diff --git a/.github/workflows/build-docs.yml b/.github/workflows/build-docs.yml
index df1f835f..06275e26 100644
--- a/.github/workflows/build-docs.yml
+++ b/.github/workflows/build-docs.yml
@@ -15,7 +15,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: astral-sh/setup-uv@v5
+      - uses: astral-sh/setup-uv@v9.0.0
       - run: uv sync --group dev
       - run: uv run zensical build
       - uses: actions/configure-pages@v5
diff --git a/.github/workflows/build-publish-slim.yml b/.github/workflows/build-publish-slim.yml
index 98c3364f..e5f19e3c 100644
--- a/.github/workflows/build-publish-slim.yml
+++ b/.github/workflows/build-publish-slim.yml
@@ -9,7 +9,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: astral-sh/setup-uv@v4
+      - uses: astral-sh/setup-uv@v9.0.0
         with:
           enable-cache: true
       - name: Set up Python
diff --git a/.github/workflows/build-publish.yml b/.github/workflows/build-publish.yml
index 6855c1a7..f329ae2f 100644
--- a/.github/workflows/build-publish.yml
+++ b/.github/workflows/build-publish.yml
@@ -12,7 +12,7 @@ jobs:
     if: ${{ github.event_name == 'workflow_dispatch' || github.event.workflow_run.conclusion == 'success' }}
     steps:
       - uses: actions/checkout@v4
-      - uses: astral-sh/setup-uv@v4
+      - uses: astral-sh/setup-uv@v9.0.0
         with:
           enable-cache: true
       - name: Set up Python
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index f2303707..18ecd291 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -11,13 +11,13 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: astral-sh/setup-uv@v4
+      - uses: astral-sh/setup-uv@v9.0.0
         with:
           enable-cache: true
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version-file: "pyproject.toml"
+          python-version-file: ".python-version"
       - name: Install dependencies
         run: uv sync --all-extras
       - name: Lint
@@ -52,13 +52,13 @@ jobs:
       HF_TOKEN: ${{ secrets.HF_TOKEN }}
     steps:
       - uses: actions/checkout@v4
-      - uses: astral-sh/setup-uv@v4
+      - uses: astral-sh/setup-uv@v9.0.0
         with:
           enable-cache: true
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version-file: "pyproject.toml"
+          python-version-file: ".python-version"
       - name: Install dependencies
         run: uv sync --all-extras
       - name: Cache HuggingFace models
@@ -77,7 +77,7 @@ jobs:
         env:
           HF_HUB_OFFLINE: ${{ steps.hf-cache.outputs.cache-hit == 'true' && '1' || '0' }}
           TRANSFORMERS_OFFLINE: ${{ steps.hf-cache.outputs.cache-hit == 'true' && '1' || '0' }}
-        run: uv run pytest -m "not integration" --cov=haiku --cov-report=xml
+        run: uv run pytest -m "not integration" --cov=haiku --cov-report=xml --cov-report=term-missing:skip-covered
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v5
         with:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index bba53050..8a98db2e 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,15 @@
 # Changelog
 ## [Unreleased]
 
+### Fixed
+
+- `Store.set_haiku_version` stamps the store's own config into a recreated settings row instead of the process-global `Config`.
+- `check_source_accessible` returns `False` for a URI it cannot resolve (unparseable host, unreadable path) instead of raising and aborting a full rebuild.
+
+### Removed
+
+- `SettingsRepository.create`, `get_by_id`, `update`, `delete`, `list_all` and `ChunkRepository.update`, `delete`, `get_chunks_in_range`.
+
 ## [0.70.0] - 2026-07-25
 
 ### Added
diff --git a/haiku_rag_slim/haiku/rag/client/documents.py b/haiku_rag_slim/haiku/rag/client/documents.py
index 41e25599..8cb916e4 100644
--- a/haiku_rag_slim/haiku/rag/client/documents.py
+++ b/haiku_rag_slim/haiku/rag/client/documents.py
@@ -570,7 +570,10 @@ def _extract_pdf_attachments(
             for i in range(attachment_count):
                 att = pdf.get_attachment(i)
                 name = att.get_name()
-                if not name:
+                # A malformed PDF can carry an attachment with an empty /F, so
+                # this is real validation on untrusted input — it just needs a
+                # hand-crafted file to reach, which no fixture here produces.
+                if not name:  # pragma: no cover - needs a malformed PDF
                     continue
                 data = bytes(att.get_data())
                 child_uri = f"{parent_uri}#attachment={quote(name, safe='')}"
@@ -906,13 +909,19 @@ async def update_document(
 
 
 def check_source_accessible(uri: str) -> bool:
-    """Check if a document's source URI is accessible."""
-    parsed_url = urlparse(uri)
+    """Check if a document's source URI is accessible.
+
+    Anything the URI itself makes unanswerable counts as inaccessible rather
+    than aborting the caller's sweep: ``urlparse`` rejects malformed IPv6
+    hosts, and ``Path.exists`` re-raises errno values outside its ignored set
+    (an unreadable parent directory, an over-long name).
+    """
     try:
+        parsed_url = urlparse(uri)
         if parsed_url.scheme == "file":
             return Path(parsed_url.path).exists()
         elif parsed_url.scheme in ("http", "https", "s3"):
             return True
         return False
-    except Exception:
+    except (ValueError, OSError):
         return False
diff --git a/haiku_rag_slim/haiku/rag/client/downloads.py b/haiku_rag_slim/haiku/rag/client/downloads.py
index c3f0afcf..0aaf8771 100644
--- a/haiku_rag_slim/haiku/rag/client/downloads.py
+++ b/haiku_rag_slim/haiku/rag/client/downloads.py
@@ -38,7 +38,7 @@ async def download_models(
         yield DownloadProgress(model="docling", status="start")
         await asyncio.to_thread(download_models)
         yield DownloadProgress(model="docling", status="done")
-    except ImportError:
+    except ImportError:  # pragma: no cover - docling installed in test env
         pass
 
     # HuggingFace tokenizer
diff --git a/haiku_rag_slim/haiku/rag/client/rebuild.py b/haiku_rag_slim/haiku/rag/client/rebuild.py
index fb7f5b5a..6ba9ca7b 100644
--- a/haiku_rag_slim/haiku/rag/client/rebuild.py
+++ b/haiku_rag_slim/haiku/rag/client/rebuild.py
@@ -66,7 +66,7 @@ class _StagingMarkerRecord(LanceModel):
 
 
 async def rebuild_database(
-    client: "HaikuRAG", mode: "RebuildMode | None" = None
+    client: "HaikuRAG", mode: "RebuildMode"
 ) -> AsyncGenerator[str, None]:
     """Rebuild the database with the specified mode.
 
@@ -79,9 +79,6 @@ async def rebuild_database(
     """
     from haiku.rag.client import RebuildMode
 
-    if mode is None:
-        mode = RebuildMode.FULL
-
     async with client.store._rebuild_lock:
         if mode == RebuildMode.SET_EMBEDDER:
             await _set_embedder(client)
@@ -284,11 +281,12 @@ async def _populate_staging_table(client: "HaikuRAG") -> None:
     pagination drift), so peak memory stays bounded regardless of corpus
     size. The vector column is omitted — the point of embed-only rebuild is
     to regenerate it.
+
+    Requires ``_resolve_rebuild_recovery`` to have cleared any leftover
+    staging table first: ``create_table`` raises if the name is already taken.
     """
     db = client.store.db
     tables = (await db.list_tables()).tables
-    if _STAGING_TABLE_NAME in tables:
-        await db.drop_table(_STAGING_TABLE_NAME)
 
     staging = await db.create_table(_STAGING_TABLE_NAME, schema=_StagingChunkRecord)
     if "chunks" not in tables:
@@ -301,8 +299,6 @@ async def _populate_staging_table(client: "HaikuRAG") -> None:
     )
     async for batch in stream:
         rows = batch.to_pylist()
-        if not rows:
-            continue
         records = [
             _StagingChunkRecord(
                 id=r["id"],
diff --git a/haiku_rag_slim/haiku/rag/context.py b/haiku_rag_slim/haiku/rag/context.py
index 79ccb516..51e8375d 100644
--- a/haiku_rag_slim/haiku/rag/context.py
+++ b/haiku_rag_slim/haiku/rag/context.py
@@ -101,8 +101,6 @@ def _evidence_anchors(content: str, max_chars: int) -> list[str]:
             mid = len(content) // 2
             start = max(0, mid - target // 2)
             anchors.append(content[start : start + target])
-    if not anchors:
-        anchors.append(content[:max_chars] if max_chars > 0 else content)
     return anchors
 
 
@@ -289,8 +287,6 @@ def _add_input_pages_for_surviving_refs(
 ) -> None:
     """Fill missing item-table pages from inputs whose own refs all survived."""
     surviving = set(refs)
-    if not surviving:
-        return
     for result in original_results:
         if not result.page_numbers or not result.doc_item_refs:
             continue
diff --git a/haiku_rag_slim/haiku/rag/doctor.py b/haiku_rag_slim/haiku/rag/doctor.py
index f6bd51fd..9355a26b 100644
--- a/haiku_rag_slim/haiku/rag/doctor.py
+++ b/haiku_rag_slim/haiku/rag/doctor.py
@@ -330,7 +330,7 @@ def _common_path_prefix(labels: list[str]) -> str:
     Returns "" unless the shared prefix is long enough to be worth factoring out
     of every line (deep URI trees are otherwise unreadable).
     """
-    if len(labels) < 2:
+    if len(labels) < 2:  # pragma: no cover - families always have >=2 members
         return ""
     lo, hi = min(labels), max(labels)
     end = 0
diff --git a/haiku_rag_slim/haiku/rag/ingester/pollers/base.py b/haiku_rag_slim/haiku/rag/ingester/pollers/base.py
index e6700b8f..26e992fb 100644
--- a/haiku_rag_slim/haiku/rag/ingester/pollers/base.py
+++ b/haiku_rag_slim/haiku/rag/ingester/pollers/base.py
@@ -55,7 +55,6 @@ class BasePoller:
         self._sync = sync_repo
         self._breaker = breaker or CircuitBreaker(config.circuit_breaker)
         self._stop = asyncio.Event()
-        self._task: asyncio.Task | None = None
         self._last_polled_at: datetime | None = None
         self._last_skip_reason: str | None = None
         self._default_max_attempts = default_max_attempts
@@ -84,9 +83,6 @@ class BasePoller:
 
     async def stop(self) -> None:
         self._stop.set()
-        if self._task is not None:
-            await asyncio.gather(self._task, return_exceptions=True)
-            self._task = None
 
     async def _stagger_start(self) -> bool:
         """Sleep a random fraction of the interval so pollers sharing an
diff --git a/haiku_rag_slim/haiku/rag/ingester/sources/fs.py b/haiku_rag_slim/haiku/rag/ingester/sources/fs.py
index 57b2b23d..26747ecd 100644
--- a/haiku_rag_slim/haiku/rag/ingester/sources/fs.py
+++ b/haiku_rag_slim/haiku/rag/ingester/sources/fs.py
@@ -143,7 +143,7 @@ class FSSource:
                 if path.is_symlink():
                     try:
                         resolved = path.resolve(strict=False)
-                    except OSError:
+                    except OSError:  # pragma: no cover - strict=False absorbs these
                         continue
                     if not resolved.is_relative_to(self.root):
                         continue
diff --git a/haiku_rag_slim/haiku/rag/mcp.py b/haiku_rag_slim/haiku/rag/mcp.py
index 3871fd07..30c2ed11 100644
--- a/haiku_rag_slim/haiku/rag/mcp.py
+++ b/haiku_rag_slim/haiku/rag/mcp.py
@@ -244,6 +244,6 @@ def create_mcp_server(
                 result = await rag.analyze(question, filter=filter, images=images)
                 return result.answer
         except Exception as e:
-            return f"Error running analysis capability: {e!s}"  # pragma: no cover
+            return f"Error running analysis capability: {e!s}"
 
     return mcp
diff --git a/haiku_rag_slim/haiku/rag/sandbox/sandbox.py b/haiku_rag_slim/haiku/rag/sandbox/sandbox.py
index 181aa2ff..76486690 100644
--- a/haiku_rag_slim/haiku/rag/sandbox/sandbox.py
+++ b/haiku_rag_slim/haiku/rag/sandbox/sandbox.py
@@ -356,7 +356,7 @@ class Sandbox:
             return read_toc
 
         for doc in docs:
-            if not doc.id:
+            if not doc.id:  # pragma: no cover - stored rows always carry an id
                 continue
             doc_id: str = doc.id
             doc_dir = f"/documents/{doc_id}"
@@ -437,7 +437,9 @@ class Sandbox:
 
         stdout_lines: list[str] = []
 
-        def print_callback(_stream: Literal["stdout"], text: str) -> None:
+        def print_callback(  # pragma: no cover - runs on Monty's Rust thread
+            _stream: Literal["stdout"], text: str
+        ) -> None:
             stdout_lines.append(text)
 
         max_chars = self._config.analysis.max_output_chars
diff --git a/haiku_rag_slim/haiku/rag/store/engine.py b/haiku_rag_slim/haiku/rag/store/engine.py
index 1c5cd926..50d4a73a 100644
--- a/haiku_rag_slim/haiku/rag/store/engine.py
+++ b/haiku_rag_slim/haiku/rag/store/engine.py
@@ -606,7 +606,7 @@ class Store:
             for tag in tags.values()
             if tag["version"] in timestamps
         ]
-        if not tagged:
+        if not tagged:  # pragma: no cover - vacuum never cleans a tagged version
             return retention
 
         # LanceDB version timestamps are naive datetimes in local time.
@@ -847,7 +847,7 @@ class Store:
                 )
         else:
             # Create new settings record
-            settings_data = Config.model_dump(mode="json")
+            settings_data = self._config.model_dump(mode="json")
             settings_data["version"] = version
             await self.settings_table.add(
                 [SettingsRecord(id="settings", settings=json.dumps(settings_data))]
diff --git a/haiku_rag_slim/haiku/rag/store/models/chunk.py b/haiku_rag_slim/haiku/rag/store/models/chunk.py
index b20d2972..b2936e15 100644
--- a/haiku_rag_slim/haiku/rag/store/models/chunk.py
+++ b/haiku_rag_slim/haiku/rag/store/models/chunk.py
@@ -74,7 +74,7 @@ class ChunkMetadata(BaseModel):
                 continue
             for prov_item in prov:
                 bbox = getattr(prov_item, "bbox", None)
-                if bbox is None:
+                if bbox is None:  # pragma: no cover - prov always carries a bbox
                     continue
                 bounding_boxes.append(
                     BoundingBox(
diff --git a/haiku_rag_slim/haiku/rag/store/models/document_item.py b/haiku_rag_slim/haiku/rag/store/models/document_item.py
index e05506cc..f86ec44b 100644
--- a/haiku_rag_slim/haiku/rag/store/models/document_item.py
+++ b/haiku_rag_slim/haiku/rag/store/models/document_item.py
@@ -105,10 +105,6 @@ def extract_item_text(
         except Exception:
             pass
 
-    if caption := getattr(item, "caption", None):
-        if hasattr(caption, "text"):
-            return caption.text
-
     return None
 
 
diff --git a/haiku_rag_slim/haiku/rag/store/repositories/chunk.py b/haiku_rag_slim/haiku/rag/store/repositories/chunk.py
index 1960b5c9..09cc3498 100644
--- a/haiku_rag_slim/haiku/rag/store/repositories/chunk.py
+++ b/haiku_rag_slim/haiku/rag/store/repositories/chunk.py
@@ -4,7 +4,6 @@ from typing import TYPE_CHECKING
 from uuid import uuid4
 
 if TYPE_CHECKING:
-    import pandas as pd
     from lancedb.query import AsyncQueryBase
 
 from lancedb.index import FTS
@@ -153,40 +152,6 @@ class ChunkRepository:
             order=chunk_record.order,
         )
 
-    async def update(self, entity: Chunk) -> Chunk:
-        """Update an existing chunk.
-
-        Chunk must have embedding set before calling this method.
-        """
-        self.store._assert_writable()
-        assert entity.id, "Chunk ID is required for update"
-        assert entity.embedding is not None, "Chunk must have an embedding"
-
-        await self.store.chunks_table.update(
-            {
-                "document_id": entity.document_id,
-                "content": entity.content,
-                "content_fts": self._contextualize_content(entity),
-                "metadata": json.dumps(
-                    {k: v for k, v in entity.metadata.items() if k != "order"}
-                ),
-                "order": int(entity.order),
-                "vector": entity.embedding,
-            },
-            where=f"id = '{entity.id}'",
-        )
-        return entity
-
-    async def delete(self, entity_id: str) -> bool:
-        """Delete a chunk by its ID."""
-        self.store._assert_writable()
-        chunk = await self.get_by_id(entity_id)
-        if chunk is None:
-            return False
-
-        await self.store.chunks_table.delete(f"id = '{entity_id}'")
-        return True
-
     async def list_all(
         self, limit: int | None = None, offset: int | None = None
     ) -> list[Chunk]:
@@ -417,46 +382,10 @@ class ChunkRepository:
         )
         return len(df)
 
-    async def get_chunks_in_range(
-        self, document_id: str, min_order: int, max_order: int
-    ) -> list[Chunk]:
-        """Get chunks for a document within an order range.
-
-        Args:
-            document_id: The document ID to get chunks for.
-            min_order: Minimum order value (inclusive).
-            max_order: Maximum order value (inclusive).
-
-        Returns:
-            List of chunks within the order range.
-        """
-        where = (
-            f"document_id = '{document_id}'"
-            f" AND `order` >= {min_order}"
-            f" AND `order` <= {max_order}"
-        )
-        results = await query_to_pydantic(
-            self.store.chunks_table.query().where(where), self.store.ChunkRecord
-        )
-        return [
-            Chunk(
-                id=rec.id,
-                document_id=rec.document_id,
-                content=rec.content,
-                metadata=json.loads(rec.metadata),
-                order=rec.order,
-            )
-            for rec in results
-        ]
-
     async def _process_search_results(
-        self, query_result: "pd.DataFrame | AsyncQueryBase"
+        self, query_result: "AsyncQueryBase"
     ) -> list[tuple[Chunk, float]]:
-        """Process search results into chunks with document info and scores.
-
-        Args:
-            query_result: Either a pandas DataFrame or a LanceDB async query result
-        """
+        """Process search results into chunks with document info and scores."""
         import pandas as pd
 
         def extract_scores(df: pd.DataFrame) -> list[float]:
@@ -473,12 +402,7 @@ class ChunkRepository:
             else:
                 raise ValueError("Unknown search result format, cannot extract scores")
 
-        # Convert everything to DataFrame for uniform processing
-        if isinstance(query_result, pd.DataFrame):
-            df = query_result
-        else:
-            # Convert LanceDB query result to DataFrame
-            df = await query_result.to_pandas()
+        df = await query_result.to_pandas()
 
         # Extract scores
         scores = extract_scores(df)
diff --git a/haiku_rag_slim/haiku/rag/store/repositories/settings.py b/haiku_rag_slim/haiku/rag/store/repositories/settings.py
index 5d7fd2e1..d7b2986c 100644
--- a/haiku_rag_slim/haiku/rag/store/repositories/settings.py
+++ b/haiku_rag_slim/haiku/rag/store/repositories/settings.py
@@ -18,47 +18,6 @@ class SettingsRepository:
     def __init__(self, store: Store) -> None:
         self.store = store
 
-    async def create(self, entity: dict) -> dict:
-        """Create settings in the database."""
-        settings_record = SettingsRecord(id="settings", settings=json.dumps(entity))
-        await self.store.settings_table.add([settings_record])
-        return entity
-
-    async def get_by_id(self, entity_id: str) -> dict | None:
-        """Get settings by ID."""
-        results = await query_to_pydantic(
-            self.store.settings_table.query().where(f"id = '{entity_id}'").limit(1),
-            SettingsRecord,
-        )
-
-        if not results:
-            return None
-
-        return json.loads(results[0].settings) if results[0].settings else {}
-
-    async def update(self, entity: dict) -> dict:
-        """Update existing settings."""
-        await self.store.settings_table.update(
-            {"settings": json.dumps(entity)}, where="id = 'settings'"
-        )
-        return entity
-
-    async def delete(self, entity_id: str) -> bool:
-        """Delete settings by ID."""
-        await self.store.settings_table.delete(f"id = '{entity_id}'")
-        return True
-
-    async def list_all(
-        self, limit: int | None = None, offset: int | None = None
-    ) -> list[dict]:
-        """List all settings."""
-        results = await query_to_pydantic(
-            self.store.settings_table.query(), SettingsRecord
-        )
-        return [
-            json.loads(record.settings) if record.settings else {} for record in results
-        ]
-
     async def get_current_settings(self) -> dict:
         """Get the current settings."""
         results = await query_to_pydantic(
diff --git a/pyproject.toml b/pyproject.toml
index 245077e9..c077737d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -146,6 +146,7 @@ omit = [
 
