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0fc6705173580f655cb981233c038fff089c6e9b
ATOCore/tests/test_retrieval.py

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feat: implement AtoCore Phase 0 + Phase 0.5 (foundation + PoC) Complete implementation of the personal context engine foundation: - FastAPI server with 5 endpoints (ingest, query, context/build, health, debug) - SQLite database with 5 tables (documents, chunks, memories, projects, interactions) - Heading-aware markdown chunker (800 char max, recursive splitting) - Multilingual embeddings via sentence-transformers (EN/FR) - ChromaDB vector store with cosine similarity retrieval - Context builder with project boosting, dedup, and budget enforcement - CLI scripts for batch ingestion and test prompt evaluation - 19 unit tests passing, 79% coverage - Validated on 482 real project files (8383 chunks, 0 errors) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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"""Tests for the retrieval system."""
from atocore.ingestion.pipeline import ingest_file
Stabilize core correctness and sync project plan state
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from atocore.models.database import get_connection, init_db
feat: implement AtoCore Phase 0 + Phase 0.5 (foundation + PoC) Complete implementation of the personal context engine foundation: - FastAPI server with 5 endpoints (ingest, query, context/build, health, debug) - SQLite database with 5 tables (documents, chunks, memories, projects, interactions) - Heading-aware markdown chunker (800 char max, recursive splitting) - Multilingual embeddings via sentence-transformers (EN/FR) - ChromaDB vector store with cosine similarity retrieval - Context builder with project boosting, dedup, and budget enforcement - CLI scripts for batch ingestion and test prompt evaluation - 19 unit tests passing, 79% coverage - Validated on 482 real project files (8383 chunks, 0 errors) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-05 09:21:27 -04:00
from atocore.retrieval.retriever import retrieve
from atocore.retrieval.vector_store import get_vector_store
def test_retrieve_returns_results(tmp_data_dir, sample_markdown):
"""Test that retrieval returns relevant chunks."""
init_db()
ingest_file(sample_markdown)
results = retrieve("What are the memory types?", top_k=5)
assert len(results) > 0
assert all(r.score > 0 for r in results)
assert all(r.content for r in results)
def test_retrieve_scores_ranked(tmp_data_dir, sample_markdown):
"""Test that results are ranked by score."""
init_db()
ingest_file(sample_markdown)
results = retrieve("architecture layers", top_k=5)
if len(results) >= 2:
scores = [r.score for r in results]
assert scores == sorted(scores, reverse=True)
def test_vector_store_count(tmp_data_dir, sample_markdown):
"""Test that vector store tracks chunk count."""
init_db()
# Reset singleton for clean test
import atocore.retrieval.vector_store as vs
vs._store = None
ingest_file(sample_markdown)
store = get_vector_store()
assert store.count > 0
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def test_retrieve_skips_stale_vector_entries(tmp_data_dir, sample_markdown, monkeypatch):
"""Retriever should ignore vector hits whose chunk rows no longer exist."""
init_db()
ingest_file(sample_markdown)
with get_connection() as conn:
chunk_ids = [row["id"] for row in conn.execute("SELECT id FROM source_chunks").fetchall()]
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [[chunk_ids[0], "missing-chunk"]],
"documents": [["valid doc", "stale doc"]],
"metadatas": [[
{"heading_path": "Overview", "source_file": "valid.md", "tags": "[]", "title": "Valid", "document_id": "doc-1"},
{"heading_path": "Ghost", "source_file": "ghost.md", "tags": "[]", "title": "Ghost", "document_id": "doc-2"},
]],
"distances": [[0.1, 0.2]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
results = retrieve("overview", top_k=2)
assert len(results) == 1
assert results[0].chunk_id == chunk_ids[0]
Add project-aware boost to raw query
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def test_retrieve_project_hint_boosts_matching_chunks(monkeypatch):
fix(retrieval): enforce project-scoped context boundaries
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target_project = type(
"Project",
(),
{
"project_id": "p04-gigabit",
"aliases": ("p04", "gigabit"),
"ingest_roots": (),
},
)()
other_project = type(
"Project",
(),
{
"project_id": "p05-interferometer",
"aliases": ("p05", "interferometer"),
"ingest_roots": (),
},
)()
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class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
fix(retrieval): enforce project-scoped context boundaries
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assert top_k == 8
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return {
"ids": [["chunk-a", "chunk-b"]],
"documents": [["project doc", "other doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p04-gigabit/pkm/_index.md",
"tags": '["p04-gigabit"]',
"title": "P04",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p05-interferometer/pkm/_index.md",
"tags": '["p05-interferometer"]',
"title": "P05",
"document_id": "doc-b",
},
]],
"distances": [[0.3, 0.25]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
fix(retrieval): enforce project-scoped context boundaries
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lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project, other_project],
