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The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
535 lines
23 KiB
Python
535 lines
23 KiB
Python
"""Re-embed script: CLI contract, orchestration, and the FAISS rebuild path."""
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from unittest.mock import MagicMock, patch
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import pytest
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from docsgpt.scripts import reembed
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def paginating_cursor(chunk_rows, *, graph_rows=(), graph_table=("graph_nodes",)):
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"""A cursor answering the reads ``reembed_pgvector`` issues, from memory.
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The chunk read is paginated by keyset, so a cursor that returns the same
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page for every ``fetchall`` never terminates. Returns the cursor and the
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mutable table backing it.
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Args:
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chunk_rows: ``(id, text)`` rows for the source's chunk table.
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graph_rows: ``(id, name)`` rows for ``graph_nodes``.
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graph_table: What ``to_regclass`` reports; ``(None,)`` for absent.
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Returns:
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``(cursor, tables)``, where ``tables["chunks"]`` and
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``tables["graph"]`` can be reassigned to change what is served.
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"""
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tables = {"chunks": list(chunk_rows), "graph": list(graph_rows)}
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pending = {"rows": []}
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cursor = MagicMock()
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def execute(query, params=None):
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text = str(query)
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if "to_regclass" in text:
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pending["rows"] = [graph_table]
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elif "FROM graph_nodes" in text:
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pending["rows"] = list(tables["graph"])
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elif "count(*)" in text:
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pending["rows"] = [(len(tables["chunks"]),)]
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elif "id > %s" in text:
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_, after_id, limit = params
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pending["rows"] = [r for r in tables["chunks"] if r[0] > after_id][:limit]
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else:
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pending["rows"] = list(tables["chunks"])[: params[1]]
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cursor.execute.side_effect = execute
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cursor.fetchall.side_effect = lambda: pending["rows"]
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cursor.fetchone.side_effect = lambda: pending["rows"][0] if pending["rows"] else None
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return cursor, tables
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class TestCLI:
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def test_defaults(self):
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args = reembed.build_parser().parse_args([])
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assert args.dry_run is False
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assert args.sources is None
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assert args.batch_size == reembed.DEFAULT_BATCH_SIZE
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def test_unsupported_store_exits_without_touching_anything(self):
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with patch.object(reembed.settings, "VECTOR_STORE", "qdrant", create=True):
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with patch.object(reembed, "run") as run:
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assert reembed.main([]) == 2
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run.assert_not_called()
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def test_supported_stores_are_pgvector_and_faiss(self):
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assert set(reembed.SUPPORTED_STORES) == {"pgvector", "faiss"}
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def test_sources_are_split_and_trimmed(self):
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with patch.object(reembed.settings, "VECTOR_STORE", "faiss", create=True):
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with patch.object(reembed, "run", return_value=0) as run:
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reembed.main(["--sources", " a , b ,, c "])
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assert run.call_args.args[1] == ["a", "b", "c"]
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def test_batch_size_is_clamped_to_at_least_one(self):
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with patch.object(reembed.settings, "VECTOR_STORE", "faiss", create=True):
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with patch.object(reembed, "run", return_value=0) as run:
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reembed.main(["--batch-size", "0"])
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assert run.call_args.args[2] == 1
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class TestRun:
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def test_no_sources_is_a_clean_exit(self):
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with patch.object(reembed, "list_source_ids", return_value=[]):
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assert reembed.run("faiss", None, 8, False) == 0
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def test_processes_every_discovered_source(self):
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with patch.object(reembed, "list_source_ids", return_value=["a", "b"]):
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with patch.object(reembed, "reembed_faiss", return_value=(3, 3)) as handler:
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assert reembed.run("faiss", None, 8, False) == 0
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assert [call.args[0] for call in handler.call_args_list] == ["a", "b"]
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def test_explicit_sources_skip_discovery(self):
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with patch.object(reembed, "list_source_ids") as discover:
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with patch.object(reembed, "reembed_faiss", return_value=(1, 1)):
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reembed.run("faiss", ["only-this"], 8, False)
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discover.assert_not_called()
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def test_one_failing_source_does_not_stop_the_others(self):
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def handler(source_id, batch_size, dry_run):
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if source_id == "bad":
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raise RuntimeError("boom")
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return (1, 1)
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with patch.object(reembed, "reembed_faiss", side_effect=handler) as spy:
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code = reembed.run("faiss", ["good", "bad", "also-good"], 8, False)
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assert code == 1, "a failure must be reported in the exit code"
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assert spy.call_count == 3, "later sources must still be attempted"
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def test_dry_run_is_reported_as_success(self):
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with patch.object(reembed, "reembed_faiss", return_value=(5, 0)):
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assert reembed.run("faiss", ["a"], 8, True) == 0
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def test_pgvector_uses_the_pgvector_handler(self):
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with patch.object(reembed, "reembed_pgvector", return_value=(1, 1)) as handler:
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reembed.run("pgvector", ["a"], 8, False)
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handler.assert_called_once()
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class TestFaissRebuild:
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@pytest.fixture
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def stores(self):
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"""An existing store to read from and the rebuilt one written back."""