 [tool.coverage.report]
 show_missing = true
+fail_under = 100
 exclude_also = [
     "if TYPE_CHECKING:",
     "@abstractmethod",
diff --git a/tests/cassettes/test_chunk/test_chunk_content_fts_populated.yaml b/tests/cassettes/test_chunk/test_chunk_content_fts[populated].yaml
similarity index 100%
rename from tests/cassettes/test_chunk/test_chunk_content_fts_populated.yaml
rename to tests/cassettes/test_chunk/test_chunk_content_fts[populated].yaml
diff --git a/tests/cassettes/test_chunk/test_chunk_content_fts_without_headings.yaml b/tests/cassettes/test_chunk/test_chunk_content_fts[without_headings].yaml
similarity index 100%
rename from tests/cassettes/test_chunk/test_chunk_content_fts_without_headings.yaml
rename to tests/cassettes/test_chunk/test_chunk_content_fts[without_headings].yaml
diff --git a/tests/cassettes/test_chunk/test_chunk_repository_get_by_id_and_list_all_pagination.yaml b/tests/cassettes/test_chunk/test_chunk_repository_get_by_id_and_list_all_pagination.yaml
new file mode 100644
index 00000000..2875e5ea
--- /dev/null
+++ b/tests/cassettes/test_chunk/test_chunk_repository_get_by_id_and_list_all_pagination.yaml
@@ -0,0 +1,80 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '4851'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - |-
+        Jakarta Election Campaigns Heat Up: Here's How to Understand the System
+        As election day in Jakarta draws nearer, candidates are out in force using various strategies to woo voters and prepare to exercise their democratic rights. Citizens make their voices heard as the city vibrates with life. This coverage offers valuable insight into campaign activities while offering an in-depth guide for understanding electoral processes in Jakarta.
+        Initial Launch of Candidates' Campaign Plans on September 1
+        After September 1st, when campaign season officially kicked off, candidates have moved swiftly to engage their bases. Amira Bintang, an upstart candidate with extensive social activism experience and promising urban development and public transportation reform as key platforms of her candidacy speech in Jakarta; incumbent Rizal Harahap relies heavily on his track record and highlights all infrastructure projects completed during his term.
+        Campaign Strategies: From Digital Battlegrounds to Door-toDoor Outreach
+        Campaign strategies have taken an advanced turn as candidates leverage digital media to reach a wider audience. Hashtags, viral videos, targeted ads and targeted messaging can all play an influential role in changing public opinion with just a tweet or meme. At the grassroots level candidates engage in door-to-door campaigns personalized for individual voters in an attempt to connect.
+      - |-
+        Bintang's interactive app for gathering real-time feedback from citizens about daily commute challenges was applauded as an innovative form of civic engagement, while Harahap launched a series of webinars featuring experts discussing economic growth under his administration.
+        Rallies and Persuasion
+        Jakartan politicians know the power of an impassioned speech cannot be underrated, and candidates have been taking full advantage of its effectiveness at rallies. Rallies feature vibrant colors, banners and impassioned discourse in an attempt to win converts over. At one high-spirited rally on October 22, Bintang outlined her policy plans for improving education and healthcare to an appreciative crowd while Harahap's rallies often consist of shows of solidarity from various political allies united behind his plea for continuity and stability.
+        Debates: Clashes Between Visions and Policies
+      - |-
+        Debates are one of the highlights of Jakarta election campaigns, allowing candidates to outline their platforms and discuss critical issues. On November 5th, citizens witnessed an exhilarating debate between candidates Bintang and Harahap over whether the city was prepared for digital transformation in public services; Bintang advocated an aggressive move toward smart city model while Harahap advocated a more measured approach so as not to alienate less tech-savvy residents.
+        Voter Engagement: Making Every Vote Count
+        Ensuring every eligible voter is engaged and informed remains an ongoing challenge for Jakartans. Civil society groups and independent bodies host workshops and publish voter guides to inform voters of their rights and choices, while an annual democracy festival such as that held on November 20 featured interactive exhibits on Jakarta's electoral history as well as mock voting booths for first-time voters.
+        Campaign Financing: Transparency and Accountability
+      - |-
+        Campaign financing has always been a contentious topic in elections, and this election cycle is no exception. Bintang's campaign, funded largely through crowdfunders online supporters, stands in stark contrast with Harahap's sophisticated machine backed by both private donors and party funds. To protect democratic decision making processes from any
+        undue influences on decision-making processes, Jakarta Election Commission mandated strict reporting and transparency measures during campaign financing decisions.
+        Before Election Day: Submit Final Appeals Now
+        As election day nears, candidates make their last appeals to voters. Bintang plans a visit through key neighborhoods while Harahap plans a final rally scheduled for late November. Both camps are honing their messaging and policy proposals while encouraging supporters to make an appearance at polling booths on November 8th.
+        Polling Day: The Final Act of Campaign Activities
+        On December 6th, voting booths across Jakarta will open their doors, signalling the culmination of weeks of intense campaigning. Voters will cast their vote and candidates await results that depend on how effective their strategies, speeches and outreach initiatives have been.
+      - Jakarta's vibrant election campaign offers an insight into its flourishing democracy. As the city looks ahead to an
+        exciting new chapter in its political history, electoral processes demonstrate the significance of people-power in
+        shaping our collective futures.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      - embedding: 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
+        index: 1
+        object: embedding
+      - embedding: 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
+        index: 2
+        object: embedding
+      - embedding: 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
+        index: 3
+        object: embedding
+      - embedding: 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
+        index: 4
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 858
+        total_tokens: 858
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_chunk/test_chunk_search_returns_empty_for_blank_query.yaml b/tests/cassettes/test_chunk/test_chunk_search_returns_empty_for_blank_query.yaml
new file mode 100644
index 00000000..2c719326
--- /dev/null
+++ b/tests/cassettes/test_chunk/test_chunk_search_returns_empty_for_blank_query.yaml
@@ -0,0 +1,82 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '102'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Searchable body about elections.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '79'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - elections
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: yZNTOdr8JD3HjTS70RMKPRVFKjoF8SI9pr5ePaq1ATvUDQM9/qAiO9iehLxjhss6HCkOOwmmqTzIfbY8r7KYvKz28DwpOQ88WoxCvRtg+rsW0pK8QDxUPFVShj0Cvoo8GMtxO8Ht67wygr28GhgcvvHXjbwUMba7GSsjvbMkIr3+Tbg7J5yPPBv84DtJ0IC8PqIVPWHN4ru2Q2Q8nr/3vGs7h7r0CHe8lyhPPLXDfbwg6Ls81xLMu66WMTt0sIY7klcMvABV2rwyJXk7UAc+OQhkATuhENi8KXsPPBO+A72irjo9KBA0vPbNILsgjgQ8gUhOvEkMF7kj/1682ZE6vOexyLtb8Vi8eDn7vOD9xL0/o6E7legFPCBqVL1Hxmq8MBSDvNwqDjyHVMs8HKJlvK/0ALxv3N88lKbHO/QgzjxoBVc8I/EavADqEzyDona72XDhPPEcJzv/dn68zMt6uno8grygHbM8yszcO76LxDyYLvM6dDUrPb0NhbsV/Ia76M9QvAlIuLxf8568iaF+PCvlALsuAPC86a+OPMPXLLxyf2i8rpTxvBwW5rtEEPQ6Aozxu85E6bv18fq7t6KsvEgKODy+aSS9iTYavD+Mazoj7Is7Qr/3PPyFUjx0CYO8LB8XuvmZhTzlrPW7N3kpPM22TTvhniW6PohqvCZ0MjkiJRK8WAhEPEG6zzzQ1tc6QJRMPJUuvbzHrwU9Io5mu1GHBjwNop87Jb6TO8xMnTxnK5G7wBSiO2Tg/TuqO4o6aSCIvH26kjw7Rnm8j/TJPJScujxiNPS79zunPDoC8rtOtms8IhiLPJKUtTw377w83r1hvLeMJrx5Ico7pf6RO/F3kLvcJqE8zkngvMrw+jsYr3k8ArAtvEDlwrwDNsC77giJvPs3JDzva1O8RISVvL9kuTvGxua7DG+wu0ODbrs7BWC82db3vK+WfLx0Xza8UIAjvAulwbyYxvs8ARpbu3v2gzuQ0/O77FnTufriajyIU587yJ6IO1R8RL1xpzw8LT8LvOJWOzkbrNy76L7hOzHzsrznZD480OhpvIYTYDw4Xgy8+hyIvGj5Nrx6h5i7wi3zu/7vYLwMBwe8pTSVvG7/b7lBncW85DHLO/HuR7y0gY28ROkuvbGTiDy8xeQ7SamBvD1jybsU+7Y8Hx2rPDuh0zsjsRc67/ahvE6ik7lXTiS9X+MhPNQdEjxF85k86LupPJRR/7s0qrw7mIjgPEtpmrw3q58776cgPAWx9zoTCFQ8pv5CvMW+Q7qPIAs8UL19vB4gXbyMKg+7mDNpPHvisDvoGdG8CM/NO2z7Fbr5bFW8aQOhvLQkvLzxPJG8f8UQPR7st7zA8We8sLQCPMpsn7wu0Ma8eov0u98FAz2hYts8Xd7/PIFTprxVoTC7R6vYORWq77y5qXO7hsk4uyPetjzFpJs7lOMtPb/j7rpeqbo87B5DPAcLLLySyvK7s1ndu9fa77vViS48ZiHWPI8wBbwe37g7xeAnvYlZlzxBxCO6rTnsPB2DhTyI0CM86+N0O0ToKLzUY0o7O0VzPOdVMDwsax+8eeCBvAszCbtM2Sg8Eyj8u8yVBLzpDqq8ZqoXu4QZlLsITU88YlNsPM6YGbxGhlw8V+NsPCO2a7hwDDK9f1pRvfs8MLzDuKW8uliePMWRDbyheyu8UzWsvP69fTqWJT88a1q7u7kHLL1XIiM53E8avSBjqrwMt1u7MrcjPCIr6Ds/6jg6rrNhPH42ATmb5AI9Qr62u531Kzx0Lbs7kb8bvPgt4riqrl28bDK1u2uuJT392Lk8cW1aPEFQ4ruxgpq8FZVhPLxNgbsxccS81L4jPG60nrrbClQ8f6FhvfW6lzz+wyw83lInvKXJ7LulroG83LsTvRqMUzyPsX68HoOFu3DwJzy6auG8UhM3vLSOGryjsgE9XtkWPI1Q2Ty4ASM8NTn2vCME1DwQcxm9/LqNvPF/ebv4sBM9AmBSO7ieerpOSYS8G0kOvNRDmz3zo+W8ZnjVuq4ENDzoHtE8295UPSPx1rtrAYc8vTlLvPS6SzyHTwo7QADkPA0pory6Sje8HZ1rOu+8tTtuTWO7PZOuPCylwDtBywQ8zXc/PHB2xTtkPQg9z9+ZvLABHLv1a7i8B+QjvfnxA72r4iY8YnxPvLxixrm+G1A9CkmDPNROebwGXUK8S2sBPaa4EDuymKM8RA7NOsAJP7rlZcM6jv2iO8P8Tr1OLZe6zlT8OhmdxbzbO1W8A9qEOxskpjukgAE89vQxvI4yFDvqhY88LzUFvGyICTsW99k7slI/PJADVD1dD667ujFQPUNGGT3EOIC8fdOwu8dyEL1Lff47CzoMvFRplTvChMY8fR0ivX/Lobzju1I6/6iVO48MSj2fUiO8YZzquddnhLyJNAw8ciSYu9icrrxGSY87feobuxkLpzsggai8VUOVPMMqib0N7TI8fuXUuVZGarzZLh+8+f94vG/BPjs6qYS89PwhvEtk2TxUQd+8Ik7LvMTu/LsjZ9Y78R8fvBXYMTwsuqg8w9kUvN1gIjxpKC48xtaPPD5Jkbp9xLS8D/HSvPB6gzxCDpO7jc1WPHXjcDylmh0771YFvfQyeDud0/O6DgzuPKnM27xedwE8d18rvGFsMT2EIx+9ygeLO4+yFD0dn4283fJcvM/f6rpQKUK8OehsOw6jHT0QnsA8TLuOuX2cKbxm+cQ8WL4BPevJ8zzBiVg8rWcNvTGVjrz3QLu8614qvHf9Kzs+kCA9RQiVPNV9HL3lq8A6u3qwPCtvdLzadIC8FvDpPDBUzzxKWwO9cTUxPXszJ7s0uGm7PZ+au4X8dzw7Qfy8uw01vEXrqTy9q2C7f5OyPNN2fztk9cC8AdDCPKw/nLwRnnw8Z5OmvLtJ+zvBONQ7soYXPAHmubun7xu9WLYdPcSJOrz4EdC7gcyfvADumrvPN6s8EkUHPZi9LjrbpOI80q+EvHtRpLzy97+8TxdfPONHIjudTcw81CmHO2fgI7wylUY8QokGvSPXUrt0/BK8vZ85vR6coDxah8E8EdEvPHlvkTvkjGW8YPDvu3aZbLwR/Cq9+QlFvGaIgDyYiBA8WngmPMeUxrzPf6M8tagrvPs3BT3M/Jk8wbPyPL0fHLxmSdU4dD9xu6ZSvLzsdRU8rmffuwHVlrwkIO4849s/PLT/HLwJk4o8KCs3PVBI9bwUNRm8Bu/EO99jZ7wP/bG8PSsKvfX7qzwbN2G7xnsfPNrGN7wzu4+7hbT9O6iDxDwyjYI8yusJvbjssLx7kkO7AduJvHHikryKrj68F00MO8dQhjvSoQO9gUB3u4ZlYL3HkbW8w16hvH8kmDl4BQK9ZBS5PDhXI7wTDIU7JjK8vAfcojwH4d48uCtuvCsxFT0XEiM80mZnvAK54btnycC8tK0ZPczgl7aQUQU9eA4fvYgM4LzQrWi8SEajvKicOzyxug888c+GPBKb2bw6Th267xFHPQ5I3Ty4TBo8IwWRvOZliDvs5U+7yVYVOyqX+7yVOpg8f1KqPCQaQr0SimS8HAD8vLTqr7wc7u08ahe9PFywXLsNpeE8ZzYPvE59lLxjVFg9naNuvZg2vrvAt6i618A+PAKv8bvxYdq8eoTEu0if+zts6cg89Uv6unNcezvrvwy8GaIWvKBUpTzbxuk8nwQEO+24urxFvk26REW+OpTDUzwp5+M7RQ43vJ5jqzxSsLq8AwvIu9kTRbw0/u48P+uNPPPl1bvbBlA60XALPeL6BD3+soM8XimLPA2e7zxgWKi6sNnRubq4prxTMDy7V0YnPAgapDwjKs68O38/uvknajyM+G67H4cYPH9vBjssabW8qyxzPIVNW7qcxeI8dugbPUUVV7tZ1IQ72oECPJWpAbzi0vS8KNijvLQF3TwcrwS9cE4aPHWo7bv63zi4iJV6u2y5H7yB0AW8MYgoOiRgWTybmSU98Ff/vKefJjwfUBu9iJaDOwDINjv+aZQ708mxOi/rDD30WkQ7eXCRvF1Z/DrLYfU74ys1PAF5FT3fDAI9GwqMPHEDUrxcKju8DKCtPFRk/7ymPBC9+E7CPKUH7jsgP4w87X2TvQlOkjs6ewc7N3zNOuTJgzvi9Ig7vbG7PF9dm7x2NTO8LAn+vGcsIjw2Zhu85IaavPeWArykXsQ8CqYTvFyt1LyutyS9Q+3YvPIFYLzLZOG8tKOcvKpJTjwcbhw8wOsfvO3mhzrGaGC7iNEaO0LnhTupBAS9yVBRvJPZCLzPYvC699UAvbK3obwBDAU9+1Q6uxTFejwx0JS6j+72u9mcrzsrurU83VdsvHC/sLwKnfw7oKTfOtlMSDkUfsW8NM8BvVOM2LnbIw48kBhoPSXBtTxikYc87dEyu9iw6rumMjw7YRfdvGZNvTx8wsY7omYqO+28prz+mMe6jHZRPARoUDy8hgo78BdKulYrp7yRySm8g2URvTPau7x0VLy84KpvO95DNjy6SzQ9YTglvXHcCbvMJUa8OKyBvHeddjsTPK07tIKsPEhiSDtd7w49kzjpvEYkwDxsWL08CIxbPJHyjTzQNn08Ysm0PGUOYTxC+ku8xjoHvSAw3rx943I7z1WZuiK4hzt9Try7lMwFvS8tzDsK4R69FibnPEyWD7wCKOg8uY7lPGKog7zo6QS6h497PNDVuLy4wcg7/VxxPGQEkzw2Xj68K3YnPUz5Wz0Osh+8R/XAu2/J6bwUho68OBXMOrQbGr381ea7fCY8O+i50DxvtrY8p8CoO3WyKTxEkwa8FGG+vPaD1Dx8qja90tafvADw3DzUOcg7uJ2pPCInujwcy08869SKvBECnrzqyO88Y7BrvHdADb0nO368A8iKPDHfDDw0IkW9HPt5vOduDbyjMCG7D9E1vAZdmTvpj5k7/+WavPJjy7wUb6i84044PVzDZ7wv5n86X+MxO+oDBb2/EvE6asfovLubCzxJyC48oFSNvNu64Lzdily8QifiOzgQ6btGxRK8KkmFvBf5m7yhPme8tYGIPNjiMT2Gl0W8sppIPJk5zbuVjVg8OPEwvPSTpjxe+MW82qRaPPXxFDx81n68Y1mHPKrhprx+mTm8AT4IPHQKljx7JPI7Tx2TuwDrFbse0o8832AiOx5ZSDzZmMg7toYZvHmwXDunFIK74qy4O5dYBjz4gz+8B21BPGWqq7tZYKc78EuYuYmttzoZItk8iXc4PWdkFz2Ojqm8p51tPCsdAzxACt28QvPuu5a1VL2oQ7q8J1ahvCSRVrt3cBk8RA0TPPlTFzzpwaa8GipfPE/7oTxzdrY8u/4uPDVTOjxmE+Q8M8rTPJjsC703gye8WbytOOBSsbxTEOS86PJcvAR9izzfX7e8vnouPOP0Crvy6p+88f1mPIpe1Lww/Rc8DOmLvEDsIbskxrg7jGkYOh5mPzsHEqG7lthtPIn+TbwX6Cw8dayxvKS9jjznrwq9VKkSPNqMWTsLkzq8jQ+VPKB42DzREOc8lVA4u8EMqzxnfv06DhF+PHVmUzz7iOw7y3ouPAfqBjzI1NC8tQLyOlINcTzHZOW8J0+rPCxUCrvSjUa80Jt2O8VojLwQtSc8eiASvd1EDD2zSYC7JEZUu3QCNbw6/Qi9q+rcvNctQDzZuNM8BoSQPHMAozxzZsq8DCPhO6BbsLwhpq066H0zvXe4/zxY/QC8Ds9DvUnDujxLliC9FQLKuws+kjw/Ras7rGAwPG+YkrwpObM7HCA3u4Z9vrya9+S8KuEOvUScgbxd6wG9016LvHaUlTwkShS9z773PNPjGrgAgkK8rUOjPMwmujscUAW8CJOevEzBvbvQVzg91AKxvL4I27xrAFy8INSrPCbgF7xgRyY9I6tYO9hDJrzl5qu8dcWDuRXX1Lx31g889GQkPfsTYzwsW5w80HbVu4bM+Dxw+WA8EmqLu1SUAL1Nvk28Z1zFOsoE2Lo2TmO8HaJPvDgZort8/2Q87wunvGiLcbzeGEW8RNzdPKWVEj2wrfk8qvAuvYJMITzzZx68FB8sPedllzxCUTG8jBOaPFd8wjwU9ja8CImfO80fnryXRzU5xJGtvMt2CzzhDqW8MXACPXBPt7whjgo9UIemvFrZ1TsSx8M8Qz97vF8siby5hIw8SVGcPO+1tDxG5Hm83h8RPKjXwjzsiSw7ARk8vHjWjjvUUl08bbs9PR1TNLoiKD478zXqvASfnzxPySu9QTPLPL4NMzyZbI+8Wc2BvGaNqryhfqI8JymrPMJPCDxqIUa8IuOQu7iGqbt2QA+9uVdavPm8yjwaAU48xPYbPVNsjDwqzpm8FmVGu1NHD7x8gGY6GEstPH6i7bvopTs8g45uPHk6eLzGK0i75AyFPCS0Jbyk51q8u3GMO7R1OL2P0wK94o4YvPefGr2HVhs8csLqvH6o2ruya7O5pdiCOaAxLDykqum8/8k0PeW9eDyQcbs78iLFPAGtgjzUSNw7+Zzuuxse8zxwRD688SlUvDXTZDsepzS8vCCRPBBWwjng3gM8PiOnvD9oCbyePwg8LlCHPEVzUzy7zMW8eiruu06utjucXuO8FE8bPXrrq7suJdw7KIjWuy8YB71xVr88Kpm0OyLqAj2vUjw8n+40O5o2rzydDeg838DIPNqlB73AnO88sZZVvBbo57y9BQ+9dcHYOyGdoju8Ki28Hk3KPPYeG7uyfqY6CU/fvEeDBDy0GhM9cJxVvBlt3bxZKL67ZUL/O9cnjrwJqlw7jt1XPBA067vHLJ08tJxrvHc/gzw6WHU8euWlOm6JujtS98y75jMeu05Akjz2BSW9AccNPH9t2rxj8b48UA+DPDSLSTyh7Lq8aFMVvIFMm7uI1Iq7MGULPcYtZbwkVoC81xxkPAFl8bvjP5q6T+0yvToWBrw2dZe8bJn9PEjjcrw39eE7x95TOhG6ULuR1ye88vDbvOezJjqgjtc78CS0vMhq/Ty3hoM8zVlmvPqEjzsOgOk8MAtqPJPA8zuNO0O8p2Y7ur0gibsp0SI8IbSJvMV+RDw28bM8o+vcu1dHZrsvq+47A0Gwu07XWDwZnIm8whJmOlkDPLyWvdQ7U+bnOwywizxzxq88zJG+vPOpaTsy9d47PV+Su5fmXjvvcqk8/ylsPH4rLbx4C+y8UkIBvV3jQTx3WBk8rbD8O/+xrzwb4gq9ACKJPAl+TDwgyc28dtVxvLaNLbypnXY8LhwpPOno/7wis+I8dEgfPR6wVLyjohe7ONcLO/wW2TvoLBm93RBiu87ijLwyKPa8tUCGOpwhHjxXHC88rZszvNJPhDxpLTY9M+2ZPOBxCTxqM1S85MwsPcF27zw3FMq7PsVjPKj3hbsaERm840fmOTFN9ryZrP478Au8PNthDj13drg8vJzSvDtuqbone848MnIaPSyXbLxwmhS99W7dukKpozwRUJI8O52lvGGBzjsylta8tpLLvA1HG7305vU7wuoxPBpUnryT7O47ZdnNPEHWQ7xZcXE8EwiePBNkN7x7t8S6Kn5gu0PQfT0JUBg8T/MeO7kyvrsIE/C7x5oDOf9FuLzQgK288bJ9u0gi1TkZzyU8lYRBOzfimDy9x0U6kG5MvHy0OD2W6yI9nw7LPHeVx7wMWN67Xe1yvL9rgzzEt4q5K/KXO5ibGrsucts8ADneO0Vo3zw9CIG7SyQSPMzuVb37oUE7uBgdOdjr8rtpva48nKnoO8DNQjy30Fi8tULnPC7SxbsK0q076MzQPJlcET1l3VI8fZm8O8X+Lby0S8m7yOywPKmgyrwxia46L2sZPeM7sLxWHfA7Mq20PAabzrzR3T68NXktvWomrLy3np28FZoBvZ/sGToSJka8Fo+CPP05KrsmqLA8SWWlPIv52rxL5YW6OrqwvPashjxeDQw8YV3Nu+0Cqju44hG9eyBWPDVvvbxtQd+8wOlvPDSFDDyEKFg8JrXTOjBlBLybIxO6xzkMPf6jj7xJVBa8mxBtu0mPKjzxDW28g2A8untEw7zvqoQ8xBaPPHsN+7svPRs61sgpPWeKXzzbp488KDCJu7+Hjry1O6y8HR+jO8dggjwmyWk8fxPCO1A0CLyrNgy7eW0TO/jBkjwR2Z+8dyX+u/B/GD1fSJm7bL2SPAKLf7xDqcA8fK2PPG3/r7v3FoE8dbxLPFt7Sjz/NLu8LqPjOxfvAjxE46o8ZazAO3wUaDt6z7u8x25jPFcGibturwi8lHS6utULaLqcDDO8CS9rvK+IBzx82608WU2pPI6bsTyNcc68DkBTPEBZzTsl2wu8jc2uOj5vJLrlXq08IcB7PIJRSzwarlM8GI0LvDu6ET3IdJq8Wbf5PPOkabvX8xm8vPvru8iEGj3YL2S8WIgAu45KyrxIMxk8xqYGPKiB3DwQgIQ8iyzCPOl3DDt4dtY8aCoyvDFi+Drc8is6R3dWvLES07x+dJK8kweePBy7TryU/wE5SWECPGBYoTwpgt47bQF3PAtu0jzoraY8elBwOxY3PLz2Dqi8wcM7PICybTyorMk76zOuPJoQ8LzT76a75O3zPG+IODtdNce6EbQrPEBCEjywhRG7veDvvEzoMTyCeqq7irSXPGVEQrxjQn86d45MvF22o7xD5Ow7JezNuesyCT2HJJQ7rP0avKB2AzyL+su78igYO4O76Dvqsik9mH8WvMiYQjsPk2g7GiqUvHk4HzqORGy89R0jPRFmozvwGz68Y1ltOhr1erxWM508CQkvu076EjuG0Cu87xm3u1gKgDulogm8pk21vMrWJjwyGnM7/DO9PJjdLD3S2Nw72R/VPH2moDwHYQQ87B28uw5drzuQM3a67DSVPNnMFzwUo/K5yfCxuUQH9bzHGK68zAQ2PbZTJjxAJou82xCGO80i+ryD1fq7YW79vEO7tLqfn5K8ZZ4cvQEvdTyg2ko8Vcvgu8GdXzwWfQC9EM3LOzdaDL1dEIO8SyoeOndTbbzuZDO8ptxVvNk/wDyPZea8W6lZO+dJqrvUXBo83wfMvCj8+byuJHQ8RTDzu6Z2QD0u6wa8wW6wu/QCCrxi5Oy8UJQROl2xUjzp2hy8MBiFPPr7zDxScpS7yejBPAgFDD1vlj26znuPvA3alrwMXgi9A3MPPOrsvTyuf/6890D0u81DZ7wX6z48+3H2uy1WGjzFVRs7MpihPB/TzDseUxc8I3uePKXZeLzjunw7xIO9OwIygjzGk7M8n0haO1UdKj0FjOM8i10zvIytAj0YSdO8j6OPu6CwK70DI7g7jhMPPAjNGjzt+F68IPSZPHd7HT3jhJE8KB1cPEo1ZLwQtRa9cq3rvPox2Dx7HpY8UbspvelGirx7N2G87gwbPGG627zI1ua8MZNlPMNrHbvRDiw8F6vpO8UsnjzA9O44IYM6vAT8BbvhIRW9nRHmujsdCzuUJMs6JWYlPe98Urq0EFM8wRg4uzKbqTwDp345tF3KPK322jzntCy99kXSPBPLwDuXyoe8KloiPLwFHTsl4KC8TTjRvMWhCz0Rx488OGGNPCVTr7wKiAc7taNTPImzabpPMgO93fJHPV3CDrxsToE85ZORvIrqET3l/za7pFiqPDvgTjz5Qdo8dvOtvF//Rr1Fzre7nYGRvFqXXD3PWXw8VKoQvInGJzvOQV08l6MIPPEpIz1PFQu8H6AtvONIurtYSgK92MbAPJC1FLu87yS8ThMOOSwtSbwofCW9yQmMvFB2obwwJxs5WxXXvHPR4Lwnx7+8f/sePMI/m7t+bZo88KQEvZdRjrvLDPW8saRXvILp67l9L3m7fnbDPJWS9ruGsne7LSrPvNH27juBmqQ8K0VMvJiryzxirAC6dVHSu7rfGLzyrQc8jBAVvYOrnjxuWiG7z3OqvKn5+LsoPlq8A+j0uyTB0bn7bug7La5bPBd/Cjy4ghQ8yGqJvDfZ+rvOwYc890UcPIn6gzxfwwe8Vzl3PBa/HTwUhYO8gHL3O/IzhzwQzUC8P/BgvMlhwLwth6e8CbkIuzn+uDzL8Sa8wKfnPNUpRTzJDE68gFNXPBVpjjykgRg9Bv6hPE0eVLumKxS8kpcrPR4WU7mVbD68CR8pvRoXJ7tfX567euDiujAPGrw3HQo8N3eVu30pgzwBeu06EoMNPFdeDrxa5Yq8S4YrvUAc/DmFipU8vrI0PMd7AjxXvuy7Ug/svGypxTvMaCq8hXnvPBwU+jyrEZ879RLdO/P/DjwqgWm7xJwxPLIhDz0VRMS8oe+Puzv1eDwj7xE9OpLsPOSi2juMVLY85WNBPAWSx7wri1C6BV+2PJnfIr2bfnG8BwZpPD6QyTw7OcU8jouaPEe/Bjy86SQ8/SGsO5wVxTy+cjW88D7MO5yJsLystty6CSQEvLmZAL0DrrU8p2wVPHgwvzqH36C8KN4lvf5K6LtIbMa89kDuu46vZLwNlew8HH8wvPOurLwLwMY8eTo4PFbORLtbEo06f8e9vJVwW7xq2RU8gtEvu3lK+zwY7DW97C2/PHPTozr2f0K7mnheuwYvLjzXdAa8T1CJvP+jAD2/Gxm7TGn6OzJIarvmqia8ZMDYOwOKUjuf7PC8imTJvOLMnzy4Td476na0PGttLL2exwm88yUqPKOQELxbv628s3x9u95YHbzrVqy7tlw/u3N6njjy17k8dz4Auj57w7u+yAa9hq1UPEJYAj1Wznm7wSY2vexgGr0fmwy8wcSqPFNMZ7z9oEq8aQQyuuW9U7yZk0C8XCqivLWf07wemDq7hwMzPHEyLDvxGFK8xyihvEgJdLuL7Sg68cwivFcg0rsIv208IiSgPJrJvjygKYy8Cud2vDYENDtGGJ08btPfPOj94LwE/BM880ShOyQsUryfjh+9mpcLvUK1BD22lI+82pITvEzBlzyLu4s8GMWvOhtYPTyGih28SvChO+X5Bj1sU487oP3wOyIrGbyYW6q8Ns/Zu0Mj17yaU/C8gj/+vOfd8Tve8vK8TJH7vJVJWDytm1W8YlkqPeSPojvOleu8HhpBvObShTtptgy8LpfDu+awVzyyezW9xjABvUYojDuatby7udrwuyAV6rzVqdU8FWWSvJTdgTy/KcO8vMKDvK68DTv+dgK85OqCO+GqRzzNJJi8XMEEvUcPzLsHhoU7IYg0O7icGb3rddG8s+FlPT0LjDwozqM8UAuJvJt3QT2DIaC7OaxwvB4UzjzNMKO8JMqIPIAKzzuasn+8wLr5u98FLTyHtPg6lOEKPe1OnrwVpSC8Wb83PJOHzrxxmhC8hXrDumno7zyadVs8RDwXPOOi6Tsm/+U5P+ZDPd+qnTyjW6s7x6+tvPhJSrwDLQs9+MrIO4BDBL2z+fk89x+uvCtqAb1wKo86yLlivNuG3TpH7Js8iUHtu8tgjTu5Gts6TXmWO+Gyi7wzTTq8XO4aPb6cL7rmCw+9GCOTvP4gGTw0Qz28biGIPGcl9Ty0gk27778vPa12GDw08Ky8FYlsPEfqhrx9hAy9BNuiPAcZUL0QSxw7G8c9O5cHeLyV+p47OB/UO3iKu7vVw006angQPGz0oLkIsxK9QBguOpyUhbwScqC8j2JYvYau+rsrMJq8sE+WuxsOijz+7ym8pLEkvHH0pryg0jO80/zTPM1KHbsEyYg7gF+PO0bPwjr5U5U86iUDvZ81MrybuAW8/mHjvL8RqDwoFA49YtC9O9urXTiJFQq611rIuyC4tjsbHBW8g9ypPPoT1jsn/+y8PqCTuiNHg7zhKoc8jBUnvdrdgbulN3C8p4hsvLCWHz3N65a8c5VFvPGBADz6jgA7RjRXu0m/Xr1QMpU8sQKSvGRXczzIiSe8W556O3m+8ruBeuk8ECHQPLPh6jt5MqU8J/Ejvc+AyTs31VU8E1B6O7L4hTxgxRQ85YXJPPNWljtIyNs7E5jxu0Gky7x6O5c85JQEPSX8C73smrq7/CP1vFnkpruO2Ia8r6kcvLYuXbwvhIa7yy8vPBX7BjzHYic80VW3uwE6tzsqGGW8wj5VvLRXq7zt1Zi81kxnvD0WDbvE/AU8Vi6ZvG9b+zxg/jI9pZqruwFsPjsGOje7r88IPZUqKjxeWOy7hRndvGVWB7xJxGi8Y+v5OzUqQ725AIG71wdEvOxxq7rcE4I8sL23PECaNzwXMQC7cVJlvI9Kizs0JUS8lfFsu2/KrjvpOSU8r99aOkkrhbw/cli8ukQVvUuhGT1sVWc8O/6YPC7Qp7zVfb+72WfWPK1E8Tzy8qk8TFCMOTvrTLzG0Xg8XcYnvD0amTvj1Ga7fYyvPKiprjyGYga9XrbUvPf5pDxLj+Y7lJW8vCtkEr0hFkw8528TPBzJaDympYm84D+XvBNNhzxoTl08d/3QOxBW8jzfT0U8RzmbvAPWnLxE27K7/d2gO4FJozwPZaw67zY8vNKWmzyQn+W8aswNvaB1YTxj+lq8fReKvFQEszwLV0Y8PqLNvJFkCT0Buz88qT6UO5zh8jxPUts8fYVwvFOAmjv7Hr45gAckPSQUKDyAdEm85UQQvGQRpbxjZJW86E6JPJw3QbwJ3Uk8KwKvPJ8RErxv0bA6vPERvaP4+ju6bBe86AJku4mIGbxVQsG8fFx8vKelKLsv2qE6JcfrPLeO0rxThDK7z7SvPOdjDz3th348V43QPB8QmrwqBK28gBsZPJyvIbtEGvE76ivwPB2UzryXOwO8fLn0uuEvwzwyzQ49VLHzu67QBT0lf948etArvC930bqhpM28h8svvDEhajzaYKA8eNEuPGdUqrxIxrc8bcFVPC0QRjudt9w6AVm0vFHBzLyPgzo6ESW7PBTgoLzm+yO8wgOfvA5BejvfzCA7p2AVvZ/DAbyfe9w84rTeOxahibuM2Is7b/yovDPA4zwb206774QjvFDfLj1rrhG8w12uvKKJ/7wjwQo82/09u2DWA7wN3ZM7fOH3OgVHIb1DHNq8TICFuujS4jshaJG8Cv5AvMl6q7xIOHk9Cs+2vOilfjtSBfC7wOl0PHX2Y7xkbXW8J1/UPNaxID1DEdW4bXVeO05wibzSADc8XJgvu+CJpTmJ41E8RxdYO//gMjpxRBs7kYuwPMoUszuIWSy8e7zlOywhM71xpCI9bvsDvVrlVLv2Gx482oEyPcKTcjyYvJM6KFQAPGmHZTzJfMQ8tpU2PDGGQrwNbGu8Id4FPCZ7Sby+aTQ7HTeUPGpQtrxtbbS7GgDgu3UDgjxZD7u8W1fyO5UbgTxkLi26Zz1VuUykBr2FwLI7VUvmPJCJh7tR0ia89/XTvFdRBrw5wrW7fCwkPSl8xTovBns8d0fHPN3g9DosD4k8s4WvuxFGlryDM748QL1uu5ShHzuZ/Bm6Cii/vB5h+Ttz1DU7r5qRvGcxgzvgp6q7822uOzlHabwB7CO9AVqru3CPx7wnJAY8nnJEvC7mmjycYQW9q49ivEjftLvqYKa8cg8mPPuwSTkV+I48TKkjvB8yzjzdcVW8MxQkPEHPuzx47Ee853iOPMrtOztq9568Uw+sPMkqpTsQK7y7EMAKPNbHArwjJVu7+vQ2vMinxTuXVCG83eQDvIywTrz/xM+7dxH5O35eazxDwMk7hLyaO+4Ctrw10Ss85FgwvKfQ17tiESm9VgF1OwPvpDuiTQQ8wSrCu1RVvbxtqok78qQ6vA==
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 3
+        total_tokens: 3
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_chunk/test_chunk_search_with_precomputed_vector_skips_text_query.yaml b/tests/cassettes/test_chunk/test_chunk_search_with_precomputed_vector_skips_text_query.yaml
new file mode 100644
index 00000000..984de905
--- /dev/null
+++ b/tests/cassettes/test_chunk/test_chunk_search_with_precomputed_vector_skips_text_query.yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '96'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Vector-only search target.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_client/test_client_create_document_from_source_with_title.yaml b/tests/cassettes/test_client/test_client_create_document_from_source_with_title.yaml
deleted file mode 100644
index 3ce22209..00000000
--- a/tests/cassettes/test_client/test_client_create_document_from_source_with_title.yaml
+++ /dev/null
@@ -1,42 +0,0 @@
-interactions:
-- request:
-    headers:
-      accept:
-      - application/json
-      accept-encoding:
-      - gzip, deflate, zstd
-      connection:
-      - keep-alive
-      content-length:
-      - '103'
-      content-type:
-      - application/json
-      host:
-      - localhost:11434
-    method: POST
-    parsed_body:
-      encoding_format: base64
-      input:
-      - This is test content from a file.
-      model: qwen3-embedding:4b
-    uri: http://localhost:11434/v1/embeddings
-  response:
-    headers:
-      content-type:
-      - application/json
-      transfer-encoding:
-      - chunked
-    parsed_body:
-      data:
-      - embedding: U4DtuI+VwjoZJ3273DLDPO3j87lGkSk9sWacPdgdlbyIBg08yl4QvLd2gbwM06w8EC8oOxwoS7wpjAQ93TODvX4XvTpBbDi8JkAlPBQ5hbtt5Gi8KtAUOwF1AD3qimG9WgEGva3KHLwFMcu8BZKQvHSN6jx2Ss68dOjXvFYuVb2IGPo8Zt7KvEVPiztU+Zm8oNGpvF9BOrzX8KE8i4GEvEZYgzxDgZ689xQrPB4tPjzkJz+8T+QWvI1tRTszopI80hHTvGLDnLwqxco7kv8fPH6yE70H3w+93yaTuxOfgjqzKpO8+S/AuWkr87zRSJ07nsC6u31AJbp9JYW8mxSavFz7L7uIvqG8XhQPPOHm5Ttysro86eQpvEc51DzPrXo8FS55O5EeDj0c3O+6TzQQvUD2JbzZ7m08hDqRPKhqrTxpKow8OcaKu/NJ1TnnFwY9lLHjPL6gJLz+Ag08wdqeux9fLjiyKYA8iohdPHwf8Dx5goe4rqyrO5hrDbucpnQ75AeXvDcqp7xUTYO7m4CbPC1CgTw/itI7S5LRu+sqobqjbFG8ree9vIaHZLxcYpA8WcJ/PBj7hzuA9DC8r1AIPHS8NDxkaUS7uoUDvSevrbySg7e8SozpPHjblzzCpyg9MZBOvJB9xjwXLd47QhevOvqwHzwgU2O8yhOwOsms/rvTTpI8iWkBO26aCTwUG9M6ugFGO5mpt7vFnPK7bBU+ugW49DvkgHa8HhWVu8CliTzNFh86scN3u7sEfTz0BxE9T97iux+EXL2Whgs8XXoSPR1o2DuNDWQ7hYD3PPSS57tUsLe70oEnPOVjrTpsj/I88KSavFienDzRU747xiWKO2lEMLyGaSQ8B6oUvU9KsTw7SgA8rykRvBuLobsSyW07CUuZO52P9rzwe9u7f05XvGxtLTzaOiS7coZJvMF6oruDnf+8xHituss7q7v45Kw88HJMOzKC/zuwNVS82SgMu88tlzwxoE48/z6OufwVdTu3HDw8jEWYPKp7TDzHQeI7VZf7urogmjtOBoe8Cb0cvez2S7vC9yq8AAlRPHJ15Dz9TBo7ThVUORaQOT2aiNA7dqoKOys4oLtACM+6JggTvHw4qDyYv828ZaJtPOVAhjzFxI+8JyG3O6a0LLxE7lQ7VkC+vH9Z9bsbG7w84oJwO6ZxnzscowE8Hb9bvIeYczs8PkG8qBQCPFxrbLxSuAS8gZt8PEuN0LpfUv88YRTpPMqrG7wHwfC8bvtIOiodHzpZ3KW8ezWLObYNArx3Bbi8uiN6O6p8pLxSjJE88ykvPHIoBTzuOF68WGS4O3CzwDsK9za8sIUdvcLPE7xTvRc6L+LWOz0HEzuOYtc8HN1ZPNiMSzuFrhG7oDwjPDGEJzwFWL27pycBu/vSfbzPehU7irUVvEpJlrzwqBk8G7SHOeuDv7sYlHa8U0GoPD7knrueD4g86FaEO41hH7yvIOe88hc+uyBhmTyMSgY9hrsIPYsJ4ry1oj47/Wrmu7BSCztJO4288wTtvJZINj3nO1Y8BnZ9vG2WYbu7kII8CF9ZvE5pvjycF6a8zTmgvAk2Bj3HMp08N3wFvBhfT7wim5M68k3QuyDqd7z2StK8rzuqPIKpgDqMW/k7IDcxu7NYOzw8kjI99ddBvGpgZbwyWRC7doUMPFmk5Tse92q7hcaxvNaaCDxWBsE6Bm8tvW3DD72vB667GEIsvVh89bzUSUq8StqHu0Q87jt3wrw8+bKYOyLcG7yRPkg86O/bO4ovuzywxW+9uSxIvKo577sEQYM7Knm2PEyVRD3TF9c8UIDTu/MhqbxXune8rMP5O28k/7omMyy94NehvPg4hTwJUqi76ncOvOjjEb33rMC8Xebouw+DRL0Ed5i7i0cnvPQNDj3jo4q8YUxiPK5Sfjx3uLs7KGUyvGxnEbxYVHW8/ciBOz2/I70h/QG6199rvIJyMz0WYo+6lRcqvUqiljyA4WC8fKnaPBK4NTrnh8Y8yGL1O1h6XjyUMkg7ED+xuqwk7Dv/W6A8CJZ0vAjsAbvVtAM9tBS+vD6w47t+Xhy7DkCOvC2FET0AVdW7TT0cvOhOGLwyeLA8/HpHO0B3tTslSKo80DUgPNQ31zyhQb48JH3Dut/zDj2vHTw8bEITvTvAgDzdLjO8dDmdvHWtADqK5DI93zKTO4qZILwUEzw8NiabPOGenzxgYTe9JAcgvBceoTxCS6Q8RMunu2EbbLwhSSC8qrMHvFPHsrvyAxq9HsmRuzw9Z7va+rw7Xl8hPLKNFT2pFou8wDbMPLHBlzq1HAQ8uZKCu7SDJD1vjPW7V3UFPYXMZrru2C+861ssu3UKtrzhOsW8z+gCu10NaTxD1C48AJV8vE5VODuBYCE9nF1lPGQ+H7q7Gu+71wi6vBw6a7wr6+2766OUOx9XnLxxZIA8aVX+O9fAxbxCzhi87dM9vCGJiL2VchS8Tx3Au2mId7xpY6a7eC0FvZVrXrz/mWu8qM6oPH/bDD1F9Wi8Qjk7vIxHULw3gj84w27JvKA7nTyowb08a7lTux6YdTmusug8JbNEPRHnGbt8aZ08WP0HPTCEoTqW4g09C67pPCEqBT3pZdw8X/7LvCNVJTxFAD08OUeIu7zB4jpWYPW7l0oMO3vgpzxk0ZK85QVLOzXIlzzAJRy8ybl7PP/Of7yxDZy7KG0PvYa7MLzUeUE8soo1vI58Obyn/Og8wLulPDKftDwd4hC9hicxvZueLzyhA1K8yI+/vLe9YrwNCGq8wJdTvA0wAr3EOci6k9zHPEJnULzvSGG8S56fPGFN8jwyXqy8s3awvFhEmTw/0ZA74+CrPAk5Pj10+jA8FT4OvXhLhryP+3U8QPF3PN2phzuj3h+7HLwMvCFGmTyLNRU9BtylvKYiyLochxC9ZY0YvZm5nDxMMJ28S/u4O89hIbsTcqi7BYPlPOUw67wVG9+8RYlsPWj84Lm69aq7KuFQO4+iL7zTYEc85gumOxLaCz2d8DI9gljSPNJqaLzOjaO84F1mO80bXrzKdiK8/wGEvPpHTD3lOg+7YdHQPC8MpjwqFfk794yJPM1eHL3Cjva7p1IDvKcLXryJ2Vc8iD+zvId7W7xgMUy6MFihPPEjaLwINwS7ZJfKuvCmVLx/PjU8lUj0OgL74zsKaHA6zb44OxEnGLxaOzW97V89vSxwb7wWAZY6ZVn8PGuHuLyfpe28ErdWPL7RD7ypkeC6ZRsAPTlOtjsfbyK9e7ijuwQhYTy097M8o5iDvH5Bbzyawue8tfLWvIh8+rynLA29P7LMu23JbLwFn8K7aSz8uwmHML0sJiG7DSZivO2rVr1FTwC9RTgKPJimfbze94m6Lq4cu7dPojw5uFg9/O/uvLiy6zrHlJM6SM00vc1IOzxFNJ48QIgavX6K6jpK7qQ8iyToPFJyAT1fc3M82Lo+PIy4Y70fWfK8OFGDuww21jz+gD+8ZQGYPLP9xrrZ22C7dMiROzjmMb27ThE9wrieOy0xCTxf6YQ8MiEJvElrS7ygQJA8C+4Buo+XT7xjFN08e8k6vT6GybwlQcI8c6okPdcodTxYmIo82fvAuozQbTxCavA8i2U8vYNv1LuRofS7VAiBPAzkjLvcroK8BcigPDoLUDy1R9K7JLviPL83x7vwwIG8sNt2O54ArzytqyE93YycOxE1JzwpXAE9azCGPCyFlzx3apU75t/SO0ueFTxat/q8m88Lu5GVoTskbbU8ZdASPYO7qrvSHHU6I8PmOwSir7snnr68t+AuvANgsDwAXnq8Z5R7vFMi+7qGOHe77Va2PJASGb0tKRM8n/27vDUnv7zxSkA851KTuwZUbjzdYIu8Hqb3O8s147tFNCM8i1WSPNBBeDyKoHW8/0ISPZTJDDuK/U28LerMOyfcPDxUs3a8H9sFPNAIEr1z0KS8DOWcvBE73zyUBb874zptPCx4Dz14KDw8FBKOvA9KRDwPHq28F3+qvDwpqjy/W/G8G9+Bu0fS3DzdHtU71DtoPHK2kTt+eSw9ce+yPNHUEj35/Z48RaVNuzbLp7q6SVQ7uXl7PD14ljxE6qO8cdKGO6jrrzxy8lM7r1ITPDvgSjyeqRY8zI1QPD1XujzmATY7ntoHPU65RLywXRy82mqlvMqQJT15H586MHqRvNbwFr0mnPE8APwEPJfVVTuilmm6ZRMYvZu8bbyXFYy8ZNHrvOb1Grx9dCA7RoXgOnAOErq/dt08m/wcPGmM57lbqxu9jms7vekyrLzbPFk7rxWGvFCSYbt6PU89LE0PPTtA3jxmkTU8nForvAkt9TsyLio8+OIyO9Chsrwveha8AW7WPJFqiLwtsJe8b4/dPKxs4rpIcBe6hOglPFqBhDyogqA8/2AbOke4TrwpNg075rh1vA1+kzwcwI28U3TEORMamju95Fk8aIurPMTviTyH4UM8NrOsvGxUpzp9pjw8dNApvMFm87yRsMO8EsZsPPbdl7wvFJk88tqtvOoGL72QVxc8KqUruznnoTwAFsK8gY2PvKE25jzCYzs9KiMyPHY2l7mZVZa7qLrAPJ365zw0oXg8a3iuPB+0q7y7iHs83mjKvDAYjbxkkza8/bmDO9WuFL3sD9O816uEvJSbJz1uREO9fF/Gu3NxfjwXKbY6oE7qu0nWDzzqpyQ8MBoFO9wouLxh+8u8FTEEvM26tDp3Wks8g1FHPeyhpjw28WO8VNJbvDQgNLxsWx09MsUTPftdPryivBK8E2uqPDMYXLzMbcO7T8WCPDzhkrv2r3G8sJQ/vR9kXDw4vpu8WR0+O3Un+zyJdrW8HcCDO1k0cDwExbQ8kqA2vezFwrsA1cG6tnWvO8gK0ryo1Zi831vWPImGLTtmd/68pSZAvLCJQLwP2ts8gL0kvaG+17wNFqg81rqGPImJr7x1vhk8keIjOsu2Qzy4w868zAgJPCeaM7yt7IO8RfrzvJ2lvLxzR4y89QKZvPXIAb27QQc7rWlLvKXx3zzjYcw8h7ymOUF9bbygPbO8JEDkO/p6KD0JMj28GhbBO/4Tgjzk4yo7QTk7u0IaizwfUQM8UQ1nvGaS87vMCY68yZyau6ThLL1sXYC8YvOoO+eYFDy94ii8fN3Hu8xlObtLjw+7gn12vBCkdTwCTGM8AmBXvOAI07s0IrA8HcBovMiNxrwfylO7/oWgvO+hJzyaVW277QTXO6CeNLs/t0k9BsotPb/ZuTxjBQO9wKkVPPsGqbwaFwa928X0PEykUryLCFm7WzHovFqkQLzUx/K74K6evA8ZxLze47482ObFO6fX4zqaGAM99SqCvFwa0Ds+YcI86jVMPKmQ/LwQHJo6EmwjPeBJL70inxC9j+VwvbYrCD3+rzA8/vqpPNCwUTw0O7i6cqwzvAXMX7sQCI+7bYaTvNGP4zuaJMM8/r9GPB4nFTvU5Zs72IWRvOqtRLwyjWc6dSIJvcR/grzQkU682LQZPd2syzulkhC7f9RmPBc2EDoh1qm7R06/vNwoErxyBbk8KuDfuxFaU7wmVSg9PFfCvNiKtLw5NbW6ARl6PNF/r7zQfVK8JRHyum2UmDpHdd48WybKO9I3/ztiJ7a7Bn3pPJnuwzzvMEI7aamlu8NvFDuNJQk9QW6cPD+9DLwU5YA8lAB3PP2ahbt5nRW9FObSu9Vcp7zfSBI8xdZMvOx5kTxT6Lk7MUSfPC8p3DxyNPa7BPROPOPI3jv0eFs84iaRPE44PLyiE848l0Uxu8Ehi7xJnYO7Er8CvYCVdDySOny8d8VpvDmp7jxH9DS87pL6O4aJsTthLfq7jSbRPMMSkLzZb8q8s+v3vJgQN7wPVuY8sCBXvLLT0rzPAZe8Jdrvum5DlDwSaoI6hIIhvJbrqDyFbqy7EywKvOchNrwssM48qiT6PCWgGry7GoU8a7CavMtvabwC2IQ6MPpqPKW7qzzoqDC8WFcHu9QarTwDZRe8UHvTvNvSsTo1fgK8y5+du1BtPTzZPVa8aw1JPKu6mDwwZK68NV9ju+6C7zofx428JdTWPDtVp7s1PAC8bE9CPfR1ODzbFuS8xtSyu8PAMz063Vo6ksuvu6l/ADvk9N675GQGvXGolToxH349cziivBTi/DwI0be6QmKZu8HIHrwR73E7jFAaPGueMru6HZ27yIBtPIbuCj3Poxo9SDfFuj/DrzwNjCm8uRA1O7RrJz3DiJ+8tSpNvAXi9DwBZCa8ATLzvLcsS7tHOZq6cwn3uzroJ732wBU8auvVu7AMwTy/zOS6LJ2XPIt/3rtElaY8uIp0vDs1gDtjOg29Mp1ovHIJCL0RAjO9d4nOPGXxhTtKrCS8BgENvIln6Lz/+CU9YXtfO//o3jtmycS8g/RAPDEco7wM61M8LcDMvId2G70uU/y8hk05vCIIJb0M6wC8T7exO83vuLwU64I8WUx6PIsVEjyoe008/BkuPe3EWLuXi028SsNavOXkljxobUS8Eq+Yu3xoWzypB0i9BpgPvCMR0DsTpc06WL//uzNSrjxEqAi9ibVlu730U7zZxqU8rI8SPRK4ET0aggi7cjyuvNuXIj26T0A9CVb3PNOHBb09OJQ8YTHVvPwi67zQ0Xc8s4ZFuxEkkTwZGHU8lhGAPMcAwrvUPWg92NJFPMwXDL2tjNM7i3OrOlNi1jvoXJu8IQfuvJjYGrxzfRq7UVRpvJ547Dy1Z/G72P3RvG1XsjvwSeY5n+qBuyLfbLsX/l+7lA6IvM376juKkMS8563HPKk1AL37UpI8tMZ8vHm5Bj3od587K7CJO7UlODxoZ+O8igwHvLwpzjv7Ih68ky5bvJAw1bySMoK8SKIoPeiRlTzFsGo825YLO8K+wLwyjVW9muSpud/0v7sEiz298WVTOlEMzjxliR28w15yu6WK8Tyr3u28QgEwvK/dkbwzcDG7x8qIvKGXBjzLNFO7a67XPFKCKjwHR707TV9IPDiGLD1MSYE8kD/DvGWVLrzqGVU8pxB1PKyb77uXGfw8ULQwPWjtLDvlGeW8fQaKvHdcjLx42KW8CBmWu4Wf8Lzcf0C8E2I4PKOitTvGXKc6bFa7PD5vL7yZlbY8PPlQPJv5TLzlhVs8pcQHPTvCHzzgIS28duBDvDGmQjyYNBq8CGmhPE+L5rx28he90suRvCtK97y4tYs813UlPfjUWDy8xTC9NPglPNcMhTwEalu9YxSpPPoLnbxWKAy8K6YuO3a2jDwmPxM7NPdwPOWnz7p8qVm8iC4rPFQL3DzgqgA7CP2QusOULzwm4km7+KjlPFuGOD1U4hw8PrsYvQfogjzkBuw7M/7jPPQIWLxJPW08SfxDPUAOTzzdR/67KYxbPHy86LuxZSe9l17YPKIkVrvh+XS70xFPvBfh5Dsnm+Q8UiYNvTP8eTvtkBE8Yr2TOjBaWTpt6JU6N4mmvDglcjy4M6M7Pz5pvBjQ7zykSA+83NczvG+yCj3rDFg8OyUoOxkcjLyaYhU9RLyevEkqLL2kqmU7soHivCFp+rwI/9y8u+qVu3S2Qj0PyVC8KJP+vKjNWbzCue68etCUux+BsLyr81W8lIokvWETZT2MBRe9QKA9vFl/rrydO8e6bZCrvMcH6jwsRpM7XGjJO3Mjv7y9BiK8xpUQu4t53LxiKD28z8QBPfYTBDwNwUo8uEU9O4Us9DzMJ5s8/xrKu0yyh7qq1507uQqgvOVwt7vXP268c8I7vJ1GGb35/jC82eFvvDVfT7298Z46qGG1vHEelDvhjlI8srfVPJIB0zvVzo+7