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)
results = retrieve("mirror architecture", top_k=2, project_hint="p04")
fix(retrieval): enforce project-scoped context boundaries
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assert len(results) == 1
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assert results[0].chunk_id == "chunk-a"
fix(retrieval): enforce project-scoped context boundaries
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def test_retrieve_project_scope_allows_unowned_global_chunks(monkeypatch):
target_project = type(
"Project",
(),
{
"project_id": "p04-gigabit",
"aliases": ("p04", "gigabit"),
"ingest_roots": (),
},
)()
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [["chunk-a", "chunk-global"]],
"documents": [["project doc", "global doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p04-gigabit/pkm/_index.md",
"tags": '["p04-gigabit"]',
"title": "P04",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "shared/engineering-rules.md",
"tags": "[]",
"title": "Shared engineering rules",
"document_id": "doc-global",
},
]],
"distances": [[0.2, 0.21]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project],
)
results = retrieve("mirror architecture", top_k=2, project_hint="p04")
assert [r.chunk_id for r in results] == ["chunk-a", "chunk-global"]
def test_retrieve_project_scope_filter_can_be_disabled(monkeypatch):
target_project = type(
"Project",
(),
{
"project_id": "p04-gigabit",
"aliases": ("p04", "gigabit"),
"ingest_roots": (),
},
)()
other_project = type(
"Project",
(),
{
"project_id": "p05-interferometer",
"aliases": ("p05", "interferometer"),
"ingest_roots": (),
},
)()
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
assert top_k == 2
return {
"ids": [["chunk-a", "chunk-b"]],
"documents": [["project doc", "other project doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p04-gigabit/pkm/_index.md",
"tags": '["p04-gigabit"]',
"title": "P04",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p05-interferometer/pkm/_index.md",
"tags": '["p05-interferometer"]',
"title": "P05",
"document_id": "doc-b",
},
]],
"distances": [[0.2, 0.2]],
}
monkeypatch.setattr("atocore.config.settings.rank_project_scope_filter", False)
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project, other_project],
)
results = retrieve("mirror architecture", top_k=2, project_hint="p04")
assert {r.chunk_id for r in results} == {"chunk-a", "chunk-b"}
def test_retrieve_project_scope_ignores_title_for_ownership(monkeypatch):
target_project = type(
"Project",
(),
{
"project_id": "p04-gigabit",
"aliases": ("p04", "gigabit"),
"ingest_roots": (),
},
)()
other_project = type(
"Project",
(),
{
"project_id": "p06-polisher",
"aliases": ("p06", "polisher", "p11"),
"ingest_roots": (),
},
)()
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [["chunk-target", "chunk-poisoned-title"]],
"documents": [["p04 doc", "p06 doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p04-gigabit/pkm/_index.md",
"tags": '["p04-gigabit"]',
"title": "P04",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p06-polisher/pkm/architecture.md",
"tags": '["p06-polisher"]',
"title": "GigaBIT M1 mirror lessons",
"document_id": "doc-b",
},
]],
"distances": [[0.2, 0.19]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project, other_project],
)
results = retrieve("mirror architecture", top_k=2, project_hint="p04")
assert [r.chunk_id for r in results] == ["chunk-target"]
def test_retrieve_project_scope_uses_path_segments_not_substrings(monkeypatch):
target_project = type(
"Project",
(),
{
"project_id": "p05-interferometer",
"aliases": ("p05", "interferometer"),
"ingest_roots": (),
},
)()
abb_project = type(
"Project",
(),
{
"project_id": "abb-space",
"aliases": ("abb",),
"ingest_roots": (),
},
)()
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [["chunk-target", "chunk-global"]],
"documents": [["p05 doc", "global doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p05-interferometer/pkm/_index.md",
"tags": '["p05-interferometer"]',
"title": "P05",
"document_id": "doc-a",
},
{
"heading_path": "Abbreviation notes",
"source_file": "shared/cabbage-abbreviations.md",
"tags": "[]",
"title": "ABB-style abbreviations",
"document_id": "doc-global",
},
]],
"distances": [[0.2, 0.21]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project, abb_project],
)
results = retrieve("abbreviations", top_k=2, project_hint="p05")
assert [r.chunk_id for r in results] == ["chunk-target", "chunk-global"]
feat(retrieval): persist explicit chunk project ids
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def test_retrieve_project_scope_prefers_exact_project_id(monkeypatch):
target_project = type(
"Project",
(),
{
"project_id": "p04-gigabit",
"aliases": ("p04", "gigabit"),
"ingest_roots": (),
},
)()
other_project = type(
"Project",
(),
{
"project_id": "p06-polisher",
"aliases": ("p06", "polisher"),
"ingest_roots": (),
},
)()
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [["chunk-target", "chunk-other", "chunk-global"]],
"documents": [["target doc", "other doc", "global doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "legacy/unhelpful-path.md",
"tags": "[]",
"title": "Target",
"project_id": "p04-gigabit",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p04-gigabit/title-poisoned.md",
"tags": '["p04-gigabit"]',
"title": "Looks target-owned but is explicit p06",
"project_id": "p06-polisher",
