refactor(usage): extract indexing metering helper; address review round 2

Round-2 claude-review findings:

- 🟡 Base-class recursion invariant: documented on embed_with_usage /
  embed_batch_with_usage that a provider overriding embed()/embed_batch() to
  delegate to the *_with_usage variant MUST also override that variant, or the
  two recurse. (No recursion today; the shipped providers pair the overrides.)
- 🟡 Processor metering had no unit test: extracted the two-event recording
  into a module-level record_indexing_usage() helper and added
  tests/unit/test_processor_metering.py (value mapping, flag/zero-chunk no-ops,
  best-effort failure swallowed).
- 🟡 SonarQube hotspots (python:S5332) were 3 http:// URLs in the new test
  fixtures (mock hosts, never contacted) blocking the quality gate
  (new_security_hotspots_reviewed). Switched them to https:// so no hotspot is
  raised.
- 🟢 Zero-chunk guard: record_indexing_usage() no-ops when chunk_count == 0, so
  an empty document no longer writes zero-value billing rows.

Deferred (stated on the PR): Mistral x.index-or-0 sort key (pre-existing,
equivalent), CHANGELOG note for the Ollama /api/embed switch (CHANGELOG is
commitizen-generated from commit bodies, which document it), class-var
query_token_count (safe under the per-request instance pattern).

Deck #67.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

nextcloud_mcp_server/providers/base.py

@@ -75,6 +75,12 @@ class Provider(ABC):
         usage from their embedding response override this. Used by the
         usage-metering hooks (Deck #67) to bill ``embeddings_queries`` by
         tokens rather than by operation count.
+
+        IMPORTANT (recursion invariant): this default calls ``self.embed``. A
+        provider that overrides ``embed()`` to delegate to ``embed_with_usage()``
+        (to avoid duplicating request logic) MUST also override this method, or
+        the two will call each other forever. The shipped providers that use
+        that delegation (Bedrock) do override both — keep that pairing.
         """
         embedding = await self.embed(text)
         return embedding, self._estimate_tokens([text])
@@ -86,6 +92,11 @@ class Provider(ABC):
 
         Returns ``(embeddings, token_count)``; the default estimates. See
         :meth:`embed_with_usage`.
+
+        IMPORTANT (recursion invariant): this default calls ``self.embed_batch``.
+        A provider that overrides ``embed_batch()`` to delegate to
+        ``embed_batch_with_usage()`` (Mistral, OpenAI, Ollama do) MUST also
+        override this method, or the two recurse infinitely. Keep the pairing.
         """
         embeddings = await self.embed_batch(texts)
         return embeddings, self._estimate_tokens(texts)

nextcloud_mcp_server/vector/processor.py

@@ -112,6 +112,65 @@ def should_use_page_aware(
     return page_aware_enabled and doc_type == "file" and bool(page_boundaries)
 