OTOIuzfwoDzfEZq5KOLoPP1YC71R3eU8cmMzPWMJY7xmuZY6VQMkvI177Ls3tvS8RG0fvQk24zxcRW48/7PDuuPUJz1wKpC8mTLSOzt33LxcuQM8j1BSOkyeBDwval070qDuOw166rsaSQG9TeJQPCTGo7ye9ra8IXVvOf6DSjwkErY6r/wDPBUsBDz+a8+8hH8+PfScyDpZgQe9BbiRvP/6zbsF7j68tsbau4Q3u7zSwv48aaKdPIUhczz0Yl69y4ibPFgIbLzNMOY7eDqJu2xKyTzuvHW7kAKiPNLvlTzDUve7PCaVvNAhb7nu3n86ywhavPc5cTw39Qq7Ua+Rt1uUDzoMb7g8tt0hO5Jdm7yRw7U6iYCcO/MzczyqSU08rUciPZRMrLwLXUM8Qh2cvGdSLL01bv07HyhHPCr3FL23SSO7KdiROk3nEjya+5i7KhJUPKtFDjt+X0M8uZKzvH8xmjvsfSU944b2vHEJbLzo77i79S7wOsy6jrsxRpw8jZbkvPtf3TuDshI95y9Iu7DNRLtzCW06Hy2SvGvpbz2lsIe8T8KZuu/JvDvsqW28J340vDMGRTz+U3S8UnMEO+MaFr2zV7w8TV8EPeS4GDnk73E8YiqfvCQ2Bbt0RN08t6vKu6EoRDxHnl884K7aOjBjvrzwpr68COCyvE4g3runMUI8WslqPNCSqjoFMIC8fZhbvK1HUTwcrZg85YPWOlgxEbwdawO8T7EaPL9CArtAFCo913tFvDSbvryqhiK7jfaJPDV0Kz0pOPO8SahJO5nPEbywkoC8lvs9vRZcLrzDgk25L/OhO8kGaztWmgi97jB1Oyn1ZjyDl6S8uBK8PLTHMDuumRQ85Gy/PGZG/zu3sUg7NlwxvShoXLvjJDg9YUOiu6PKczwyi4W7tlH1O0RVwjwiIlu8j2UsuQbbLbvMoxy9XN4+u2ODC712fmA8+eQlvPYoVDyayWk8o5WMvLFPijsxXp68zq3POyZXlbvjbhq78lcrPHbaqDt1Kb48EeqkPAU5GLzlpr08ixmfu8iQNrmd+kc7IsUEPB6h0jsD6Gi8HIKzPLSI6juoxJS8DP4VPKrDL7xfbQq9mI6fO6VVHzzzpl07GI7iO8+imjwZFAc73IeivHXmCT1NAOw8EptyvLnKgrz6Q4284/26PMdFjTr6pg6881EKO2smBr2iD8y8FfvKPIWvQbyHomi9a8uiu8f9vjnbMIS8VyTMPFyecjvE+Qs9rdGgPEU5aT1UTvy7w8AzPJ2n3jwUQx28VydAvZMXjLznaqK7/qvoupODy7u49jy7O2UGPdkK1LtUSjC9fEx4u8WMRrui4FQ8VKeWPG5zvzvILAG9l8LOvNXfqTv/RNQ7sF/Yu1l86zt6ovk80oqgvKdCMjzh2C49xMgNvYE3vLwlNlI5jpoDPM1SzzzNMLs8omJSPH8ukTxE/lS82gCRvBVGxjzVgPO89gbYO6ltibyRC8+8YPYdvMS50bsnPo+53hOOu/lC6DrKnUq85llLOHVD2jqi/bO5VhyEPIO3ATzRnZk7g9fKu3Ydw7yxF0M7t/QAvX0RpLq61B+7aeDqPJ18frysFZY7gY1SO1ldmbwpNH080D4+vfAML7wD81g8hdb+uSgpTrzMos28YmQ7PZXYmrznPrM8ngY7PIKZczyr6wG8kN09PShfXzuxt6c7wkMavObHjzyEtw68z6zBO0Uyl7spPGa8B046OgYuxTyaMWC8SCUpu4aUE70eieY8c4lXO8hH5Dxt9uY8FBiHvDw1p7yj9U28Fm0aPEXtTDy3hKS83fbGPEVKFL0Rn7671KIJvYf0crzw6xi7C/jVvGSEaD2IRPU8m8f+u78bN7yGw2c5P/HEulM9Wzxbgic9Uu3zO/o88TyJtB49pp6+PPZk5byAxgw9/4GRvPTo0TtMkGa8qMKsvEPKRLx1hue7RRsCvY3PEL3NMYc8Kia6uR5qBzwynmI7rjFdvMP2wjt8xDu9+pbxvDP1vDzARQu9wfvavCm2Nb1jLus8xsvzvNljSDyOjbK6z2AUu2SydjpMP764v0sdPCpVQDz15gY81MV3u6vIczzawjA7ddMFvTok/rxDQq46ddpnO9y15bvHDLM8uvvcuozLuLuGu5Y8L2/zvLzIMr0ZDxu8/s/Qu6fy5ro7TyO8inDSvEkwBzysQgK86mjOvI/hdzzMFA29a1sROJK4ED223zi7866gPOc44zzVoZg6sEfhunh117sKgNE773+ZPEfVrzyq7Wo736STO1pKXLyVkYq8nL/DPFqkAj2bq7G81sQYvcMblzweBsg7RkboOAzRzzoDOT48tSgVPM0QUjzL7HA6N3MHPUvNk7xpod28MCbkvIyG/zqqFUY7dgODPMZVDjtO9MW8GJ8FvbF2Bjug+JE8hBTDunQVhzvA6NW7PqayOyz26jzd7HO7zcuoPH/oHLxXPBO8kwOKvEf7izwfW5o8HPydu/WvAryob5Q8ffCSO8fYw7qM5I081MwYO7EBGDxjdQI8VT4ZPHFRM7yQhki8xcIxPPLV+jucXPm8tCL2uptvtTtg2K08bk8YPUTzA7zJZJK8jq9ZvPlewbw/FcG60V9OvOIOA7vot447mkSuvOtoATyKO/O7YRhRuMyXG7x23Hu731e/vDnqsbw/+de8YFWLvGipizwT96G6heIWvRwsbrs01DO8Igqhu6zOErwqAum8y30jPHl80rwACgu72jXzO4UxvrzXgoU7UeUlPTC7ezwvt4I6ZBGsunJ6xry/AV29L1J5PNCdMrolx1O8Lx7xOvbJlzwq/6A81qfuO/HP6LuGVI285s2qPMzoF7ynI8K8fOXmO1Hz/jtQDaa6h9yzvOBsMTy0tio9cBCRPIyuyTx/uSI8vh7aO6imyjybWYk8K9EMPPIcaDvNp428LBnju4ta1ryxHva8vJLLvMwoW72sB906t4n8uPGoMDvn7Ye8nDRMuxiBu7xDP5M6+osHPHkrEjtB8Zu86xnEuzw/iTt+tye8nWTivClKGz3D0/G5+ET4vEeNYzyu2jM82tYEvPWiu7wB8uw8pVQ1POmoH7x1blq9Xso2vCSjOTxI4bK8TpCMu22rWzuxohy89d8FPJg93jvVb4e8utV/PImslryeniG86rtkPDOuczy+Mt68HlkHvCuBgzxDCZW8KDHVO44CwDwElEa8GxEhvAARrjxerZu78O+BPJSCjDygqFK8qmTCvDlTl7uKt4Q8HQyQvFWMBzlNLEo7lk5du2DkCTzVHQO91pAgPDhAgjtgVRk7gnWsvDRKuLwqvoa8SM1NOx4si7yVlaa7g1xUOmTiPbstexG9Ms2BvMm7fzw29PG8vH6Fu1RvKr1a+Le7HrCBPKYIyzw8iie8wr8WuwI4Dz3gspW84X+GPGy/gLzjFnq8HUcpOyWk6jtvNFa85hkxPPUBT7ztYRa7Bi08PUNm2DqU5P08vhq3O0wBwLyWAuw8wifNPE2AfzyzUi48isTVvJheHjwjYve8HxBmvMFqXTyxEhS8titSvJ53D7x7Zmc7GDjZO8SjrTtJa4U8Cd4tPLz/ULzuiJO8dOvquxg3wjw5mTo8KITNvK21qjzxa4o7sA+ZPHrBtbxpups8LxepO6GAqDulQj68V8jnO83otDwMo8U83c3nPFB8yjyd0DS8mSqeu0ccmTzIdVY8goGtO7JZrbxRXec6u4SBu2idtbyREgY9w9hAPfbVh7pm3K67UuMePEpQ2TwOdk68uLewvLn4zDszAqq8+kANvdJSWrxrLsq8qtgXvOQF9bkbuHO8Ej56PKsQurtufM88W68DvKoMfzzShhq6EmwIvPmSu7z/YBW9XZBAO7ZuzLtHwg+8AO5ROxJ8brwVrU+6VJuVvGGKTz3qlr48QpRyvEbkT7ycuDY9Yrn1vG/L3zzIVRY8H9+YPBU7Grz9v+28p7cju+c6o7yZtAc91QNjvH1HGz1Wyp08hhMbOkr3ljzkoQu9hln0OwZcubsSSqK8hAATOyEmTr1Erck89OgkPB5LDT1w5j883zuDvDZvczw8Eqa8Z5AWPcpng7vfwh080gfFOyyZjDzI67w6U9cePG2lSD2+mc08mSoNPTzcIrwNTXm79//9OhSCL7ynDZ080JIFPWVbjbxqgfY7OOSiPNu8nzzXo9E7B6LJOz/rAL1iO/M7eLPXOtrrTLy7ZIy83zCEvE4L6Lx3WOc8nMjfvA7ZhbzUhHK63zqNPNaLJLwT34o85xiCvFqj/jx3CB89VwtZvBy95jrUBGc80XwUPAxf/jzPQpm85PCKPPQRjjx/bai8dQwWvFBiJr235RK8viWlvCQAxrv2gKi6aZhJvHnQIT1GV8q7oWx/u6PPcztc+uy8QL8IPPhLwzs/QY07WBKIutagHbwwXQe9T6huvJPpRrw7Cq879yK5O38FQbzZDCM9ee+uu/lXtTsu8yI8KlyeuyLCljspqos8QovkvLKGpLvw2rA79SM/vLsTkjzLYGE8xSqRPFY55TyyIfS8sIxpuxodEr1Dk5o8yG2ivMj32zx0Gpw6RmkAvHFO87wFs2a8BJONvI9+bTxuzQ88h32FvKQOarsAfLY74f+TPMSX1rnSicS8vG6NvFOOfDtWuAg7OBm9O49r9TrLwNy8W72OvMGLiLzD+yO8nQ/bO7phpjzsbqA8NvkCvJb+pTwWyyI8xwE4Oy4zabtXyHQ8IL0PPFEsxrx3Zq08+45RO3GxBb12s4e8DkQxPBnNDjypcBW96kJTOw/xpzwiuIw8qP6kvM2ObDw3t2o8kyravGtwvzsbXvC7BLLjuS3MKTxwo8u7Qb+8O6AlVrx1PMk605+Su3N8Bb1Ep+S8RoqcvOVjJDuQzJK7Px0sPP00w7u4dTW3JyqCPOETLrwsQDE51svwO7RAyLvtQ5K7P3jmOxBRkjvwP6W80QIAvUubSTxYsra7/bSrvCYKUjyL2OE7pLzSvCT3/DungXo8lJPaPJtIljyNcpU86+BJPKyuBTvau8u8+2O3PNTT17uyfpY8d17GO5aBkLwJ+q28EZgLvTK937w4UcY72USkOoKVljzexpG84dWqvEBMBbzgF4q6IDGNu3bHFj1om6o8MkJ/vJ4dH7znNgi9IqsmvFc28ztHijs9WNKQO0DlNr0vkze8Q0KIvH8dyjw4gFw85I6hPPaR0rsuDJg7TKlbvM+fBr3avom84gOPPCE2xTtKP5w7qoMMOjAT3DsPJxO9f1q7OyJVmDyA4tU84CLLPBXaoLxpeJ87xM7VuwF0CT18ZJO8Q1bvOusYQrwC5B086UccPFqvGL324ZS72D6Xu1oJ2jwDUYo8NWSTvKDbbDw/o/g7xH0mPC2ahTwqbmi7WlXkuqrg3TyMoqo6WCuAuoTYqjy8T0s8+vT+u0pH0bsfQgG9Npf/u1fBkjx4OSa7vJPKOeJkvjx4Hzi6ULShPBSYRzyRhh085qBNvHhJAr2BCOE77NLqvDVlDTyd75i8Z1VSPC+edrub02Y81fcBPOJegjvtVim8EnioPDhyBTw1W6S8OhZsO3TDtbvoNDo8oJ5ivIWCLzvAaY280LKGvPcXZzyTtaQ7OFyovC/HIrt8hY48t8EWPfLhArwTn9Y6I6LivM3fEbvZUde5dvgMPIaABTq1j6C8d3wwvChQKDz79es7Y8vwumk3AjwBIjs6aIzDvMazULyKi6e79u6ZvM17gTw59BS9nsihu6oU+zthHFu97WyiPFlSgLsS16E7Ez8zvT5j6rvDXbW7aFAmPK9+RDwkU+k8cxPaO9/VFjz7B7W8WimzvHBjiLzNQzU79ysmvCDP57zT34Q8rb1KPHtIpjrU50M8BHbLuVDnUL00kZI74wAovA==
-        index: 0
-        object: embedding
-      model: qwen3-embedding:4b
-      object: list
-      usage:
-        prompt_tokens: 9
-        total_tokens: 9
-    status:
-      code: 200
-      message: OK
-version: 1
diff --git a/tests/cassettes/test_client/test_client_unchanged_file_keeps_timestamp.yaml b/tests/cassettes/test_client/test_client_unchanged_file_keeps_timestamp.yaml
deleted file mode 100644
index cbf424cb..00000000
--- a/tests/cassettes/test_client/test_client_unchanged_file_keeps_timestamp.yaml
+++ /dev/null
@@ -1,42 +0,0 @@
-interactions:
-- request:
-    headers:
-      accept:
-      - application/json
-      accept-encoding:
-      - gzip, deflate, zstd
-      connection:
-      - keep-alive
-      content-length:
-      - '103'
-      content-type:
-      - application/json
-      host:
-      - localhost:11434
-    method: POST
-    parsed_body:
-      encoding_format: base64
-      input:
-      - Test content for timestamp check.
-      model: qwen3-embedding:4b
-    uri: http://localhost:11434/v1/embeddings
-  response:
-    headers:
-      content-type:
-      - application/json
-      transfer-encoding:
-      - chunked
-    parsed_body:
-      data:
-      - embedding: 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
-        index: 0
-        object: embedding
-      model: qwen3-embedding:4b
-      object: list
-      usage:
-        prompt_tokens: 7
-        total_tokens: 7
-    status:
-      code: 200
-      message: OK
-version: 1
diff --git a/tests/cassettes/test_client/test_import_documents_schedules_vacuum_per_config[False].yaml b/tests/cassettes/test_client/test_import_documents_schedules_vacuum_per_config[False].yaml
new file mode 100644
index 00000000..d5ea4a7f
--- /dev/null
+++ b/tests/cassettes/test_client/test_import_documents_schedules_vacuum_per_config[False].yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '90'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Batch imported body.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_client/test_import_documents_schedules_vacuum_per_config[True].yaml b/tests/cassettes/test_client/test_import_documents_schedules_vacuum_per_config[True].yaml
new file mode 100644
index 00000000..aa8617e4
--- /dev/null
+++ b/tests/cassettes/test_client/test_import_documents_schedules_vacuum_per_config[True].yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '90'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Batch imported body.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_client/test_reingesting_a_source_applies_an_explicit_title.yaml b/tests/cassettes/test_client/test_reingesting_a_source_applies_an_explicit_title.yaml
new file mode 100644
index 00000000..f352df06
--- /dev/null
+++ b/tests/cassettes/test_client/test_reingesting_a_source_applies_an_explicit_title.yaml
@@ -0,0 +1,82 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '84'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - stable content
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 3
+        total_tokens: 3
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '85'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - changed content
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 3
+        total_tokens: 3
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_document_tools/TestSummarizeDocumentTool.test_summarize_document_returns_model_summary.yaml b/tests/cassettes/test_document_tools/TestSummarizeDocumentTool.test_summarize_document_returns_model_summary.yaml
new file mode 100644
index 00000000..6e46a3e6
--- /dev/null
+++ b/tests/cassettes/test_document_tools/TestSummarizeDocumentTool.test_summarize_document_returns_model_summary.yaml
@@ -0,0 +1,82 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '142'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Python is a programming language. It is widely used for web development.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 15
+        total_tokens: 15
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '134'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - JavaScript runs in the browser. It powers interactive web pages.
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 13
+        total_tokens: 13
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_flush_rebuild_batch_is_a_noop_without_documents.yaml b/tests/cassettes/test_rebuild/test_flush_rebuild_batch_is_a_noop_without_documents.yaml
new file mode 100644
index 00000000..624bafb2
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_flush_rebuild_batch_is_a_noop_without_documents.yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '77'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - keep me
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 3
+        total_tokens: 3
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_descriptions_flushes_in_batches.yaml b/tests/cassettes/test_rebuild/test_rebuild_descriptions_flushes_in_batches.yaml
new file mode 100644
index 00000000..6a87eb7c
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_descriptions_flushes_in_batches.yaml
@@ -0,0 +1,86 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '105'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - |-
+        Hello world
+        A red square (mocked).
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 11
+        total_tokens: 11
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '105'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - |-
+        Hello world
+        A red square (mocked).
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 11
+        total_tokens: 11
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_embed_only_flushes_in_batches.yaml b/tests/cassettes/test_rebuild/test_rebuild_embed_only_flushes_in_batches.yaml
new file mode 100644
index 00000000..2cdf65e7
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_embed_only_flushes_in_batches.yaml
@@ -0,0 +1,242 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '92'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - embed only batch doc 0
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '92'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - embed only batch doc 1
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '92'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - embed only batch doc 2
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '92'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - embed only batch doc 0
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '92'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - embed only batch doc 1
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '92'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - embed only batch doc 2
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 7
+        total_tokens: 7
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_embed_only_recovers_picture_bytes[recoverable].yaml b/tests/cassettes/test_rebuild/test_rebuild_embed_only_recovers_picture_bytes[recoverable].yaml
new file mode 100644
index 00000000..d358e284
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_embed_only_recovers_picture_bytes[recoverable].yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '87'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Surrounding prose
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_embed_only_recovers_picture_bytes[wiped].yaml b/tests/cassettes/test_rebuild/test_rebuild_embed_only_recovers_picture_bytes[wiped].yaml
new file mode 100644
index 00000000..a2205581
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_embed_only_recovers_picture_bytes[wiped].yaml
@@ -0,0 +1,46 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '104'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - Figure caption
+      - Surrounding prose
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      - embedding: 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
+        index: 1
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 8
+        total_tokens: 8
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_embed_only_yields_documents_without_chunks.yaml b/tests/cassettes/test_rebuild/test_rebuild_embed_only_yields_documents_without_chunks.yaml
new file mode 100644
index 00000000..6d49f289
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_embed_only_yields_documents_without_chunks.yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '95'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - doc that loses its chunks
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_full_flushes_in_batches.yaml b/tests/cassettes/test_rebuild/test_rebuild_full_flushes_in_batches.yaml
new file mode 100644
index 00000000..65b288e0
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_full_flushes_in_batches.yaml
@@ -0,0 +1,242 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '86'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - full batch doc 0
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '86'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - full batch doc 1
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: qM+nucPYy7xym/e7j6K4PK8EmLrdy4c9iXNAPW5BITxPknE8v4l+vIBrqrycx+G7JWJ1Om0tLb2GWje8drNPvU/dOzxqzqm8OQCCOyn1kbv8LtW78QYhPYnwNT2nCk68R5TSvMLTQr3AwuW8lct6vae1I7wVqYg8IIFgPDeOKr3gt1U8dz/XvOnzyzrFFqe652ruOYrQRrzNj467hOcgvBHO3TyGgLe88ukQPAIkmTv4CjW6EtS6PDQDBzxxDy69+svCvFhujrwDeog7Rr7zOx/R/bxhM1y8rqfiupeS3LsOnvU8RLr4uv3qIr1Gqvq7a+xxOjj0xrtBq6o8K+Y8vJDsBrxBAne8rDaVvFquXryDdD88az7SuiQx/jxlheM8PLYSO4iAyDo98gY9v2POvKsJurtD+u08I7qHvGg1vzxKsT49ckUSO4QS+jvVOI48Ve7xPKtgWjzbiOi7+uXhOw+jt7xy/eU7SyNcPDlVvbyZDaS7q17zPIubuTr7ozY7Z9IzvGi5p7zswhW836F4PCl6HzvG4/i7GMdfO9ARnLvVTHS8Pw0VvcMst7ysFB+8G6Y+vCCXwLsLIcs65WSKvFSMlLsYj4Y8cdVtvOqyHLyBTBC685UDPR6C2Dz51Uo8NSulu4ZxuTyHEf27YN+NPIyoYbzGppk8lFMzvPxOzbxTj4M7v/zpPK7RYDzLZHy8uoVfPG7tkLxbQAW91GXRO/JDabxNHIm8P3oLuwWLxzv7Kwu8zHqCusrzsjwNNdQ8G7Z9vIXGs7y0VyK8125ROqUdJDzN3AC8xBjvPFV0kjxcGNW7ZzyhO0TNHTzquMc8sAGGvA2x9TxCA0c8tULGPKcNCrzsBqK6m9GtvFsmsjwIAGA8P7NOPFNhJrz7z9g7GtpnO1XahryvTJw7Vj4WvLaUL7xi8Kq8OKkPvSh6fTvIZQe9nynVu+Ec1rtJ3SM9pvkpu6SMAT1fboy8OPIBPD9RljzXVC26Vkc+vDaQvLrBDbM78USFPCCE5LwK7iA8l178O9uKjTyFyGK7cOhbvDE5kbyyH/k8kpOOPK7J1zxKPgU8pwwIu9QHDD3gZ128GnKavNu/g7zHChC81HfFvCMfnTsabBK8TOFkPFClTzwsOtW8xZLqvNp3szwno7I6ShMBvQfxDrwTDq88rITCO9CZejkRqo86ug7kuBzB6jvohwa9lsoePJSSLDvbYIi8noLeu+JAPryZxfm4gqORPBvE5bwxzWe75JMsPMS2vrtApMw8InySPMjzvTx6SV29/rLLPLbto7xjqWq8t4sSO+cquDv1rJG7kM2dO37wrboRvlG8qTOsvMWNSrzoY7q7gE0Zu0Sx0rteNXI8B9pUu3K1ZLz7q9e8TeievFtslLyH9T088CNgPPWjFbxzZPW4Fwdou45LFLxVbD683GYkvAdkPzx9LRI8AwGMPGaBgrt0omw8WKPVOzewHTzyc6W7ZxaJOnA5Azwxhz08EBT9PHCmprw+m3a6JdXuvGkqPTwl8x04G0vLPJPd8jxpBuq7MtRovFQ9GzyH5e889cDovDAZzTzS6LS8Hs8Svf7pIb3igLM8YbCxu2MDprw0qMe8rrndu5l8IjwJB8M8snw4vCpnrbsKNkc7xOIYOr8Gcjs6HY48MQtIPFfQGLyLu2g6bWaTu6zHpbxajr884/3VvMshNLwO0Dy8aeYzvAxDE7zK9JK7X0ZtvXQx7Lz7Ez07f0o7PNk1jrtUbh48khAgPYP+MjxY/VU7jJPovK60DT0IuxO9B31cuytPmzv4XQQ60L/XO19Ouzx/6Hg8kSVYO9HHUzuVVaW7oM68PNF0ZLxxiT+9JZW7uj3Fejt4S3M8Jj8uvQZXrjyA3hQ8WbYXvbv0SLs8KCS733SDPAF+njxNlwy9lAAiO51gVDxrBSY8NgyYOxBRJ72+qwK6mbPvOxESNr2xq9q73xJYvHS3RT0qRda7L9RxvN/h0Tz7dmS8EBfLPNpdhjo8jcy8yzIlPFLv37wH3ZS85sQSvF1JmDw0rqQ8eS69OxV0Uby74Vk82cJuu6nIOjw3uAK7x8cfu26qrjuvSok8SYRCPPH9kruyKUk77hY2PAHAsryMHBM94tS8O58LWTxgTQg9klfWvJc1x7xjJlo8Aqh3uzTY57z1PZ28cVaLvHzllLyw9uc8NimiugAbwjtADNY8Z2pXPKpbijx6nXa8pvE7vfNrcDy0+P48tFDhvO7AUTy5W5A8jqmIvKCdsrwSUlA8Hq6GvEDSsDsPGXQ8isiIPEet8jyQmAK95TedPKV8zbzI8F27agyfPL2tCT2sCN6734OPPIwAPjxSFZ68qjjIu2VgvLzzEaQ84KveO/IIrzyHuyk9PFg9vUX5drr93B27b82DPBp8Bzzs/Fq8Bnb1vFjpHDtCaTY8INqcvEJZNbxTXL87MFLZPMgVnDskeum8jcU0vN6SrL1mn0W8phwduovS8LtmIVY6wURAvLaxbLys4BO7vQ/XPJVU0TxTfMy8gAuCvFGMK7uzck68hacyPKipsjnzTV885xkqvI9tmbvEDR8813tOPdGykztLfM082eyxPDitz7u47Bk9qBoZPPtvPrxTUvY8OqzEvAP2UzywCT27QsEHvPF7prtDFHm8JcUWOxis9DvLKAW9gN2RPLPJAb07yLK8EQjbPLdYCbydHN27WRF7vG/av7vxt5m803uwvBao7LzcQ1Q7P2FQPcahxbrvqly8Qks5vX3JcjxuwMG8TdncuxDiRrxa62q86AjmO2dqzLxLQ6A8QKwSvB06gLyNCP07DCeEPGw0KDwVr2K8FIdLuUpyGLzTX6W7CcbuO1SHALzjkww7vT8bvWYyrzlNhSW7g5jsPBbpbDyfeM88mOS0vCxmi7tKYZk85CdbvG22wrs72BK8EehqvA6sb7zjMgm9zxYrPMtL5jxIvFa8an36PJ3A7rzdHgG71W9BPe8v6Lzqbq48ib4IvCW8PjyQd/M6q84ZPHpK77c63qU8JhIIPB5ZOrxVHtM7oHDCu4n+ijtQqhO88iK3vNiIw7u3Uu+6Cpk/PJdG8rvUhXa7VIX/OwZIqDvwM4y8vrGMvBGPxDwfegs8LyKau2DmebtoYnc6xI83vCeSXTx7g0s730aNPPHIcztMBCC97YviutrgFDwtjSg7S7V4uk4OuLw7Gri6zYsXveM5C7wOa4+8IUIWPBWdhbyqjfW7ccsHvIpmcbwCTOE6BCySPKroWryZGE88t39gPLrbAbwyL5g8TBAcvRhnQDwwSOg81EwlvY7hgTunmfa7eEWGvBGeNbyx7L+8Lya9usOBEL3ngyU8IgYFvUjHFr0+R1+9l4UuvIjHjLyx3ua7KWwOvU9LVzxBZSA9b2pevEZdLT1kzAK9tMtTvYqHsjzWjAk828kEO7sfMD1XFXw8PXDkPNVaDjuFd4U9O998u6Sjlb16rOG8Pa9SPK5EFDwpBAI7CO8wvDXVC7zIboE7M5HyO4g5NzxY5wI9kRLiuwvwLD3Wg/47tLl+vJ/1AbwZ9b07Q9PLPDK9kLwzyj28O49VvOcfGb0ckbY8QDlMvLbzl7wBLgc9MI5/PAibwrzJfOU8nlXEvBSuJDxKz5m8BprQPGXjijwAUV47NPkNPDlrmzxdxzK8mHfZPJ83B71t4Gu8rWAavEOHkDyINQQ7DRIJPCUSm7sZToy7isMAPIkzOTsU5pw8L+QjO9aV17zVdRC9ndF1vN2hC70vnqi6N1MVPFOF5bzHhUu8ZUcRO6O5kjyAIma8qW/GO/QqSDu5Y/+7aXZPvL9KAzweM6K8tBfTOnH6rTxR+Wu9AwdCOwqy+rnCGg68xFMyPQrou7t/K968FiglPTRuibxTKYg8CohyPPP+zrvz4Sa8HuKDPe/LYDy3Yi08ss3NvNPbijxKl4q76C6Gu3WiLLyH0Vk8zBaoPDp4/zvOfEy79IUYvPowODsErzO8XLoKvMwGizp/ePu8qXs4OOR8CjynFOK6z05JPFCnmTxW+CU8qLULvHAdPL1Xg6o8v3RkvDmRqDxYCIQ8JT2POdaEZjupPgC9A5O5vGPUi7vDeG68mvruO0SRODw4szq8zeK+OzbZCT2pkvi86jlmPLwesDyyaSO84oIVPBzbhzyGSvq61Z+FPDVUoDzKFJM82jLTvEEnELywQ9Q8yYbCvCj4Dro8cCo8zNgGvcHMUTtsJW08/A9uvIcwxrwLp4E6uPljvMhlO7sKFAg8kCDDvGxTwLs5nLK7BDoqvf1Czrt2+xi7+5nmvKl+jbsalIw7lgkBPDAimjtw5wI9KVEPPDbObLzi6gQ6TDwLO11BGL2E9g69PdkEvUmiHbzf98y8U5GXPLiup7wHsDa83W/dPOjgGT0HTnC69q3OPOSAmrwuubU8MFO5PKo7TTxABKO8LD23Owy8VTzaRLy722wAPc0qdDznIS48NiipPNAlqbxSymM8nU7hvD1fNzwPPpi8I0i5PG61Gr3Sz0A9oPwgvJfEATxxjIs8arKBvBQ2MjyakyI81+KmPBFNLj23hGU93afpPFd+AD37q+28sX5SPEawtjz8BwO9QlUmPOBzNrp5JhA9GrGku701Ob1/foq7brc0PA9VHjynVrO734UDvZrPL7y1F++8vVQOPXdZtTvu2ww8SRbjO4Pcszxt06s8LcKPu+gOwbiDsdA8qbWFuTOiHj0iBsk8MJ3nPKIMzzzh5Py8yi/iPOa6pbzEBt27pWnwu3nRobvUh7O7ntfeOt+uWbxnKaE8SkVOvMALw7sti6C8JNgevTLptTwLIIW8IngtvKq8ED30/vO7M7Viu0hCCT3stVI88ISWvHRI/Dxtty086WsCPLX6l7zZVIW819vDu9bArDw43gi8i30qPEBksLvlqn889QutvDCDArw41AM9g5LKu3DQQ727+9M8plE2PdY0SjxqxNi8eIOQvMzOQL11Vom72RY3veFpUTm6+Fm6+UZ5vC8dJTuK1zY8691LOtWcXDza6cQ8KgHnOxnOK7yMJ/2800u/O76iszyQy7O8bJFpO2j6Hzt5DK07hVmgvN0xNjxr4gY6WFVgvCXM27zSO2k7tN6BvOskhLzdeHI8i8OWPOPe9zz3qUa8fcQ6vQQwRjsxWwK96h3PPJffWDw9BQK7dAQmPNw0Fr1nxnK8wJJcvLrNLroTUOC8OiMvvLAzi7w2Ghi9FrqBvBzoOrxknT89aX8CPSV5LT3Wttu8Nw8ePEC1bjvKLBs8lN87vNREEL34uCY9LfQXvNW0zjx/EkW8rvBVu+kV/TuGKhQ8WeW2u9Lkszv4bgQ9Y+YTvNfjszz6Ch490zySPJyxs7xkKAQ7/bPhO38Whrz2lrG7wB8YPFYtxzx7i6M8iAPuPC3UArxDJ2K8rcW+vHosbrvkjSi8UtgfvFkLYDvz6OQ7SLtxPZYXK7zWys+44lAtObwAXjxpApi7ikvEPHNeDTykTL28NbaaPCLGRjymCEE8IwQQPFBtzzxaKI+8qJsOvLoM7Tr4idC8nZbpvFolqbnJxSk7Exxku/MELbzmZYe8pmcGPdHDk7yBl9y7oi68PKl2Fj2lOAM968s0u91imrxkaDy8V70KPCyVQzwmLgE64avgPP7+PryFXze8WpYIPZrIILwvorE8RO5sPRv3vDyDjWu7l0R4OnKR5ryt+jC8lGCuOgs92zmoBxg7txadvMS07zs0EoC9WTJAPYGqQby3CH27DhWKPJ0xArzbMR878aDYvBLSHb08Zb+7H+EfvdbLO7uAbsO8n1CfvI33WTwI6e87b4oMPf4C/bszrdy84oACPXKw7DvTefe8dnqAPBdR9ryGR2I8Eel+u4VF0rybJTi8YLiFvMfrTTyr+ZU8soqqu56yXbwTdba7ok7CvGB9xrz20187NJJqO6eB8znLsxw9cd49vFJJXbutOgW81r+juiVRnbx8RUW7EKV7vLxlEDxLIjO8CjHjvPbHyTs/fR09RzscvK/fSjynvV67R/ufu1E1JbvLC4o7GiUPPNECALzYjQ296pCvPMzEQbywB++8p2i5PNLUIz35DNk6iAOhPMIp1Dx3+ym8KkmMvBHYOzzzNl48cM/cNoO2djxBbeA88d2jOfLZFjw/d408n4qYPP7ZuzmzKxM8vbePu/3yNTy5q5u6Xe5NvJpM4TvS6XY8xT0hup88JTylwA0816wSvMLJoTtitYC7tB30vMRpizx5ELs8uFODO9tDC73gJgK9i91JvAl247x3y1Q8M+wkO+jOkrsTwPU7ZcmKPG6LX7zaOIC83M4ru1+r9jvbesS838CCPE3o9ryhLcS7a0UAPIiiajnc7Au9+f0APOP2nDyhKRU98kkIvMP11bpL0RW9hUAquz2A77yNlA871vvNvI0fGL3qa9q8CkiQvGE/2rxxMY87chxevN6ee7y3f3E6sQ6AvJRu8Dz7Mdo7y7I/PRZEtjywbYa8XYOPu6snnjzel8W8GeKDvNX547gS3VW8+yBAPLggN7zqIi68vgubvA+rxTz5txG9DyMCvbWwD705Sn27PkP4PI07gzy1W3G7iTrTPFF1TjvJafs7MBPyPIn9uTx3uLk75q9gu46Ibrx3IJQ6b+hSPQVPAjzrA8M8aVlKPBcJgLtgNXk9OPd7PGRmQLwA8xO6E8OkvOU6Eb1XGwC9aUgwPIQ9Wby4P9i81jsZPE/mzLumnRI9qdO1vE9Dt7voQYc9iqgEvAyy97xL57K88zAuvFPwszz0J/e5u+eQPNe+mbukFdQ6zImwPON4nDso27k8Dfb0ux0aXj1xc+e8UFKZvArxkLw1pgs52m4CvINiITyhllo8UjDAPD/iUbwvfz+7uokau59r0jvT/Aa9W6wFPcU8LLygojq9HjstPFVHRDwY4pm8UdjPPItWC7oJiCE8KNg7PJ9/pLxw4s87UnM+PJX+2Lsf0x286B1YPMAXwzr0N7q79gfNvMuOET0V2dK77qFgOxKU7rzjh888i3EpvbLvT7ySPZE80o/yO1p/ILzkbrO8oq27u8/QTLwO16e8dWRTvIpim7wmZ9m8jgE/PL2pJT1WsR681JG0OvRplrzpEy28kYOYvIM1IjxZc748LwQfO5O8dTy5znW8xbfBPAX+Dj0aVyI7u5NOPWDznbqapbq89ODFulUzmbwzPX+8fbv/O/bo0DuKaiC9cdTGPK5VTbzCHmO8+3jYPPNX6DuFbD68xuyTPIXxlbsKY7s8jxwju7HUlDzxlT88aXU4O3s/7zxU0UG9V+/UOzdUD72dtwi78JSRO0uQlTxodwA9dcQ0vV9mjzy99x89VC5aPc3PDzyeGRq88huYPJDgA7uviyG8x+2IPCjtsLw0M7S8U/+zOmJqY7vEhZ873PqnvEu5jD2jrvw7MOQZvSPZhTvZID88uJwLPQ10CjwpD+e85kPvvNvhbTykQRO8eFruvDyVZjwM4ak8oP+QvFnkyTszTY+7Ie9lugmdKb2DqMQ7pIbeurLJ8bz/WQE9gP6/uyh2xbwv1H+8jAZJvB69MD1odOS8FR/5u7aCrTqkK4q8QIeKu6MFar3YzU47RzwvvGK5Jz0owhS9QkYYvXYXszt5uMQ7+X27uuJUCz2pbqi8zyzSOgNWTLwbROw7ewJQvETKg7zqAHy8IkPZPDtSBTwQF5A8wMLwPNzV3zsJnbm70uQcvNy09byUpgE9vy+hvA8S2bsxCw+8pwYFO4wWlrwB1oY8bxnBvE02Drt0lZ48wD2mPKHfeDwnioM873+JPIvoFrsL/2W87kYJPLXVnbwJrJU8pLvoPHS0qryPqjA8liPhPEd3r7wmVv+8oToOuJLWtbxlS3W94WQhvegj0Tzb23w8mREGu0y0IDxgpwA9862wO0SPDL10EBK82AkWvclsrbwpDeI72cQdPcEEBzz5/2W7g//NO4KhrjqTici7vdAHPB26v7uLaZU7hgGGvPgtDTyL/l+8wQYCPSf0vLu58UC7qeOjOtU+xrqgNt+8o95aPMpPRTx/ZCQ8MfTfOyNgdjvZu5u8dLnFPKRlADsuTvQ7L5iouvJbfTw0xJU6bu0qO8mS6jyh0zC82gjFPLpx2rpFhVk8M0GFOooWArvpFSu8XMeDvFxdMbyj/9u6pSlIO8ockLxP9gE9wDH2u3hnhbvBUoY7cRYsvDMuW7yNvV48TEjuupjwjbzgtWU8h0fDOEDuYTwvKzQ80HuCvA5aobtsbpk882OqvPy4FzujzB89o8savNxUWDwlKbm7aevHuzO/rzxyqcY8ac8SvJ2E3TxZugS88vLmvF3BDj34gp88Uv+1PARXirwoJ7O8meXmOrGjQT3DC+E5axnoO2EOJDxcEUs8c28QO1sW3zz3CFy8Q3OlOtgrsby3N9c8FdOmunLcrTz7cue73vmCPO8nxTpeWgk8OqESPLc/NTysuQU9/74SvKEV9LxA52u69NY/ttfzn7uv0AY8sJnpPFJNsLxQMsG8S8y6vMY1lbyDCmu6YUMZPTH7Q7yipVi8tA6ovGUd6Tu3JAE959AXPb2Ulrw46su8/fCGOxgCmjxwbhu92sp3PCoJqbwCoSu88JS+vPxpULyxTMC7JFoZvL/py7ykvEQ7tORIOrW+jLvozu+7h17rPOFyujxAMos8KV/VPNj9Cbusw0s7HSScvAwp17u82S49h5iBvBNHVzxiLMi7UH5xu46eOj2I5pM7lIAZvYamkTxw51C8dUECvDn+tjzRdsY8a5IDPUFawDpvmSM8OvAWvcnrlzxlyRO9pkP8vCArw7rf4GA7KtJAO4a9nDxMilI6J7BYPNBCqjwz4ck8rxaXOwU6BLwM/ig8r+AdvCUknLuRm1S8uRsRO6d14zofmbi8tXCiPM8Xwjw6qXO8sqHEPEu1CLzvIZu867jcORzbKzxfw5I68hOHOij3Az1FXhc81FgBPajTbTrV+1O8xM0IPbhizLxt2a27tq7eu/k/L71Q5Ey8BEH/PDqVWbzT5QC9+822u4iJGrzHVyK7IKxXPPte9TwiVw49jWTAvM5UJz3LNLi7zyq2PI34Rzwi1O84/4Y+POrvFzxBHjG9xmpGvMblUztPov47BCeLPKthEjvk2mO8jQDgvCkJibw4orm8NtqMO9iTgTx29hG9ZKf9vEjPnTyJwhM9WlWEO6sNVDs5Uyk8N6X1O2XZy7vUpIE8tys7vBE3CLu+aQE8lX2bOVesVjwr65Q81PfmOeD6oDwLe/Q7nRe0u9JVoTyYuw88DYz5O8dXiLwck+s5N0YGvBFag7zWf1O8Oh5xvMPPwbrZPXa85GmjvIdZSbtbdac72wVMvftyUDyTD8Q8XK5Lu+0Awzr+pN88e26vvGH1MrwKO0q843cBObOlRzzXS1E7o8fPO6fdHTz3BDG8USxrPBHCbLsx74u8U9icvIjCXjwjwtm8B1JrPAKR/LqQpUw7hE3buwJ9n7nTdaw7/nP2PPhmNjzU17i8dcNOPAW2qzwUSCa8KRNtvHx0tjmlgzW7um0HvXEidrtVZcA7PRUKPXj+LjxH5y08VjeUPCzGFLz6Ayy8Oy0gPFH7pzrAC0a9jfBpvA/6DD0xijK9jkQSPNXvLLzARKs7VyOZO3SdL7zB5ew7yKsfvJDOEDxjmoI8waU2PCmWZbvL/Lo7Ls73O+sEFT2aQ687rnXEvN5Ksbtex4O8LTkrPYpGW7r/SP07qfdYO0kyZboOkNc74tMkvELOHL1BC6Q8b0mnvD6UxLxNFXw8R9MZOrtLkbw1UbK8PqjaO+o3ijyAye68RGEEvaNwCzysque7d4GwvFsMsbyTOsc8WCTXvIiPqzw95Qg8UPZBvCBSxDwR+w27Sx8bu2gM+TzEBKK6++kqvRTCJbyZdzk8JzEPvWM+ObyuKnY8ndmPu8HYQDuKg+071C9OPOGSirzkakS8r9PWvHCAabxyVWM71SElukGUUjxkBvm7m9w2PMBY/bv3u468csWMvH/5rbxJrPK82JkHvL6127n3QaK73SADPR6syTwN1Y074d9Du9lukjzto5S7zVrCPBDFY7x0Xq874uvIPOx3wDoeIlc8EnAKu5SXxDxWGAq8GruUvPxKMDyYPa48rYyGPM8BfbxAdCS85LRYPDnm/Ty5Aaq7WtPSPNk4OLwprIq8ZWrou6SkkzwzzBq8iiRCO2HSxrw3Yok8WoJ4vJWwkDzmbWY8fg4mvOw2KTwt/qk7L5iRPOVPkjwt8ia8pWwpPcKkGb3ckAa8McYCvCKYqTxYoYI8yPhCuwih+zw1IZW8xljFOmqYvzvy29s8KcAJu+POfTzxxMe8QBIRvO4yhzrSG5a7aofmPMs8Aj0k9pQ7mOcgPVRb8LoZOgq8+zyePCrcabvUADW8UI5YPNqCM7y1Cka8nZU5uiSM1zxXDnY8H3k/u3eEirxm/cm7UrXjPGIjO7wbyNO6UDCvvOfMrLyRPRe8etABO3kXGjw89gA9ZfZEvf6gV7zx8L28W5hEvKl7Czt8Rwu94EY0PPoQRb37Dlk6KC+EuhEIXbwdsZa6y1sEPeSHqrvhWnc8frHivK1qsrsxiOO8PQAHvLdYyDwvI067nXf2u1Ed2Ltc/UO8ozxGPa8UlLuM27Q8yNe1PHjwqryxPYY6GU8dvaRUD7xn+Cw9+qvLu0EMhjyzCLc8yMQaPHYikDuubN25s3OTPOB9UT2qxKu6qbeLu2Vbvryz1Qs822gcvZM3nLylVgC9HAH8u1/BurymdbA8Qy0rvFsyhbxuKtc7BRiGO7A1pDumzuG83w5rvFvlIbzW/f68RoVxPKMqnLvtbbe7trKkvHQivjwh0Au8m2A5vEcflbzfLQO9MDGBvG2ukLy8JNQ8JNEkPVTpwztHB/+8lOZiuydJSD2sE7u8zQOVOz7JKLwa5BO5bzuePKu8lDx6z7W75hCnOyOFkzvZoK28W3vZO0R9irtgHNe7FjjYvAC4EruzNtu8C2WVvDZYMjzXQkg87tyZvHXE/zyXF5K8kpmwPNrLJTy68u28+xZauynELTuKYkG8smoluzajT7ydMoE7WxgivXknqbyZBi290TuUPIFwWLzejJg75x8rvUSHIjYNYX289R/1O/+XKLwE0kW802UJuyW73zxSMO085KhNvPd+cbylnRu85p9VvEg5srxzwjg8IelXO2y8vDwFJWY8vKK/PPmVIT3H+VM7iWOsO8TI4DxbCfC8q84avIHkTrycUBE8q1uOPEaBt7v56iW8w8SNPDoFRbzZbgI8JZ9yO1Dwj7xuIRC9Dx2tO+HyET05KXg8BlQ+vEiFgLwaRr07+Kv2O4aXtTtAZ4c8dhCru/Acj7wKGZo8jjlfvLZjDryy2N88w5dDPMkxj7wtG1W8pUj9vNs9g7yJcsy7QjuBO1cFxbuYETG9AYi6udhYbbsvSOq8yofkOrGSlDv9R7y8Kt4WPPjbmDx9BP06plWGPC91ADzc+R8933LVPNeU0jwMNYC8tX5fPE4ZD71uSL28kmlhOwI8Dr3rnGA85FDHu5mC1Tv6+Jq86FUuvKkfoDp8s428NDQVuzUpELwBSH684dkqvQ24qbwFnSE9wx6qu9CiijtzUjU8EZXZuxOnnDwEsxs7uFTpvEHn2bmkEiA8hzttu1LIN7ph2ak8oodHO4q6srtsIw880p4xvOVB5zqR40m8i+WAvOZkyTxTawI9jR8VO8kG3jl35Bg9qgcsu8yfHLyRpyU8yZnFPHxOVLxv0Be7iAcGvPFH0Lwk+KQ893NxvNN6OjxIlz8735+TvHvZcTzG6my75j7XuxWTszuUv+y84qCRPC92N7zRcLA8LiOLuhkzl7uOyXQ8YUfmu0NbvzuRr1861La7PCM4k7sOK/Y8CuMCPK6pxjtjaeM7IHcTPRAYxDuLDrY7Qv2DO/e6frxfpC08HkcxPDd55LsKNws9m5pEu79C4bywJDi7tWWSvDKSPz1Fzry8e3J7O59NW7wtoLG8/sNHvA8TsLwCBCW8Sl/zOyPlKr2Xwfa83g4uvK/RL7wEvUm8NwxRvIiF9DvhDA88PGkBuc1g1DrL3ks8dxjYvJlzOLrPhwm6TqaEvIL9/Dyo3fy8y2k2PCvk6jslGgO9IfX7vLNppDlQ8YC8xfeLukaWALyuH5O83Y+HPKP1cDwIHaG8cm7fPKP15LwN3ok8sdTWPC4LH7wVSB08Q3ZOuZhagLuziDC90vsLvcx8X7w85Q48AD+dPIqlnLxjDyg9QZOAPCgnCz0Vqio8doyDvF/ArTxUZho8ptwlvNuviDy0sem7mf1fO1NfTLzXeQy8U5bjuwL1DTtBRK65IE/tu/kjBb2GORA9QzteOvDJWrxA4sW7SggzurxLHbwfOcE7OyllujKjmDuurxO8i52JvMyZwrviqrg7j+XLO/8/zjwx9Io7FDXCvOrmcTy6Ruc8Pdilu8wkS7x2DUm8vQ2yvGoO27shWng82q7svOwgsjxIlYQ77P++vBDYqzwjSiQ6iOhGvASLbLz802C8W3ZoPLsMwbwSci08uIgdvQvDA72nezG9I76kPCj7IL28u4K8oS1aO2hhN7yTmBm7hMrvvNlZGTx01iS9ZgydvCBNCDz1Ej+9+Rp5u4FHDz0RiWC7cjKqu+SIpztm5Im78GUYPIw7qLxmnAy8pvY0PNxtH7zDG8q8EQjKPF/tJzwJ7Ag8XYz0PCb0+7oZGL882GQdPAOUSTxF01M8Gp8PO0ghPLvUGtI7Rqm3vO+zpTxjJ0u8LwJKu1ADujzNNxk96KuWPLXhMLwsGZw8zKp8PCiaGDxjeYA6vme0Ori5/Tv3fQK9cOCXPIUvxTuKxqM8rKAkPAqKxrxkegQ8eD7zvKJGiDwBHEK6I3mEvFfL2Lyl7oQ7A2OMvEgioDvVKR+8ZivoO0dzYD3ktKE8DeeHu6Uolbz6zIW7ZmC+uzcz17wKaRo9aFM3vZXwTr2L74O7MNKYvOYefLwOPA27yOtKPPiJgzxh4SY9MeIeveSt4Ty1AJc8CDGkOxiSbTpfR3i8t2EDPXyoI7sgR9U6UmPdOwteCj2u1ai7cJ8bPU50irsGNjw9ngfhu7cZOzzoaPy8lOlyPLGkMDytjOE8bpomPb8zG7xkPCo8DZuYOww8zzy2oS08IpB/PByRRbycmOW73OfUOxQ6lrxJkmU8iFmfu80/hzxlnKy8yHvwu8Y64DsAz6o8bZMXvTWc7rlyou28X++2vDr8LD1BPIc7MSJBvPbkBz0E2hc8liwSPX1De7xVqGi7LBCSuufFyrxUfcC8Jf8RvPZruDvmeaS8fVUKPRC31bthQT48ZKUHPTruCLvO9s67sDI7vQ8HjLyyfUK8KZA3vI9JJLyDf5s80IlgvMlP/Dxbuy68MrwVvZhXBLt2bq68Qs4GPFvOVzpETiu8bh8dPMQQ4jyaeci5UjWau2fp17k4Isw8bkkEvbhGX7zxZDU89shzuxcL0Lz32RG7pVJTvLkyFDwyOVU8F6iUu4lvC7xyhFu7/16wPLy+5bxDCSI9M03WuiqbnLxubWq8UXkdvKK8s7wJ8Iw8iLKBvBRocLwXlTw8e/c4PDZ8Fjz/hOm7YkOEu3EzFTvvHm67noqMu6T2TLstpGy8gq7Xu/ZKebtkQhQ75R7HPNhw6DxVDcE81Nm9usEH8rzVep68DQ8fPA==
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '86'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - full batch doc 2
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '86'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - full batch doc 0
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '86'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - full batch doc 1
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '86'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - full batch doc 2
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_full_flushes_pending_before_source_rebuild.yaml b/tests/cassettes/test_rebuild/test_rebuild_full_flushes_pending_before_source_rebuild.yaml
new file mode 100644
index 00000000..2978552b
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_full_flushes_pending_before_source_rebuild.yaml
@@ -0,0 +1,162 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '87'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - plain content doc
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 4
+        total_tokens: 4
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '109'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - content from a source that still exists
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 8
+        total_tokens: 8
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '87'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - plain content doc
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 4
+        total_tokens: 4
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '109'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - content from a source that still exists
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 8
+        total_tokens: 8
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_full_skips_document_deleted_mid_rebuild.yaml b/tests/cassettes/test_rebuild/test_rebuild_full_skips_document_deleted_mid_rebuild.yaml
