fix(vector): address PR review round 2 — status branching, doc_id guard, doc restore

- _ensure_keyword_payload_indexes: distinguish 400 (schema conflict, warning)
  from other status codes (5xx/network, error) so a transient outage doesn't
  silently leave the collection unindexed.
- build_search_result_from_point: use .get("doc_id") + return None on missing
  instead of KeyError-crashing the search; reverse metadata merge order so
  payload-derived chunk_index/total_chunks win over caller-supplied extras.
- docs/configuration.md: restore the OpenAI/Mistral/Bedrock/Simple provider
  sections + reference-table rows that were dropped in the rebase. Reword
  the "Startup migrations" bullet to describe what the code actually does
  (no sampling — full scroll, zero writes when clean). Add operator note
  about the SemanticSearchResult.id TypeError path.
- tests: pytest.approx for float equality (Sonar python:S1244); coverage
  for non-400 → ERROR, payload={doc_id: None}, and missing doc_id key.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

nextcloud_mcp_server/search/algorithms.py

@@ -11,6 +11,8 @@ from nextcloud_mcp_server.config import get_settings
 from nextcloud_mcp_server.vector.placeholder import get_placeholder_filter
 from nextcloud_mcp_server.vector.qdrant_client import get_qdrant_client
 
+logger = logging.getLogger(__name__)
+
 
 @runtime_checkable
 class NextcloudClientProtocol(Protocol):
@@ -91,7 +93,6 @@ async def get_indexed_doc_types(user_id: str) -> set[str]:
         ...     # Search notes
     """
 
-    logger = logging.getLogger(__name__)
     settings = get_settings()
 
     qdrant_client = await get_qdrant_client()
@@ -205,15 +206,19 @@ def build_search_result_from_point(
     if point.payload is None:
         return None
 
-    doc_id = str(point.payload["doc_id"])
+    raw_doc_id = point.payload.get("doc_id")
+    if raw_doc_id is None:
+        logger.warning("Skipping point %s: missing doc_id in payload", point.id)
+        return None
+    doc_id = str(raw_doc_id)
     doc_type = point.payload.get("doc_type", "note")
 
-    metadata: dict[str, Any] = {
-        "chunk_index": point.payload.get("chunk_index"),
-        "total_chunks": point.payload.get("total_chunks"),
-    }
-    if metadata_extras:
-        metadata.update(metadata_extras)
+    # Caller-supplied metadata is merged first; payload-derived common fields
+    # (chunk_index, total_chunks) win in case of key collisions so they always
+    # reflect the actual point.
+    metadata: dict[str, Any] = dict(metadata_extras) if metadata_extras else {}
+    metadata["chunk_index"] = point.payload.get("chunk_index")
+    metadata["total_chunks"] = point.payload.get("total_chunks")
 
     # File-specific metadata for PDF viewer
     if doc_type == "file" and (path := point.payload.get("file_path")):

nextcloud_mcp_server/vector/qdrant_client.py

@@ -46,9 +46,21 @@ async def _ensure_keyword_payload_indexes(
         except UnexpectedResponse as e:
             body = getattr(e, "content", b"") or b""
             body_text = body.decode("utf-8", errors="replace")
-            logger.warning(
-                "Failed to create payload index on '%s': %s", field, body_text
-            )
+            # 400 is the expected schema-conflict path (index already exists
+            # with a different type). 5xx / network-shaped errors should not
+            # be silently downgraded — keep the loop going so the remaining
+            # fields still get attempted, but log at error so operators see it.
+            if e.status_code == 400:
+                logger.warning(
+                    "Schema conflict on payload index '%s': %s", field, body_text
+                )
+            else:
+                logger.error(
+                    "Unexpected error creating payload index on '%s' (status %s): %s",
+                    field,
+                    e.status_code,
+                    body_text,
+                )
 
 
 async def _backfill_doc_id_to_string(