from django.urls import reverse

from agent_core.results import AgentResult
from apps.audit.models import AgentAuditLog
from apps.audit.models import NotificationRecord
from apps.chat.models import Conversation
from apps.chat.services import create_conversation_for_batch
from apps.documents.models import SubmissionBatch, UploadedDocument


def _create_conversation_with_batch():
    batch = SubmissionBatch.objects.create(
        batch_id="SUB-20260604-001",
        product_name="新型冠状病毒 2019-nCoV 核酸检测试剂盒",
        workflow_type="registration",
        conversation_id="conv-001",
        file_count=2,
        page_count=12,
        import_status="completed",
    )
    conversation = Conversation.objects.create(
        conversation_id="conv-001",
        title="新型冠状病毒 2019-nCoV 核酸检测试剂盒",
        product_name=batch.product_name,
        batch_id=batch.batch_id,
        task_status="processing",
        node_results=[
            {"label": "资料包导入", "status": "已完成"},
            {"label": "目录汇总", "status": "处理中"},
        ],
    )
    return batch, conversation


def test_chat_post_returns_agent_result_and_audit_log(client, db, monkeypatch):
    batch, conversation = _create_conversation_with_batch()
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="说明书.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )

    monkeypatch.setattr(
        "apps.chat.views.run_agent",
        lambda *args, **kwargs: AgentResult(answer="模拟回答", status="success"),
    )

    response = client.post(
        reverse("chat:detail", args=[conversation.conversation_id]),
        {"message": "如何处理异常？"},
    )

    assert response.status_code == 200
    content = response.content.decode("utf-8")
    assert "审核智能体" in content
    assert "模拟回答" in content
    assert AgentAuditLog.objects.count() == 1
    assert AgentAuditLog.objects.get().batch_id == batch.batch_id


def test_chat_rejects_empty_message(client, db):
    _batch, conversation = _create_conversation_with_batch()

    response = client.post(reverse("chat:detail", args=[conversation.conversation_id]), {"message": ""})

    assert response.status_code == 200
    assert AgentAuditLog.objects.count() == 0
    assert "请输入要咨询的问题" in response.content.decode("utf-8")


def test_chat_passes_selected_document_ids_to_agent_core(client, db, monkeypatch):
    batch, conversation = _create_conversation_with_batch()
    selected = UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="selected.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="other.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )
    captured = {}

    def fake_run_agent(scenario_config, user_input, options=None):
        captured["options"] = options or {}
        return AgentResult(answer="ok", status="success")

    monkeypatch.setattr("apps.chat.views.run_agent", fake_run_agent)

    response = client.post(
        reverse("chat:detail", args=[conversation.conversation_id]),
        {"message": "只查选中文档", "document_ids": [str(selected.id)]},
    )

    assert response.status_code == 200
    assert captured["options"]["document_ids"] == [selected.id]
    assert captured["options"]["conversation_id"] == conversation.conversation_id
    assert captured["options"]["batch_id"] == batch.batch_id


def test_chat_renders_three_column_workspace_and_node_results(client, db):
    batch, conversation = _create_conversation_with_batch()
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="说明书.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )

    response = client.get(reverse("chat:detail", args=[conversation.conversation_id]))

    content = response.content.decode("utf-8")
    assert response.status_code == 200
    assert "会话历史" in content
    assert "对话区与节点导航" in content
    assert "上传区" in content
    assert "资料包导入 / 已完成" in content
    assert "目录汇总 / 处理中" in content


def test_chat_execution_creates_notification_record_from_agent_result(client, db, monkeypatch):
    batch, conversation = _create_conversation_with_batch()
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="说明书.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )

    monkeypatch.setattr(
        "apps.chat.views.run_agent",
        lambda *args, **kwargs: AgentResult(
            answer="执行完成",
            status="success",
            notification_payload={
                "batch_id": batch.batch_id,
                "conversation_id": conversation.conversation_id,
                "product_name": batch.product_name,
                "notify_reason": "task_completed",
                "owners": [
                    {
                        "owner_role": "注册资料负责人",
                        "feishu_user_id": "ou_demo_1",
                    }
                ],
            },
        ),
    )

    response = client.post(
        reverse("chat:detail", args=[conversation.conversation_id]),
        {"message": "执行审核"},
    )

    assert response.status_code == 200
    record = NotificationRecord.objects.get()
    assert record.notify_reason == "task_completed"
    assert record.batch_id == batch.batch_id
    assert record.web_detail_url.endswith(f"/audit/{AgentAuditLog.objects.get().id}/")


def test_chat_execution_creates_failed_notification_record_and_updates_conversation(client, db, monkeypatch):
    batch, conversation = _create_conversation_with_batch()
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="说明书.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )

    monkeypatch.setattr(
        "apps.chat.views.run_agent",
        lambda *args, **kwargs: AgentResult(
            answer="执行失败",
            status="failed",
            error="规则执行失败",
            node_results=[
                {"code": "package_import", "label": "资料包导入", "status": "已完成"},
                {"code": "overview", "label": "目录汇总", "status": "已完成"},
                {"code": "risk", "label": "风险预警", "status": "已阻断"},
                {"code": "feishu_notify", "label": "飞书通知", "status": "失败"},
            ],
            notification_payload={
                "batch_id": batch.batch_id,
                "conversation_id": conversation.conversation_id,
                "product_name": batch.product_name,
                "notify_reason": "task_failed",
                "owners": [
                    {
                        "owner_role": "注册申报负责人",
                        "feishu_user_id": "ou_demo_2",
                    }
                ],
            },
        ),
    )

    response = client.post(
        reverse("chat:detail", args=[conversation.conversation_id]),
        {"message": "执行失败任务"},
    )

    assert response.status_code == 200
    record = NotificationRecord.objects.get()
    conversation.refresh_from_db()
    assert record.notify_reason == "task_failed"
    assert record.message_status == "failed"
    assert record.web_detail_url.endswith(f"/audit/{AgentAuditLog.objects.get().id}/")
    assert conversation.task_status == "failed"
    assert conversation.node_results[-1]["label"] == "飞书通知"


def test_chat_execution_persists_agent_node_results_to_conversation(client, db, monkeypatch):
    batch, conversation = _create_conversation_with_batch()
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="说明书.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )

    monkeypatch.setattr(
        "apps.chat.views.run_agent",
        lambda *args, **kwargs: AgentResult(
            answer="已生成风险结论",
            status="success",
            node_results=[
                {"code": "package_import", "label": "资料包导入", "status": "已完成"},
                {"code": "overview", "label": "目录汇总", "status": "已完成"},
                {"code": "completeness", "label": "法规完整性检查", "status": "已完成"},
                {"code": "field_extraction", "label": "字段抽取", "status": "已完成"},
                {"code": "consistency", "label": "一致性核查", "status": "待复核"},
                {"code": "risk", "label": "风险预警", "status": "已阻断", "summary": "存在高风险"},
                {"code": "word_export", "label": "Word 回填导出", "status": "待处理"},
                {"code": "feishu_notify", "label": "飞书通知", "status": "待处理"},
            ],
            notification_payload={
                "batch_id": batch.batch_id,
                "conversation_id": conversation.conversation_id,
                "product_name": batch.product_name,
                "notify_reason": "task_completed",
                "owners": [],
            },
        ),
    )

    response = client.post(
        reverse("chat:detail", args=[conversation.conversation_id]),
        {"message": "执行节点任务"},
    )

    assert response.status_code == 200
    conversation.refresh_from_db()
    assert len(conversation.node_results) == 8
    assert conversation.task_status == "success"
    assert conversation.latest_summary["answer"] == "已生成风险结论"


def test_create_conversation_for_batch_initializes_eight_workflow_nodes(db):
    conversation = create_conversation_for_batch(
        "SUB-20260604-001",
        "新型冠状病毒 2019-nCoV 核酸检测试剂盒",
    )

    labels = [node["label"] for node in conversation.node_results]
    assert len(labels) == 8
    assert labels == [
        "资料包导入",
        "目录汇总",
        "法规完整性检查",
        "字段抽取",
        "一致性核查",
        "风险预警",
        "Word 回填导出",
        "飞书通知",
    ]


def test_chat_page_shows_upload_entry_and_dynamic_context_cards(client, db):
    batch, conversation = _create_conversation_with_batch()
    conversation.node_results = [
        {"label": "资料包导入", "status": "已完成"},
        {"label": "目录汇总", "status": "已完成"},
        {"label": "法规完整性检查", "status": "已完成"},
        {"label": "字段抽取", "status": "已完成"},
        {"label": "一致性核查", "status": "待复核"},
        {"label": "风险预警", "status": "已阻断"},
        {"label": "Word 回填导出", "status": "待处理"},
        {"label": "飞书通知", "status": "待处理"},
    ]
    conversation.save(update_fields=["node_results"])
    UploadedDocument.objects.create(
        batch=batch,
        scenario_id="document_review",
        original_name="说明书.md",
        file_type="md",
        size=1,
        status=UploadedDocument.STATUS_INDEXED,
    )

    response = client.get(reverse("chat:detail", args=[conversation.conversation_id]))

    content = response.content.decode("utf-8")
    assert response.status_code == 200
    assert "继续上传资料" in content
    assert "最高风险等级" in content
    assert "是否允许正式导出" in content
    assert "通知状态" in content
    assert "飞书通知 / 待处理" in content