import pytest

from review_agent.models import KnowledgeBaseDocument
from review_agent.services import build_knowledge_context, send_message, stream_message


pytestmark = pytest.mark.django_db


def test_build_knowledge_context_ignores_irrelevant_rag_chunks(monkeypatch):
    monkeypatch.setattr(
        "review_agent.services.search_knowledge_base",
        lambda query, n_results=5: {
            "query": query,
            "results": [
                {
                    "source": "附件 4 体外诊断试剂注册申报资料要求及说明.doc",
                    "text": "预期用途应明确产品用于检测的分析物和功能。",
                    "score": 7.636,
                    "metadata": {"source_type": "regulatory_document"},
                }
            ],
            "error_message": "",
        },
    )

    context = build_knowledge_context("孙之烨是谁")

    assert context == ""


def test_build_knowledge_context_uses_full_document_when_name_matches(settings, tmp_path, monkeypatch, django_user_model):
    settings.MEDIA_ROOT = tmp_path
    user = django_user_model.objects.create_user(username="owner", password="pass")
    document_path = tmp_path / "resume.txt"
    document_path.write_text(
        "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。",
        encoding="utf-8",
    )
    KnowledgeBaseDocument.objects.create(
        user=user,
        display_name="孙之烨简历",
        original_name="孙之烨-260510.txt",
        storage_path=str(document_path),
        file_size=document_path.stat().st_size,
        status=KnowledgeBaseDocument.Status.ACTIVE,
        is_active=True,
        indexed_chunk_count=2,
    )
    monkeypatch.setattr(
        "review_agent.services.search_knowledge_base",
        lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
    )

    context = build_knowledge_context("孙之烨是谁")

    assert "全文材料" in context
    assert "来源：用户知识库/孙之烨-260510.txt" in context
    assert "完整经历：曾组织技术分享并带队参加竞赛" in context


def test_send_message_refuses_out_of_scope_answer_without_knowledge_context(monkeypatch, django_user_model):
    from review_agent.models import Conversation

    user = django_user_model.objects.create_user(username="owner", password="pass")
    conversation = Conversation.objects.create(user=user, title="会话")
    monkeypatch.setattr(
        "review_agent.services.search_knowledge_base",
        lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
    )
    monkeypatch.setattr(
        "review_agent.services.generate_reply",
        lambda *args, **kwargs: pytest.fail("out-of-scope answer without knowledge context must not call LLM"),
    )

    _, assistant_message = send_message(conversation, "孙之烨是谁")

    assert "没有在当前启用的知识库材料中找到" in assistant_message.content
    assert "与当前主营业务无关" in assistant_message.content


def test_stream_message_refuses_out_of_scope_answer_without_knowledge_context(monkeypatch, django_user_model):
    from review_agent.models import Conversation

    user = django_user_model.objects.create_user(username="owner", password="pass")
    conversation = Conversation.objects.create(user=user, title="会话")
    monkeypatch.setattr(
        "review_agent.services.search_knowledge_base",
        lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
    )
    monkeypatch.setattr(
        "review_agent.services.stream_reply",
        lambda *args, **kwargs: pytest.fail("out-of-scope answer without knowledge context must not call streaming LLM"),
    )
    monkeypatch.setattr(
        "review_agent.services.generate_reply",
        lambda *args, **kwargs: pytest.fail("out-of-scope answer without knowledge context must not call fallback LLM"),
    )

    frames = list(stream_message(conversation, "给我一份红烧肉菜谱"))

    assert any("没有在当前启用的知识库材料中找到" in frame for frame in frames)
    assert any("与当前主营业务无关" in frame for frame in frames)
    assert any("done" in frame for frame in frames)


def test_business_question_without_knowledge_context_can_use_llm(monkeypatch, django_user_model):
    from review_agent.models import Conversation

    user = django_user_model.objects.create_user(username="owner", password="pass")
    conversation = Conversation.objects.create(user=user, title="会话")
    monkeypatch.setattr(
        "review_agent.services.search_knowledge_base",
        lambda query, n_results=5: {"query": query, "results": [], "error_message": ""},
    )
    monkeypatch.setattr(
        "review_agent.services.generate_reply",
        lambda *args, **kwargs: "注册检验报告通常用于证明产品性能符合要求。",
    )

    _, assistant_message = send_message(conversation, "注册检验报告有什么作用")

    assert "注册检验报告" in assistant_message.content