e8f00fcff4
haiku.rag.config exported two configuration instances: the lazy _config behind get_config/set_config, and Config, loaded at import time. Nothing linked them, and eleven signatures captured Config as a default argument, so set_config could not reach the factories, the client, the store or the MCP server. reranking/base.py went further and snapshotted the configured reranker name into a class attribute at import. Config is removed. Internal defaults are config: AppConfig | None = None, resolved through get_config() per call. RerankerBase._model is None and CohereReranker takes its model name as an argument, like every other reranker. The suite patched attributes on Config while production read the instance get_config() returns, a different object, so those patches were no-ops waiting to happen. They now go through get_config().
124 lines
4.5 KiB
Python
124 lines
4.5 KiB
Python
import asyncio
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import pytest
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import haiku.rag.client as client_mod
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from haiku.rag.client import HaikuRAG
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from haiku.rag.client.documents import _refresh_doc_metadata
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from haiku.rag.config import get_config
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from haiku.rag.store.models.chunk import Chunk
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def _docling_doc(name: str, text: str):
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from docling_core.types.doc.document import DoclingDocument
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from docling_core.types.doc.labels import DocItemLabel
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doc = DoclingDocument(name=name)
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doc.add_text(label=DocItemLabel.TEXT, text=text)
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return doc
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@pytest.mark.asyncio
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async def test_schedule_vacuum_is_debounced(temp_db_path, monkeypatch):
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"""Rapid writes within the throttle window schedule only one background
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vacuum; once the interval elapses, a new one is scheduled."""
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t = {"now": 1000.0}
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monkeypatch.setattr(client_mod, "monotonic", lambda: t["now"])
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async with HaikuRAG(temp_db_path, create=True) as client:
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calls: list[int] = []
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async def fake_vacuum(*_a, **_k):
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calls.append(1)
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monkeypatch.setattr(client.store, "vacuum", fake_vacuum)
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for _ in range(3):
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client._schedule_vacuum()
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await asyncio.gather(*client._vacuum_tasks)
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assert len(calls) == 1 # debounced within the interval
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t["now"] += client_mod._VACUUM_MIN_INTERVAL_S + 1
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client._schedule_vacuum()
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await asyncio.gather(*client._vacuum_tasks)
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assert len(calls) == 2 # interval elapsed -> a new vacuum scheduled
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@pytest.mark.asyncio
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async def test_debounced_writes_still_collapse_on_close(temp_db_path, monkeypatch):
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"""Even when scheduled vacuums after the first are debounced, the writes are
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marked dirty so the close-time drain runs a final collapse."""
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t = {"now": 1000.0}
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monkeypatch.setattr(client_mod, "monotonic", lambda: t["now"])
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calls: list[int] = []
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async with HaikuRAG(temp_db_path, create=True) as client:
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async def fake_vacuum(*_a, **_k):
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calls.append(1)
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monkeypatch.setattr(client.store, "vacuum", fake_vacuum)
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client._schedule_vacuum() # schedules the first background pass
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client._schedule_vacuum() # debounced (no task)
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await client._await_vacuum_tasks()
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# one scheduled background pass + one final collapse on drain
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assert len(calls) == 2
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assert client._vacuum_dirty is False
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@pytest.mark.asyncio
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async def test_metadata_refresh_sweep_schedules_vacuum(temp_db_path):
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"""A source re-sweep that only rolls source_revision (MD5/revision
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short-circuit) writes document_meta and must still schedule the (debounced)
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vacuum, so that tiny churn gets reclaimed instead of accumulating."""
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dim = get_config().embeddings.model.vector_dim
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async with HaikuRAG(temp_db_path, create=True) as client:
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doc = await client.import_document(
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_docling_doc("d", "body"),
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[Chunk(content="body", embedding=[0.1] * dim, order=0)],
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uri="mem://sweep",
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metadata={"source_revision": "r1"},
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)
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# Isolate the refresh: the import already scheduled a vacuum.
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client._vacuum_dirty = False
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await _refresh_doc_metadata(
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client,
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doc,
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title=None,
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user_metadata={},
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source_metadata={"source_revision": "r2", "md5": "same"},
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)
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assert client._vacuum_dirty is True
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@pytest.mark.asyncio
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async def test_metadata_refresh_waits_for_write_lock(temp_db_path):
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"""The revision/MD5 short-circuit write serializes with other writers so
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it cannot land inside another writer's critical section (e.g. between
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create_tag's version snapshot and its per-table tag creation)."""
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dim = get_config().embeddings.model.vector_dim
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async with HaikuRAG(temp_db_path, create=True) as client:
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doc = await client.import_document(
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_docling_doc("d", "body"),
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[Chunk(content="body", embedding=[0.1] * dim, order=0)],
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uri="mem://sweep",
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metadata={"source_revision": "r1"},
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)
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async with client.store._write_lock:
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task = asyncio.create_task(
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_refresh_doc_metadata(
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client,
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doc,
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title=None,
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user_metadata={},
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source_metadata={"source_revision": "r2", "md5": "same"},
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)
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)
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await asyncio.sleep(0.1)
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assert not task.done()
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refreshed = await task
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assert refreshed.metadata["source_revision"] == "r2"
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