 
+async def record_indexing_usage(
+    *,
+    enabled: bool,
+    provider: str,
+    model: str,
+    doc_type: str,
+    user_id: str,
+    chunk_count: int,
+    token_count: int,
+    total_chars: int,
+) -> None:
+    """Record the two billable usage events for one embedded document.
+
+    ``pages_chunks`` is the volume (chunks embedded); ``embeddings_queries`` is
+    the embedding request's token count — the same metric search records, so the
+    meter bills embedding tokens whether they were incurred indexing a document
+    or embedding a query (Deck #67).
+
+    Best-effort and flag-gated: a metering failure is logged and never breaks
+    indexing. No-op when metering is disabled or the document produced no chunks
+    (an empty batch embeds nothing and would only write zero-value rows).
+
+    Privacy note: ``user_id`` stays tenant-local — the CP rollup aggregates
+    GROUP BY (day, metric) into ``usage_daily`` (no metadata column), so nothing
+    here reaches Stripe; it is retained only to keep Deck #67's future per-user
+    attribution derivable from the app DB without a re-migration.
+    """
+    if not enabled or chunk_count == 0:
+        return
+
+    metadata = {
+        "provider": provider,
+        "model": model,
+        "doc_type": doc_type,
+        "user_id": user_id,
+        "total_chars": total_chars,
+    }
+    try:
+        store = await UsageEventStore.shared()
+        # enabled=True: the guard above already confirmed the flag, so the store
+        # skips a second uncached Settings build per record (ADR-024).
+        await store.record_usage_event(
+            metric="pages_chunks", value=chunk_count, metadata=metadata, enabled=True
+        )
+        await store.record_usage_event(
+            metric="embeddings_queries",
+            value=token_count,
+            metadata=metadata,
+            enabled=True,
+        )
+    except Exception:
+        # Reached only when shared()/store construction itself raises
+        # (record_usage_event swallows its own write failures). Metering is on,
+        # so warn rather than hide the "enabled but no billing data" case.
+        logger.warning(
+            "usage metering hook (indexing embeddings) skipped", exc_info=True
+        )
+
+
 async def processor_task(
     worker_id: int,
     receive_stream: MemoryObjectReceiveStream[DocumentTask],
@@ -825,55 +884,21 @@ async def _index_document(
                 chunks=len(chunk_texts),
                 chars=total_chars,
             )
-            # Usage metering (Deck #67): record chunks embedded as a billable
-            # 'pages_chunks' event. Best-effort and gated on the flag so the
-            # off-path (OSS default) touches no storage; placed after the
-            # embedding succeeds so it can never affect the indexing path.
-            #
-            # Privacy note: user_id stays tenant-local — the CP rollup
-            # aggregates GROUP BY (day, metric) into usage_daily (no metadata
-            # column), so nothing here reaches Stripe; it is retained only to
-            # keep Deck #67's future per-user attribution derivable from the
-            # app DB without a re-migration.
-            if settings.usage_metering_enabled:
-                # Two billable events per indexed document: 'pages_chunks' is
-                # the volume (chunks embedded); 'embeddings_queries' is the
-                # token count of the embedding request — the same metric search
-                # records, so the meter bills embedding tokens whether they were
-                # incurred indexing a document or embedding a query (Deck #67).
-                metering_metadata = {
-                    "provider": provider,
-                    "model": settings.get_embedding_model_name(),
-                    "doc_type": doc_task.doc_type,
-                    "user_id": doc_task.user_id,
-                    "total_chars": total_chars,
-                }
-                try:
-                    store = await UsageEventStore.shared()
-                    await store.record_usage_event(
-                        metric="pages_chunks",
-                        value=len(chunk_texts),
-                        metadata=metering_metadata,
-                        # The outer guard already confirmed the flag, so pass
-                        # enabled=True directly — the store then skips a second
-                        # uncached Settings build here (ADR-024).
-                        enabled=True,
-                    )
-                    await store.record_usage_event(
-                        metric="embeddings_queries",
-                        value=embed_tokens,
-                        metadata=metering_metadata,
-                        enabled=True,
-                    )
-                except Exception:
-                    # Reached only when shared()/store construction itself
-                    # raises (record_usage_event swallows its own write
-                    # failures). Metering is on, so warn rather than hide the
-                    # "enabled but no billing data" case in DEBUG logs.
-                    logger.warning(
-                        "usage metering hook (indexing embeddings) skipped",
-                        exc_info=True,
-                    )
+            # Usage metering (Deck #67): record the chunk volume +
+            # embedding-token count for this document. Best-effort and
+            # flag-gated; placed after the embedding succeeds so it can never
+            # affect the indexing path. See record_indexing_usage for the
+            # metric/privacy details.
+            await record_indexing_usage(
+                enabled=settings.usage_metering_enabled,
+                provider=provider,
+                model=settings.get_embedding_model_name(),
+                doc_type=doc_task.doc_type,
+                user_id=doc_task.user_id,
+                chunk_count=len(chunk_texts),
+                token_count=embed_tokens,
+                total_chars=total_chars,
+            )
 
     async def generate_sparse_embeddings():
         """Generate sparse embeddings (BM25 for keyword matching)."""

tests/unit/providers/test_gateway_provider.py

@@ -331,8 +331,9 @@ def test_trailing_slash_base_url_normalized():
 async def test_gateway_embed_with_usage_forwards_after_bearer(monkeypatch):
     """embed_with_usage refreshes the bearer, then returns the (embedding,
     token_count) from the inherited OpenAI implementation."""
+    # https mock host (never contacted — the OpenAI client is patched below).
     provider = GatewayProvider(
-        base_url="http://gw:8083/v1", embedding_model="mistral/mistral-embed"
+        base_url="https://gw:8083/v1", embedding_model="mistral/mistral-embed"
     )
 
     order: list[str] = []
@@ -364,8 +365,9 @@ async def test_gateway_embed_with_usage_forwards_after_bearer(monkeypatch):
 
