192 lines
8.5 KiB
Python
192 lines
8.5 KiB
Python
import json
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import time
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from types import SimpleNamespace
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from sqlalchemy import select
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from sqlalchemy.orm import Session
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from app.models import Comment, ContentItem, Hotspot, Report, Task
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from app.schemas import CreateTaskRequest
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from app.services.report_service import DEFAULT_SUMMARY
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from app.services.task_service import create_task, run_task
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from tests.helpers import make_test_client
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class FakeXhsPlatform:
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def fetch_hotspots(self, *, limit):
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from app.platforms.base import HotspotData
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return [HotspotData(source_hot_id="h1", title="热点一", rank=1, heat_value="100", raw_data={"id": "h1"})]
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def search_items_by_hotspot(self, keyword, *, limit):
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from app.platforms.base import ContentItemData
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return [
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ContentItemData(source_item_id="n1", item_type="note", title=f"{keyword} 笔记", raw_data={"id": "n1"})
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]
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def fetch_comments(self, source_item_id, *, limit):
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from app.platforms.base import CommentData
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return [CommentData(source_comment_id="c1", content="评论一", like_count=5, raw_data={"id": "c1"})]
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ai_prompts: list[str] = []
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def successful_ai_response(prompt: str) -> str:
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ai_prompts.append(prompt)
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comments = json.loads(prompt[prompt.index("[") :])
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comment_id = comments[0]["comment_id"]
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return json.dumps(
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[{"comment_id": comment_id, "sentiment": "positive", "labels": ["认可"], "reason": "喜欢"}],
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ensure_ascii=False,
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)
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def test_xiaohongshu_task_flow_persists_hotspots_items_and_comments(monkeypatch):
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ai_prompts.clear()
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with make_test_client() as (_client, engine):
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monkeypatch.setattr("app.services.task_service.build_platform", lambda _platform: FakeXhsPlatform())
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summary_provider = lambda metrics, typical, *, word_limit=200: (
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ai_prompts.append(f"只返回一段中文总结 word_limit={word_limit} sample={metrics['sample_count']}")
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or "这是一段真实 AI 报告摘要。"
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)
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monkeypatch.setattr("app.services.task_service.build_ai_dependencies", lambda: (successful_ai_response, summary_provider))
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with Session(engine) as session:
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task = create_task(
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session,
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CreateTaskRequest(platform="xiaohongshu", hotspot_limit=1, item_limit_per_hotspot=1, comment_limit_per_item=10),
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submit_background=False,
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)
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task_id = task.id
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with Session(engine) as session:
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run_task(task_id, session_factory=lambda: session)
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persisted = session.get(Task, task_id)
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assert persisted.status == "success"
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assert persisted.processed_items_count == 1
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assert persisted.successful_items_count == 1
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assert persisted.analysis_status == "normal"
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assert session.scalar(select(Hotspot).where(Hotspot.task_id == task_id)).title == "热点一"
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assert session.scalar(select(ContentItem).where(ContentItem.task_id == task_id)).source_item_id == "n1"
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comment = session.scalar(select(Comment).where(Comment.task_id == task_id))
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assert comment.content == "评论一"
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assert comment.ai_analysis_status == "success"
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assert comment.sentiment == "positive"
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assert comment.labels == '["认可"]'
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assert comment.reason == "喜欢"
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item_report = session.scalar(select(Report).where(Report.task_id == task_id, Report.report_type == "item"))
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hotspot_report = session.scalar(select(Report).where(Report.task_id == task_id, Report.report_type == "hotspot"))
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assert item_report is not None
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assert hotspot_report is not None
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assert item_report.summary == "这是一段真实 AI 报告摘要。"
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assert hotspot_report.summary == "这是一段真实 AI 报告摘要。"
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assert DEFAULT_SUMMARY not in item_report.markdown_content
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assert DEFAULT_SUMMARY not in hotspot_report.markdown_content
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assert any("只返回一段中文总结" in prompt for prompt in ai_prompts)
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def test_xiaohongshu_task_flow_marks_comments_failed_when_ai_parse_fails(monkeypatch):
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with make_test_client() as (_client, engine):
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monkeypatch.setattr("app.services.task_service.build_platform", lambda _platform: FakeXhsPlatform())
