328 lines
12 KiB
Python
328 lines
12 KiB
Python
from django.urls import reverse
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from agent_core.results import AgentResult
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from apps.audit.models import AgentAuditLog
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from apps.audit.models import NotificationRecord
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from apps.chat.models import Conversation
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from apps.chat.services import create_conversation_for_batch
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from apps.documents.models import SubmissionBatch, UploadedDocument
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def _create_conversation_with_batch():
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batch = SubmissionBatch.objects.create(
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batch_id="SUB-20260604-001",
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product_name="新型冠状病毒 2019-nCoV 核酸检测试剂盒",
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workflow_type="registration",
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conversation_id="conv-001",
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file_count=2,
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page_count=12,
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import_status="completed",
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)
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conversation = Conversation.objects.create(
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conversation_id="conv-001",
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title="新型冠状病毒 2019-nCoV 核酸检测试剂盒",
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product_name=batch.product_name,
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batch_id=batch.batch_id,
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task_status="processing",
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node_results=[
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{"label": "资料包导入", "status": "已完成"},
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{"label": "目录汇总", "status": "处理中"},
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],
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)
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return batch, conversation
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def test_chat_post_returns_agent_result_and_audit_log(client, db, monkeypatch):
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batch, conversation = _create_conversation_with_batch()
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="说明书.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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monkeypatch.setattr(
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"apps.chat.views.run_agent",
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lambda *args, **kwargs: AgentResult(answer="模拟回答", status="success"),
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)
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response = client.post(
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reverse("chat:detail", args=[conversation.conversation_id]),
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{"message": "如何处理异常？"},
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)
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assert response.status_code == 200
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content = response.content.decode("utf-8")
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assert "审核智能体" in content
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assert "模拟回答" in content
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assert AgentAuditLog.objects.count() == 1
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assert AgentAuditLog.objects.get().batch_id == batch.batch_id
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def test_chat_rejects_empty_message(client, db):
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_batch, conversation = _create_conversation_with_batch()
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response = client.post(reverse("chat:detail", args=[conversation.conversation_id]), {"message": ""})
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assert response.status_code == 200
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assert AgentAuditLog.objects.count() == 0
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assert "请输入要咨询的问题" in response.content.decode("utf-8")
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def test_chat_passes_selected_document_ids_to_agent_core(client, db, monkeypatch):
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batch, conversation = _create_conversation_with_batch()
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selected = UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="selected.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="other.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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captured = {}
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def fake_run_agent(scenario_config, user_input, options=None):
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captured["options"] = options or {}
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return AgentResult(answer="ok", status="success")
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monkeypatch.setattr("apps.chat.views.run_agent", fake_run_agent)
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response = client.post(
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reverse("chat:detail", args=[conversation.conversation_id]),
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{"message": "只查选中文档", "document_ids": [str(selected.id)]},
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)
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assert response.status_code == 200
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assert captured["options"]["document_ids"] == [selected.id]
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assert captured["options"]["conversation_id"] == conversation.conversation_id
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assert captured["options"]["batch_id"] == batch.batch_id
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def test_chat_renders_three_column_workspace_and_node_results(client, db):
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batch, conversation = _create_conversation_with_batch()
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="说明书.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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response = client.get(reverse("chat:detail", args=[conversation.conversation_id]))
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content = response.content.decode("utf-8")
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assert response.status_code == 200
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assert "会话历史" in content
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assert "对话区与节点导航" in content
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assert "上传区" in content
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assert "资料包导入 / 已完成" in content
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assert "目录汇总 / 处理中" in content
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def test_chat_execution_creates_notification_record_from_agent_result(client, db, monkeypatch):
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batch, conversation = _create_conversation_with_batch()
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="说明书.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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monkeypatch.setattr(
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"apps.chat.views.run_agent",
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lambda *args, **kwargs: AgentResult(
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answer="执行完成",
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status="success",
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notification_payload={
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"batch_id": batch.batch_id,
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"conversation_id": conversation.conversation_id,
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"product_name": batch.product_name,
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"notify_reason": "task_completed",
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"owners": [
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{
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"owner_role": "注册资料负责人",
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"feishu_user_id": "ou_demo_1",
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}
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],
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},
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),
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)
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response = client.post(
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reverse("chat:detail", args=[conversation.conversation_id]),
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{"message": "执行审核"},
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)
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assert response.status_code == 200
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record = NotificationRecord.objects.get()
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assert record.notify_reason == "task_completed"
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assert record.batch_id == batch.batch_id
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assert record.web_detail_url.endswith(f"/audit/{AgentAuditLog.objects.get().id}/")
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def test_chat_execution_creates_failed_notification_record_and_updates_conversation(client, db, monkeypatch):
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batch, conversation = _create_conversation_with_batch()