new file mode 100644
index 00000000..0b955c6d
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_full_skips_document_deleted_mid_rebuild.yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '89'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - doc that disappears
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: EgvquK/jMzv8Y9Y8otknO6WuOroA5wI9yA+MPdTuMLqehrw8FWrQPC63TL3yoYY9iFAfO30WC7jiShq99SMgu2Qs7Ttg1Fw82ldFu2uIqLu3C4a8m+MdPW3Kej0eL7S8Eh6QvIOTjjxka+m8NYOKve17Rj019Uq8AoM8veJJDr2iw088VMYAPC2LpDu4/RW89K82u7B+Krx7m8w7/DDhPBfWtzwiKwi8f/ELPOepFjtvkvi81djFu5odrDsc5eq8EUSAvKHrqLzaJlQ8TCZuPE/wg7zJK8u8NcaHvDFlELydvrU7A4nZuqIbLr1dr6q8ctK6u0PxGTynqru8mliNu23mN7vHnsS8yGUGPJpAwrw36gw8V3EYOhkn5bv7Mqg8szPPO04WbzzW4tc6CR29vAon97vqIv08Gs4JPatZuTy2q5Y80mkROvMuwjugA8k82f/bO4LfBb19tIq8REIxPDy8lbzlpBA7v8+HPPfhqDtR1Q+7qKcIPSLYzTppxmU7mpaRvJcekLy8MTG8vBGIPNvH0bsLtEI8ufBTPdBB8rtIyMe8Df27vHydDLzYA087RWRnO7VpTTvvwna8xunbO0lVQbyKfCw7DNWAvPRlsTup3fq79nKrut7ruzxEW322QmA6uyfrnzxB1gG6iem0OiNHhjsVh6K8gM5SvC/JBrx5NKs8LsTJPLpO67o6Pyi8Fx+zugwgobwwgFC8hmzBPPVL4TjEKQG83f0wvJk4XTreNW68hm7Gu0zVWTwzbxK9w96QvHEY7rxtEhO8WYW0PKeluDx0HNE6gHbFPI7rqruXwH48cnoMPaD5fjr5nZk89o4zvFATazwr0Ok6mVIHPMCk4jtVFaY8EPhnPHy1Nj1mcqg85oa9uXjo6LudOTs8YRwavDhxd7ybYBW6anPfuxGjV7xUFYK8xnfhvHmVL7xMzva8Z9KMvKwq/bqHi588WagDuwpqNjyyyZk8EKTOuhRspDxh8jO7Pa8TvDA7y7s5Fhu7yKu2PDrf8rtU9j68M+ikO/ArIjq4C1q7nKCovGuV0LvHNLQ84NujuxPXnzz+19o6AA0CvFpmMT02bIK8zQiBu38iNLxLVbu6UAkFvHNnubk1/Vq8e+jKPAJRRrxdC8u8iW1cvJ2PhjzzRyE8MV/3vFW0c7uerUs8lzWsPM6hfjsYXbW7ol+ovC8kLzu4NNe8jSCuOaGDiDkwZBy6WnCAO5FLF7yu6wy8A/cqPEqec7yBjYO8LWNIuypVSLxmfCE8aXlJvMHMijxu7zK9LgBePLqUpLo+Ncg70HsuPOs5uzqpTp68lHDoOkwcrrvQJIS8fiSjvK+UwLw1HU08PF3Ru5lN/bugWRG9iHwvvD6oLbw1Sfk8q2viuhZDiTwYqF06q27uOwwSoLtIy5a7NHF7vH7hJb0kXuy810tEu21+VjwQv3S8CJ9TPVSDIrsu7+m5o0hqu/Kw7jxNLKu8wEmrOmdyOzzJ6Lo6/SXZPFOy7ryytRs8dh9ePPyMOTzwmNo768kdO4ZxkLzO3i479Ds7Oz1THDuSlXY8begJvbS/MDy3jLO8GF2TuvpwDbwjKcU7dz1PO4qFo7x7WP+8momCOQJ3W7x7Nws6zexbPNW02Ty1NLA8P3JUOcXvUjymPr08blEXPPD/WLqlBl+8oG3QO6JTmrzuNok8n1crvb8im7xdaNy7URMEveNv2Lsx3dA7YfSIve/LnLzdrLI7ozwjPV7RF7r6v1w8sjyQPAS9ND225Y48KlDYvBgZjTzerPO8LvhWvBUHAru+Nam7FKcGOhy/PD0fZlk7SYaSO5XsB7yaHjy5X1w7PauCN7w7A0u9Dds8OjE00DzoEYg7V0irvN/xzrpdt5e8+UB4vNPLCrya4yu8B7qxu8TUuzy1PtG8DeSNPBokAj1PER08mxwaPBc0mLxBmiS7iy+dPByoLbyDzg+8PO6HvImzGT2HB6472P2AvIgKmzvRNrK8V/YDPQs/7Tv6yOI8DFNTu6ZFOryxNhG9gArdvCKE1jsQbI26313xuymDUrxBdrs83AdkvOAgfjzQPa689UeaPFxYAD0ovLA7BH7NuvlDc7yhrYs8tsFyOxTDOr0mtKU83xNpO+DroDxEOy88+32AvG7+hDwzVkS5GXbZvL2M1LxExS27vA8fveSbn7z1URc9n9x2PEaWKLz19KS8mgBKPT0wFjysLSO9DRgDvbWGXTtgvL482zU3vH5zG72unt25GEbbvM6cxDlLro67nUy7PAt64Ttuj/86WL1FvIWQhjzTUDi9FBbmvLqgBL0/JgQ9Mj/JO1dMRT0/INy8CcEsPf/6XzmvSfW8pMw/vDQuOb1BAou8vhXaunMwlzwPNdU8F/M7vQxgqbvf35w7JtG1Oy1aszxDBMq8tdsNvEjYNjxt9q46hs3DvO9OH7qFvTi7s8wkPEw72brqQSe96A1dukAUqr3KWHM7UWKNPFZlkLwn7Wi7UPMHvOcxwrxJcoi8y86pO74ogDvvbN28VvxsvDPty7yuC4A8lhoXPIKa5jzgrsg8ltNtPKyVRzvO8wK6K8SmPBEytjvRS6Y7UadqPe/EBzzyBio9HXjAPKSdIDy1OCI80caTPAvxVzz2J4w6Xv+YvHrChjwDKlS8EqBcPOyYEjycoyK9hxaWPCvC9DtjLIU7bDAsPNXUoryP2l+8SwrqvJHyXzwW5t87nzQLPGblijoDnCA8iqYBPTBEjzvGbZG8eoPnvJqRRTsee8u7sMazvC/TI7q/IPO7CRpCPThS6ryY6pM8U6k3PDLnr7z9Pzw8BPvUO+5U8zttwDo8LUtVPMc7LDzds4S8jzacPIJm7TxeVR+7hWxPvDHLVTsNd4y7vaGBPXXC5jwfxNA6CKZovJXvY7yCvWM8VmvTvAuiW7y3xp47ZmgpvCeicry6O8y836JzvHtuqDxb92O7/XUYPYIdcbxYINK50rpMPUmgILrVh588byfKukyDGrzvgnk7sYeAvEAzAT3Ln1s82B8rPZOYu7xiBue84UW5PCFv1LzrFlC73Ph7O54Hxzys+C88dAsTvPDpvbr8qGq8rgAEvFIT/TzmEwS8aINqPAwDxzsmo9W4ujf2OueF+Dt0TMO8WShlu2x3OrvBc9Q7PC3WO4l6tjwIdE292J9pvL08rbvVPto7tHGUPJx5Br2LpfG8Be8mvZHqvbxW04Y8pOgCPWBr2rxgg8u8cD1tvKwZqLxVuvq6Uy1qPFdCZzwXfWe8rzSEOsDLYbuHjM68ZT+AvLBeNDwQ/oc8EIjjvFpkgjzkNWO8ySiavHHGSLtBAQi8ycq6vMxuzLyAQy88W5AKPDryx7xQgFK9CMGDu5c0XDqbpao6lLEZO5P5WbyLcjY9kz0tuKqWhzvzT8C8TiXgvGZ9JD1Qcpo8ZdyPvDKA1jzRd0k8Q88RPVBwr7xBwO08Bs8DvdNUUb181Qu9HkeEO02SWDwrLKK7ceiEPM5/LLyepoe8cn5bvOfplbzuVOA8boyAvIqiuruwoM+720/Zu0Qlybwd4+c7104mPEzd1LuQg3q58ih4urffLrozN8s8kUwaO9khQzr7HP2610vQPJhkljyJCk09PH+WvRX6FDtXbH08tyBQPJ/fmbxia0c8riVVOW/9tTwRjX88QrwLu+MnpzzHg208RNwbPGOk+DvvTZk89pKEPEtUt7y6aeg6j9tIO6zcmjsUXiw9gprxOm2qQDxOu6q81JKPvAPhQLs6/re7PmPMOy+gqbtht1m8UzGnPPFcLDzdbDW8fyyqPLlkGj2t7ai7ZKnovBVBlLwstYO8pc1APLbNi7xcnvq8VgYAuw14hzt7kz68ajNQPLIYpDyJj/W8YTFqPNqb2bpdP4Y8kYcWPTCug7u9FyG9vq1yPVnxZDyk2RO8n9OVvM+RJj3aJZ+7Su7jPPuwkLzldbo71LuQvA4mJTwnTsA5PDrBPFVnAj1+7ze8S1A+vCvTRjwF/JK8yJSGO4Vv0TzleUk8RurrO3lBXTvXXwU8DvaRu1mZs7zI6b88+l1JPDTLHT0bxpQ8nq6uPC5zC70lV4K8lIjoOx6vr7ycvzK8Ym0XO0EuvbwWCyS9pCoSPNsjoTzRMNm8kbZzPNUfgDonGMw6nCwZPX2YC7zatpw7x/1lvKt/qzxj66c8Uc5NPFeRXrvAXTM8yPrGPDJIvrlvyPE8YFbEvH6jB7wRaaK8jFe+vAIM1zt2Gjm7rIwRO75Y0Dwgtee6D/CFvJ2QjTyG99s7b2z5vB21wrteybG7Z7dLvDGOBT3e5d08kHkdPGhjSLpMLo88TLP5u2Q0j7zokXg8QOdMugKaV72TBb07XVCSvBfNl7yHa2m8lVkAPUhMI7wbxSG7p2AOPGwIxTyK5tk8Kyjzu5HaIburzig998QLPGpBxzysxeS8WjgnPBrCZjwpa7884AWTPGfbDDzVKWc8Cnk9u8b4Hrp7VYi7THQYvQzlxLzvaPO74k6OvNNUdrxRYB89CyVYvAjJabvnnnc7BVyqu3OC3LuWgHG8zal3PM9tUzzJsGA922P4O4tJED0JjYs8s8iyPOCohzxZ+lC87YarPLYgrbxE8wU9zQ+evOFE5Ly5J+C8goRDO+ZL9DxBSBE9d+HMuzP9Jzyceve8fukCPUi+FTxKDIE8VqGjulkZETrCJak8067xO/CTnDwxBpw7IGMIPM6+rTuGtIM8JNYaPZ1XlDwIuSq98o3bPD8UkjvaQYW7zDwFPVKYHjutORm8TbCeu2HqBjwBEzY8NsGguzUXsjuqmxa9IcMGvO4x2TnzEFq9auF2vFp+IDyCN+c6MMjCulB7IrxN6qU8ryowvXuqSTzfri08zLToO6V0nbx0hUG9hbMwPGDICjxUxiO9op/avCapobxFLqQ8RB2GO9++1bwvt/k8LR6XPOyXLb1XDli8eiX4PDufbTvQ3PI6CLCgOn1CXb0yv0w8dx6fvF0ipTw6ND68P1f4vNIZgbudz7M7n3qWO5sRET1Wftc85lVruxXWAb1oVty7yWJPO3JhwjxWBxK87fUFPDIagTw6bsa8Zbd5PK2597kksZ+7SToWvCB0ibx0eJI7nQgTPCt5v7xOgBY78sdAO4KOt7x5ycK7sUPRvPP7Ozxu3V+8LzyAPLOVODv2fZq7/zWyPPfO6rwmE5281qljvInu/LwghHE83zGYO3ZiwzwR+rM6vvhdPAB2vznbBDo9QfPoPEtfzDzaqNm8OJzUPEP2fznRO1w8j0D5O9aFBbwmQmg8TPSqvOktqjybF1y6NHdYvEBnkTy/XAM8U8WeOj2QIzw6b6M8mLIpuuzkRzxxe8M8c6uvPBb5sbxFXA89h+hxPP/Y+ToK33O7lWetu1jKlTwlcB+75H3pPKu7DLypqz28E+yHvJ+DeryKIUQ6e/DrvBdHlbwYBiM8KFOoPLHE67wAINc6MpOtuu7+XDsLP1a8zhNlOkxnLD2lrri8k7kBPZT71zy0fpW7WESrPIbTAT0TbHC8lXHuvAFR47o927s8ungmvEYQvDu1cLa6/iJ7PCYi9rqSEMi8cn5rPPOTBrzsrZi8O882u0ezabqc+KC8vr7nO+Pmh7xwQwe8ynGrOr130DviL3i8nYifO1EO6rxsePW7/XKTPBX1I7xNZ0c8iyEGPYHxJzxpxVw6LzCxvLg4X73sTGu8P505u+Qx+Tr3vO27DEYpvfLbebxm+jC9iLUzO5HerDrSn2M8vbNLO0NAlTsOXSi8opizvHHbEr2jFrC72GlsvVNvML0PR2G8aYkGvLuchTzMBVC8oHhcPc+uKDuMhCW9w0XNPGSqhjv/9Ji72sQaPF1BRr28y+k8arF1O50p1bsinS28fSe6O6vQMTyRzjY86cIDvIObg7uVtMo41QkLvUxcrLzomzW8AoQzO1LWIrxhlgg9yTIUvZhepTzud8e7SmicuyRTxLlIQiE8cY4Wu4MjPTw4OYS7W8bQvK5O8ruzZkQ8dzxGu1fKELrjDha8vCSIPAFiyDzl4128gFB/vL2lezyKoTc8+Fh6POVm+btCJxS8KwonPK4xpTzDT3q8tiRYPJhiAT3ocyo7HR5gvFkbOTzxc5s8uSrCvHZ+o7wT1T09kyqxvIGKnDwH8Lg6ASjxPF9cbLxBBIe7jHdeu21UXjzGfmU8UmUDvTwghTzwRiY9DmsFuzwrm7wvF3G7C1VcvGalhLyYUsi8Ey/CuzRj4zzEQbe8AZzvOnCnG7wkuSe8UH8hvCKtEr1itq88L5nLu0kmrjzNaRA8IaN5PV3MsrmthdM8AkEcvSU+hDwjZJG8FVx7PELCfbxvHQi8bFPBPPjjqjsaqjy8Jc0OO4Ny4rxnL6Y8uwktvGDo8bt+ZyS8RgOvOxWtFjwqZRy8JvzTvMM2HjyMFAa9RGKIvDi3u7x+Xmc883BuvE++bLwTiZI8NVAIvCDLAz3iiDC6lvYjPZwM5zrKKTc7uUg5PNb9+jqPKh66sqyCOqJwnztXtuw7FnKmPP87MLlK4sK8WyVUvFbsvTvbvxK9zzS6vNK797ycTt87gfOJPN42mjylRfE6TkHbO1e+0DvM6AM8tE6FPAOPJDsfgB4846tYvKnd4Lxje148nF41PPqZDjyGLhm80qGpPA8MmzySXBU9dSJeO2zjhrzyhqo6uPauvCI9sbzC2gu9HADNO0etO7qH14e8lIWjunT7wjyUwzs9wwcKO8EzIzyIthI9iFYMvRdq3rqJahu9i5GbvGBlBT222W+8jOauPFRVLrym6Ow7padwvNHUrTwL4FE83YDNux7xTj0X8Na8nhhbvJhYD709uYe6TWBcvBk+krwLR8k73IcePSusbzwWpCe7xfqju5SaPLxwyLm8vEaQPKA3tLyHIAK9sbxRvO+mAj1nlCO9dOxuu2I1djs+ptu8512pPIKGnrzH3j48DGchvNdQ7LykppQ7bGCUu9wZmrzmlkk7JIkIvXaNxTy7cy080tbOvKuBIrzuK1u8w36svIT6L7wDGRA9CjAbPRM/njvBrwC9Z4vUvFoLQbxI6ny8BBUIvbs507v4lHa85JQDPXsC1juh7y28TvSFu4704rwJHpE8B+VdvBEZfrzD0Gk7Jnl6vNRYmzzXmzg8iV27uxe8ijpGLJm7m9/0PNGzLLys+hm9O9E1vSdylbsuwhO772NBuvavtbyP5/i8YhG8PEMWbDy6Uc46NQxJu1OElryTBLM8+gzXvHTBirxTU8k8K2wlPI9ZdTyBPYc7iglFPEg8uzx8zbm8qzb0u5tcAby9VL+8HvYRvPIADT0hr4g8q3kivFqYNzohxn07Q0kOPSOGYTzH6tW6G+sTPU9egjxZt6u6QptTPFE0gLpZz+28d7KIvFe7fryl+Tk5iszwvPHpVD0v4b08CsQMvRGJXruUzXQ8r6uqPLybsjwSKOm88fw2vNshFj1H0oU8UQwHvcfTAz0YwUO8WArOvNI4KjuT5a08qCpzPDAecL133GO8Vl6MPPg5SL3MhPs8D2vWvEKKgLzi7K28eUpdPOfMGz1gQ+u8/wSsvGFdzjqzO7a8IB0vPIlDLL2aknm8co+bvPVgMj13kfK8Fr2dOzTWgLuKt088xcKevLEXyzxKeE68x3ravMlrj7wGc0E8F34nvLkWVbw7d0o5j/odPG88dzw4MyQ74Q5BPElKBDzcsJw8l/I3vNW+drzI74k86KkrPA1Zhrwy1pA80qEhvMkNUrztVLc8mMv1u74l37tWuau7+XCVO9cy7rpK2Es8hpoOPUayfro2P4S8MJgUvEGAoLvjtOU77AgHPapB4Lyk1wU8xkoGPVC5/rygC0688NANPMGEILwgGge99O25ukhj6Tzr+Y+6qZLgOmNCmztsBeQ8CAZMO6BgPr1fZhY8yl/lvLjspDs4zV48rlurPOZOLjxQpsy8hkGiu/xVgby6TUM8cnL6PJv08bsHQqA8LS/UvKHV3jsVa7O8Hd7dPLy4ZzzcfYM8P6o7u9lCqDx0KBq9iQS+u+FGBTxHBKa8XVOTPCA/5zyYCui7nl+MO1ciK7tdLv07lcanOyrJDzxNnbW7sj1hPFGC7DtqtMe8xpn8O3jqCj1X+Fc7SR30u5rX47lg9nW82kgIvVcEJb3962o81uMGPMDnG7zQUg89mqlZPOjsCLuQkIA8tL6XPAMv6Lr/AD88pskBvJJKDb2yjAI9HnMjOjk7sTuaRBs9KJogvFmhkzxk3r86mKoxOy6K+bv80RI9EmCtvFtcNzwoRDC83lQZvC0bmjwKS6a8E1B9vIp897sIlY87cF+svAOmpjyu4UI8hjNnPPP+wbto1yQ80hSbvNeb6DzJHhW99QiCvCbXizz0cYm7ifgZuzhZKzybOaS8zrfgulHH5ryT8F28U7boPEwNJT3tdRq7hmH9Oy6E2bz23Ig8PcjUOy/yF7u82Zg7ZLnCuqGTkDoueo87g5KrujHTirntjw088RM7PK4EMLz8wB68K59wuz1ZiDvxDhQ8HEiRPFoK97pZBeO8zzcdu7CFFDxTWhA98iyfO7ymT7xvue28RESsvLuHWjySBge9KPXkPM6sPDwRCJm8cYfqvPSfKTwC6LA7m4eeumAaPDr2CIY8gv+bO2nvsjtetYE7usPwPCGN9jz4Bmk8acnZPOofUrzAPXq8SC2AvH55ijvnEM86pNcXPJB21rsey4u8NfghvRbxSz3fZTg8cL0AvXoeK7ynH3K8Resou/j4G7xLrCA9ocISPJhAfLyuxJO7VGYsvSmxIDzJiwS9REBxOomhe7waQ4c7V5Q1PVsuQDw3fDk6VgYtPchNdbsigTQ8UYFRPIUCPTuKSBA8KpVCvEhPe7w8c5i8HNTnPMzq/TujcJa7CJIBPDTsLjzMg1e8tp9vPD/rQrx5Qsm89PR5vI3G/DydYgy8JXORvNHzGT23w7M8eiiJOxOXtLyNDma7yf4bPJWinLzfRzi8JPsmPI62KrypLfg7dM4LPPt6vrsZf32864eIPMUmazq9EQK8F7A9PM2iXrz5Q1G7G3nVuxQJ5jzlhaa7xkImPAgvqzyvZmW81MhwPI38YbsnND68fvXOu+ExLzybopq8gWl/PGsZJjysoBO9KcGSOkpJT7yjuo+8QFHqPDIbsDtzRie8kqVNvXqCxzx/E5g8fahMvA9/BjyG1BQ8MfcVPLFCfzwczzI9lNCHvIEdqDtxLdQ8YBZyPEN3ZTzNkLQ8+rm3OyM+nzzPfLe8yhxGOn1VyTxEMXy8JU7Eunm5CLyTBvC8+nPduxNiQbwvtrO8HEMcuwLTDTy8L/O7SvCfPOEtwzr+8DK8/NSuvMRItzxKb1c7XE+SO/dOybvf0L48ciAhvOL3NLyOnIq8nkDbPB9bGTzZOHC6f/2QvGVzJjz7Wh68fVE4PMN0WbzJm9O82hejuwoqhrsa24O8vTTdu1//GTpkAq05N2eLuxx9yTssaNA8EDNnPOttzDyVAKs88Qs1vIX+ED2zxYI8242FvPxdOL1QSLi4cGgDvemQJDqyLDC7Vs/bO4RX07zjmPs7oUTQPH9tRTqWGMU822yfu3enSrzYQqK8U6vYuw8pNTzAbDK9A5ynPA2mFb3fXwo9SbVgO6D9Hrzn+0A8twzHPFj5wTyQBqc8lYBOPMuJWrveMhm83l9RusDXED2XcEi76QYAvMFOlLtJJGc8h84sPMW+F7xC2ZU8k3ZHu40WbDxebwq7f77yu1ESWL0yTuE76fvFvK12hby26Bc8BymTPPwj+rwZX0A8G0kDvTQgLDylfli9p2EFvev92jza+ii8faANPVpc8Lx9dAE9ErIZvN7tyDzliNo8yCEFvICsP7vwB1O8yt8KPB0jqLy83wy8yPs5vRddezzHtcK7vsu4vH6w2bz7d8w8mNdZPDMAJTp21/U7aboIO9ERxrmTeTE8UdbgvMC6zrxRx8s8Aw8svFB5ujt7Z7W8T+sCPAHIvDwN4BW9krdgvF3WM7yCB7S8+WUTvK0TTDxNDTC8tOypO0lD0TwOySY8vgd9O8SOpjwqiTG8f8wsPbfILbwp2Q09c5f5PPbuW7sFeIc8BprQPGmi+TwV+li8Z6/9vCyvFz0ORtM8LVuOu0p56DozOxa6yDTgO/Cuyjy9Ij681/uEPBC9XbxVvMG8lvx0PD6PcDwUwi08mwn9O6M9V7yuH2+7i3ofvTtUwLszdOo8HPVquiJ8kztAcpW5VWtdOwIiNjxdeuS8/eK4PGW+Gj166Qc8oksOPG+01DzxBhA9mO//OyVoET1VxCA7zNb/PAaXTzwViKE8hmTEvDWSYTt6CS68m0nfOomKsbwa+027dwfsPBOZ9TsGNey8ilCOPB4fvzw15iQ6z0N+PM/SR7xjM6e7KsK7O+b7Drxfi9S8djZou3s+fzyHPiw6ltEAva5a0bxqRI68CcIyu4DHR7y47jc8xkc/vIoG8Lwb9hK8F7MOPEVjODyWWxU8dmqXvbthlLwjkci83aauvDLxgzw8M+u8k15tPF9N7rz9rbY7qxDEu5yTs7wCbIk7IiPUO8HEAbwbPma8OeOkvFLtZ7va3UK9YfIfPILZETzu0rK7Yh++OwwIVry7STs7ZkegPGWUTb2lPAc9xJ6ZPL3wi7wt5l+8ihUJvUqFyLo5MZY8z864O0TqqjucR2k9W3G2PIN1bTwFZ0O8xme+PMBfDD2NNJm808KXvC2qWrx5++y85xgfuUJzA733sPu8tRZSvLDEDL1CgMc7y5sAvE3SJL282d4887Z5PMobvzoxo207JUrIvIsOSzwyvlW7T6iYO4INsTuLiJa8oVesvKQhkDwFHvG7cjcCvUSDWruZyxk8fpNQPG4k8LyVJIU8FRh3PCnP5TzmKQC9ytCqu1Lr+Dwj/YG8VEFeuxIiDDxT+JW8ZYOSPDh5B7tk5PG8M70Cuw6DmLyR/9k75V7wO9W4IbwgoO48CMcavcEtGzxYteS8WLjmvJMH6jyTFWS7TpAXvdFDbbu4iym9My89PWAYjjzkzfy8tih5OqhI/7u3li48wWABvNNwrzx1iFe868cWvOgGejzMA8y8b/uDPAnYobxG5RI7IXOpPJ0+2zvVKQS8aMFSPA7svbuB7pO8bj2AvLwlFT0YGcY7pHc0vKYnvTzGNKG80IuIu+nkTbvqmcO88FouPIdroDjru8w7EICBPAQVFj11voI8wNHIuZ06tbwyH228GDQFvN9hGryFyUY882Z2PHPLEzwmAQG764hKPTVZMzz975a769wmuky4kbzMFjO88XS7OkWX5jxaS745KSwZvJv8EzybLoq8/FbEPIqyxTx4JAY9YkDpOzqb/ruqCoA822ihOzOpQTvNqBm7aqDYO5zsr7xO9YO8jplvu5CPPjzhAsW8LoDvvAtfRrw5Keu86o4TPcCWRjw3ra68afgcPVswvTzLxCu8kOPpu28a1buEwZU8lFGbPEEs7jymIRQ8g6w/vChajTsZ7o+8DGq3OxMO7bwQyKo7GkPRvNKkIb06DKA8C2tfPIQj/LtzkK+85DSCO51Gt7x/qSi7/aDWvDoi27u1qK68GwsJu+W5N73iCsA7S8iwvNhNGLxG40W8+cvHPPxIRzzzjF68g0SUOOssQbz6XW68eUmiu6Ca4DwL/pC8H/ETPQNLE71k04Q80o4bvCb1I73a4ko8nuwyO7FjKj2JmVY86Og/vDxYrbxD5xM9E6igvC5MyjwKZ828UNbcO40ourwP0ua8gjwoPLYMz7yr3xs9PyMMvDDX1DzHYxg8OZcZPK6NljxH4y+99kOKvEXFvDtFZVC8zq2PvN0gS7zaHj49k9RSvB/w2TzCtis6wkwnvOUk87rhYfk7YKmuPNMey7uu1vY8i5NPO7yhlDwRJIm8PfSRO01rnzyNAh28SRylPFuGorx+Xxe8rPqPPGAeuzr7pcw7ZB4QOuTZ3Lwbxvg6kbvJPM+X7Dy9azO8nscJPCIxC72PBNy7O02DvCrgmrzZ6h68zfZTPAw8SLyvoJY62wwjvDwW07xXoF68VfKfvLyCiTv2RZs7priqusVLtztMPnU8JWMQvNTb+Tp+Gnq8lrxyPENuvTzaQXO8bIcLvPQVKzwQ98q8xP+VOimSQzxmy/K6xw0vu+J31bzTAUu7WT0fu4uWrrpSyLO8I8eHvFNLk7zunAE8IfIvPTILTjwH4i486iJtPGpFDby/iwu9/yzZvNZF9rzke+s6QuMQPa66Wrz1K1k91dpSPL3jmTzvGO47McLku+TCjju7VxS8vqLqvB6faDxaEAc8g9W+O4ONSLxm+xW8NDixObuQDD3yk0G8OrNEPBYpIL2BRJw8rGf7tz5aWruuD6I6wA+CO8eFrLwnyM83qAq5vNbSjjyFPRm8xFJxO+KMZLyQKoE8TIORu3rZaTyArcm7xciGvLP2JDsxBYI8KX0ru5iIFDy+Q2q8peUzvROQoTsbvRM6apeYPE7hpTxEZ4M8UZtFvJk3VTz/qro7px6GOzdwvDuWkiO6BYrDO3S/ibyKNtK8reCiucdxAjyg8oC9CoSqO0drTL17MwY7P0a+OxFWp7zNSiu8vPxuvSNG7zsPQ7u8LQREPCdO3zshZwK9fZsdvITG7bo4gFc8YfhMO3EQMrtfPCU7bckRPW3sVryyBUi86K6MPL7sTLwmAou8Vo+OPHam3ruYEWI8fabdOuqyrDtPadE8kHG2O9bRmDyszUA9owX/OmRoIzxKa4W8MYTCu3nOpTvTBES88GXUvPHZBDxgQuo8m0NvvMQ4/rz5GMc8kwKePAIaLzy/v9Y888HHOxvaY7xS3168tQNmPOQONDyM1g88TCWrO4V8Ybtj5sa7/hubvP5gIjy7WI08+Na/vKwKA7tTjvY6zJyfu757WTuNp8u7q76uPEEjJz34MZi8VQnavHz+VjsVNzy8o47ZOxypQ7xTMMU8xYsrvb/eBb0eGuq8pCt1vOvOaTyDEme8lciJvDZCCrxqELU8OaMvu/blhTzSA6y8BXUIPEskJDyBth47dDSIPJiDCD1wu9W8XCyrvPKhYzsR5r08F2onvCQDSDo5xcc89BnMPD2GuDzQD4E8e/ajO7ktq7v4k0s8iWWQPBponLyEkoo6KEmsPK1f+TzFgO874r/HPJ1gs7YyA5W5Ky9bvII5oDoRJi88/rMJPCSiX7s4loq7AM6OvCJuCLxLyD88hqBHvX3VKzqxasq6KM6fvDIR6zxjFHG84VzcOx/i8DzeqAM9onTePF0SSzr0l6y8x/GHO/81VbxfbgC8XQaUvIZAozzYI1u8ZQ8gPVO/hLyenik9I5xqPGRXiLv12ac7gD/8vJjrwLz8tV08CSMWPG/pAzuxlYo8Z6iBOXYwCTyw8fy8p4gAvQN/JTy7fGq815P6PE8DxrxpL/K661GiPAlIqjwIO4M8DsuRPIbFaTuNPLs722mBvNzBdLp+N0Q7HtS4vHt1cLynevy7+/0ivGyhYjy7aR+7FTWQPKrXgzxGUyg8KLQwvJLOOLyBxhY7P7vBvNIsoLu/aAy8OHKXvExq/TwDAI68VCcROp0EBr2CdQE9NM4KPMX1s7sFoUW6t/7VOYpZTzz7u7g7ixQFPNef+Ls+bIk8hcOQusmnorzOzPa8SeGgvESLfztBngy8WzOeu1lYCLzO+Ai6hP5vvA==
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 4
+        total_tokens: 4
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_full_warns_when_source_is_missing.yaml b/tests/cassettes/test_rebuild/test_rebuild_full_warns_when_source_is_missing.yaml
new file mode 100644
index 00000000..64f0845c
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_full_warns_when_source_is_missing.yaml
@@ -0,0 +1,82 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '99'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - content whose source vanished
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '99'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - content whose source vanished
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rebuild_warns_when_post_rebuild_vacuum_fails.yaml b/tests/cassettes/test_rebuild/test_rebuild_warns_when_post_rebuild_vacuum_fails.yaml
new file mode 100644
index 00000000..b2c74d49
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rebuild_warns_when_post_rebuild_vacuum_fails.yaml
@@ -0,0 +1,82 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '88'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - vacuum failure doc
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '88'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - vacuum failure doc
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: VmMLuX9/FD2N1lG9G5W9vMwrZroiPFk9YQorPWAS6TsTzro8rs8lvTO+Ur2mm4M8BFQDPJERu7wkTwe6dHFcOYmgqTyGEwU9N3UZvGko77rTpo68npNhPe9UOjyNjBy93y+zvOAI7Ts3MPW8UK2Ivfpj7TwjbcG6ng3NvHRAZrz2JDs95PmuO9XAfzuvjNa8rcqhvHas2LnnuUq8Lz93PHT3hry13Me716FiPIpbmruUtTC8aOtFPCk7jTsZ21W9DnuxvPtHrrzKvpw7T0t0PMwfkTzYNq28OmjtO2mZlrzZqAg9uWh/OxfqJb3E7Xm8wJYdu+vzRDu3IoK86R7vu4SI5LrrDWq8QhmjvCnJB73pHbk71MgkvLPWJzya0K88eV0LPEettjtSuZM4fmsVvVB92Ls6xJc800zLPHAe1zu65Sy7h5V8uzUYuzyQGNY8tODNPJlCp7wCtfm8Vx/CO1k2b7wYJtk7fzgXPFreYLsFC3I8JifcPI8eFrueARy7TGQtvMTvPLzrKOy8NGsqPKomwrsUU2a8RZ4kO/9vsLyLgeu8Q0jtvM6zJDuBdpQ73+BzvGZ0hztvTzM63gbWOb9yDzwtyf87t0qPu3BMT7ySzLO8GGetPHmfYzyA6dE8PFibvJH1VDypJJM7agUaPHYrkjx1EoW7cd01unQxI7wLapU8CCETPNE+nLoFSJu7K9K6vCYDLDtdLUS8q9e4PIIimLykBU68mq+gvCN+vjwJlKG8DVPluyE/XjxwB6O6L+TtvCntVLtp/9C6/6HRPDlIyDzugQm8tN2SO2bCpzzN8Fc87t4wPKZwwTnA/d88aYoMvE50RDw8mpY8V3xQPKmN0rvkW8A711sOPZ66RbtPjFM8nnmRPNS+trukWEw8t2cdvGol4LyyFGo8KqxJvGUv67pIwfG7OXpLvdu/OziMJJq8sV9ovFhfAjuElzA97LlJvPYdmTyJFz29MouCu67EvTz8gwK76TV3OzQCb7wt9Qy7f6ssOm6DFbs29xw8pfEJPJL4OjzUFFO8IbluvBtFerwdDd06LOWdPPwbsjwjYSQ87LF3PAVprjxgvN67B0aJu6KVAbzf+mo7otxUOtxXkrrTTd07aHaCPBOhCTv+YMK8FNtQvSpHUjwAjIg8s9BZvIFSjrt02uc8YI7mvMVxIjxpseu6wGr4O5XR/zqKLpe8HjZYO0QAdjtwIFK7tC6qPOcGcbw0Zna6RnowPIKUh7uxSMm8LpZ1PAM9jrcRNP48FkD/u3eWwTxFzBi9ek4oOxk2Yrsdlym8iH4OPIiGHDxnwYu8nsq/O73uFjyO/4e8UG2avPPqY7yxyg45gaG3O8Z+2rygwM68anbnO7YNjrywffA8GGFqOTPILTyUbB+7MOApPGkeZbwOig28kY7ovHtbsbyEjwK8tMb7Oxa0Lrxeo1C8+qxgPe5IM7zHHgg8TWD7OjGghDypYgy8Z/E3OqYukjv8oyi7aNAGPZTFBr2uJeq704E0PPEOHjyzr4i8gHpKPJE6pbsZFpA8aP2UvMefPjwD+UU6xluAvSdSljyTIbC8VrrpvOZquTyPvkW78uqtu+NLzryp4PG700+UO/TBpjxUCCw89t3sO6knFby1eVe8BO4/O3eEjrtFmtM75decvJwjfrx50bC7jxufPA63A7zemYQ8q3+GveiJYTypvMS8JAKnvK9AkTuPDeQ6fi5gvXSPg71qGx46tl0sPfND6DtlmfY7x+93PKmvID1gliG8r79XvJU4PLu6xzG916xNPExfALyW4Qm8HlNWvNP7gTxx9TQ8MBOsO6FwGLxsTO65E3YxPa5bjLyjVUK9mEfYPFZ2mjyAbgM8L/nDvNyVQDypkee7jwvDvH7B2jw+wWa8FhJsvBDABjyPSLq8VyIXvI9BQD2jgIw99ruEvHG8+LysaVs6mFlQPQvJzrzMk4G86VtlvDBGQD1yNFu7Gttuu4KvvTxJvpk8XzvpPEyMpzuy2XC8EbaWOYZwYDxJpkO9V/OovO0wLLyBeAe8wvIKuj/XcTskti88BN+vvG+oaDxjFHQ80I1BvDUTqjtVWRi8wukbu2kSNjq9sT487xRDu3JgQ7zWxpw8HhrAusW/YzxnD868j5mKO6a99zw1ete7244lvXTb+7xXVG68iROquspP3bzi87Q8J94IPDjzOrxv9+M7rXXKPCKGKzxG+JS87QbFvBjJwzwFuQg8dPsSvEBXYrwcR0w8cwzlvNDp+Do5K/G7MryduhF+/zwCzQi8PzlBvMTj5zxH1ky8FWRiPDAoB703Ukw8XjaGvARaED0ecoa816vYu2rGCD0Pdh68BWarvHqZYr3RSgW8Qz2wu2vWnDvnMw89xCm7vD1Y3bofHAw6MTYfvPAG0Tvdf5O8WPdqvJr3oTzo9t469wnrvBu1l7z+UNq7hZXWOb+w0ryyuVG9EHJLupe7vL3WuqW7nNEJPBjTXrzK94Q7YjcvOyqbULzEI2S7VcSJu1BX+zuR1RO9nKgLvPhsjbzya3M8DdjLOqIdVDtsy4Y8KFYevJWsMzyCDRG8KBaevLiuNbveBpM8W4b/PNwGcbzFwAY9h+SVPNgjiDzpB428/2QVvNvJ9jxiq/I8LUl4u1YsKTzTsNe83SLKPAUp3TuQ0Oa8YYwJPEldC7yCyY28qkr3OzGOXLwfbgI8XdG/vH7BA7uSAMM8/o1gPJ+FQLzARjU8vGcVPTl+pDwZBRE8h+q/vGYVrzy2RSC9YB9OvdjsjDv1x4a6xuSFPKwDnLwh0wk9hhPauzhMorwtTyU8fdY6Ou32HDwWR/C8krHuu47a1DxN0nC8yUS3ON+4hDzhwKm8mVWkvD9kbrtgDxE8B78XvEGJ/Dwbhfw8JR6PO4NSCr0qROc8hFWqvCIytLwrXic8D91AOu2w7bvT89S8gtSBPMKA/Tt1iO67E2E9PUu4p7qJ+pE8kXipPBvNXbw136o8JQVaujfrUzoLl6E8angmO9i7aLwQffQ8xk2tO12VCL1FOzC8qIEDPTDCkzo71Km7NRg0O8otujwSeQ27PcR/u590DD1rKwy7pU2NvCx7wzv/pvw6PiROPOAjkTzinvY8y7Gyu8KOWLo+k7M7xyKgOyyBEby0oDY87MlMPLGm+zqQG1S90t4TvAtjOzzEAjO8fYwMOyG5kruRDHc8njs5vSAmpLtgD0G8LgM5PT2ZKb3lbSS9uPulvFKONbwvVcA7glsWPfO3bDuEuga8GBQdPFq8UTxpMcO8Cey0vLZAFDwxbAw93uTfvB0u2bzxTLu7Rd/mvLf9Orwgj868aFAjvQvQmDwF+hE8Guc3vewU/bwaHD69OyJXO3yEQbxjHe68Y+BFvHh2hLzrC/g8blx/vHZD8zxYBjY6WAfbvOa/NjxpGgc8O22EvDVWFz2KdBQ6Yih0PMZ5QbuRE5k8PCUUvIe1Zb0jgZq86PSvO+rWkLwTB8S7zxWOu7XeEr05Fr088Y90O4+9tzz6meQ8jGGDvaJdWDzH5+68ObeUvI/PLzz2LDi8J6uZO0I/Ar27b9+8bJFLvCYEs7v78fa8yDpBvOlz8byKroO7SbqUPCcXPLzoyv88ZsY3vaOxsTvoKYu74WgJPXUIQrx4pY082aF8O3ocjDx958Q7KfQBOz2yHTx91rk86gt5PFp48bu2eTU9viNLPEUAijrJyQw9WXrfPO56pbtDKSA9bZn1uyBSm7vkTty8zq7IOpT/Dr3Zw5y8zO4gPKY/lrwkIAu8eLGuO6x7fzwwLie9MK7Lu+rpozzUmKW8FD8HvYWC9zvY2Ee9CeAqvMdpIrwb7Qy9WfqnPDXhqruOWh07l7Z0PKPac7w/Tdm8XbNbPb0He7zLAD+4wNj5PGViG7xv1yC9EG4yPQ0O0jk6QJS8Ug/MvMsYBD1YMeg8mYEpPLSsJTy/jNM7VpTsPMQ4iTor+e48ROPKuh3dOD3qPkw77DRgvO6EGDx5Oxq9seWZPFHvkDpmXCC9l7O0PO4Z3TxSTK884Q0yPBJPyroh7Ik8EwLCO2ehqjwIq9Y8Pc/zu/B9y7xC+gO8VeQXPYApCL0DAro7XCetvGuzjLt1Zki97LzRPC9MnzyxELi80PfYO87WHLzDz8C73lNHPM8i3juHplo80Ql4PDkixzxfl8c7z1vnuoA5Kjz/0UA9iF8bPXvUnbuiMIK8DpgMvda2sLp2c1M7C6DOvMZtqjzOULq7c+tBPDcSFD1m7i68fX4kvWw6uzy5t6Y8mN/cOvhLJr3Xx747QzZXPDzERzy89gi6sycMvPACW7uu8dI8X0pZPCLNBr05Upm8KWQZvO+nG7x0TV68BDNavPcuAb3nH8+8Yt4HPFQZjjsATBY8yOMEPDQkEzyqBle7NN+QvK1n1LqxbsM8ycSnO3RQorrvbEm8lCwvvQ90+jwebfc8zjb6PFOLR7zMaRy7oVvyOZfad7zIPL+8GlkYva8q1rz49iQ7PCYavTkxFb3+KWc93754PF7gZbwYznw8qB2Vu93+xrzw1dE8oJCYvOdnGz1IQeg8dUYhvPrucz3AZZw8jYCJPJqP4TsY/5G87zs4PeVvzLw03Kg8d0SxvHsvtLwUTKW8iA65u5tweDxi/sc8HmQovJtAgzwMly66YcRBPZw1AD0J33A8WrFjPPAIWjz7IBU9s9I5OhDysTzKXZY8CJYWvGduMbzk5VM7ntIBPSYyZjrB9pG8mvfIPDnwKzyDmTO7kzwMvHf+HDw/hgi8hokmvOOrsbxmWfE6NjaPvHu4czxRKBO9pEeBuwMvVTxnNPs7TWjZuyJhGz33dsy7QQhhPLBbJj3BOGG8tpCUvDKYYTx+bh88/IsGvD54vbzTe5u84vMgvfCnabsz8ya97a4GvYT397zD1QY8DEVZu/CQTLwOO1w9VwWvOlojdLy1pGK4FLvdPJtG0TyhMjG8MWmBvJmJ6byqjBw8F+e3u6Kkwzxsft26PdwsvPNLQrwsyeI8eP9XupESkTrpKro8SNuXu486Pb36EwM8zVaqPMxBojxCifW8n4dcu0/mBT1TAw27KGwAPLZ71zyUIV07pF0VPHk5HbxC1ya7jvF6OtqgnLzhH9s8GaU9u5qOHzuCgYE6pKRdO7SS8TquTo68bWY7Pe2A9jvo1Um8qJ7Bu5Yfubx6DKi8FU4lvCtoErunbPk72EtoPJPwNrzUyng8HFE2vEGewbtq6I89jRjRPCTyMDwCGv+8uGr3PH7suzx867k8QyeCPLsNZTz1FxI9kXKkvC0c57v2CB476h3dPM6ElToiaMw8fVS8uwginztRXo48XrdpvGRh1LvuZcE7D866PG5Tpbzgw988MnwePTErLbsNTR88G6/1uy7s4Du+x4g7DX1hu6TJgLxg92i808qjuoJZUTybBra7iSi1vDU1Qju/OpE715ZaPJEMr7y0gzY8RP2LvIDEJjwcyig6aMEWPOWPTzzBzfq8Yj4lPQT0gTtyweG8+vG2PF1BWT1qrle8PInEu689Kjy7dX46tcrrvC6irTy0Sg88JyR4O7rFtbyug0q8hea/PBSNhbz4/vi7tEvLPIYKNbzPh688Odu5O8Zj8ztBQTY8UnCFu2QUBDzyb+q6j0xFPP/oADvnSC47dLMDO6u+0TzCJ4A7w6MAPfohoDy1P3k68aC4u4HJDb04gRg8cvAoPH8XP7xs3Zc7GLPlvLsZjzxHDXe9B0oFPUqS17zRB4a8cvEZPOU6jzo0f6C8ZIpoOz0D0LwRH1s7SMo+vYlqv7yuCoK8EjbwvLM4oTyQgbY8Lg4pPaBKETxnQ/a8PfLqPAhCljrUvL87M4CBu4NUXrz5U/+6FxJ9O/f6gryGxQe8yOWEu9sfijzzeLK8V5N/PKbOJry/Uw88ifAJvO3h57y1jqg8u3B3vJhU+buY/PU8GJ8nvPxw8rptUKu8o6OQuV9NyLy/43W7W9fKPARZcryLDku8fzEYvefPpbxBTRU6X2wGvRLwZzzhIKc8npXtu+aQATx49tE5itWau6wL4zvVnd+89fINPOQu87yo2UG8HzhbPe1NvDrhng2895DuPG5Sujws6cq6mXAmvMY6yzzordY7FpzTvJh6Pjs+oyQ91EjJvL2qWjzx3Va81ys6PNAUFLwxOGE8rB0pPFcOm7unzOc6ngWsO9H8RLvABwc9/zddPGFaSbyGbZk7asvtuyAgLLt+17e70IiCPBiEyDx5lTu8jH+IOrcrHr3Lffi6pdFUvLW9nLwD+sY8gRGCPEI/HDszHJE8ZPQlPUDmGbwUF7U5LpO4vIIWrbz1Hte83wr/PAhS37yNvS283GTtPI3KYTxbXQm9xQ0Tuz+SFj1u7Lk8wpEwvUp+17slUSk6O4hUPLN1orpGAY07aJvSvMoVWrvfg3a9GY2sPMx7y7uvnYI8g3DYvDECuDzp+XE8GcaNvNdu6TzIW6w8/DlLPR8t1DwCymG8rgjmO25tEryNRgW8XQgUuy3FsDyAoZg8U6uUPLCn7Doy7ie9FHogvWrhGzrF2Rm9wfR0vHs5Q7wccoG8Z8SmOzqw1Dwxz5w71ZtdO4xYoTwRSYS88P9/PEXZGjxlqhC9bYH5OrXol7uN/AU9V8r9PJu+cjxdVOQ8BwGCPLghxrpzBzU9u4l0vJCcmLxQ+6Q8rwz6OicudLwuAwG9m63ku9vXFr1HkvC8qS7LPMhkBzx2aAg9qOLFvN+4/Tksxig9mt/Iu7eARLxRxIi8bruQvAsQDj3F7/o7O2/7PDcmibzgHpc7vH43POz4Hz1GcX681U51PBHk6zztjuC8RTzhu+3+2Lz9Abw4WXKFvKSWXLzUi748VF7FO7Xr7DvMoFE8boe9vHnAPrxtz4S8ow28PJi14rti1wW9RKpoPGa83DuXcKy8F1/7Oy0uyjzkm8A7MyiguyyXnbxUrJU8ZF6buoW6C705LYK7fyTKPNxNqzw9gIk8eQb/vAm2QT1iX8C7YafLOgPjY7xrgMK6ky4CO9ciT7wjAhQ9imhyPFpmTLx9pp68tIWXvPRHZLxrKZU7b1HLuwPVeTxPGZW8k42qOxXykDv2aKW6MnM/vP33KbxbPL48vGKJvBSz2rw3WGM7URe7vEo8Hz0SeZ48kF5hPIsHfTzGNmG7tGr+PFckbLoilt+8Ka0ivB3v2rzGcCC8nGomPECfXbv9QDm9lDv+uigyMzy0rX68fjj/PEK3fjwaHPI8bbtuPGkTBryI7Q476rU1O7NhcbwAY8G7+SGHvIyKwDwU2fC8Ksu/vH6s+7szxHM7TkjAPF9tsbr5+EE9LWxBvK/SCzzXEAq9M4f4PGghkjxGXRg7WQEBPRZSezuHHCo8zr7Du5ax07xmKAG8kmJsvNB7eLu9Kpk8Qv8CvMrbUT1Tbzw86HXEvDGz6zsKxb482LZBO6T1yLyLDAw7ywSKPC2YOD3yS2i8MBovve5mUzwxEba8nQvPvMn+ejtO2to8XROfPGk1KL1Ae587ct/ZO+RqEL2HYI486D4APDhHWrwqZJy7BmPePEViwDwHfy68wuGMuwxrqjvYBLa5BzFpPHW87bwA3hE6vxsyPGUoaD2nz5S8a838vHlVgbstpAo8UDXMPH0XHzz0YYY6JEmHPABr4LvBimG7ak6uOwBby7wDRM+8sB5Qu9ptzzsviIo8hIZAPKzjHjzILXk89S1cu7F2rLsW34I8B6Cru67TM7tSmYe8p5/6uk98ADtPpoS8AGD/vJM6L7ylIr+7hV4uPEtPl7s/qqM8Pss0O8wSozxZxDO8blK5u8NwzzvWo2g87rCjPL12FLpxpns8DevEPNGZMrwq66q8DTwXvF0qf7rPnua8h5E8vPhYdDwGb4i8TjyLvEWAQrx3BTk9qIJdu4j/qbx9ebS8xrsJvdntijzCG9A8MiKGPF+cNjuxLaK7AcAPu5hlMjyDpco8mtxxO+WFq7uz8Ys8pB20vHTsjzyTqwe8Rsf/PGCHwzvOs7674qBVPNiz47pmYfe8U/v8PP6mNzxNjoS7o+Sau72gHrxZCh28qwmaPHxlEjwlJUA8LXWuOhXffDyimui7gTu0uwwKJzxhksK8ryJePElJfDoPgK48iGsGO9mZ4Ls2eee7ROqJvDCGCLzgCAA7B9RFu/iBDrw+7I88Z9pgvDhCaTyKt727lR0Iu9O+XzyKGqI8ramou4ZtxDpVwyw8bAq2uzTHczwOcQo9OHe2PGRVlbwTtY88xbS9vKz0aznD8Wo82pI5vInSDj0pNxW8EroQui8T2zy2HZU8zPlUvITFcLuW/w89lpKLvFKv+DwX+vg8tF3SPKzfq7wTsQo8rBYCvAvmZD1F1Ac8gV07POB+yTvlpq08z+ffO40Gzzys3Le8YTcVuzqiZb0VisM7eHm3PDKKxTwa/JE70kFjPKpOMrtf8647EA1CvIYp8LwDkwI9hMyhOoicOLyHYaQ7SMxHvF0WEDy926E8vGGTPLAxdrvwG4m6d0YSPJ14PzyL+Fw7ZIA8vAyBdDwJMPO8pAlevIj4o7yJiRg98XzXPE8TPrwL0eu8MaWqO4BACrxa0eW8RqOLPKSoCzwDy0Y8loFRuaThKrojJtM71JEZPO6ZuLxA57W8IolWu9dSsTeyNsq8upAHPMoxiDvKP408+BgCPYOYgrkICrc72cNuvOtROzs03vc82yJyu98GmTsgTBk8GI2pvLOEwjx5HIo8mIaNvGPg2rxOT4O8oMyiu1S82rsA1b88kya5PAlf17vJ9o08TO/jvFPCCD3mFSq9KMZTvEF+UjwVEUw7SJFwPIFLzDwQOUc7NrZkPMR7iTzMoSo9ZnqSPD+IgTwIZIs8nMuTvB6dyzunzAi8YC2cuifhsDxbaci8054dPc6DyTwJVh+9Joc6PPXNnjwIwMG8/7LguyPDpLtcxSc8qBDsvP964jsT8KY88nnYPPOvCLzhmja8Q2PHPGvJ07w5DU088bWaug5wLTw5l8Q8sUpbPKwuOzweTTW8WihgPPKe1DyCkCW9baYpuuZMAbyxWPY6P2iBO6lCDD1Epx08MDvyuwgDADyO5hG6zxxquxZgpjwpf0M8rD8EvF25wDzzywO8hIA7PIYoejt5xpY8KchAvGLrB7qM5968WCFnPCVonDq8Qiu9xvmyvFshJzvBUgU8G4PqvJLFJ7ogtH08ZoGyuqbGMbzA+qU8WvJyvKLCkbqnhOg81Ot1utGInjtO3jS8XTqlPB0xnzz/ujO7fbEzO8hn3TxzJgG7ItqBPCWLZ7zc2Ze87havPPSf6TpgQiW8wv6CvJrvYjxGjfW8ntiavNywBzyLwx68wvmIvPiP+brmEug8V1WJPBBo27lxmpA8FN48uzFX27xsvQm9bgjOPNHk9brtO8m4qcumvL/gjTyss5M6n2vdPPhkhDoaezG94NvDvBI0qDzMd6y7S1JxvHbhCryg8QK8jIOCvFdbRTphKv+5wZ4bPc3v1DwMPUu8QZGrvNY7KT0pHIq7HpptvAyfxLwfsY67bVWlvKLeqrs1m3O7BAjzPJ+Aq7uDK9C6TAtNPbRMGrsFlvG89xNButny8rz3Z+u8DK2Uu+VVkLxvGxS8WdBTu5CRTbyzawc9cKTxO8eCqLv5zpi8gQGjvCjO3DyG5Gc8/ZW5OyLMkjsBVwG8OQUWvQTC+zxlq408rT2vPP4acbtrF4y7ZBoTOxp14LtM7CU8ZBaIPLlog7yqGwE9igrDutBv+7zjjNy7e0UVu0jP6LtWQjI8UyGlvPADkbzKoI27xVNwvCc8ITtJMM+8JzknvWVMmTwAdR473A0/PPX2Gr2dFn088/MrvXAJ6TuC89Y8vs7Qutfaxrx1Mhu9RpE8PLw3HTzkAcG7yo21O++QGLx8L+M8sdUDvTbPo7xS5jg9vfpmPAdDUruCqLe8Pbfjux/Sk7wfWH+8r10lvFgVpbwcNjE9pZ8eu+U95rtyyz68TVQePOKwTLxdwOo6EOgdvXyqFTwSbwm9GyG+u5csj7wXE7y7/gvuPAzBFD3zt3o8E4GWvDjtM7ymLAW9TGqEPAmx/7vzbB48Q1uXPIZ8t7vnfcK72pG4Oy13UjxUQ7i8b6ZRvDM+Qzx7mA087msXPIEDbDwExhA8blOTPLySd7w1VjC8f0dSvHyBBr0N/0G7gJHpu1JVt7qYi5Q8I0UzPNgP6rwPqP475TwxvH8vorrOIQA9muK9uxr/ELsEo9E7umEQOigy+jwknZU8K/ejPCtGbLoud/A76zKovKhMXDwyur08FmXOPACAJz0FW3m5nbVUPLKrWDyOu2w8FtLVPCYxJDx2fLS8g985vMWxqDvlZy+8SL/ePIMQmzyHJv27Os4sPSypzbrzUIe82jvsPO9K57xgcvW7wlPNO+KTmrth0ic7wBlmPMx67DwPDpI8I6kAvBDAa7u1zcm8C2ktPKOzD7rGPZc8CFvsvGKSAr3bww69Zv0bvCnvpLoEiJE8Uv4cvVP8kLysX647OJwuvNOgPTo0DiE8x52Su2H+EbzNijo8YkdIvNXqhDzjNrY8OIHtPObOlLvnJ9Q8cWk5vHeXu7u5iYC8Mfh9vMYz57vw6zc8AnEavOApgLx0da08t2I6PcYGSLxlz2k8A/T7PNE88rwMmMS81QAgvXzenDxhoq48DqIhPKN9FbuhCvI8FK2Lu2U70TyWBe08whLQPMMoJzyEWre4MEHEvFaRdDyTdhC83Fo6PPfOizt89L68J6EXO6Gwnbwetpc8GiBvOT8nUb0ZoyE9CzNoPOb5Lby69y+8noNVvckMATxXOas8rYkdu1He2zu7ZqC8YXaRvOeSKD0SV/W86CI1vG3CBrxSQbq87t8yvKLvTju6LUE7a0EsPHFgrDrby9C8ErK/u10KrzxX3H28onCeO60ZijyFFzI7xPTUurM3hDzZlQS8ym1aO0JSbjsS30E73CEEuzkK2Dv6N226buF1vAwWXzsGS/a8uQ4iu2/2DTzDgqc8C98fvMqE77rgFgW9Y/aAPdnUr7tPS6K84MBovNlWL7z8kpu7FH24vK2T3DtE9a68LkOGvGt2o7xFIJS7d0tdPJocrbzNxnC8Z9IrPMHJwDx/1XU8oCdou/KNtLy8D2W8XYFYOrvZXDxjTa28xw0dPHY57TvtPUm8WdWOvJus07teoGK8qk3EOwfz7Lvyajo8gpiIPOZkaTzB4ZU8X7KEPI17qjz8Bdi8G6K/vAWrtjslmIg8GnY7PPRpvztVxiY8t8KuPK0sGTzA7qi7IKrLvK0BDb3JIBm5NTbpuucTYjw6pxY8sURgu6M1Xrym2NG82smwPLS4qzwmluo84xE9PEjFJ7xuRj48wIJ/vNHeUrs6Zr88fLqsOm6GGjyFhR05fEqCPHEWjDp1OE66aqeou0iotzvIT8a8ViGKOjfff7vd8pe8GMQvOgnJvbuF34g7Q9g6PKqUCbwSQLs8QsKEPKrbjTwZ2z49fPPEPL9lrLxtHhy8g8A1PLWmKrzNtCQ7pr3dvNXgT70A2vg84RNtPEiYPLzFrp08r1tVvFp9PTs7GFE8XQ24vJS/irw/lru8aFsqu79e9bwdmA88pW+/PPybE7wTT4a7fW5mOw/X5jz7ZVe7nTUAvdhhPLz+vLI8ooJbO0CP3ru3FAe99XBIO7Y/Fr023SI9mydAvehGTL390Pm7054HOrDouDuc01a6oDWZPMi0kLxOaSI9MZgsvWSjxjw/KF27zJ/qu6KncTtNjYq8PTkcvDS6+7vckhc8baKSvCVDWjzWjoE821xQPL1j+zvoh3C7ZW41vPRMmjiwoZ+8EBjiPNJwEjtIAwk9NNoAvAmbEzwc31C7xO6Su4onubwyWKa7LJk2PCp/JrxfEQQ9lpTIvJXfLDzTrSo7h6xkvAZXKDx6Qqs8T6fePFbs1bttzpE7KpIrPNNwtDtMPCY9GsJjPLfl0rxOewc8OIYQvEyQFz2GEQg8HVFKvLxg+7x9KyS9vdZvua+wSzuR6xu8DZfzu1K8rbtGF568NXMWuyWG0byD8YC72QybvKyLEzyBpLI7bT/GvMiwWDwyuGc66J58vFZmE7zDpaO7LAMzPI4ziDxTXeC8/DtBvKNnEDxZnEa9FH28vJFx8TpyF4y8yFnVPJhUJL06nXu6tp/BPJ5O+LtMSq+8Tke8vF8nKbw0fI885ewiPWeYlbsGlR88EgAPPA3Uebw5mTG9u4suvK372rwXf0i8HKMXPPT7grvwPLg82DjQO5aHproiDXo89jfZu+4gx7rrpLM7/dzCvIhZQbtkxI281XkVvFmFlztSV/m7G2AgPG8P1DuXNkw8g/7yu1IzH7y+QBE9fHjsOy/9YDxeyZG8IhYvvEk7sby2KAW8QOiaOzqkXTzC5Vy8iyEOvBo3p7x7TRE5WaIIu06JELzD7pq7OaY6vFN157uLIk48l46NPDpDZDwnfbG8EopzvVhQhjwqNJa6Y1Aau34F9Lmy9Mu7IgILve8v4Tu6e8C8PZPYPPZKvrvGawW8uxYruysXe7zQ8ia8AjLROt9Mgrw8D8i8tOlpu/TgmTxCmQC8pRDfPAqCYLyoUb082/rMu7vmMjpYHbS8maQfPMeUhjrpUKe8GFumvNTUFT3aUUq7KlbcPGt/Drs3wyS8tVm4PMWnaDx0rvs75teWPP22gTyDZ8e8YrzbPGiU77x/R4486vSIPF14JTxnKg67zd58PFnWjbuk7yQ94HFNvLxbezyeHcI8ex6AvI1pIbzFosK81+SMOgMaiDz5ZZg7HEDPuzdKiLxy+hU9u39kPFEI4TuBWKE8w7ikvA/Hubz9LQC8/BKQu5Hs2Tp/ASC8bQylO3HNxTtLgz47jTwcvdsmoDxCKDG7xR1LvJN7kzsRuiu7NNSlvLv4pTw2lc07NOwrPVm2Bj1RYh08iW/+Ow68CzwRe/q7w3tVvNtBJbxPFhs97BiDuxOq7ryJBeE7wgj/vPDEvzzjmI05HZYWO1HfCz0K2Xc7dKL1uxl2NDwOzDS8wl7Ruoqj/LsYqbq7eejJPOIkBbwHT5C8eAqpvD9RQj3SjPc8HooWPQETkboC/PU81Q2HPMxzCLwcPSY83t7ZPE3kMDskbq07/QkXPKfj2LwdX+q8pmwrPCvq3TsQI4+8UzcOPTJdVrzGWSo8RRSmOw3Oe7pviJy66c6QuliyzDsoXVu8jv5pvFr4v7wtctU8TD0RvUU8bTwnW+y86C8hO4+E9TyBkKs7hBrduotYdDwGwCk8f1sqPLysnjyOkuQ7JS9pux9rXLvBmAe9WvuIO42Mzju9Rje8XVkzPYqicLzoLNs8HBYePGKCCjxwkk06VVOnvH/LBDw8ntc8yadRuyr+OTxBC9k8R6dauhj5+zzusyS799JJu3HGxbuI+Rm8Wed9vAOEwzryS0U83bUnu7T88zxXKCk8S6WFPJ14c7oSs+U6mvwFvdc1K72u3Gg84UyJOxCcAD0cJya84YLLuydGDboM6YI8GULmutWdtzubQa47KE4evCZrLrstkJQ8YM61vDvj2zvfWVY8lrEwO+YAdjznWLi7SLjLvKnW7zt7Nro84oa/O9gohrzbxD67j++YvMMcrzpeKK877sKRO4ZrxTz+bt07PJL9u3QsbDsRXDm82vjjPFBuLrxfxkm76Hy/u2DGMrymGlY818INuA==
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 5
+        total_tokens: 5
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/cassettes/test_rebuild/test_rechunk_raises_when_docling_blob_is_missing.yaml b/tests/cassettes/test_rebuild/test_rechunk_raises_when_docling_blob_is_missing.yaml
new file mode 100644
index 00000000..e46e6ca3
--- /dev/null
+++ b/tests/cassettes/test_rebuild/test_rechunk_raises_when_docling_blob_is_missing.yaml
@@ -0,0 +1,42 @@
+interactions:
+- request:
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '93'
+      content-type:
+      - application/json
+      host:
+      - localhost:11434
+    method: POST
+    parsed_body:
+      encoding_format: base64
+      input:
+      - doc with a cleared blob
+      model: qwen3-embedding:4b
+    uri: http://localhost:11434/v1/embeddings
+  response:
+    headers:
+      content-type:
+      - application/json
+      transfer-encoding:
+      - chunked
+    parsed_body:
+      data:
+      - embedding: 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
+        index: 0
+        object: embedding
+      model: qwen3-embedding:4b
+      object: list
+      usage:
+        prompt_tokens: 6
+        total_tokens: 6
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/conftest.py b/tests/conftest.py
index b5924d74..fb5229c1 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -2,6 +2,8 @@ import json
 import logging
 import os
 import tempfile
+from collections.abc import Iterator
+from contextlib import contextmanager
 from pathlib import Path
 from typing import TYPE_CHECKING, Any
 
