110 lines
3.5 KiB
Python
110 lines
3.5 KiB
Python
"""Request/result models.
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``extra="forbid"`` is load-bearing: it emits ``additionalProperties: false`` in the
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generated JSON Schema, which structured outputs requires.
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The remaining constraints (``ge``/``le``, string lengths, list lengths) are *not*
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expressible in structured outputs -- the SDK strips them from the schema it sends and
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re-applies them client-side during validation. They therefore act as a post-hoc
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validation gate, not as a generation constraint. Normalization runs in ``mode="before"``
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validators so that de-duplication happens *before* the length ceiling is enforced; a
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model that returns 31 near-duplicate keywords collapses under the limit instead of
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failing the candidate.
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"""
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from __future__ import annotations
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from typing import Annotated, Any, Literal
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from pydantic import BaseModel, ConfigDict, Field, field_validator
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class StrictModel(BaseModel):
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model_config = ConfigDict(extra="forbid")
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def _normalize_keywords(value: Any) -> Any:
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"""Trim, drop empties, de-duplicate case-insensitively, preserve first spelling."""
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if not isinstance(value, list):
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return value
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seen: set[str] = set()
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normalized: list[str] = []
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for item in value:
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if not isinstance(item, str):
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continue
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collapsed = " ".join(item.split())
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if not collapsed:
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continue
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key = collapsed.casefold()
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if key in seen:
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continue
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seen.add(key)
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normalized.append(collapsed)
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return normalized
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class ATSScore(StrictModel):
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# Profile fields are extracted verbatim from the resume; all are nullable because a
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# resume may simply not state them, and null must stay distinguishable from "".
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candidate_name: str | None = Field(default=None, max_length=120)
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job_title: str | None = Field(default=None, max_length=120)
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current_company: str | None = Field(default=None, max_length=120)
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years_experience: int | None = Field(default=None, ge=0, le=60)
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match_score: int = Field(ge=0, le=100)
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matched_keywords: list[str] = Field(default_factory=list, max_length=30)
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missing_keywords: list[str] = Field(default_factory=list, max_length=30)
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summary_critique: str = Field(min_length=1, max_length=500)
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@field_validator("matched_keywords", "missing_keywords", mode="before")
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@classmethod
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def _normalize(cls, value: Any) -> Any:
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return _normalize_keywords(value)
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@field_validator("candidate_name", "job_title", "current_company", mode="before")
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@classmethod
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def _blank_profile_text_to_none(cls, value: Any) -> Any:
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if isinstance(value, str):
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collapsed = " ".join(value.split())
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return collapsed or None
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return value
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@field_validator("summary_critique", mode="before")
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@classmethod
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def _collapse_whitespace(cls, value: Any) -> Any:
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if isinstance(value, str):
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return " ".join(value.split())
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return value
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class CompletedCandidate(ATSScore):
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filename: str
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status: Literal["completed"] = "completed"
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class FailedCandidate(StrictModel):
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filename: str
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status: Literal["failed"] = "failed"
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error_code: str
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error_message: str
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CandidateResult = Annotated[
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CompletedCandidate | FailedCandidate,
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Field(discriminator="status"),
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]
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class ScoreResponse(StrictModel):
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request_id: str
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total: int
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succeeded: int
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failed: int
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results: list[CandidateResult]
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class ErrorResponse(StrictModel):
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request_id: str
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error_code: str
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error_message: str
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