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existing = MagicMock()
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existing.get_chunks.return_value = [
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{"doc_id": "1", "text": "alpha", "metadata": {"i": 0}},
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{"doc_id": "2", "text": "beta", "metadata": {"i": 1}},
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]
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rebuilt = MagicMock()
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with patch.object(
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reembed.VectorCreator, "create_vectorstore", side_effect=[existing, rebuilt]
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) as factory:
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yield existing, rebuilt, factory
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def test_rebuilds_from_stored_text_and_saves(self, stores):
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existing, rebuilt, factory = stores
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seen, written = reembed.reembed_faiss("s1", batch_size=8, dry_run=False)
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assert (seen, written) == (2, 2)
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rebuilt.save_local.assert_called_once()
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docs = factory.call_args_list[1].kwargs["docs_init"]
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assert [d.page_content for d in docs] == ["alpha", "beta"]
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assert [d.metadata for d in docs] == [{"i": 0}, {"i": 1}]
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def test_embeddings_key_comes_from_settings(self, stores):
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"""A placeholder here is sent as the server's bearer token."""
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_, _, factory = stores
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with patch.object(reembed.settings, "EMBEDDINGS_KEY", "sk-real", create=True):
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reembed.reembed_faiss("s1", batch_size=8, dry_run=False)
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keys = [call.kwargs.get("embeddings_key") for call in factory.call_args_list]
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assert keys == ["sk-real", "sk-real"]
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def test_chunk_ids_are_preserved(self, stores):
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"""Re-embedding must not renumber chunks.
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Fresh ids orphan every GraphRAG ``graph_node_chunks`` row for the
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source and invalidate any id a client already holds.
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"""
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_, _, factory = stores
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reembed.reembed_faiss("s1", batch_size=8, dry_run=False)
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assert factory.call_args_list[1].kwargs["ids"] == ["1", "2"]
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def test_existing_index_is_opened_past_the_dimension_check(self, stores):
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"""A width change is the main reason to run this script.
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``assert_embedding_dimensions`` refuses to open an index whose width
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differs from the configured model -- and its error message recommends
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this script, so without the opt-out the advice failed on every source.
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The chunk text lives in the sidecar, so reading it needs no match.
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"""
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_, _, factory = stores
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reembed.reembed_faiss("s1", batch_size=8, dry_run=False)
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assert factory.call_args_list[0].kwargs["skip_dimension_check"] is True
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# The rebuild writes the new width, so it must still be checked.
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assert "skip_dimension_check" not in factory.call_args_list[1].kwargs
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def test_batch_size_is_forwarded_to_the_rebuild(self, stores):
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"""On a remote embeddings server the whole index is otherwise one POST."""
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_, _, factory = stores
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reembed.reembed_faiss("s1", batch_size=8, dry_run=False)
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assert factory.call_args_list[1].kwargs["batch_size"] == 8
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def test_existing_index_is_not_deleted(self, stores):
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"""The rebuild must not destroy the old index before the new one exists."""