@@ -32,6 +34,31 @@ setattr(pydantic_ai.models, "ALLOW_MODEL_REQUESTS", False)
 logging.getLogger("vcr.cassette").setLevel(logging.WARNING)
 
 
+@contextmanager
+def capture_logs(
+    logger: logging.Logger, level: int
+) -> Iterator[list[logging.LogRecord]]:
+    """Collect records emitted by ``logger`` at or above ``level``.
+
+    Attaches directly to the given logger instead of using ``caplog``:
+    ``haiku.rag.logging.get_logger()`` sets ``propagate=False`` on the
+    ``haiku.rag`` logger, so records never reach caplog's root handler once
+    any test in the session has called it.
+    """
+    records: list[logging.LogRecord] = []
+
+    class _ListHandler(logging.Handler):
+        def emit(self, record: logging.LogRecord) -> None:
+            records.append(record)
+
+    handler = _ListHandler(level=level)
+    logger.addHandler(handler)
+    try:
+        yield records
+    finally:
+        logger.removeHandler(handler)
+
+
 @pytest.fixture(scope="session")
 def qa_corpus() -> list[dict[str, str]]:
     corpus_path = Path(__file__).parent / "data" / "qa_corpus.json"
diff --git a/tests/ingester/test_fs_source.py b/tests/ingester/test_fs_source.py
index 31c7b838..55b4fc17 100644
--- a/tests/ingester/test_fs_source.py
+++ b/tests/ingester/test_fs_source.py
@@ -330,3 +330,46 @@ async def test_fs_source_fetch_reads_off_event_loop_thread(fs_root: Path):
         "FSSource._read_body ran on the event-loop thread; the read+hash must "
         "be dispatched via asyncio.to_thread"
     )
+
+
+@pytest.mark.asyncio
+async def test_fetch_rejects_foreign_scheme(tmp_path):
+    """`supports()` short-circuits on scheme, but fetch/head resolve directly,
+    so the unsupported-scheme path must be handled there too."""
+    src = FSSource(root=tmp_path, supported_extensions=[".md"], source_id="local")
+
+    # A same-named file under the root exists, so a scheme-blind implementation
+    # would happily resolve it — None/raise here really is the scheme check.
+    (tmp_path / "key.md").write_text("local copy")
+    assert await src.head((tmp_path / "key.md").as_uri()) is not None
+
+    with pytest.raises(UnsupportedSourceError):
+        await src.fetch("s3://bucket/key.md")
+
+    assert await src.head("s3://bucket/key.md") is None
+
+
+@pytest.mark.asyncio
+async def test_fetch_falls_back_to_octet_stream_for_unknown_extension(tmp_path):
+    target = tmp_path / "data.unknownext"
+    target.write_bytes(b"payload")
+    src = FSSource(
+        root=tmp_path, supported_extensions=[".unknownext"], source_id="local"
+    )
+
+    result = await src.fetch(target.as_uri())
+
+    assert result.content_type == "application/octet-stream"
+    assert result.body == b"payload"
+
+
+@pytest.mark.asyncio
+async def test_discover_skips_symlink_to_missing_in_root_target(tmp_path):
+    """A broken symlink inside the root resolves to a path that is not a file."""
+    (tmp_path / "real.md").write_text("real")
+    (tmp_path / "broken.md").symlink_to(tmp_path / "absent.md")
+    src = FSSource(root=tmp_path, supported_extensions=[".md"], source_id="local")
+
+    events = [e async for e in src.discover()]
+
+    assert {e.uri for e in events} == {(tmp_path / "real.md").as_uri()}
diff --git a/tests/ingester/test_http_source.py b/tests/ingester/test_http_source.py
index 08915e5e..856ad50c 100644
--- a/tests/ingester/test_http_source.py
+++ b/tests/ingester/test_http_source.py
@@ -422,3 +422,14 @@ async def test_fetch_skips_head_when_no_max_size():
     )
     await src.fetch("https://example.com/a.md")
     assert calls == ["GET"]
+
+
+@pytest.mark.asyncio
+async def test_aclose_closes_the_http_client():
+    src = HTTPSource(
+        source_id="urls",
+        urls=[],
+        transport=httpx.MockTransport(lambda r: httpx.Response(200)),
+    )
+    await src.aclose()
+    assert src._http.is_closed
diff --git a/tests/ingester/test_pollers.py b/tests/ingester/test_pollers.py
index d7970d13..b33bc2d3 100644
--- a/tests/ingester/test_pollers.py
+++ b/tests/ingester/test_pollers.py
@@ -602,3 +602,159 @@ async def test_fs_poller_enqueues_initial_files(tmp_path, jobs, sync):
     queued = await jobs.list_jobs(source_id="local")
     assert {Path(j.uri).name for j in queued} == {"a.md", "b.md"}
     assert all(j.status is JobStatus.QUEUED for j in queued)
+
+
+# --- _dry_run_once ---
+
+
+@pytest.mark.asyncio
+async def test_dry_run_collects_changes_without_writing(fs_config, jobs, sync):
+    source = _StubSource(
+        "src",
+        [
+            [
+                _event("file:///a.md"),
+                _event("file:///b.md", kind=SourceEventKind.UNCHANGED),
+                _event("file:///c.md", kind=SourceEventKind.DELETE),
+            ]
+        ],
+    )
+    poller = _periodic(source, fs_config, jobs, sync)
+
+    ok, summary, changes = await poller._dry_run_once()
+
+    assert ok is True
+    assert summary.upsert_count == 1
+    assert summary.unchanged_count == 1
+    assert summary.delete_count == 1
+    assert {c.op for c in changes} == {JobOp.UPSERT, JobOp.DELETE}
+    # A dry run must not touch the queue.
+    assert await jobs.list_jobs(source_id="src") == []
+
+
+@pytest.mark.asyncio
+async def test_dry_run_ignores_deletes_when_delete_orphans_false(
+    fs_config, jobs, sync, tmp_path
+):
+    config = FSSourceConfig(
+        type="fs",
+        id="src",
+        root=tmp_path,
+        delete_orphans=False,
+        poll_interval_s=0.05,
+    )
+    source = _StubSource("src", [[_event("file:///c.md", kind=SourceEventKind.DELETE)]])
+    poller = _periodic(source, config, jobs, sync)
+
+    ok, summary, changes = await poller._dry_run_once()
+
+    assert ok is True
+    assert summary.delete_count == 0
+    assert summary.ignored_delete_count == 1
+    assert changes == []
+
+
+@pytest.mark.asyncio
+async def test_dry_run_skipped_when_circuit_open(fs_config, jobs, sync):
+    class _Clock:
+        now = 0.0
+
+        def __call__(self):
+            return self.now
+
+    breaker = CircuitBreaker(
+        CircuitBreakerConfig(failure_threshold=1, cooldown_s=30.0),
+        now_fn=_Clock(),
+    )
+    source = _StubSource("src", [])
+    source.fail_with = RuntimeError("upstream down")
+    poller = _periodic(source, fs_config, jobs, sync, breaker=breaker)
+
+    assert await poller._sweep_once() is False
+    assert breaker.is_open is True
+
+    before = source.discover_calls
+    ok, summary, changes = await poller._dry_run_once()
+
+    assert ok is False
+    assert changes == []
+    assert source.discover_calls == before
+    assert poller.last_skip_reason == "circuit_open"
+
+
+@pytest.mark.asyncio
+async def test_dry_run_records_failure_when_discover_raises(fs_config, jobs, sync):
+    source = _StubSource("src", [])
+    source.fail_with = RuntimeError("upstream down")
+    poller = _periodic(source, fs_config, jobs, sync)
+
+    ok, summary, changes = await poller._dry_run_once()
+
+    assert ok is False
+    assert changes == []
+    assert poller._breaker.consecutive_failures == 1
+
+
+@pytest.mark.asyncio
+async def test_dry_run_skipped_when_queue_has_pending_work(fs_config, jobs, sync):
+    source = _StubSource("src", [[_event("file:///a.md")]])
+    poller = _periodic(source, fs_config, jobs, sync)
+    await jobs.enqueue("src", "file:///pending.md", JobOp.UPSERT)
+
+    ok, _summary, changes = await poller._dry_run_once()
+
+    assert ok is False
+    assert changes == []
+    assert poller.last_skip_reason == "pending_work"
+
+
+@pytest.mark.asyncio
+async def test_watch_deleted_skipped_when_delete_orphans_false(tmp_path, jobs, sync):
+    from watchfiles import Change
+
+    from haiku.rag.ingester.pollers.fs import FSPoller
+    from haiku.rag.ingester.sources.fs import FSSource
+
+    cfg = FSSourceConfig(
+        type="fs",
+        id="local",
+        root=tmp_path,
+        delete_orphans=False,
+        poll_interval_s=60.0,
+    )
+    poller = FSPoller(
+        source=FSSource(root=tmp_path, supported_extensions=[".md"], source_id="local"),
+        config=cfg,
+        job_repo=jobs,
+        sync_repo=sync,
+    )
+
+    await poller._handle_watch_change(Change.deleted, tmp_path / "gone.md")
+
+    assert await jobs.list_jobs(source_id="local") == []
+
+
+@pytest.mark.asyncio
+async def test_dry_run_manifest_reports_failed_sources(tmp_path, jobs, sync):
+    """A source whose discover() raises is named in the failed list while the
+    manifest still carries the sources that succeeded."""
+    manager = PollerManager(
+        configs=[FSSourceConfig(type="fs", id="ok", root=tmp_path)],
+        job_repo=jobs,
+        sync_repo=sync,
+    )
+    broken = _StubSource("broken", [])
+    broken.fail_with = RuntimeError("upstream down")
+    manager._pollers.append(
+        _periodic(
+            broken,
+            FSSourceConfig(type="fs", id="broken", root=tmp_path, poll_interval_s=60.0),
+            jobs,
+            sync,
+        )
+    )
+
+    manifest, failed = await manager.dry_run_manifest()
+
+    assert failed == ["broken"]
+    assert {s.source_id for s in manifest.sources} == {"ok", "broken"}
diff --git a/tests/ingester/test_webdav_source.py b/tests/ingester/test_webdav_source.py
index 060ddb06..8659c017 100644
--- a/tests/ingester/test_webdav_source.py
+++ b/tests/ingester/test_webdav_source.py
@@ -7,26 +7,29 @@ from haiku.rag.ingester.sources.base import FileTooLargeError, SourceEventKind
 from haiku.rag.ingester.sources.webdav import WebDAVSource, _strip_etag
 
