Two changes that belong together:
1. builder.build_context() now passes project_hint into retrieve(),
so the project-aware boost actually fires for the retrieval pipeline
driven by /context/build. Before this, only direct /query callers
benefited from the registered-project boost.
2. retriever now applies two more ranking signals on every chunk:
- _query_match_boost: boosts chunks whose source/title/heading
echo high-signal query tokens (stop list filters out generic
words like "the", "project", "system")
- _path_signal_boost: down-weights archival noise (_archive,
_history, pre-cleanup, reviews) by 0.72 and up-weights current
high-signal docs (status, decision, requirements, charter,
system-map, error-budget, ...) by 1.18
Tests:
- test_context_builder_passes_project_hint_to_retrieval verifies
the wiring fix
- test_retrieve_downranks_archive_noise_and_prefers_high_signal_paths
verifies the new ranking helpers prefer current docs over archive
This addresses the cross-project competition and archive bleed
called out in current-state.md after the Wave 1 ingestion.
176 lines
6.3 KiB
Python
176 lines
6.3 KiB
Python
"""Tests for the retrieval system."""
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from atocore.ingestion.pipeline import ingest_file
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from atocore.models.database import get_connection, init_db
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from atocore.retrieval.retriever import retrieve
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from atocore.retrieval.vector_store import get_vector_store
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def test_retrieve_returns_results(tmp_data_dir, sample_markdown):
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"""Test that retrieval returns relevant chunks."""
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init_db()
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ingest_file(sample_markdown)
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results = retrieve("What are the memory types?", top_k=5)
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assert len(results) > 0
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assert all(r.score > 0 for r in results)
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assert all(r.content for r in results)
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def test_retrieve_scores_ranked(tmp_data_dir, sample_markdown):
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"""Test that results are ranked by score."""
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init_db()
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ingest_file(sample_markdown)
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results = retrieve("architecture layers", top_k=5)
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if len(results) >= 2:
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scores = [r.score for r in results]
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assert scores == sorted(scores, reverse=True)
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def test_vector_store_count(tmp_data_dir, sample_markdown):
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"""Test that vector store tracks chunk count."""
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init_db()
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# Reset singleton for clean test
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import atocore.retrieval.vector_store as vs
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vs._store = None
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ingest_file(sample_markdown)
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store = get_vector_store()
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assert store.count > 0
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def test_retrieve_skips_stale_vector_entries(tmp_data_dir, sample_markdown, monkeypatch):
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"""Retriever should ignore vector hits whose chunk rows no longer exist."""
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init_db()
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ingest_file(sample_markdown)
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with get_connection() as conn:
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chunk_ids = [row["id"] for row in conn.execute("SELECT id FROM source_chunks").fetchall()]
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class FakeStore:
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def query(self, query_embedding, top_k=10, where=None):
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return {
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"ids": [[chunk_ids[0], "missing-chunk"]],
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"documents": [["valid doc", "stale doc"]],
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"metadatas": [[
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{"heading_path": "Overview", "source_file": "valid.md", "tags": "[]", "title": "Valid", "document_id": "doc-1"},
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{"heading_path": "Ghost", "source_file": "ghost.md", "tags": "[]", "title": "Ghost", "document_id": "doc-2"},
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]],
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"distances": [[0.1, 0.2]],
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}
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monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
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monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
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results = retrieve("overview", top_k=2)
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assert len(results) == 1
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assert results[0].chunk_id == chunk_ids[0]
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def test_retrieve_project_hint_boosts_matching_chunks(monkeypatch):
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class FakeStore:
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def query(self, query_embedding, top_k=10, where=None):
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return {
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"ids": [["chunk-a", "chunk-b"]],
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"documents": [["project doc", "other doc"]],
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"metadatas": [[
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{
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"heading_path": "Overview",
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"source_file": "p04-gigabit/pkm/_index.md",
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"tags": '["p04-gigabit"]',
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"title": "P04",
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"document_id": "doc-a",
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},
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{
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"heading_path": "Overview",
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"source_file": "p05-interferometer/pkm/_index.md",
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"tags": '["p05-interferometer"]',
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"title": "P05",
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"document_id": "doc-b",
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},
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]],
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"distances": [[0.3, 0.25]],
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}
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monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
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monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
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monkeypatch.setattr(
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"atocore.retrieval.retriever._existing_chunk_ids",
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lambda chunk_ids: set(chunk_ids),
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)
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monkeypatch.setattr(
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"atocore.retrieval.retriever.get_registered_project",
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lambda project_name: type(
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"Project",
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(),
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{
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"project_id": "p04-gigabit",
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"aliases": ("p04", "gigabit"),
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"ingest_roots": (),
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},
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)(),
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)
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results = retrieve("mirror architecture", top_k=2, project_hint="p04")
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assert len(results) == 2
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assert results[0].chunk_id == "chunk-a"
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assert results[0].score > results[1].score
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def test_retrieve_downranks_archive_noise_and_prefers_high_signal_paths(monkeypatch):
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class FakeStore:
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def query(self, query_embedding, top_k=10, where=None):
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return {
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"ids": [["chunk-archive", "chunk-requirements"]],
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"documents": [["archive doc", "requirements doc"]],
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"metadatas": [[
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{
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"heading_path": "History",
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"source_file": "p05-interferometer/pkm/_archive/old/Error-Budget.md",
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"tags": '["p05-interferometer"]',
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"title": "Old Error Budget",
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"document_id": "doc-a",
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},
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{
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"heading_path": "Overview",
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"source_file": "p05-interferometer/pkm/Requirements/Error-Budget.md",
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"tags": '["p05-interferometer"]',
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"title": "Error Budget",
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"document_id": "doc-b",
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},
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]],
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"distances": [[0.2, 0.24]],
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}
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monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
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monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
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monkeypatch.setattr(
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"atocore.retrieval.retriever._existing_chunk_ids",
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lambda chunk_ids: set(chunk_ids),
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)
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monkeypatch.setattr(
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"atocore.retrieval.retriever.get_registered_project",
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lambda project_name: type(
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"Project",
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(),
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{
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"project_id": "p05-interferometer",
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"aliases": ("p05", "interferometer"),
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"ingest_roots": (),
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},
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)(),
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)
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results = retrieve(
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"interferometer error budget vendor constraints",
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top_k=2,
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project_hint="p05-interferometer",
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)
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assert len(results) == 2
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assert results[0].chunk_id == "chunk-requirements"
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assert results[0].score > results[1].score
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