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117 lines
3.9 KiB
Python
117 lines
3.9 KiB
Python
"""Deep Research must not report success when a research block fails (issue #595).
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A subtopic that raises (or exhausts its iteration budget without finishing) is
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backfilled with empty knowledge so the surviving subtopics still yield a report.
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The fix keeps that resilience but makes the shortfall explicit in the result
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envelope (``metadata.partial`` / ``failed_block_count`` / ``failed_block_titles``)
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instead of returning a clean-success shape with missing evidence.
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"""
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from __future__ import annotations
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import types
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from unittest.mock import patch
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import pytest
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from deeptutor.agents.research.pipeline import ResearchedBlock, ResearchPipeline, SubTopicItem
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from deeptutor.core.context import UnifiedContext
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from deeptutor.core.stream_bus import StreamBus
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pytestmark = pytest.mark.asyncio
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class _FakeLLM:
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binding = "openai"
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model = "gpt-x"
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api_key = "k"
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base_url = "u"
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api_version = None
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extra_headers: dict = {}
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reasoning_effort = None
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class _FakeRegistry:
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def build_openai_schemas(self, _names):
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return []
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def build_prompt_text(self, _names, **_kwargs):
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return "- none"
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def get(self, _name):
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return None
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def get_enabled(self, _names):
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return []
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def _make_pipeline() -> ResearchPipeline:
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with (
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patch("deeptutor.agents.research.pipeline.get_llm_config", lambda: _FakeLLM()),
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patch("deeptutor.agents.research.pipeline.get_tool_registry", lambda: _FakeRegistry()),
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):
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return ResearchPipeline(language="en", runtime_config={"queue": {"max_length": 5}})
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async def _run(pipeline: ResearchPipeline) -> dict:
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async def fake_emit(*_args, **_kwargs):
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return None
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with patch("deeptutor.agents.research.pipeline.emit_capability_result", fake_emit):
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return await pipeline._run_inner(
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context=UnifiedContext(session_id="s1", user_message="research this"),
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topic="Research topic",
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image_attachments=[],
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confirmed_outline=[SubTopicItem(title="A"), SubTopicItem(title="B")],
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stream=StreamBus(),
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client=None,
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)
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async def test_failed_block_marks_result_partial() -> None:
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pipeline = _make_pipeline()
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async def fake_research_block(self, *, block, queue, citations, topic, context, stream, client):
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queue.mark_researching(block.block_id)
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if block.block_id == "block_1":
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raise RuntimeError("synthetic block failure")
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queue.mark_completed(block.block_id)
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return ResearchedBlock(block=block, knowledge=f"knowledge for {block.block_id}")
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async def fake_write_report(self, *, topic, blocks, citations, stream, client):
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return "REPORT_OK"
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pipeline._research_block = types.MethodType(fake_research_block, pipeline)
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pipeline._write_report = types.MethodType(fake_write_report, pipeline)
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result = await _run(pipeline)
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meta = result["metadata"]
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assert result["response"] == "REPORT_OK" # surviving evidence still produces a report
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assert meta["partial"] is True
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assert meta["failed_block_count"] == 1
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assert meta["failed_block_titles"] == ["A"]
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assert meta["block_count"] == 2
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async def test_all_blocks_complete_is_not_partial() -> None:
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pipeline = _make_pipeline()
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async def fake_research_block(self, *, block, queue, citations, topic, context, stream, client):
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queue.mark_researching(block.block_id)
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queue.mark_completed(block.block_id)
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return ResearchedBlock(block=block, knowledge=f"knowledge for {block.block_id}")
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async def fake_write_report(self, *, topic, blocks, citations, stream, client):
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return "REPORT_OK"
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pipeline._research_block = types.MethodType(fake_research_block, pipeline)
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pipeline._write_report = types.MethodType(fake_write_report, pipeline)
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result = await _run(pipeline)
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meta = result["metadata"]
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assert meta["partial"] is False
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assert meta["failed_block_count"] == 0
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assert meta["failed_block_titles"] == []
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