 async def test_gateway_embed_batch_with_usage_forwards_after_bearer(monkeypatch):
     """embed_batch_with_usage also refreshes the bearer before delegating."""
+    # https mock host (never contacted — the OpenAI client is patched below).
     provider = GatewayProvider(
-        base_url="http://gw:8083/v1", embedding_model="mistral/mistral-embed"
+        base_url="https://gw:8083/v1", embedding_model="mistral/mistral-embed"
     )
     ensured = {"n": 0}
 

tests/unit/providers/test_ollama.py

@@ -15,8 +15,9 @@ from nextcloud_mcp_server.providers.ollama import OllamaProvider
 @pytest.fixture
 def ollama_provider():
     # Construct with no models so __init__ skips _check_model_is_loaded (no
-    # network call), then enable embeddings post-construction.
-    provider = OllamaProvider(base_url="http://ollama:11434")
+    # network call), then enable embeddings post-construction. https mock host
+    # (never contacted — client.post is patched in each test).
+    provider = OllamaProvider(base_url="https://ollama:11434")
     provider.embedding_model = "nomic-embed-text"
     return provider
 

tests/unit/test_processor_metering.py

@@ -0,0 +1,104 @@
+"""Unit tests for the indexing-path usage-metering helper (Deck #67).
+
+``record_indexing_usage`` records the two billable events (``pages_chunks`` +
+``embeddings_queries``) after a document's chunks are embedded. These cover the
+value mapping, the flag/zero-chunk no-ops, and the best-effort failure path
+without standing up the full document pipeline.
+"""
+
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from nextcloud_mcp_server.vector import processor
+
+
+@pytest.fixture
+def store_spy(monkeypatch):
+    """Patch UsageEventStore.shared() to return a spy store."""
+    store = MagicMock()
+    store.record_usage_event = AsyncMock()
+    monkeypatch.setattr(
+        processor.UsageEventStore, "shared", AsyncMock(return_value=store)
+    )
+    return store
+
+
+@pytest.mark.unit
+async def test_records_pages_chunks_and_token_count(store_spy):
+    """Both events fire: pages_chunks = chunk count, embeddings_queries = tokens."""
+    await processor.record_indexing_usage(
+        enabled=True,
+        provider="mistral",
+        model="mistral-embed",
+        doc_type="file",
+        user_id="alice",
+        chunk_count=110,
+        token_count=4242,
+        total_chars=170826,
+    )
+
+    calls = store_spy.record_usage_event.await_args_list
+    by_metric = {c.kwargs["metric"]: c.kwargs["value"] for c in calls}
+    assert by_metric == {"pages_chunks": 110, "embeddings_queries": 4242}
+    for c in calls:
+        # Hot-path fast-gate + tenant-local attribution metadata.
+        assert c.kwargs["enabled"] is True
+        assert c.kwargs["metadata"]["provider"] == "mistral"
+        assert c.kwargs["metadata"]["model"] == "mistral-embed"
+        assert c.kwargs["metadata"]["user_id"] == "alice"
+        assert c.kwargs["metadata"]["doc_type"] == "file"
+
+
+@pytest.mark.unit
+async def test_disabled_is_noop(store_spy):
+    """Flag off → no store access, no events."""
+    await processor.record_indexing_usage(
+        enabled=False,
+        provider="mistral",
+        model="mistral-embed",
+        doc_type="file",
+        user_id="alice",
+        chunk_count=10,
+        token_count=20,
+        total_chars=5,
+    )
+    store_spy.record_usage_event.assert_not_awaited()
+
+
+@pytest.mark.unit
+async def test_zero_chunks_is_noop(store_spy):
+    """A document with no chunks records nothing (no zero-value rows)."""
+    await processor.record_indexing_usage(
+        enabled=True,
+        provider="mistral",
+        model="mistral-embed",
+        doc_type="file",
+        user_id="alice",
+        chunk_count=0,
+        token_count=0,
+        total_chars=0,
+    )
+    store_spy.record_usage_event.assert_not_awaited()
+
+
+@pytest.mark.unit
+async def test_store_failure_is_swallowed(monkeypatch):
+    """A store-construction failure is logged, never raised into indexing."""
+    monkeypatch.setattr(
+        processor.UsageEventStore,
+        "shared",
+        AsyncMock(side_effect=RuntimeError("boom")),
+    )
+
+    # Must not raise.
+    await processor.record_indexing_usage(
+        enabled=True,
+        provider="mistral",
+        model="mistral-embed",
+        doc_type="file",
+        user_id="alice",
+        chunk_count=3,
+        token_count=7,
+        total_chars=9,
+    )