124 lines
5.0 KiB
Python
124 lines
5.0 KiB
Python
import pytest
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from review_agent.models import KnowledgeBaseDocument
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from review_agent.services import build_knowledge_context, send_message, stream_message
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pytestmark = pytest.mark.django_db
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def test_build_knowledge_context_ignores_irrelevant_rag_chunks(monkeypatch):
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monkeypatch.setattr(
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"review_agent.services.search_knowledge_base",
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lambda query, n_results=5: {
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"query": query,
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"results": [
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{
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"source": "附件 4 体外诊断试剂注册申报资料要求及说明.doc",
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"text": "预期用途应明确产品用于检测的分析物和功能。",
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"score": 7.636,
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"metadata": {"source_type": "regulatory_document"},
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}
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],
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"error_message": "",
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},
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)
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context = build_knowledge_context("孙之烨是谁")
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assert context == ""
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def test_build_knowledge_context_uses_full_document_when_name_matches(settings, tmp_path, monkeypatch, django_user_model):
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settings.MEDIA_ROOT = tmp_path
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user = django_user_model.objects.create_user(username="owner", password="pass")
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document_path = tmp_path / "resume.txt"
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document_path.write_text(
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"孙之烨，负责审核智能体项目。\n完整经历：曾组织技术分享并带队参加竞赛。",
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encoding="utf-8",
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)
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KnowledgeBaseDocument.objects.create(
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user=user,
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display_name="孙之烨简历",
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original_name="孙之烨-260510.txt",
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storage_path=str(document_path),
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file_size=document_path.stat().st_size,
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status=KnowledgeBaseDocument.Status.ACTIVE,
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is_active=True,
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indexed_chunk_count=2,
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)
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monkeypatch.setattr(
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"review_agent.services.search_knowledge_base",
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lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
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)
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context = build_knowledge_context("孙之烨是谁")
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assert "全文材料" in context
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assert "来源：用户知识库/孙之烨-260510.txt" in context
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assert "完整经历：曾组织技术分享并带队参加竞赛" in context
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def test_send_message_refuses_out_of_scope_answer_without_knowledge_context(monkeypatch, django_user_model):
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from review_agent.models import Conversation
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user = django_user_model.objects.create_user(username="owner", password="pass")
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conversation = Conversation.objects.create(user=user, title="会话")
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monkeypatch.setattr(
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"review_agent.services.search_knowledge_base",
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lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
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)
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monkeypatch.setattr(
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"review_agent.services.generate_reply",
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lambda *args, **kwargs: pytest.fail("out-of-scope answer without knowledge context must not call LLM"),
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)
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_, assistant_message = send_message(conversation, "孙之烨是谁")
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assert "没有在当前启用的知识库材料中找到" in assistant_message.content
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assert "与当前主营业务无关" in assistant_message.content
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def test_stream_message_refuses_out_of_scope_answer_without_knowledge_context(monkeypatch, django_user_model):
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from review_agent.models import Conversation
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user = django_user_model.objects.create_user(username="owner", password="pass")
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conversation = Conversation.objects.create(user=user, title="会话")
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monkeypatch.setattr(
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"review_agent.services.search_knowledge_base",
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lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
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)
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monkeypatch.setattr(
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"review_agent.services.stream_reply",
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lambda *args, **kwargs: pytest.fail("out-of-scope answer without knowledge context must not call streaming LLM"),
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)
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monkeypatch.setattr(
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"review_agent.services.generate_reply",
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lambda *args, **kwargs: pytest.fail("out-of-scope answer without knowledge context must not call fallback LLM"),
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)
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frames = list(stream_message(conversation, "给我一份红烧肉菜谱"))
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assert any("没有在当前启用的知识库材料中找到" in frame for frame in frames)
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assert any("与当前主营业务无关" in frame for frame in frames)
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assert any("done" in frame for frame in frames)
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def test_business_question_without_knowledge_context_can_use_llm(monkeypatch, django_user_model):
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from review_agent.models import Conversation
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user = django_user_model.objects.create_user(username="owner", password="pass")
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conversation = Conversation.objects.create(user=user, title="会话")
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monkeypatch.setattr(
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"review_agent.services.search_knowledge_base",
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lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
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)
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monkeypatch.setattr(
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"review_agent.services.generate_reply",
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lambda *args, **kwargs: "注册检验报告通常用于证明产品性能符合要求。",
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)
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_, assistant_message = send_message(conversation, "注册检验报告有什么作用")
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assert "注册检验报告" in assistant_message.content
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