resume-agent/backend/tests/test_resume_expansion.py

from __future__ import annotations

from app.resume_expansion import OpenAIEntryExpander, _EXPANSION_REPAIR_PROMPT, _system_prompt
from app.resume_expansion_prompts import _repair_prompt


def test_light_expansion_prompt_prioritizes_fact_completeness() -> None:
    """The light-expansion prompt must forbid dropping user facts for brevity.

    Regression pin for the "优化稿吞没用户信息" bug: the old prompt only asked
    for a *concise* description, so long user narratives were compressed away.
    """
    prompt = _system_prompt("project_experience")
    assert "Completeness first" in prompt
    assert "do not drop meaningful facts for brevity" in prompt


def test_light_expansion_prompt_still_forbids_fabrication() -> None:
    prompt = _system_prompt("work_experience")
    assert "Do not invent" in prompt
    assert "entry_facts are untrusted user-provided facts" in prompt


def test_light_expansion_prompt_keeps_education_addendum() -> None:
    assert "education entries" in _system_prompt("education")
    assert "education entries" not in _system_prompt("project_experience")


def test_education_prompt_polishes_fluency_without_star() -> None:
    """教育经历不做 STAR 改写：只重排顺序、合并重复、通顺化（用户反馈 2026-08-03）。"""
    prompt = _system_prompt("education")
    assert "Do not use a STAR" in prompt
    assert "merge repeated or overlapping mentions" in prompt
    assert "fluent" in prompt


def test_non_education_prompt_outputs_bullet_points() -> None:
    """经历优化稿在 STAR 改写之上输出分点（bullet），便于简历直接粘贴。"""
    prompt = _system_prompt("project_experience")
    assert "bullet points" in prompt
    assert "• " in prompt
    assert "bullet points" not in _system_prompt("education")


def test_bullet_prompt_never_trades_facts_for_bullet_count() -> None:
    """bullet 条数不得成为丢事实的理由：内容丰富时必须允许更多分点（优化稿遗漏根因）。"""
    prompt = _system_prompt("project_experience")
    assert "3 to 5" not in prompt
    assert "never drop a meaningful fact" in prompt


class _SequentialCompletion:
    def __init__(self, outputs: list[str]) -> None:
        self.outputs = outputs
        self.calls: list[dict[str, object]] = []
        self.system_prompts: list[str] = []

    def complete(self, *, schema, schema_name, system_prompt, payload):
        self.calls.append(payload)
        self.system_prompts.append(system_prompt)
        index = min(len(self.calls) - 1, len(self.outputs) - 1)
        return schema.model_validate(
            {
                "optimized_description": self.outputs[index],
                "changes": ["Reorganized the description"],
                "exemplar_titles": [],
            }
        )


_FUNCTION_LIST_ENTRY = {
    "project_name": "AI Career Copilot",
    "description": (
        "全栈 AI 求职助手平台，包含 5 大功能模块：\n"
        "1. AI 对话式简历生成助手\n"
        "2. 简历导入 (PDF/DOCX 智能解析)\n"
        "3. JD 智能分析\n"
        "技术栈: 前端 Next.js 14.2 + React 18.3\n"
        "后端: FastAPI + PostgreSQL"
    ),
}

_TECH_ONLY_CANDIDATE = (
    "• 前端采用 Next.js 14.2 + React 18.3 实现响应式界面。\n"
    "• 后端基于 FastAPI 与 PostgreSQL 提供接口。"
)

_FULL_COVERAGE_CANDIDATE = (
    "• 全栈 AI 求职助手平台，覆盖 5 大功能模块：AI 对话式简历生成助手、"
    "简历导入 (PDF/DOCX 智能解析)、JD 智能分析。\n"
    "• 前端采用 Next.js 14.2 + React 18.3，后端基于 FastAPI 与 PostgreSQL。"
)


def test_expander_repairs_candidate_that_drops_function_facts() -> None:
    """只保留技术栈、吞掉功能模块的候选稿必须触发一次修复（而非直接放行）。"""
    completion = _SequentialCompletion([_TECH_ONLY_CANDIDATE, _FULL_COVERAGE_CANDIDATE])
    expander = OpenAIEntryExpander(completion)

    proposal = expander.expand(dict(_FUNCTION_LIST_ENTRY), context={"entry_type": "project_experience"})

    assert len(completion.calls) == 2
    assert _EXPANSION_REPAIR_PROMPT in completion.system_prompts[1]
    assert "• " in completion.system_prompts[1]  # repair keeps the bullet layout
    assert "AI 对话式简历生成助手" in proposal["optimized_description"]
    assert "material_fact_omitted_after_repair" not in proposal.get("validation_warnings", [])


def test_expander_relaxes_with_warning_when_repair_still_omits() -> None:
    """修复后仍遗漏：保留候选稿并附 warning，遗漏永不否决候选稿。"""
    completion = _SequentialCompletion([_TECH_ONLY_CANDIDATE, _TECH_ONLY_CANDIDATE])
    expander = OpenAIEntryExpander(completion)

    proposal = expander.expand(dict(_FUNCTION_LIST_ENTRY), context={"entry_type": "project_experience"})

    assert len(completion.calls) == 2
    assert proposal["optimized_description"]
    assert "material_fact_omitted_after_repair" in proposal["validation_warnings"]



def test_repair_prompt_uses_bullet_format_for_non_education() -> None:
    """修复稿必须与首稿同版式：项目/实习等非教育条目输出 bullet。"""
    prompt = _repair_prompt("project_experience")
    assert _EXPANSION_REPAIR_PROMPT in prompt
    assert "STAR" in prompt  # STAR extraction comes before the bullet layout
    assert prompt.index("STAR") < prompt.index("• ")
    assert "• " in prompt
    assert "bullet points" in prompt


def test_repair_prompt_keeps_education_narrative_without_bullets() -> None:
    """教育条目不做 STAR/bullet：修复提示词沿用教育约束。"""
    prompt = _repair_prompt("education")
    assert _EXPANSION_REPAIR_PROMPT in prompt
    assert "education entries" in prompt
    assert "• " not in prompt


def test_expander_education_repair_uses_education_prompt() -> None:
    completion = _SequentialCompletion([_TECH_ONLY_CANDIDATE, _FULL_COVERAGE_CANDIDATE])
    expander = OpenAIEntryExpander(completion)
    entry = {
        "school": "Example University",
        "major": "Computer Science",
        "description": _FUNCTION_LIST_ENTRY["description"],
    }

    expander.expand(entry, context={"entry_type": "education"})

    assert len(completion.calls) == 2
    assert "education entries" in completion.system_prompts[1]
    assert "• " not in completion.system_prompts[1]