from __future__ import annotations import json from types import SimpleNamespace from typing import Any from app.llm_services import ( AnchorExtractionOutput, OpenAICompatibleStructuredClient, OpenAIExperienceExtractor, OpenAIResumeRewriter, ) from app.main import create_app from app.settings import Settings, load_settings class FakeCompletions: def __init__(self, responses: list[str | Exception]) -> None: self.responses = list(responses) self.calls: list[dict[str, Any]] = [] def create(self, **kwargs: Any) -> Any: self.calls.append(kwargs) response = self.responses.pop(0) if isinstance(response, Exception): raise response message = SimpleNamespace(content=response, parsed=None, refusal=None) return SimpleNamespace(choices=[SimpleNamespace(message=message)]) class FakeOpenAI: def __init__(self, responses: list[str | Exception]) -> None: self.completions = FakeCompletions(responses) self.chat = SimpleNamespace(completions=self.completions) def llm_settings(**overrides: Any) -> Settings: values: dict[str, Any] = { "llm_provider": "openai", "openai_api_key": "test-key-not-a-secret", "openai_base_url": "https://example.test/v1", "openai_model": "test-model", "openai_timeout_seconds": 12.0, "openai_max_retries": 2, "structured_output_retries": 1, "structured_output_mode": "json_schema", "fallback_to_rules": False, } values.update(overrides) return Settings(**values) def anchor_response() -> str: return json.dumps( { "record_type": "work_experience", "field_updates": { "school": None, "major": None, "degree": None, "company": "星河科技有限公司", "position": "产品经理", "project_name": None, "project_role": None, "start_date": "2022-03", "end_date_or_present": "present", }, "evidence_spans": [ {"field": "company", "quote": "星河科技有限公司"}, {"field": "position", "quote": "产品经理"}, {"field": "start_date", "quote": "2022年3月"}, {"field": "end_date_or_present", "quote": "至今"}, ], "ambiguities": [], }, ensure_ascii=False, ) def test_anchor_extraction_retries_validates_and_redacts_phone() -> None: fake = FakeOpenAI(["not-json", anchor_response()]) completion = OpenAICompatibleStructuredClient(llm_settings(), fake) extractor = OpenAIExperienceExtractor(completion) patch = extractor.extract_anchor( "我从2022年3月至今在星河科技有限公司担任产品经理，电话13800138000", "work_experience", ["company", "position", "start_date", "end_date_or_present"], ) assert patch == { "company": "星河科技有限公司", "position": "产品经理", "start_date": "2022-03", "end_date_or_present": "present", } assert len(fake.completions.calls) == 2 call = fake.completions.calls[-1] assert call["model"] == "test-model" assert call["timeout"] == 12.0 assert call["response_format"]["type"] == "json_schema" serialized_messages = json.dumps(call["messages"], ensure_ascii=False) assert "13800138000" not in serialized_messages assert "[手机号已脱敏]" in serialized_messages def test_experience_extraction_uses_pydantic_and_exact_evidence() -> None: response = json.dumps( { "title": "后端工程师", "organization": "星河科技", "role": "后端工程师", "highlights": ["优化接口耗时，降低30%"], "metrics": ["30%", "99%"], "confidence": 0.93, "evidence_spans": [ {"field": "organization", "quote": "星河科技"}, {"field": "role", "quote": "后端工程师"}, {"field": "highlights", "quote": "优化接口耗时，降低30%"}, ], "ambiguities": [], }, ensure_ascii=False, ) extractor = OpenAIExperienceExtractor( OpenAICompatibleStructuredClient(llm_settings(), FakeOpenAI([response])) ) result = extractor.extract("在星河科技担任后端工程师，优化接口耗时，降低30%") assert result.organization == "星河科技" assert result.highlights == ["优化接口耗时，降低30%"] assert result.metrics == ["30%"] assert result.confidence == 0.95 