Add project-aware boost to raw query
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@@ -88,6 +88,7 @@ class QueryRequest(BaseModel):
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prompt: str
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top_k: int = 10
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filter_tags: list[str] | None = None
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project: str | None = None
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class QueryResponse(BaseModel):
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@@ -258,7 +259,12 @@ def api_refresh_project(project_name: str, purge_deleted: bool = False) -> Proje
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def api_query(req: QueryRequest) -> QueryResponse:
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"""Retrieve relevant chunks for a prompt."""
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try:
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chunks = retrieve(req.prompt, top_k=req.top_k, filter_tags=req.filter_tags)
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chunks = retrieve(
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req.prompt,
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top_k=req.top_k,
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filter_tags=req.filter_tags,
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project_hint=req.project,
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)
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except Exception as e:
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log.error("query_failed", prompt=req.prompt[:100], error=str(e))
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raise HTTPException(status_code=500, detail=f"Query failed: {e}")
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@@ -6,6 +6,7 @@ from dataclasses import dataclass
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import atocore.config as _config
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from atocore.models.database import get_connection
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from atocore.observability.logger import get_logger
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from atocore.projects.registry import get_registered_project
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from atocore.retrieval.embeddings import embed_query
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from atocore.retrieval.vector_store import get_vector_store
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@@ -28,6 +29,7 @@ def retrieve(
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query: str,
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top_k: int | None = None,
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filter_tags: list[str] | None = None,
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project_hint: str | None = None,
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) -> list[ChunkResult]:
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"""Retrieve the most relevant chunks for a query."""
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top_k = top_k or _config.settings.context_top_k
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@@ -71,6 +73,9 @@ def retrieve(
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meta = results["metadatas"][0][i] if results["metadatas"] else {}
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content = results["documents"][0][i] if results["documents"] else ""
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if project_hint:
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score *= _project_match_boost(project_hint, meta)
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chunks.append(
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ChunkResult(
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chunk_id=chunk_id,
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@@ -85,6 +90,8 @@ def retrieve(
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)
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duration_ms = int((time.time() - start) * 1000)
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chunks.sort(key=lambda chunk: chunk.score, reverse=True)
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log.info(
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"retrieval_done",
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query=query[:100],
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@@ -96,6 +103,35 @@ def retrieve(
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return chunks
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def _project_match_boost(project_hint: str, metadata: dict) -> float:
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"""Return a project-aware relevance multiplier for raw retrieval."""
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hint_lower = project_hint.strip().lower()
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if not hint_lower:
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return 1.0
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source_file = str(metadata.get("source_file", "")).lower()
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title = str(metadata.get("title", "")).lower()
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tags = str(metadata.get("tags", "")).lower()
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searchable = " ".join([source_file, title, tags])
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project = get_registered_project(project_hint)
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candidate_names = {hint_lower}
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if project is not None:
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candidate_names.add(project.project_id.lower())
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candidate_names.update(alias.lower() for alias in project.aliases)
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candidate_names.update(
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source_ref.subpath.replace("\\", "/").strip("/").split("/")[-1].lower()
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for source_ref in project.ingest_roots
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if source_ref.subpath.strip("/\\")
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)
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for candidate in candidate_names:
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if candidate and candidate in searchable:
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return 2.0
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return 1.0
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def _existing_chunk_ids(chunk_ids: list[str]) -> set[str]:
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"""Filter out stale vector entries whose chunk rows no longer exist."""
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if not chunk_ids:
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@@ -393,3 +393,26 @@ def test_project_update_endpoint_rejects_collisions(tmp_data_dir, monkeypatch):
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assert response.status_code == 400
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assert "collisions" in response.json()["detail"]
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def test_query_endpoint_accepts_project_hint(monkeypatch):
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def fake_retrieve(prompt, top_k=10, filter_tags=None, project_hint=None):
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assert prompt == "architecture"
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assert top_k == 3
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assert project_hint == "p04-gigabit"
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return []
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monkeypatch.setattr("atocore.api.routes.retrieve", fake_retrieve)
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client = TestClient(app)
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response = client.post(
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"/query",
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json={
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"prompt": "architecture",
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"top_k": 3,
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"project": "p04-gigabit",
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},
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)
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assert response.status_code == 200
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assert response.json()["results"] == []
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@@ -67,3 +67,54 @@ def test_retrieve_skips_stale_vector_entries(tmp_data_dir, sample_markdown, monk
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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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