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78 lines
3.4 KiB
Python
78 lines
3.4 KiB
Python
from __future__ import annotations
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from pathlib import Path
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import pytest
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from paperforge.query_planning import build_query_plan, enrich_query_plan_with_runtime
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from paperforge.commands.query_plan import run as query_plan_run
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class _Args:
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def __init__(self, query: str, intent: str, vault_path: Path, json: bool = True) -> None:
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self.query = query
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self.intent = intent
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self.vault_path = vault_path
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self.json = json
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def test_query_plan_identifier_exact_prefers_paper_context() -> None:
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plan = build_query_plan("10.1016/j.heliyon.2024.e38112", "known-paper")
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assert plan["query_class"] == "identifier_exact"
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assert plan["recommended_primary"]["command"] == "paper-context"
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def test_query_plan_mixed_author_year_rewrites_to_author_year_search() -> None:
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plan = build_query_plan("Lin 2024 Electrical Stimulation", "discover")
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primary = plan["recommended_primary"]
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assert plan["query_class"] == "mixed_query"
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assert primary["command"] == "search"
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assert primary["args"]["query"] == "Lin"
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assert primary["args"]["year_from"] == 2024
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assert primary["args"]["year_to"] == 2024
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def test_query_plan_content_prefers_retrieve() -> None:
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plan = build_query_plan("galvanotaxis", "content")
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assert plan["query_class"] == "content_term"
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assert plan["recommended_primary"]["command"] == "retrieve"
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assert any(step["action"] == "interactive_fulltext_fallback" for step in plan["fallback_plan"])
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def test_query_plan_runtime_enrichment_without_retrieve(monkeypatch: pytest.MonkeyPatch, tmp_path: Path, capsys: pytest.CaptureFixture[str]) -> None:
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monkeypatch.setattr(
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"paperforge.commands.query_plan.enrich_query_plan_with_runtime",
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lambda plan, vault: {
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**plan,
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"runtime": {"retrieve_available": False, "vector_status": {"db_exists": False, "chunk_count": 0, "healthy": True, "error": ""}},
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"scope_assessment": {
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"source": "library",
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"label": "full library",
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"estimated_paper_count": 120,
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"fulltext_ready_count": 80,
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"recommended_mode": "ask_user_before_broad_grep",
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},
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"interactive_fallback_required": True,
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"suggested_modes": [
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{"mode": "ask_for_scope_limit", "description": "Ask first."},
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{"mode": "fulltext_rg_or_grep", "description": "Search fulltext."},
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],
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},
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)
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args = _Args("galvanotaxis", "content", tmp_path)
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assert query_plan_run(args) == 0
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out = capsys.readouterr().out
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assert '"interactive_fallback_required": true' in out.lower()
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assert '"mode": "ask_for_scope_limit"' in out
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def test_query_plan_discover_prefers_context_for_known_domain(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None:
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plan = build_query_plan("骨科 里有什么", "discover")
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monkeypatch.setattr("paperforge.embedding.get_embed_status", lambda vault: {"db_exists": False, "chunk_count": 0, "healthy": True, "error": ""})
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monkeypatch.setattr(
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"paperforge.worker.asset_index.read_index",
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lambda vault: {"items": [{"domain": "骨科", "lifecycle": "fulltext_ready", "collections": []} for _ in range(5)]},
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)
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enriched = enrich_query_plan_with_runtime(plan, tmp_path)
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assert enriched["recommended_primary"]["command"] == "context"
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assert enriched["recommended_primary"]["args"]["domain"] == "骨科"
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