108 lines
3.6 KiB
Python
108 lines
3.6 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.documents.models import UploadedDocument
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def test_chat_post_returns_agent_result_and_audit_log(client, db):
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response = client.post(
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reverse("chat:index", args=["knowledge_qa"]),
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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 "mock-model" 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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def test_chat_rejects_empty_message(client, db):
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response = client.post(reverse("chat:index", args=["knowledge_qa"]), {"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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selected = UploadedDocument.objects.create(
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scenario_id="knowledge_qa",
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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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other = UploadedDocument.objects.create(
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scenario_id="knowledge_qa",
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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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from agent_core.results import AgentResult
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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:index", args=["knowledge_qa"]),
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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 other.id not in captured["options"]["document_ids"]
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def test_chat_renders_structured_output_references_and_tool_calls(client, db, monkeypatch):
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def fake_run_agent(scenario_config, user_input, options=None):
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return AgentResult(
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answer="建议先隔离现场。",
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structured_output={
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"output_type": "quality_report",
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"summary": "发现异常批次需要立即处置。",
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"risk_level": "high",
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"suggested_actions": ["隔离现场", "通知负责人"],
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},
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references=[
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{
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"source": "sop.md",
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"content": "异常处理 SOP：先隔离现场，再通知负责人。",
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}
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],
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tool_calls=[
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{
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"tool_name": "query_demo_records",
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"success": True,
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"result": {"records": [{"title": "A线缺陷"}]},
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"error": "",
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}
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],
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model_name="mock-model",
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status="success",
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)
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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:index", args=["quality_analysis"]),
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{"message": "分析 A 线异常"},
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)
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content = response.content.decode("utf-8")
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assert response.status_code == 200
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assert "结构化结果" in content
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assert "发现异常批次需要立即处置" in content
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assert "引用片段" in content
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assert "sop.md" in content
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assert "工具调用" in content
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assert "query_demo_records" in content
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assert "查看本次审计日志" in content
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