def test_sdk_boundary_redacts_email_wechat_and_split_phone() -> None: fake = FakeOpenAI([anchor_response()]) completion = OpenAICompatibleStructuredClient(llm_settings(), fake) completion.complete( schema=AnchorExtractionOutput, schema_name="resume_anchor_extraction", system_prompt="extract", payload={ "user_text": ( "手机 138-0013-8000，邮箱 user@example.com，微信号: resume_helper" ) }, ) request_text = json.dumps(fake.completions.calls[0]["messages"], ensure_ascii=False) assert "138-0013-8000" not in request_text assert "user@example.com" not in request_text assert "resume_helper" not in request_text assert "[手机号已脱敏]" in request_text assert "[邮箱已脱敏]" in request_text assert "[微信号已脱敏]" in request_text def test_json_object_mode_includes_the_pydantic_schema() -> None: fake = FakeOpenAI([anchor_response()]) settings = llm_settings(structured_output_mode="json_object") completion = OpenAICompatibleStructuredClient(settings, fake) completion.complete( schema=AnchorExtractionOutput, schema_name="resume_anchor_extraction", system_prompt="提取事实。", payload={"user_text": "在星河科技担任产品经理"}, ) call = fake.completions.calls[0] assert call["response_format"] == {"type": "json_object"} assert "output_json_schema" in call["messages"][1]["content"] assert "只返回" in call["messages"][0]["content"] def test_rewriter_sends_allow_listed_facts_and_rejects_new_numbers() -> None: response = json.dumps( { "items": [ { "source_id": "experience_0", "bullets": [ { "text": "优化接口性能，将接口耗时降低30%", "evidence": ["优化接口耗时，降低30%"], }, { "text": "支持100万用户稳定访问", "evidence": ["优化接口耗时，降低30%"], }, ], } ] }, ensure_ascii=False, ) fake = FakeOpenAI([response]) rewriter = OpenAIResumeRewriter( OpenAICompatibleStructuredClient(llm_settings(), fake) ) profile = { "name": "张三", "phone": "13800138000", "account_phone": "13900139000", "phone_source": "manual", "metadata": {"private_note": "never-send-this"}, "job_type": "social", "anchor_type": "work_experience", "anchor": { "company": "星河科技", "position": "后端工程师", "start_date": "2022-01", "end_date_or_present": "present", }, "experiences": [ { "raw_text": "联系电话13800138000", "title": "后端工程师", "organization": "星河科技", "role": "后端工程师", "highlights": ["优化接口耗时，降低30%"], "metrics": ["30%"], "confidence": 0.9, } ], } resume = rewriter.rewrite(profile) assert resume["basics"]["masked_phone"] == "138****8000" item = resume["sections"][1]["items"][0] assert item["resume_bullets"] == ["优化接口性能，将接口耗时降低30%"] request_text = json.dumps(fake.completions.calls[0]["messages"], ensure_ascii=False) assert "13800138000" not in request_text assert "13900139000" not in request_text assert "never-send-this" not in request_text assert "张三" not in request_text def test_settings_load_dotenv_and_create_app_wires_openai_defaults( tmp_path, monkeypatch ) -> None: env_file = tmp_path / ".env" env_file.write_text( "\n".join( [ "RESUME_AGENT_LLM_PROVIDER=openai", "OPENAI_API_KEY=dummy-key", "OPENAI_BASE_URL=https://gateway.test", "OPENAI_MODEL=test-model", "RESUME_AGENT_LLM_FALLBACK_TO_RULES=false", ] ), encoding="utf-8", ) for name in ( "RESUME_AGENT_LLM_PROVIDER", "OPENAI_API_KEY", "OPENAI_BASE_URL", "OPENAI_MODEL", "RESUME_AGENT_LLM_FALLBACK_TO_RULES", ): monkeypatch.delenv(name, raising=False) settings = load_settings(env_file) fake = FakeOpenAI([anchor_response()]) application = create_app( database_path=tmp_path / "llm.db", settings=settings, openai_client=fake, ) assert isinstance(application.state.resume_agent.extractor, OpenAIExperienceExtractor) assert settings.openai_base_url == "https://gateway.test" assert "dummy-key" not in repr(settings)