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monkeypatch.setattr("app.services.task_service.build_ai_dependencies", lambda: (lambda _prompt: "not-json", None))
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monkeypatch.setattr("app.services.ai_service.time.sleep", lambda _seconds: None)
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with Session(engine) as session:
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task = create_task(
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session,
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CreateTaskRequest(platform="xiaohongshu", hotspot_limit=1, item_limit_per_hotspot=1, comment_limit_per_item=10),
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submit_background=False,
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)
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task_id = task.id
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with Session(engine) as session:
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run_task(task_id, session_factory=lambda: session)
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persisted = session.get(Task, task_id)
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comment = session.scalar(select(Comment).where(Comment.task_id == task_id))
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assert persisted.status == "success"
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assert persisted.analysis_status == "insufficient"
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assert persisted.analysis_success_rate == 0.0
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assert comment.ai_analysis_status == "failed"
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assert comment.sentiment == "unknown"
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assert comment.labels == "[]"
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assert comment.reason == "ai_parse_failed"
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def test_xiaohongshu_task_flow_keeps_item_success_when_ai_request_raises(monkeypatch):
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with make_test_client() as (_client, engine):
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monkeypatch.setattr("app.services.task_service.build_platform", lambda _platform: FakeXhsPlatform())
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monkeypatch.setattr("app.services.ai_service.time.sleep", lambda _seconds: None)
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def failing_requester(_prompt):
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raise RuntimeError("ai unauthorized")
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monkeypatch.setattr("app.services.task_service.build_ai_dependencies", lambda: (failing_requester, None))
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with Session(engine) as session:
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task = create_task(
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session,
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CreateTaskRequest(platform="xiaohongshu", hotspot_limit=1, item_limit_per_hotspot=1, comment_limit_per_item=10),
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submit_background=False,
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)
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task_id = task.id
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with Session(engine) as session:
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run_task(task_id, session_factory=lambda: session)
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persisted = session.get(Task, task_id)
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comment = session.scalar(select(Comment).where(Comment.task_id == task_id))
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assert persisted.status == "success"
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assert persisted.successful_items_count == 1
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assert persisted.failed_items_count == 0
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assert persisted.analysis_status == "insufficient"
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assert persisted.analysis_success_rate == 0.0
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assert comment.ai_analysis_status == "failed"
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assert comment.reason == "ai_parse_failed"
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def test_xiaohongshu_task_flow_times_out_stalled_ai_request(monkeypatch):
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with make_test_client() as (_client, engine):
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monkeypatch.setattr("app.services.task_service.build_platform", lambda _platform: FakeXhsPlatform())
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monkeypatch.setattr(
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"app.services.task_service.get_settings",
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lambda: SimpleNamespace(ai_max_retries=1, ai_timeout_seconds=0.01),
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)
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def stalled_requester(prompt):
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time.sleep(0.2)
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comments = json.loads(prompt[prompt.index("[") :])
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return json.dumps(
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[{"comment_id": comments[0]["comment_id"], "sentiment": "positive", "labels": ["超时后不应采用"], "reason": "late"}],
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ensure_ascii=False,
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)
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monkeypatch.setattr("app.services.task_service.build_ai_dependencies", lambda: (stalled_requester, None))
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with Session(engine) as session:
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task = create_task(
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session,
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CreateTaskRequest(platform="xiaohongshu", hotspot_limit=1, item_limit_per_hotspot=1, comment_limit_per_item=10),
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submit_background=False,
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)
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task_id = task.id
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with Session(engine) as session:
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run_task(task_id, session_factory=lambda: session)
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persisted = session.get(Task, task_id)
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comment = session.scalar(select(Comment).where(Comment.task_id == task_id))
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assert persisted.status == "success"
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assert persisted.finished_at is not None
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assert persisted.analysis_status == "insufficient"
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assert comment.ai_analysis_status == "failed"
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assert comment.sentiment == "unknown"
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assert comment.reason == "ai_parse_failed"
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