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existing, rebuilt, _ = stores
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reembed.reembed_faiss("s1", batch_size=8, dry_run=False)
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existing.delete_index.assert_not_called()
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def test_dry_run_reads_but_never_rebuilds(self):
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existing = MagicMock()
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existing.get_chunks.return_value = [{"doc_id": "1", "text": "a", "metadata": {}}]
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with patch.object(
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reembed.VectorCreator, "create_vectorstore", return_value=existing
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) as factory:
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seen, written = reembed.reembed_faiss("s1", batch_size=8, dry_run=True)
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assert (seen, written) == (1, 0)
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assert factory.call_count == 1, "no rebuild store may be constructed"
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def test_empty_index_is_a_no_op(self):
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existing = MagicMock()
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existing.get_chunks.return_value = []
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with patch.object(
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reembed.VectorCreator, "create_vectorstore", return_value=existing
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):
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assert reembed.reembed_faiss("s1", batch_size=8, dry_run=False) == (0, 0)
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class TestPgvectorWithoutTheExtension:
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"""Mocked pgvector paths.
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The live tests in ``test_reembed_pgvector_live`` skip wherever the cluster
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has no pgvector build -- which includes CI -- so the SQL shape and the
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batching contract are pinned here too.
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"""
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@pytest.fixture
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def store(self):
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"""A store whose cursor serves the paginated reads, not a fixed page.
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``reembed_pgvector`` walks the source by keyset, so a cursor that
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returns the same rows for every ``fetchall`` never terminates. The fake
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answers each of the three queries the function issues from one in-memory
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table, which tests mutate through ``rows``.
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"""
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cursor, table = paginating_cursor([(1, "alpha"), (2, "beta"), (3, "gamma")])
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store = MagicMock()
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store._table_name = "documents"
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store._vector_column = "embedding"
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conn = MagicMock()
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conn.cursor.return_value = cursor
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store._get_connection.return_value = conn
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store._embedding.embed_documents.side_effect = lambda texts: [
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[0.5] * 4 for _ in texts
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]
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with patch.object(
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reembed.VectorCreator, "create_vectorstore", return_value=store
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), patch.object(reembed.settings, "GRAPHRAG_ENABLED", False):
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yield store, conn, cursor, table
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def test_reads_and_rewrites_every_chunk(self, store):
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_, conn, cursor, _ = store
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seen, written = reembed.reembed_pgvector("s1", batch_size=64, dry_run=False)
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assert (seen, written) == (3, 3)
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cursor.executemany.assert_called_once()
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conn.commit.assert_called()
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def test_pages_are_bounded_by_batch_size(self, store):
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"""The read is paginated, so a huge source never lands in memory at once."""
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_, _, cursor, table = store
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table["chunks"] = [(i, f"chunk-{i}") for i in range(1, 11)]
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seen, written = reembed.reembed_pgvector("s1", batch_size=3, dry_run=False)
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assert (seen, written) == (10, 10)
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selects = [
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call for call in cursor.execute.call_args_list
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if "SELECT id, text" in str(call.args[0])
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]
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# Four pages of at most 3, then one empty page to end the walk.
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assert len(selects) == 5
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assert all(call.args[1][-1] == 3 for call in selects)
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def test_dry_run_counts_without_reading_the_text(self, store):
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fake_store, _, cursor, _ = store
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seen, written = reembed.reembed_pgvector("s1", batch_size=64, dry_run=True)
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assert (seen, written) == (3, 0)
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fake_store._embedding.embed_documents.assert_not_called()
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cursor.executemany.assert_not_called()
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assert any(
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"count(*)" in str(call.args[0]) for call in cursor.execute.call_args_list
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)
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def test_batches_commit_separately(self, store):
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_, conn, cursor, _ = store
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reembed.reembed_pgvector("s1", batch_size=2, dry_run=False)
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# 3 rows at batch 2 is two write transactions.