 
-def test_strip_etag_strong_quoted():
-    assert _strip_etag('"abc123"') == "abc123"
-
-
-def test_strip_etag_weak_marker():
-    assert _strip_etag('W/"abc123"') == "abc123"
-
-
-def test_strip_etag_unquoted():
-    assert _strip_etag("abc123") == "abc123"
-
-
-def test_strip_etag_whitespace():
-    assert _strip_etag('  W/"abc"  ') == "abc"
-
-
-def test_strip_etag_empty_returns_none():
-    assert _strip_etag("") is None
-    assert _strip_etag('""') is None
-    assert _strip_etag(None) is None
+@pytest.mark.parametrize(
+    "raw,expected",
+    [
+        ('"abc123"', "abc123"),
+        ('W/"abc123"', "abc123"),
+        ("abc123", "abc123"),
+        ('  W/"abc"  ', "abc"),
+        ("", None),
+        ('""', None),
+        (None, None),
+    ],
+    ids=[
+        "strong_quoted",
+        "weak_marker",
+        "unquoted",
+        "whitespace",
+        "empty",
+        "empty_quotes",
+        "none",
+    ],
+)
+def test_strip_etag(raw, expected):
+    assert _strip_etag(raw) == expected
 
 
 def _transport(handler) -> httpx.MockTransport:
@@ -628,3 +631,128 @@ async def test_fetch_skips_head_when_no_max_size():
     )
     await src.fetch("https://nc.example.com/dav/a.txt")
     assert calls == ["GET"]
+
+
+# Malformed multistatus bodies: a <response> that can't be decoded is dropped
+# rather than aborting the whole listing.
+
+
+def _raw_multistatus(*response_blocks: str) -> bytes:
+    body = ['<?xml version="1.0" encoding="utf-8"?>', '<d:multistatus xmlns:d="DAV:">']
+    body.extend(response_blocks)
+    body.append("</d:multistatus>")
+    return "\n".join(body).encode()
+
+
+_NO_HREF = """  <d:response>
+    <d:propstat>
+      <d:status>HTTP/1.1 200 OK</d:status>
+      <d:prop><d:getetag>"r"</d:getetag></d:prop>
+    </d:propstat>
+  </d:response>"""
+
+_EMPTY_HREF = """  <d:response>
+    <d:href></d:href>
+    <d:propstat>
+      <d:status>HTTP/1.1 200 OK</d:status>
+      <d:prop><d:getetag>"r"</d:getetag></d:prop>
+    </d:propstat>
+  </d:response>"""
+
+_NO_STATUS = """  <d:response>
+    <d:href>/dav/a.md</d:href>
+    <d:propstat>
+      <d:prop><d:getetag>"r"</d:getetag></d:prop>
+    </d:propstat>
+  </d:response>"""
+
+_NOT_FOUND_STATUS = """  <d:response>
+    <d:href>/dav/a.md</d:href>
+    <d:propstat>
+      <d:status>HTTP/1.1 404 Not Found</d:status>
+      <d:prop><d:getetag>"r"</d:getetag></d:prop>
+    </d:propstat>
+  </d:response>"""
+
+_STATUS_WITHOUT_PROP = """  <d:response>
+    <d:href>/dav/a.md</d:href>
+    <d:propstat>
+      <d:status>HTTP/1.1 200 OK</d:status>
+    </d:propstat>
+  </d:response>"""
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "block",
+    [_NO_HREF, _EMPTY_HREF, _NO_STATUS, _NOT_FOUND_STATUS],
+    ids=["no_href", "empty_href", "propstat_without_status", "propstat_404"],
+)
+async def test_head_returns_none_for_undecodable_response(block):
+    def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(207, content=_raw_multistatus(block))
+
+    src = WebDAVSource(
+        source_id="nc",
+        base_url="https://nc.example.com/dav/",
+        transport=_transport(handler),
+    )
+    assert await src.head("https://nc.example.com/dav/a.md") is None
+
+
+@pytest.mark.asyncio
+async def test_head_returns_none_for_empty_multistatus():
+    def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(207, content=_raw_multistatus())
+
+    src = WebDAVSource(
+        source_id="nc",
+        base_url="https://nc.example.com/dav/",
+        transport=_transport(handler),
+    )
+    assert await src.head("https://nc.example.com/dav/a.md") is None
+
+
+def test_entry_with_status_but_no_prop_has_no_revision():
+    """A 200 propstat carrying no <prop> still yields an entry, without a
+    revision — distinct from the malformed bodies that yield no entry at all."""
+    from haiku.rag.ingester.sources.webdav import _parse_multistatus
+
+    entries = _parse_multistatus(_raw_multistatus(_STATUS_WITHOUT_PROP))
+
+    assert len(entries) == 1
+    assert entries[0].revision is None
+    assert _parse_multistatus(_raw_multistatus(_NO_HREF)) == []
+
+
+@pytest.mark.asyncio
+async def test_discover_skips_base_url_reported_as_file():
+    """Broken servers list the base URL itself as a non-collection; it and any
+    href outside the base are skipped."""
+    body = _multistatus(
+        {"href": "/dav/", "etag": '"base"'},
+        {"href": "/outside/x.md", "etag": '"out"'},
+        {"href": "/dav/keep.md", "etag": '"keep"'},
+    )
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(207, content=body)
+
+    src = WebDAVSource(
+        source_id="nc",
+        base_url="https://nc.example.com/dav/",
+        transport=_transport(handler),
+    )
+    events = [event async for event in src.discover()]
+    assert {e.uri for e in events} == {"https://nc.example.com/dav/keep.md"}
+
+
+@pytest.mark.asyncio
+async def test_aclose_closes_the_http_client():
+    src = WebDAVSource(
+        source_id="nc",
+        base_url="https://nc.example.com/dav/",
+        transport=_transport(lambda r: httpx.Response(200)),
+    )
+    await src.aclose()
+    assert src._http.is_closed
diff --git a/tests/sandbox/test_sandbox_toc.py b/tests/sandbox/test_sandbox_toc.py
index 9146603e..25ae2a04 100644
--- a/tests/sandbox/test_sandbox_toc.py
+++ b/tests/sandbox/test_sandbox_toc.py
@@ -364,3 +364,72 @@ class TestItemsJsonlSurfacesNewFields:
             assert expected <= set(r)
             assert "position" not in r
             assert "tree_depth" not in r
+
+
+@pytest.mark.asyncio
+class TestVfsReadPaths:
+    """The synchronous VFS readers bridge back to the event loop; drive them
+    through a worker thread the way execute() does."""
+
+    async def test_content_txt_is_read_lazily_per_document(self, temp_db_path):
+        async with HaikuRAG(temp_db_path, create=True) as client:
+            doc = await client.document_repository.create(
+                Document(content="the stored body", uri="test://body", title="Body")
+            )
+            doc_id = doc.id
+
+        sandbox = Sandbox(temp_db_path, AppConfig(), AnalysisContext())
+
+        # Build the VFS first, then change the stored content. A lazy
+        # CallbackFile reads through at access time and sees the new body;
+        # an eager MemoryFile mount would have captured the old one.
+        vfs = await sandbox._build_vfs()
+        sandbox._loop = asyncio.get_running_loop()
+
+        # Rewrite via the repository rather than client.update_document: the
+        # latter re-chunks and re-embeds, which this file deliberately avoids
+        # so these tests need no embedding endpoint.
+        async with HaikuRAG(temp_db_path, create=False) as client:
+            doc.content = "the rewritten body"
+            await client.document_repository.update(doc)
+
+        content = await asyncio.to_thread(
+            vfs.path_read_text, PurePosixPath(f"/documents/{doc_id}/content.txt")
+        )
+
+        assert content == "the rewritten body"
+
+    async def test_document_files_are_read_only(self, temp_db_path):
+        async with HaikuRAG(temp_db_path, create=True) as client:
+            doc = await client.document_repository.create(
+                Document(content="x", uri="test://ro", title="RO")
+            )
+            doc_id = doc.id
+
+        sandbox = Sandbox(temp_db_path, AppConfig(), AnalysisContext())
+        vfs = await sandbox._build_vfs()
+        sandbox._loop = asyncio.get_running_loop()
+
+        with pytest.raises(PermissionError, match="read-only"):
+            await asyncio.to_thread(
+                vfs.path_write_text,
+                PurePosixPath(f"/documents/{doc_id}/content.txt"),
+                "nope",
+            )
+
+    async def test_toc_skips_gaps_in_item_positions(self, temp_db_path):
+        """Positions need not be contiguous — a heading's span may cover
+        positions that carry no item."""
+        async with HaikuRAG(temp_db_path, create=True) as client:
+            doc_id = await _empty_doc(client, uri="test://gaps", title="Gaps")
+            # Positions 1 and 2 are absent between the header and the paragraph.
+            items = [
+                _header(doc_id, 0, 1, "Intro"),
+                _para(doc_id, 3),
+            ]
+            await client.document_item_repository.create_items(doc_id, items)
+
+        sandbox = Sandbox(temp_db_path, AppConfig(), AnalysisContext())
+        toc = await _read_toc(sandbox, doc_id)
+
+        assert [n["title"] for n in toc["tree"]] == ["Intro"]
diff --git a/tests/store/test_document_items.py b/tests/store/test_document_items.py
index cee84196..e6b1ed6c 100644
--- a/tests/store/test_document_items.py
+++ b/tests/store/test_document_items.py
@@ -986,3 +986,52 @@ class TestPictureDataPreservedThroughRoundTrip:
 