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="说明书.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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monkeypatch.setattr(
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"apps.chat.views.run_agent",
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lambda *args, **kwargs: AgentResult(
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answer="执行失败",
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status="failed",
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error="规则执行失败",
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node_results=[
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{"code": "package_import", "label": "资料包导入", "status": "已完成"},
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{"code": "overview", "label": "目录汇总", "status": "已完成"},
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{"code": "risk", "label": "风险预警", "status": "已阻断"},
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{"code": "feishu_notify", "label": "飞书通知", "status": "失败"},
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],
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notification_payload={
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"batch_id": batch.batch_id,
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"conversation_id": conversation.conversation_id,
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"product_name": batch.product_name,
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"notify_reason": "task_failed",
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"owners": [
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{
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"owner_role": "注册申报负责人",
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"feishu_user_id": "ou_demo_2",
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}
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],
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},
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),
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)
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response = client.post(
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reverse("chat:detail", args=[conversation.conversation_id]),
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{"message": "执行失败任务"},
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)
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assert response.status_code == 200
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record = NotificationRecord.objects.get()
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conversation.refresh_from_db()
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assert record.notify_reason == "task_failed"
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assert record.message_status == "failed"
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assert record.web_detail_url.endswith(f"/audit/{AgentAuditLog.objects.get().id}/")
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assert conversation.task_status == "failed"
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assert conversation.node_results[-1]["label"] == "飞书通知"
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def test_chat_execution_persists_agent_node_results_to_conversation(client, db, monkeypatch):
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batch, conversation = _create_conversation_with_batch()
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="说明书.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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monkeypatch.setattr(
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"apps.chat.views.run_agent",
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lambda *args, **kwargs: AgentResult(
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answer="已生成风险结论",
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status="success",
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node_results=[
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{"code": "package_import", "label": "资料包导入", "status": "已完成"},
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{"code": "overview", "label": "目录汇总", "status": "已完成"},
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{"code": "completeness", "label": "法规完整性检查", "status": "已完成"},
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{"code": "field_extraction", "label": "字段抽取", "status": "已完成"},
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{"code": "consistency", "label": "一致性核查", "status": "待复核"},
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{"code": "risk", "label": "风险预警", "status": "已阻断", "summary": "存在高风险"},
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{"code": "word_export", "label": "Word 回填导出", "status": "待处理"},
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{"code": "feishu_notify", "label": "飞书通知", "status": "待处理"},
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],
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notification_payload={
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"batch_id": batch.batch_id,
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"conversation_id": conversation.conversation_id,
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"product_name": batch.product_name,
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"notify_reason": "task_completed",
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"owners": [],
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},
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),
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)
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response = client.post(
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reverse("chat:detail", args=[conversation.conversation_id]),
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{"message": "执行节点任务"},
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)
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assert response.status_code == 200
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conversation.refresh_from_db()
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assert len(conversation.node_results) == 8
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assert conversation.task_status == "success"
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assert conversation.latest_summary["answer"] == "已生成风险结论"
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def test_create_conversation_for_batch_initializes_eight_workflow_nodes(db):
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conversation = create_conversation_for_batch(
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"SUB-20260604-001",
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"新型冠状病毒 2019-nCoV 核酸检测试剂盒",
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)
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labels = [node["label"] for node in conversation.node_results]
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assert len(labels) == 8
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assert labels == [
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"资料包导入",
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"目录汇总",
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"法规完整性检查",
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"字段抽取",
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"一致性核查",
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"风险预警",
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"Word 回填导出",
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"飞书通知",
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]
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def test_chat_page_shows_upload_entry_and_dynamic_context_cards(client, db):
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batch, conversation = _create_conversation_with_batch()
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conversation.node_results = [
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{"label": "资料包导入", "status": "已完成"},
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{"label": "目录汇总", "status": "已完成"},
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{"label": "法规完整性检查", "status": "已完成"},
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{"label": "字段抽取", "status": "已完成"},
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{"label": "一致性核查", "status": "待复核"},
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{"label": "风险预警", "status": "已阻断"},
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{"label": "Word 回填导出", "status": "待处理"},
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{"label": "飞书通知", "status": "待处理"},
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]
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conversation.save(update_fields=["node_results"])
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UploadedDocument.objects.create(
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batch=batch,
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scenario_id="document_review",
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original_name="说明书.md",
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file_type="md",
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size=1,
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status=UploadedDocument.STATUS_INDEXED,
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)
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response = client.get(reverse("chat:detail", args=[conversation.conversation_id]))
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content = response.content.decode("utf-8")
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assert response.status_code == 200
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assert "继续上传资料" in content
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assert "最高风险等级" in content
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assert "是否允许正式导出" in content
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assert "通知状态" in content
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assert "飞书通知 / 待处理" in content
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