Module 5 phase 4 step 1 (docs/kb/modules/05-faza4-plan.md, §4): first user-facing HTTP entry point to the KB. FastAPI wrapping kb_retrieval.cascade_query/flat_query — GET /search (query_text -> embed via Ollama@SOLARIA -> cascade/flat -> envelope join -> JSON with per-source links) and GET /healthz. Search API only, no answer synthesis (phase 5) and no server-side dist filtering — the 0.45/0.55 colour thresholds are a frontend concern (plan §7, a later step). Hard startup invariant (plan §2 decision 2): refuses to start unless the configured EMBED_MODEL is present in both document_chunk.model and document_summary.embedding_model. Note the latter: document_summary.model is the LLM that *wrote* the summary (claude-haiku-4-5/gemma3:12b), not the embedder — checked live against kb-postgres@PIHA before writing this, see app/startup.py's docstring. Verified end-to-end with a live docker run: the invariant crash-loops on a mismatched EMBED_MODEL and passes through to a real /search hit against the live corpus with a correct model. Repo-only: no deploy, no npm/OIDC/DNS wiring (plan §8, later step), no local embed fallback (plan §5, later step) — Ollama@SOLARIA is called directly and a failure surfaces as 503, not a crash. Also: scripts/deploy/deploy.sh's gate now builds each service via `docker compose build` instead of a raw `docker build <svc_dir>`, so a service whose docker-compose.yml declares a repo-root build context (needed here to COPY packages/kb-retrieval/, the packages/ Dockerfile convention already documented in CLAUDE.md) resolves the same way in the gate as it does at real deploy time (deploy-node.sh's `docker compose ... up --build`). No behavior change for existing single-context services — verified against llm-gateway's compose file. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
164 lines
6.4 KiB
Python
164 lines
6.4 KiB
Python
"""Unit tests for /search's core logic (app.search.run_search) -- no real DB, no real Ollama.
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Same mocking style as packages/kb-retrieval/tests/test_retrieval.py, extended with an
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`envelope` table fixture for the join app/db.py adds on top of kb_retrieval."""
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from __future__ import annotations
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import pathlib
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import sys
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sys.path.insert(0, str(pathlib.Path(__file__).resolve().parents[1]))
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from app.search import run_search # noqa: E402
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class _FakeConn:
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"""summaries: [(envelope_id, dist), ...]. chunks_by_envelope: envelope_id -> [(chunk_index,
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text, dist), ...]. envelopes: envelope_id -> {"source": ..., "entities": [...]}."""
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def __init__(self, summaries=None, chunks_by_envelope=None, envelopes=None):
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self._summaries = list(summaries or [])
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self._chunks_by_envelope = chunks_by_envelope or {}
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self._envelopes = envelopes or {}
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async def fetch(self, query, *params):
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if "FROM document_summary" in query:
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_, _model, limit = params
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return [{"envelope_id": eid, "dist": dist} for eid, dist in self._summaries[:limit]]
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if "FROM document_chunk" in query and "= ANY" in query:
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_, envelope_ids, limit = params
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rows = [
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{"envelope_id": eid, "chunk_index": idx, "text": text, "dist": dist}
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for eid in envelope_ids
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for idx, text, dist in self._chunks_by_envelope.get(eid, [])
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]
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rows.sort(key=lambda r: r["dist"])
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return rows[:limit]
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if "FROM document_chunk" in query: # flat path
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_, limit = params
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rows = [
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{"envelope_id": eid, "chunk_index": idx, "text": text, "dist": dist}
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for eid, chunk_list in self._chunks_by_envelope.items()
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for idx, text, dist in chunk_list
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]
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rows.sort(key=lambda r: r["dist"])
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return rows[:limit]
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if "FROM envelope" in query:
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(envelope_ids,) = params
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return [
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{"id": eid, "source": self._envelopes[eid]["source"], "entities": self._envelopes[eid]["entities"]}
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for eid in envelope_ids
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if eid in self._envelopes
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]
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raise AssertionError(f"unexpected query: {query}")
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class _FakeEmbedResponse:
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def __init__(self, payload):
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self._payload = payload
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async def __aenter__(self):
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return self
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async def __aexit__(self, *exc):
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return False
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def raise_for_status(self):
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pass
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async def json(self):
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return self._payload
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class _FakeSession:
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def __init__(self):
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self.post_calls: list[dict] = []
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def post(self, url, json):
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self.post_calls.append({"url": url, "json": json})