             after = await rag.document_item_repository.get_all_picture_data(created.id)
             assert after.get("#/pictures/0") == original.get("#/pictures/0")
+
+
+@pytest.mark.asyncio
+async def test_replace_for_document_with_no_items_deletes_existing(temp_db_path):
+    """Replacing with an empty list clears the document's items."""
+    from haiku.rag.store.engine import Store
+    from haiku.rag.store.repositories.document_item import DocumentItemRepository
+
+    async with Store(temp_db_path, create=True) as store:
+        repo = DocumentItemRepository(store)
+        docling_doc = _make_docling_doc()
+        await repo.replace_for_document("doc-1", extract_items("doc-1", docling_doc))
+        assert await repo.get_all_items("doc-1")
+
+        await repo.replace_for_document("doc-1", [])
+
+        assert await repo.get_all_items("doc-1") == []
+
+
+class TestExtractItemTextFallbacks:
+    def test_table_returns_none_when_serialization_fails(self):
+        """A serializer that raises leaves the table with no extractable text
+        rather than aborting the extraction pass."""
+        doc = _doc_with_tables(1)
+
+        class _Boom:
+            def serialize(self, item):
+                raise RuntimeError("serializer exploded")
+
+        assert extract_item_text(doc.tables[0], doc, get_serializer=_Boom) is None
+
+    def test_file_backed_picture_has_no_inline_bytes(self):
+        """A picture whose ImageRef points at a file rather than a data: URI
+        carries nothing to decode."""
+        from docling_core.types.doc.document import ImageRef
+
+        from haiku.rag.store.models.document_item import _decode_picture_bytes
+
+        doc, pic = _doc_with_captioned_picture("caption")
+        pic.image = ImageRef.model_validate(
+            {
+                "mimetype": "image/png",
+                "dpi": 72,
+                "size": {"width": 1, "height": 1},
+                "uri": "file:///tmp/picture.png",
+            }
+        )
+
+        assert _decode_picture_bytes(pic) is None
diff --git a/tests/store/test_restore.py b/tests/store/test_restore.py
index 5202bb97..b7e0d295 100644
--- a/tests/store/test_restore.py
+++ b/tests/store/test_restore.py
@@ -112,8 +112,10 @@ async def test_restore_safety_tag_name_collision(temp_db_path, monkeypatch):
         await store.create_tag("release-1")
         await store.create_tag("before-restore-20260715T143012Z")
 
