codetf.py

from __future__ import annotations

from enum import Enum
from typing import Optional

from pydantic import BaseModel, model_validator

from ..common import Change, CodeTFWriter, Finding, FixQuality
from ..v2.codetf import Finding as V2Finding


class Run(BaseModel):
    """Metadata about the analysis run that produced the results"""

    vendor: str
    tool: str
    version: str
    # Optional free-form metadata about the project being analyzed
    # e.g. project name, directory, commit SHA, etc.
    projectMetadata: Optional[str] = None
    # Analysis duration in milliseconds
    elapsed: Optional[int] = None
    # Optional free-form metadata about the inputs used for the analysis
    # e.g. command line, environment variables, etc.
    inputMetadata: Optional[dict] = None
    # Optional free-form metadata about the analysis itself
    # e.g. timeouts, memory usage, etc.
    analysisMetadata: Optional[dict] = None


class FixStatusType(str, Enum):
    """Status of a fix"""

    fixed = "fixed"
    skipped = "skipped"
    failed = "failed"
    wontfix = "wontfix"


class FixStatus(BaseModel):
    """Metadata describing fix outcome"""

    status: FixStatusType
    reason: Optional[str] = None
    details: Optional[str] = None


class ChangeSet(BaseModel):
    path: str
    diff: str
    changes: list[Change] = []


class Reference(BaseModel):
    url: str
    description: Optional[str] = None

    @model_validator(mode="after")
    def validate_description(self):
        self.description = self.description or self.url
        return self


class Strategy(Enum):
    ai = "ai"
    hybrid = "hybrid"
    deterministic = "deterministic"


class AIMetadata(BaseModel):
    provider: Optional[str] = None
    models: Optional[list[str]] = None
    total_tokens: Optional[int] = None
    completion_tokens: Optional[int] = None
    prompt_tokens: Optional[int] = None


class GenerationMetadata(BaseModel):
    strategy: Strategy
    ai: Optional[AIMetadata] = None
    provisional: bool


class FixMetadata(BaseModel):
    # Fix provider ID, corresponds to legacy codemod ID
    id: str
    # A brief summary of the fix
    summary: str
    # A detailed description of the fix
    description: str
    references: list[Reference] = []
    generation: GenerationMetadata


class FixResult(BaseModel):
    """Result corresponding to a single finding"""

    finding: Finding | V2Finding
    fixStatus: FixStatus
    changeSets: list[ChangeSet] = []
    fixMetadata: Optional[FixMetadata] = None
    fixQuality: Optional[FixQuality] = None
    # A description of the reasoning process that led to the fix
    reasoningSteps: Optional[list[str]] = None

    @model_validator(mode="after")
    def validate_fixMetadata(self):
        if self.fixStatus.status == FixStatusType.fixed:
            if not self.changeSets:
                raise ValueError("changeSets must be provided for fixed results")
            if not self.fixMetadata:
                raise ValueError("fixMetadata must be provided for fixed results")
        return self


class CodeTF(CodeTFWriter, BaseModel):
    run: Run
    results: list[FixResult]