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return _FakeEmbedResponse({"embedding": [0.01] * 1024})
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class TestRunSearchHappyPath:
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async def test_cascade_hit_joins_envelope_and_shapes_paperless_link(self):
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conn = _FakeConn(
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summaries=[("paperless:119", 0.1)],
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chunks_by_envelope={"paperless:119": [(2, "hit text", 0.34)]},
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envelopes={"paperless:119": {"source": "paperless", "entities": []}},
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)
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session = _FakeSession()
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result = await run_search(
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conn, session, "http://fake-ollama", "polisa PZU", "cascade", "bge-m3", "claude-haiku-4-5"
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)
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assert result["query"] == "polisa PZU"
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assert result["mode"] == "cascade"
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assert result["sol_status"] == "up"
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assert len(result["results"]) == 1
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hit = result["results"][0]
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assert hit["envelope_id"] == "paperless:119"
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assert hit["source"] == "paperless"
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assert hit["dist"] == 0.34
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assert hit["chunk_index"] == 2
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assert hit["text"] == "hit text"
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assert hit["link"] == "https://paper.kapala.org/documents/119/details"
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async def test_flat_mode_skips_cascade_stage1(self):
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conn = _FakeConn(
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chunks_by_envelope={"paperless:1": [(0, "a", 0.2)]},
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envelopes={"paperless:1": {"source": "paperless", "entities": []}},
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)
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session = _FakeSession()
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result = await run_search(
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conn, session, "http://fake-ollama", "q", "flat", "bge-m3", "claude-haiku-4-5"
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)
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assert result["mode"] == "flat"
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assert len(result["results"]) == 1
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async def test_gmail_hit_carries_header_metadata_not_a_link(self):
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conn = _FakeConn(
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summaries=[("<msgid@example.com>", 0.1)],
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chunks_by_envelope={"<msgid@example.com>": [(0, "body text", 0.4)]},
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envelopes={
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"<msgid@example.com>": {
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"source": "gmail",
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"entities": [
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{"type": "headers", "from": {"name": "A", "address": "a@b.com"}, "subject": "s", "date_raw": "d"}
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],
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}
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},
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)
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session = _FakeSession()
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result = await run_search(
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conn, session, "http://fake-ollama", "q", "cascade", "bge-m3", "claude-haiku-4-5"
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)
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hit = result["results"][0]
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assert hit["source"] == "gmail"
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assert hit["subject"] == "s"
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assert hit["link"] is None
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assert hit["mail_ui_url"] is None
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class TestRunSearchNoGoodResults:
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async def test_results_above_no_answer_threshold_are_still_returned_unfiltered(self):
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# Plan §7: the 0.55 "no answer" colour threshold is a frontend concern -- the API
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# must not silently drop/hide a poor match, only report its true dist so the caller
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# (UI or eval harness) can apply that policy itself.
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conn = _FakeConn(
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summaries=[("paperless:1", 0.6)],
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chunks_by_envelope={"paperless:1": [(0, "unrelated text", 0.62)]},
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envelopes={"paperless:1": {"source": "paperless", "entities": []}},
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)
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session = _FakeSession()
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result = await run_search(
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conn, session, "http://fake-ollama", "unrelated query", "cascade", "bge-m3", "claude-haiku-4-5"
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)
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assert len(result["results"]) == 1
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assert result["results"][0]["dist"] == 0.62
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async def test_no_summaries_yields_empty_results_not_an_error(self):
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conn = _FakeConn(summaries=[], chunks_by_envelope={}, envelopes={})
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session = _FakeSession()
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result = await run_search(
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conn, session, "http://fake-ollama", "nothing matches", "cascade", "bge-m3", "claude-haiku-4-5"
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)
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assert result["results"] == []
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