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assert cursor.executemany.call_count == 2
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assert conn.commit.call_count == 2
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def test_failed_batch_rolls_back_and_raises(self, store):
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_, conn, cursor, _ = store
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cursor.executemany.side_effect = RuntimeError("write failed")
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with pytest.raises(RuntimeError):
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reembed.reembed_pgvector("s1", batch_size=64, dry_run=False)
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conn.rollback.assert_called_once()
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def test_connection_is_returned_even_on_failure(self, store):
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fake_store, _, cursor, _ = store
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cursor.executemany.side_effect = RuntimeError("boom")
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with pytest.raises(RuntimeError):
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reembed.reembed_pgvector("s1", batch_size=64, dry_run=False)
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fake_store.close.assert_called_once()
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def test_null_text_does_not_crash_the_embed_call(self, store):
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fake_store, _, _, table = store
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table["chunks"] = [(1, None), (2, "beta")]
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seen, written = reembed.reembed_pgvector("s1", batch_size=64, dry_run=False)
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assert (seen, written) == (2, 2)
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assert fake_store._embedding.embed_documents.call_args.args[0] == ["", "beta"]
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def test_empty_source_is_a_no_op(self, store):
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fake_store, _, _, table = store
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table["chunks"] = []
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assert reembed.reembed_pgvector("s1", batch_size=64, dry_run=False) == (0, 0)
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fake_store._embedding.embed_documents.assert_not_called()
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def test_source_discovery_returns_sorted_ids(self):
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store = MagicMock()
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store._table_name = "documents"
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cursor = MagicMock()
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cursor.fetchall.return_value = [("b",), ("a",)]
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conn = MagicMock()
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conn.cursor.return_value = cursor
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store._get_connection.return_value = conn
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with patch.object(
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reembed.VectorCreator, "create_vectorstore", return_value=store
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):
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assert reembed.list_source_ids("pgvector") == ["b", "a"]
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class TestFaissSourceDiscovery:
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def test_source_ids_come_from_index_directories(self):
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storage = MagicMock()
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storage.list_files.return_value = [
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"indexes/src-a/index.faiss",
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"indexes/src-a/index.pkl",
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"indexes/src-b/index.faiss",
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]
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with patch(
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"docsgpt.storage.storage_creator.StorageCreator.get_storage",
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return_value=storage,
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):
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assert reembed.list_source_ids("faiss") == ["src-a", "src-b"]
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def test_storage_failure_is_reported_as_a_usable_error(self):
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storage = MagicMock()
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storage.list_files.side_effect = OSError("permission denied")
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with patch(
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"docsgpt.storage.storage_creator.StorageCreator.get_storage",
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return_value=storage,
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):
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with pytest.raises(reembed.ReembedError, match="permission denied"):
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reembed.list_source_ids("faiss")
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def test_unsupported_store_error_names_the_alternatives(self):
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with patch.object(reembed.settings, "VECTOR_STORE", "milvus", create=True):
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assert reembed.main([]) == 2
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class TestGraphNodeReembedding:
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"""``graph_nodes.name_embedding`` seeds every graph traversal.
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It is written once at extraction time and never revisited, so rewriting
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only the chunk table leaves the graph seeding from the previous model --
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and since mpnet and granite-311m are both 768-dimensional, the column
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accepts the mismatch and nothing reports it.
