app/schemas/answer_evaluation.py

"""Pydantic schemas for the answer evaluation endpoint."""

from pydantic import BaseModel, ConfigDict, Field


class AnswerEvaluationRequest(BaseModel):
    """Request model for POST /ai/v2/evaluate-answer."""

    model_config = ConfigDict(extra="forbid")

    question_id: str = Field(..., min_length=1, max_length=50)
    question_text: str = Field(..., min_length=5, max_length=2000)
    student_answer: str = Field(..., min_length=1, max_length=5000)
    model_answer: str = Field(..., min_length=1, max_length=5000)
    rubric: str = Field(..., min_length=1, max_length=2000)
    max_marks: int = Field(..., ge=1, le=100)
    grade: int = Field(..., ge=6, le=8)
    subject: str
    lo_id: str = Field(..., min_length=1, max_length=50)
    bloom_level: str


class AnswerEvaluationResponse(BaseModel):
    """Response model for POST /ai/v2/evaluate-answer."""

    prediction_id: str
    model_version: str
    source: str
    confidence: float = Field(..., ge=0.0, le=1.0)
    timestamp: str
    predicted_marks: float = Field(..., ge=0.0)
    max_marks: int
    concepts_covered: list[str]
    missing_points: list[str]
    feedback: str
    teacher_review_required: bool  # always True in V2