"document_id": "doc-b",
},
{
"heading_path": "Overview",
"source_file": "shared/global.md",
"tags": "[]",
"title": "Shared",
"project_id": "",
"document_id": "doc-global",
},
]],
"distances": [[0.2, 0.19, 0.21]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project, other_project],
)
results = retrieve("mirror architecture", top_k=3, project_hint="p04")
assert [r.chunk_id for r in results] == ["chunk-target", "chunk-global"]
fix(retrieval): preserve project ids across unscoped ingest
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def test_retrieve_empty_project_id_falls_back_to_path_ownership(monkeypatch):
target_project = type(
"Project",
(),
{
"project_id": "p04-gigabit",
"aliases": ("p04", "gigabit"),
"ingest_roots": (),
},
)()
other_project = type(
"Project",
(),
{
"project_id": "p05-interferometer",
"aliases": ("p05", "interferometer"),
"ingest_roots": (),
},
)()
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [["chunk-target", "chunk-other"]],
"documents": [["target doc", "other doc"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p04-gigabit/status.md",
"tags": "[]",
"title": "Target",
"project_id": "",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p05-interferometer/status.md",
"tags": "[]",
"title": "Other",
"project_id": "",
"document_id": "doc-b",
},
]],
"distances": [[0.2, 0.19]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: target_project,
)
monkeypatch.setattr(
"atocore.retrieval.retriever.load_project_registry",
lambda: [target_project, other_project],
)
results = retrieve("mirror architecture", top_k=2, project_hint="p04")
assert [r.chunk_id for r in results] == ["chunk-target"]
fix(retrieval): enforce project-scoped context boundaries
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def test_retrieve_unknown_project_hint_does_not_widen_or_filter(monkeypatch):
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
assert top_k == 2
return {
"ids": [["chunk-a", "chunk-b"]],
"documents": [["doc a", "doc b"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "project-a/file.md",
"tags": "[]",
"title": "A",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "project-b/file.md",
"tags": "[]",
"title": "B",
"document_id": "doc-b",
},
]],
"distances": [[0.2, 0.21]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: None,
)
results = retrieve("overview", top_k=2, project_hint="unknown-project")
assert [r.chunk_id for r in results] == ["chunk-a", "chunk-b"]
fix: pass project_hint into retrieve and add path-signal ranking 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.
2026-04-06 18:37:07 -04:00
fix(retrieval): fail open on registry resolution errors
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def test_retrieve_fails_open_when_project_scope_resolution_fails(monkeypatch):
warnings = []
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
assert top_k == 2
return {
"ids": [["chunk-a", "chunk-b"]],
"documents": [["doc a", "doc b"]],
"metadatas": [[
{
"heading_path": "Overview",
"source_file": "p04-gigabit/file.md",
"tags": "[]",
"title": "A",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p05-interferometer/file.md",
"tags": "[]",
"title": "B",
"document_id": "doc-b",
},
]],
"distances": [[0.2, 0.21]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: (_ for _ in ()).throw(ValueError("registry overlap")),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.log.warning",
lambda event, **kwargs: warnings.append((event, kwargs)),
)
results = retrieve("overview", top_k=2, project_hint="p04")
assert [r.chunk_id for r in results] == ["chunk-a", "chunk-b"]
assert {warning[0] for warning in warnings} == {
"project_scope_resolution_failed",
"project_match_boost_resolution_failed",
}
assert all("registry overlap" in warning[1]["error"] for warning in warnings)
fix: pass project_hint into retrieve and add path-signal ranking 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.
2026-04-06 18:37:07 -04:00
def test_retrieve_downranks_archive_noise_and_prefers_high_signal_paths(monkeypatch):
class FakeStore:
def query(self, query_embedding, top_k=10, where=None):
return {
"ids": [["chunk-archive", "chunk-requirements"]],
"documents": [["archive doc", "requirements doc"]],
"metadatas": [[
{
"heading_path": "History",
"source_file": "p05-interferometer/pkm/_archive/old/Error-Budget.md",
"tags": '["p05-interferometer"]',
"title": "Old Error Budget",
"document_id": "doc-a",
},
{
"heading_path": "Overview",
"source_file": "p05-interferometer/pkm/Requirements/Error-Budget.md",
"tags": '["p05-interferometer"]',
"title": "Error Budget",
"document_id": "doc-b",
},
]],
"distances": [[0.2, 0.24]],
}
monkeypatch.setattr("atocore.retrieval.retriever.get_vector_store", lambda: FakeStore())
monkeypatch.setattr("atocore.retrieval.retriever.embed_query", lambda query: [0.0, 0.1])
monkeypatch.setattr(
"atocore.retrieval.retriever._existing_chunk_ids",
lambda chunk_ids: set(chunk_ids),
)
monkeypatch.setattr(
"atocore.retrieval.retriever.get_registered_project",
lambda project_name: type(
"Project",
(),
{
"project_id": "p05-interferometer",
"aliases": ("p05", "interferometer"),
"ingest_roots": (),
},
)(),
)
results = retrieve(
"interferometer error budget vendor constraints",
top_k=2,
project_hint="p05-interferometer",
)
assert len(results) == 2
assert results[0].chunk_id == "chunk-requirements"
assert results[0].score > results[1].score
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