b196357 cf05092 b196357 cf05092 899a7c7 babc153 902cd29 | 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 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 | from __future__ import annotations
from datetime import UTC, datetime
from enum import StrEnum
from typing import Optional
from sqlmodel import Field, SQLModel
class EdgeType(StrEnum):
EXPLICIT_IMPORT = "explicit_import"
IMPLICIT_DEPENDENCY = "implicit_dependency"
INTRA_FILE = "intra_file"
CIRCULAR = "circular"
class ReviewStatus(StrEnum):
PENDING = "pending"
IN_PROGRESS = "in_progress"
REVIEWED = "reviewed"
class Severity(StrEnum):
LOW = "low"
MEDIUM = "medium"
HIGH = "high"
class AnalyzerStatus(StrEnum):
OK = "ok"
TIMEOUT = "timeout"
MISSING = "missing"
PARSE_ERROR = "parse-error"
NO_OUTPUT = "no-output"
class ModuleNode(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
module_id: str = Field(index=True)
name: Optional[str] = None
raw_code: str
ast_summary: str
summary: Optional[str] = None
linter_flags: str = "[]"
parent_module_id: Optional[str] = Field(default=None, index=True)
is_chunk: bool = False
dependency_reason: str = ""
review_annotation: Optional[str] = None
review_status: ReviewStatus = Field(default=ReviewStatus.PENDING)
review_summary: Optional[str] = None
created_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
updated_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
class ModuleEdge(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
source_module_id: str = Field(index=True)
target_module_id: str = Field(index=True)
edge_type: EdgeType = Field(default=EdgeType.EXPLICIT_IMPORT)
import_line: str
weight: float = 1.0
connection_summary: str = ""
class LinterFinding(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
module_id: str = Field(index=True)
tool: str = Field(index=True)
line: int
severity: Severity
code: str
message: str
class ReviewAnnotation(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
module_id: str = Field(index=True)
episode_id: str = Field(index=True)
task_id: Optional[str] = Field(default=None, index=True)
step_number: int
action_type: str
note: str
reward_given: float = 0.0
attributed_to: Optional[str] = Field(default=None, index=True)
is_amendment: bool = False
created_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
class EpisodeRecord(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
episode_id: str = Field(index=True)
task_id: str = Field(index=True)
module_id: str = Field(index=True)
total_steps: int
cumulative_reward: float = 0.0
created_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
class TaskDefinition(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
task_id: str = Field(index=True)
task_level: str = Field(index=True)
target_module_id: str = Field(index=True)
description: str
ground_truth_ref: str
class SeedMeta(SQLModel, table=True):
key: str = Field(primary_key=True)
value: str
class AnalyzerRun(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
analyzer: str = Field(index=True)
analyzer_version: str = ""
status: AnalyzerStatus = Field(default=AnalyzerStatus.OK)
findings_count: int = 0
command: str = ""
command_hash: str = ""
error_message: Optional[str] = None
started_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
finished_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
class AnalyzerFinding(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
analyzer_run_id: int = Field(index=True)
analyzer: str = Field(index=True)
module_id: str = Field(index=True)
line: int
severity: Severity = Field(default=Severity.MEDIUM)
rule_id: str = Field(index=True)
message: str
evidence: str = ""
created_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
class TrainingRun(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
run_id: str = Field(index=True)
model_name: str = Field(index=True)
model_sha256: str = ""
deterministic_findings: int = 0
agent_findings: int = 0
true_positives: int = 0
false_positives: int = 0
false_negatives: int = 0
precision: float = 0.0
recall: float = 0.0
passed_non_regression: bool = True
output_path: str = ""
run_config_json: str = "{}"
created_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
class TrainingAnnotation(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
source_root: str = Field(index=True)
run_id: str = Field(index=True)
module_id: str = Field(index=True)
task_id: str = Field(index=True)
judge_verdict: str = ""
avg_reward: float = 0.0
correct_attributions_json: str = "[]"
wrong_attributions_json: str = "[]"
action_counts_json: str = "{}"
action_type: str = ""
action_payload: str = "{}"
thinking_quality: float = 0.0
created_at: datetime = Field(default_factory=lambda: datetime.now(UTC))
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