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"""
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@pytest.fixture
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def graph(self):
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store = MagicMock()
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store._embedding.embed_documents.side_effect = lambda texts: [
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[0.5] * 4 for _ in texts
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]
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cursor = MagicMock()
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cursor.fetchone.return_value = ("graph_nodes",)
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cursor.fetchall.return_value = [
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("n1", "Alpha"),
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("n2", "Beta"),
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("n3", "Gamma"),
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]
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conn = MagicMock()
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conn.cursor.return_value = cursor
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return store, conn, cursor
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def test_rewrites_every_node_name(self, graph):
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store, conn, cursor = graph
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written = reembed.reembed_graph_nodes(
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store, conn, "s1", batch_size=64, dry_run=False
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)
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assert written == 3
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store._embedding.embed_documents.assert_called_once_with(
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["Alpha", "Beta", "Gamma"]
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)
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statement = cursor.executemany.call_args.args[0]
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assert "graph_nodes" in statement and "name_embedding" in statement
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conn.commit.assert_called()
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def test_dry_run_counts_without_embedding(self, graph):
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store, conn, cursor = graph
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assert reembed.reembed_graph_nodes(store, conn, "s1", 64, dry_run=True) == 3
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store._embedding.embed_documents.assert_not_called()
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cursor.executemany.assert_not_called()
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def test_missing_table_is_a_no_op(self, graph):
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store, conn, cursor = graph
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cursor.fetchone.return_value = (None,)
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assert reembed.reembed_graph_nodes(store, conn, "s1", 64, dry_run=False) == 0
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store._embedding.embed_documents.assert_not_called()
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def test_batches_commit_separately(self, graph):
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store, conn, cursor = graph
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reembed.reembed_graph_nodes(store, conn, "s1", batch_size=2, dry_run=False)
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assert cursor.executemany.call_count == 2
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assert conn.commit.call_count == 2
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def test_failed_batch_rolls_back_and_raises(self, graph):
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store, conn, cursor = graph
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cursor.executemany.side_effect = RuntimeError("write failed")
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with pytest.raises(RuntimeError, match="write failed"):
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reembed.reembed_graph_nodes(store, conn, "s1", 64, dry_run=False)
|
|
conn.rollback.assert_called_once()
|
|
|
|
def test_pgvector_run_skips_the_graph_when_disabled(self):
|
|
store, conn, cursor = self._pgvector_mocks()
|
|
with patch.object(
|
|
reembed.VectorCreator, "create_vectorstore", return_value=store
|
|
), patch.object(reembed.settings, "GRAPHRAG_ENABLED", False):
|
|
reembed.reembed_pgvector("s1", batch_size=64, dry_run=False)
|
|
assert not self._graph_statements(cursor)
|
|
|
|
def test_pgvector_run_reembeds_the_graph_when_enabled(self):
|
|
store, conn, cursor = self._pgvector_mocks()
|
|
with patch.object(
|
|
reembed.VectorCreator, "create_vectorstore", return_value=store
|
|
), patch.object(reembed.settings, "GRAPHRAG_ENABLED", True):
|
|
reembed.reembed_pgvector("s1", batch_size=64, dry_run=False)
|
|
assert self._graph_statements(cursor)
|
|
|
|
@staticmethod
|
|
def _pgvector_mocks():
|
|
cursor, _ = paginating_cursor(
|
|
[(1, "alpha"), (2, "beta")],
|
|
graph_rows=[("n1", "Alpha"), ("n2", "Beta")],
|
|
)
|
|
store = MagicMock()
|
|
store._table_name = "documents"
|
|
store._vector_column = "embedding"
|
|
conn = MagicMock()
|
|
conn.cursor.return_value = cursor
|
|
store._get_connection.return_value = conn
|
|
store._embedding.embed_documents.side_effect = lambda texts: [
|
|
[0.5] * 4 for _ in texts
|
|
]
|
|
return store, conn, cursor
|
|
|
|
@staticmethod
|
|
def _graph_statements(cursor):
|
|
return [
|
|
call
|
|
for call in cursor.executemany.call_args_list
|
|
if "graph_nodes" in str(call.args[0])
|
|
]
|
|
|
|
|
|
class TestEmbedsInProcess:
|
|
"""A batch job should not round-trip every chunk through the broker."""
|
|
|
|
def test_delegation_is_turned_off_for_the_run(self, monkeypatch):
|
|
from docsgpt.core.settings import settings
|
|
|
|
monkeypatch.setattr(settings, "EMBEDDINGS_DELEGATE_TO_WORKER", True, raising=False)
|
|
monkeypatch.setattr(settings, "VECTOR_STORE", "pgvector", raising=False)
|
|
seen = {}
|
|
with patch.object(reembed, "run", side_effect=lambda *a, **k: seen.setdefault(
|
|
"delegating", settings.EMBEDDINGS_DELEGATE_TO_WORKER
|
|
) or 0):
|
|
assert reembed.main(["--dry-run"]) == 0
|
|
assert seen["delegating"] is False
|
|
|
|
|
|
class TestRecordsTheModel:
|
|
"""``sources.model`` is what the boot mismatch check reads."""
|
|
|
|
def test_a_re_embedded_source_is_stamped(self, monkeypatch):
|
|
from docsgpt.core.settings import settings
|
|
|
|
monkeypatch.setattr(settings, "EMBEDDINGS_NAME", "new/model", raising=False)
|
|
conn = MagicMock()
|
|
session = MagicMock()
|
|
session.__enter__ = MagicMock(return_value=conn)
|
|
session.__exit__ = MagicMock(return_value=False)
|
|
with patch("docsgpt.storage.db.session.db_session", return_value=session):
|
|
reembed.record_source_model("src-1")
|
|
params = conn.execute.call_args.args[1]
|
|
assert params == {"model": "new/model", "id": "src-1"}
|
|
|
|
def test_a_dry_run_stamps_nothing(self, monkeypatch):
|
|
with patch.object(reembed, "record_source_model") as record, patch.object(
|
|
reembed, "list_source_ids", return_value=["a"]
|
|
), patch.object(reembed, "reembed_pgvector", return_value=(3, 0)):
|
|
reembed.run("pgvector", None, 64, True)
|
|
record.assert_not_called()
|
|
|
|
def test_a_real_run_stamps_each_source(self, monkeypatch):
|
|
with patch.object(reembed, "record_source_model") as record, patch.object(
|
|
reembed, "list_source_ids", return_value=["a", "b"]
|
|
), patch.object(reembed, "reembed_pgvector", return_value=(3, 3)):
|
|
reembed.run("pgvector", None, 64, False)
|
|
assert [c.args[0] for c in record.call_args_list] == ["a", "b"]
|
|
|
|
def test_a_failed_source_is_not_stamped(self):
|
|
with patch.object(reembed, "record_source_model") as record, patch.object(
|
|
reembed, "list_source_ids", return_value=["a"]
|
|
), patch.object(reembed, "reembed_pgvector", side_effect=RuntimeError("boom")):
|
|
assert reembed.run("pgvector", None, 64, False) == 1
|
|
record.assert_not_called()
|
|
|
|
|
|
class TestThePinIsResolved:
|
|
"""The script must embed with the model the installation is pinned to.
|
|
|
|
``resolve_embeddings_pin`` runs in ``docsgpt.app``, which this script
|
|
never imports. An install pinned in ``app_metadata`` with no
|
|
``EMBEDDINGS_NAME`` in the environment -- every stock Kubernetes
|
|
deployment, whose manifests carry no embedding config -- would otherwise
|
|
rewrite its whole index with the legacy code default and stamp
|
|
``sources.model`` to match, creating the cross-model index this script
|
|
exists to repair.
|
|
"""
|
|
|
|
def test_main_resolves_the_pin_before_reading_the_store(self):
|
|
order = []
|
|
with patch(
|
|
"docsgpt.storage.db.embeddings_pin.resolve_embeddings_pin",
|
|
side_effect=lambda *a, **k: order.append("pin"),
|
|
), patch.object(reembed.settings, "VECTOR_STORE", "pgvector", create=True), patch.object(
|
|
reembed, "run", side_effect=lambda *a, **k: (order.append("run"), 0)[1]
|
|
):
|
|
assert reembed.main([]) == 0
|
|
assert order == ["pin", "run"], "the pin must resolve before anything embeds"
|
|
|
|
def test_an_unsupported_store_still_resolved_the_pin_first(self):
|
|
with patch(
|
|
"docsgpt.storage.db.embeddings_pin.resolve_embeddings_pin"
|
|
) as pin, patch.object(reembed.settings, "VECTOR_STORE", "qdrant", create=True):
|
|
assert reembed.main([]) == 2
|
|
pin.assert_called_once()
|