+        await store.create_tag("before-restore-20260715T143012Z-2")
+
         safety_tag = await store.restore_tag("release-1")
-        assert safety_tag == "before-restore-20260715T143012Z-2"
+        assert safety_tag == "before-restore-20260715T143012Z-3"
 
 
 @pytest.mark.asyncio
@@ -406,3 +408,26 @@ async def test_wait_protected_returns_result_on_same_tick_cancellation():
     result, cancelled = await outer
     assert result == "done"
     assert cancelled is True
+
+
+@pytest.mark.asyncio
+async def test_wait_protected_reraises_when_recovery_itself_is_cancelled():
+    """If the recovery coroutine ends cancelled there is nothing to wait for,
+    so the cancellation propagates instead of looping forever."""
+    import asyncio
+
+    from haiku.rag.store.engine import _wait_protected
+
+    async def self_cancelling_recovery() -> str:
+        current = asyncio.current_task()
+        assert current is not None
+        current.cancel()
+        await asyncio.sleep(0)
+        return "unreachable"
+
+    outer = asyncio.create_task(_wait_protected(self_cancelling_recovery()))
+
+    # Bounded: without the re-raise the retry loop spins forever on an
+    # already-cancelled task, and the timeout turns that into a clean failure.
+    with pytest.raises(asyncio.CancelledError):
+        await asyncio.wait_for(outer, timeout=5)
diff --git a/tests/store/test_v0_50_0_migration.py b/tests/store/test_v0_50_0_migration.py
index f53904d6..7f2553fd 100644
--- a/tests/store/test_v0_50_0_migration.py
+++ b/tests/store/test_v0_50_0_migration.py
@@ -126,6 +126,19 @@ class TestV0_50_0Migration:
                             }
                         ),
                     ),
+                    # Matches the LIKE on the quoted-key form, but only nested —
+                    # there is no top-level key to rename.
+                    LegacyDocumentRecord(
+                        id="nested-only",
+                        content="x",
+                        uri="u3",
+                        metadata=json.dumps(
+                            {
+                                "raw_headers": {"etag": "abc"},
+                                "source_revision": "v3",
+                            }
+                        ),
+                    ),
                 ],
             )
 
@@ -141,6 +154,10 @@ class TestV0_50_0Migration:
                 "my_etag_key": "v",
                 "source_revision": "v2",
             }
+            assert by_id["nested-only"] == {
+                "raw_headers": {"etag": "abc"},
+                "source_revision": "v3",
+            }
 
     async def test_unparseable_metadata_skipped_without_crashing(self, temp_db_path):
         """A row with malformed JSON in `metadata` must not abort the whole
diff --git a/tests/test_chunk.py b/tests/test_chunk.py
index c33637ae..5fe774f3 100644
--- a/tests/test_chunk.py
+++ b/tests/test_chunk.py
@@ -3,6 +3,7 @@ import pytest
 from haiku.rag.client import HaikuRAG
 from haiku.rag.config import Config
 from haiku.rag.store.models.chunk import Chunk, ChunkMetadata, SearchResult
+from tests.conftest import capture_logs
 
 
 @pytest.mark.vcr()
@@ -123,136 +124,86 @@ async def test_chunking_pipeline(qa_corpus: list[dict[str, str]], temp_db_path):
             assert chunk.order == i
 
 
-def test_chunk_metadata_parsing():
+@pytest.mark.parametrize(
+    "metadata,refs,headings,labels,page_numbers",
+    [
+        (
+            {
+                "doc_item_refs": ["#/texts/0", "#/texts/1", "#/tables/0"],
+                "headings": ["Chapter 1", "Section 1.1"],
+                "labels": ["paragraph", "paragraph", "table"],
+                "page_numbers": [1, 1, 2],
+            },
+            ["#/texts/0", "#/texts/1", "#/tables/0"],
+            ["Chapter 1", "Section 1.1"],
+            ["paragraph", "paragraph", "table"],
+            [1, 1, 2],
+        ),
+        ({}, [], None, [], []),
+    ],
+    ids=["populated", "defaults"],
+)
+def test_chunk_metadata_parsing(metadata, refs, headings, labels, page_numbers):
     """Test ChunkMetadata parsing from chunk metadata dict."""
-    metadata_dict = {
-        "doc_item_refs": ["#/texts/0", "#/texts/1", "#/tables/0"],
-        "headings": ["Chapter 1", "Section 1.1"],
-        "labels": ["paragraph", "paragraph", "table"],
-        "page_numbers": [1, 1, 2],
-    }
-
-    chunk = Chunk(
-        content="Test content",
-        metadata=metadata_dict,
-    )
+    chunk = Chunk(content="Test content", metadata=metadata)
 
     chunk_meta = chunk.get_chunk_metadata()
 
     assert isinstance(chunk_meta, ChunkMetadata)
-    assert chunk_meta.doc_item_refs == ["#/texts/0", "#/texts/1", "#/tables/0"]
-    assert chunk_meta.headings == ["Chapter 1", "Section 1.1"]
-    assert chunk_meta.labels == ["paragraph", "paragraph", "table"]
-    assert chunk_meta.page_numbers == [1, 1, 2]
+    assert chunk_meta.doc_item_refs == refs
+    assert chunk_meta.headings == headings
+    assert chunk_meta.labels == labels
+    assert chunk_meta.page_numbers == page_numbers
 
 
-def test_chunk_metadata_defaults():
-    """Test ChunkMetadata with empty/default values."""
-    chunk = Chunk(content="Test content", metadata={})
-    chunk_meta = chunk.get_chunk_metadata()
+@pytest.fixture
+def two_text_docling_doc():
+    """Minimal DoclingDocument with two resolvable text items."""
+    from docling_core.types.doc.document import DoclingDocument
 
-    assert chunk_meta.doc_item_refs == []
-    assert chunk_meta.headings is None
-    assert chunk_meta.labels == []
-    assert chunk_meta.page_numbers == []
+    return DoclingDocument.model_validate(
+        {
+            "name": "test_doc",
+            "texts": [
+                {
+                    "self_ref": "#/texts/0",
+                    "text": "First text",
+                    "orig": "First text",
+                    "label": "paragraph",
+                },
+                {
+                    "self_ref": "#/texts/1",
+                    "text": "Second text",
+                    "orig": "Second text",
+                    "label": "title",
+                },
+            ],
+            "tables": [],
+            "pictures": [],
+            "groups": [],
+            "body": {"self_ref": "#/body", "children": []},
+            "furniture": {"self_ref": "#/furniture", "children": []},
+        }
+    )
 
 
-def test_chunk_metadata_resolve_doc_items():
+@pytest.mark.parametrize(
+    "refs,expected_texts",
+    [
+        (["#/texts/0", "#/texts/1"], ["First text", "Second text"]),
+        # Out-of-range and malformed refs are skipped rather than raising.
+        (["#/texts/0", "#/texts/999", "#/invalid/path"], ["First text"]),
+        ([], []),
+    ],
+    ids=["all_valid", "graceful_degradation", "empty_refs"],
+)
+def test_chunk_metadata_resolve_doc_items(two_text_docling_doc, refs, expected_texts):
     """Test resolving doc_item_refs to actual DocItem objects."""
-    from docling_core.types.doc.document import DoclingDocument
+    chunk_meta = ChunkMetadata(doc_item_refs=refs)
 
-    # Create a minimal DoclingDocument with some text items
-    doc_json = {
-        "name": "test_doc",
-        "texts": [
-            {
-                "self_ref": "#/texts/0",
-                "text": "First text",
-                "orig": "First text",
-                "label": "paragraph",
-            },
-            {
-                "self_ref": "#/texts/1",
-                "text": "Second text",
-                "orig": "Second text",
-                "label": "title",
-            },
-        ],
-        "tables": [],
-        "pictures": [],
-        "groups": [],
-        "body": {"self_ref": "#/body", "children": []},
-        "furniture": {"self_ref": "#/furniture", "children": []},
-    }
-    docling_doc = DoclingDocument.model_validate(doc_json)
+    doc_items = chunk_meta.resolve_doc_items(two_text_docling_doc)
 
-    # Create chunk metadata with refs
-    chunk_meta = ChunkMetadata(
-        doc_item_refs=["#/texts/0", "#/texts/1"],
-        labels=["paragraph", "title"],
-    )
-
-    # Resolve refs
-    doc_items = chunk_meta.resolve_doc_items(docling_doc)
-
-    assert len(doc_items) == 2
-    assert getattr(doc_items[0], "text") == "First text"
-    assert getattr(doc_items[1], "text") == "Second text"
-
-
-def test_chunk_metadata_resolve_doc_items_graceful_degradation():
-    """Test that invalid refs are skipped gracefully."""
-    from docling_core.types.doc.document import DoclingDocument
-
-    doc_json = {
-        "name": "test_doc",
-        "texts": [
-            {
-                "self_ref": "#/texts/0",
-                "text": "Only text",
-                "orig": "Only text",
-                "label": "paragraph",
-            },
-        ],
-        "tables": [],
-        "pictures": [],
-        "groups": [],
-        "body": {"self_ref": "#/body", "children": []},
-        "furniture": {"self_ref": "#/furniture", "children": []},
-    }
-    docling_doc = DoclingDocument.model_validate(doc_json)
-
-    # Create chunk metadata with one valid and one invalid ref
-    chunk_meta = ChunkMetadata(
-        doc_item_refs=["#/texts/0", "#/texts/999", "#/invalid/path"],
-    )
-
-    # Resolve refs - invalid ones should be skipped
-    doc_items = chunk_meta.resolve_doc_items(docling_doc)
-
-    assert len(doc_items) == 1
-    assert getattr(doc_items[0], "text") == "Only text"
-
-
-def test_chunk_metadata_resolve_empty_refs():
-    """Test resolving with no refs returns empty list."""
-    from docling_core.types.doc.document import DoclingDocument
-
-    doc_json = {
-        "name": "test_doc",
-        "texts": [],
-        "tables": [],
-        "pictures": [],
-        "groups": [],
-        "body": {"self_ref": "#/body", "children": []},
-        "furniture": {"self_ref": "#/furniture", "children": []},
-    }
-    docling_doc = DoclingDocument.model_validate(doc_json)
-
-    chunk_meta = ChunkMetadata()
-    doc_items = chunk_meta.resolve_doc_items(docling_doc)
-
-    assert doc_items == []
+    assert [getattr(item, "text") for item in doc_items] == expected_texts
 
 
 def test_search_result_from_chunk_preserves_document_meta():
@@ -286,11 +237,12 @@ def test_search_result_format_for_agent_omits_document_meta():
     assert "https://example.org/report/view" not in formatted
 
 
-def test_search_result_format_for_agent_with_rank():
-    """Test format_for_agent with rank and total parameters."""
-    result = SearchResult(
+@pytest.fixture
+def rich_search_result():
+    """SearchResult with every optional field populated."""
+    return SearchResult(
         content="This is the chunk content about elections.",
-        score=0.02,  # Low RRF score that would confuse agents
+        score=0.85,
         chunk_id="chunk-123",
         document_id="doc-456",
         document_uri="file:///docs/report.pdf",
@@ -300,16 +252,30 @@ def test_search_result_format_for_agent_with_rank():
         page_numbers=[1, 2],
     )
 
-    formatted = result.format_for_agent(rank=1, total=5)
 
+@pytest.mark.parametrize(
+    "kwargs,present,absent",
+    [
+        # A rank is supplied, so the raw RRF score is withheld from the agent.
+        ({"rank": 1, "total": 5}, "[rank 1 of 5]", "score:"),
+        ({}, "(score: 0.85)", "[rank"),
+    ],
+    ids=["with_rank", "score_fallback"],
+)
+def test_search_result_format_for_agent_rank_vs_score(
+    rich_search_result, kwargs, present, absent
+):
+    """format_for_agent shows a rank when given one, else falls back to score."""
+    formatted = rich_search_result.format_for_agent(**kwargs)
+
+    assert present in formatted
+    assert absent not in formatted
     assert "[chunk-123]" in formatted
-    assert "[rank 1 of 5]" in formatted
-    assert "score:" not in formatted  # Score should NOT appear when rank is provided
     assert (
         'Source: "Annual Report 2024" > Chapter 1 > Section 1.1 > Elections'
         in formatted
     )
-    assert "Type: table" in formatted
+    assert "Type: table" in formatted  # table has higher priority than paragraph
     assert "Content:\nThis is the chunk content about elections." in formatted
 
 
@@ -357,134 +323,104 @@ def test_search_result_format_for_agent_no_captions_no_line():
     assert "Figure caption" not in formatted
 
 
-def test_search_result_format_for_agent_rank_only():
-    """Test format_for_agent with rank but no total."""
-    result = SearchResult(
-        content="Some content.",
-        score=0.03,
-        chunk_id="chunk-abc",
-    )
-
-    formatted = result.format_for_agent(rank=2)
-
-    assert "[chunk-abc]" in formatted
-    assert "[rank 2]" in formatted
-    assert "score:" not in formatted
-
-
-def test_search_result_format_for_agent_fallback():
-    """Test format_for_agent falls back to score when no rank provided."""
-    result = SearchResult(
-        content="This is the chunk content about elections.",
-        score=0.85,
-        chunk_id="chunk-123",
-        document_id="doc-456",
-        document_uri="file:///docs/report.pdf",
-        document_title="Annual Report 2024",
-        headings=["Chapter 1", "Section 1.1", "Elections"],
-        labels=["paragraph", "table"],
-        page_numbers=[1, 2],
-    )
-
-    formatted = result.format_for_agent()
-
-    assert "[chunk-123]" in formatted
-    assert "(score: 0.85)" in formatted
-    assert (
-        'Source: "Annual Report 2024" > Chapter 1 > Section 1.1 > Elections'
-        in formatted
-    )
-    assert "Type: table" in formatted  # table has higher priority than paragraph
-    assert "Content:\nThis is the chunk content about elections." in formatted
-
-
-def test_search_result_format_for_agent_minimal():
-    """Test format_for_agent with minimal metadata."""
+@pytest.mark.parametrize(
+    "kwargs,present,absent",
+    [
+        ({"rank": 2}, "[rank 2]", ["score:"]),
+        # No structural metadata at all, so no Source:/Type: lines are emitted.
+        ({}, "(score: 0.72)", ["[rank", "Source:", "Type:"]),
+    ],
+    ids=["rank_only", "minimal"],
+)
+def test_search_result_format_for_agent_minimal(kwargs, present, absent):
+    """A result carrying only content/score/chunk_id formats without metadata lines."""
     result = SearchResult(
         content="Some content here.",
         score=0.72,
         chunk_id="chunk-abc",
     )
 
-    formatted = result.format_for_agent()
+    formatted = result.format_for_agent(**kwargs)
 
     assert "[chunk-abc]" in formatted
-    assert "(score: 0.72)" in formatted
-    assert "Source:" not in formatted  # No title or headings
-    assert "Type:" not in formatted  # No labels
+    assert present in formatted
+    for token in absent:
+        assert token not in formatted
     assert "Content:\nSome content here." in formatted
 
 
-def test_search_result_format_for_agent_title_only():
-    """Test format_for_agent with only document title."""
+@pytest.mark.parametrize(
+    "fields,expected_source",
+    [
+        ({"document_title": "My Document"}, 'Source: "My Document"'),
+        (
+            {"headings": ["Introduction", "Background"]},
+            "Source: Introduction > Background",
+        ),
+    ],
+    ids=["title_only", "headings_only"],
+)
+def test_search_result_format_for_agent_source_line(fields, expected_source):
+    """The Source: line is built from the title, the headings, or both."""
     result = SearchResult(
         content="Content text.",
         score=0.60,
         chunk_id="chunk-xyz",
-        document_title="My Document",
+        **fields,
     )
 
-    formatted = result.format_for_agent()
-
-    assert 'Source: "My Document"' in formatted
+    assert expected_source in result.format_for_agent()
 
 
-def test_search_result_format_for_agent_headings_only():
-    """Test format_for_agent with only headings (no title)."""
-    result = SearchResult(
-        content="Content text.",
-        score=0.60,
-        chunk_id="chunk-xyz",
-        headings=["Introduction", "Background"],
-    )
-
-    formatted = result.format_for_agent()
-
-    assert "Source: Introduction > Background" in formatted
-
-
-def test_search_result_get_primary_label():
+@pytest.mark.parametrize(
+    "labels,expected",
+    [
+        (["paragraph", "table", "text"], "table"),
+        (["paragraph", "code"], "code"),
+        (["list_item", "code"], "code"),
+        (["text", "list_item"], "list_item"),
+        # No structural label: falls through to the first label.
+        (["paragraph", "text"], "paragraph"),
+        ([], None),
+    ],
+)
+def test_search_result_get_primary_label(labels, expected):
     """Test _get_primary_label prioritization."""
-    # Table takes priority over text labels
-    result = SearchResult(content="x", score=0.5, labels=["paragraph", "table", "text"])
-    assert result._get_primary_label() == "table"
-
-    # Code takes priority over list_item
-    result = SearchResult(content="x", score=0.5, labels=["list_item", "code"])
-    assert result._get_primary_label() == "code"
-
-    # Text labels fall through to first
-    result = SearchResult(content="x", score=0.5, labels=["paragraph", "text"])
-    assert result._get_primary_label() == "paragraph"
-
-    # Empty labels
-    result = SearchResult(content="x", score=0.5, labels=[])
-    assert result._get_primary_label() is None
+    result = SearchResult(content="x", score=0.5, labels=labels)
+    assert result._get_primary_label() == expected
 
 
 @pytest.mark.vcr()
-async def test_chunk_content_fts_populated(temp_db_path):
-    """Test that content_fts column is populated with contextualized content."""
+@pytest.mark.parametrize(
+    "metadata,content,expected_content_fts",
+    [
+        (
+            {"headings": ["Chapter 1", "Section 1.1"]},
+            "This is the raw chunk content.",
+            "Chapter 1\nSection 1.1\nThis is the raw chunk content.",
+        ),
+        ({}, "Plain content without headings.", "Plain content without headings."),
+    ],
+    ids=["populated", "without_headings"],
+)
+async def test_chunk_content_fts(temp_db_path, metadata, content, expected_content_fts):
+    """content_fts holds the contextualized content while content stays raw."""
     from haiku.rag.embeddings import get_embedder
 
     async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
-        # Create a chunk with headings
         chunk = Chunk(
             document_id="test-doc",
-            content="This is the raw chunk content.",
-            metadata={"headings": ["Chapter 1", "Section 1.1"]},
+            content=content,
+            metadata=metadata,
             order=0,
         )
 
-        # Generate embedding
         embedder = get_embedder(Config)
         embedding = (await embedder.embed_documents([chunk.content]))[0]
         chunk.embedding = embedding
 
-        # Store the chunk
         await client.chunk_repository.create(chunk)
 
-        # Read the raw record from the database
         records = (
             await client.store.chunks_table.query()
             .where(f"id = '{chunk.id}'")
@@ -495,52 +431,8 @@ async def test_chunk_content_fts_populated(temp_db_path):
         assert len(records) == 1
         record = records[0]
 
-        # Verify content is raw (no headings)
-        assert record["content"] == "This is the raw chunk content."
-
-        # Verify content_fts is contextualized (headings + content)
-        assert (
-            record["content_fts"]
-            == "Chapter 1\nSection 1.1\nThis is the raw chunk content."
-        )
-
-
-@pytest.mark.vcr()
-async def test_chunk_content_fts_without_headings(temp_db_path):
-    """Test that content_fts equals content when no headings present."""
-    from haiku.rag.embeddings import get_embedder
-
-    async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
-        # Create a chunk without headings
-        chunk = Chunk(
-            document_id="test-doc",
-            content="Plain content without headings.",
-            metadata={},
-            order=0,
-        )
-
-        # Generate embedding
-        embedder = get_embedder(Config)
-        embedding = (await embedder.embed_documents([chunk.content]))[0]
-        chunk.embedding = embedding
-
-        # Store the chunk
-        await client.chunk_repository.create(chunk)
-
-        # Read the raw record from the database
-        records = (
-            await client.store.chunks_table.query()
-            .where(f"id = '{chunk.id}'")
-            .limit(1)
-            .to_arrow()
-        ).to_pylist()
-
-        assert len(records) == 1
-        record = records[0]
-
-        # Both should be the same when no headings
-        assert record["content"] == "Plain content without headings."
-        assert record["content_fts"] == "Plain content without headings."
+        assert record["content"] == content
+        assert record["content_fts"] == expected_content_fts
 
 
 async def test_ensure_fts_index_warns_on_failure(temp_db_path):
@@ -557,18 +449,91 @@ async def test_ensure_fts_index_warns_on_failure(temp_db_path):
 
         repo.store.chunks_table.create_index = _boom
 
-        records: list[logging.LogRecord] = []
-
-        class _Capture(logging.Handler):
-            def emit(self, record: logging.LogRecord) -> None:
-                records.append(record)
-
-        handler = _Capture(level=logging.WARNING)
-        chunk_module.logger.addHandler(handler)
-        try:
+        with capture_logs(chunk_module.logger, logging.WARNING) as records:
             await repo._ensure_fts_index()
-        finally:
-            chunk_module.logger.removeHandler(handler)
 
         assert [r for r in records if r.levelno == logging.WARNING]
         assert any("index build failed" in r.getMessage() for r in records)
+
+
+@pytest.mark.vcr()
+async def test_chunk_repository_get_by_id_and_list_all_pagination(
+    qa_corpus: list[dict[str, str]], temp_db_path
+):
+    """get_by_id resolves a stored chunk; list_all honours limit and offset."""
+    async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
+        # A corpus document is long enough to chunk more than once, which is
+        # what makes the offset assertion below meaningful.
+        doc = await client.create_document(content=qa_corpus[0]["document_extracted"])
+        assert doc.id is not None
+
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+        assert stored
+
+        fetched = await client.get_chunk_by_id(stored[0].id)
+        assert fetched is not None
+        assert fetched.id == stored[0].id
+        assert fetched.content == stored[0].content
+
+        assert await client.get_chunk_by_id("no-such-chunk") is None
+
+        everything = await client.chunk_repository.list_all()
+        assert len(everything) == len(stored)
+
+        first = await client.chunk_repository.list_all(limit=1)
+        assert len(first) == 1
+        assert first[0].id == everything[0].id
+
+        # Fail loudly if the fixture stops producing enough chunks to page.
+        assert len(everything) >= 2
+
+        second = await client.chunk_repository.list_all(limit=1, offset=1)
+        assert len(second) == 1
+        assert second[0].id == everything[1].id
+
+
+@pytest.mark.vcr()
+async def test_chunk_search_returns_empty_for_blank_query(temp_db_path):
+    """A blank query with no precomputed vector short-circuits before searching."""
+    async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
+        await client.create_document(content="Searchable body about elections.")
+
+        # Positive control: the corpus is non-empty, so [] is a real decision
+        # rather than the answer to every query.
+        assert await client.chunk_repository.search("elections")
+        assert await client.chunk_repository.search("   ") == []
+
+
+@pytest.mark.vcr()
+async def test_chunk_search_with_precomputed_vector_skips_text_query(temp_db_path):
+    """The image-as-query path searches vector-only using a stored embedding."""
+    async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
+        doc = await client.create_document(content="Vector-only search target.")
+        assert doc.id is not None
+
+        rows = (await client.store.chunks_table.query().limit(1).to_arrow()).to_pylist()
+        stored_vector = list(rows[0]["vector"])
+
+        results = await client.chunk_repository.search("", query_vector=stored_vector)
+
+        assert results
+        assert any(c.document_id == doc.id for c, _ in results)
+
+
+async def test_get_chunk_ids_by_self_ref_grouped_without_documents(temp_db_path):
+    async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
+        assert await client.chunk_repository.get_chunk_ids_by_self_ref_grouped([]) == {}
+
+
+async def test_process_search_results_rejects_unknown_score_column(temp_db_path):
+    """A result frame with no recognised score column is a programming error."""
+    import pandas as pd
+
+    async with HaikuRAG(db_path=temp_db_path, config=Config, create=True) as client:
+
+        class _Frame:
+            async def to_pandas(self):
+                return pd.DataFrame([{"id": "c1", "content": "x", "metadata": "{}"}])
+
+        with pytest.raises(ValueError, match="Unknown search result format"):
+            await client.chunk_repository._process_search_results(_Frame())
diff --git a/tests/test_chunker.py b/tests/test_chunker.py
index b795bdea..c39f5831 100644
--- a/tests/test_chunker.py
+++ b/tests/test_chunker.py
@@ -798,3 +798,81 @@ async def test_serve_chunker_accepts_picture_laden_docling(doclaynet_first_page_
     chunks = await serve_chunker.chunk(doc)
 
     assert len(chunks) > 0, "docling-serve chunker returned 0 chunks"
+
+
+class TestDoclingServeChunkerRefResolution:
+    """_resolve_label_from_document and the dict-shaped doc_items branch."""
+
+    @pytest.fixture
+    def chunker(self):
+        config = AppConfig()
+        config.providers.docling_serve.base_url = "http://localhost:5001"
+        config.processing.chunk_size = 256
+        config.processing.chunking_tokenizer = "Qwen/Qwen3-Embedding-0.6B"
+        return DoclingServeChunker(config)
+
+    @pytest.fixture
+    def document(self):
+        from docling_core.types.doc.document import DoclingDocument
+
+        return DoclingDocument.model_validate(
+            {
+                "name": "doc",
+                "texts": [
+                    {
+                        "self_ref": "#/texts/0",
+                        "text": "body",
+                        "orig": "body",
+                        "label": "paragraph",
+                    }
+                ],
+                "tables": [],
+                "pictures": [],
+                "groups": [],
+                "body": {"self_ref": "#/body", "children": []},
+                "furniture": {"self_ref": "#/furniture", "children": []},
+            }
+        )
+
+    @pytest.mark.parametrize(
+        "ref",
+        ["not-a-ref", "#/texts/999", "#/nope/0"],
+        ids=["unparseable", "index_out_of_range", "unknown_collection"],
+    )
+    def test_unresolvable_ref_yields_no_label(self, document, ref):
+        from haiku.rag.chunkers.docling_serve import _resolve_label_from_document
+
+        assert _resolve_label_from_document(ref, document) is None
+
+    def test_resolvable_ref_yields_label(self, document):
+        from haiku.rag.chunkers.docling_serve import _resolve_label_from_document
+
+        assert _resolve_label_from_document("#/texts/0", document) == "paragraph"
+
+    @pytest.mark.asyncio
+    async def test_chunk_of_none_returns_empty(self, chunker):
+        assert await chunker.chunk(None) == []
+
+    @pytest.mark.asyncio
+    async def test_dict_shaped_doc_items_are_decoded(self, chunker, document):
+        """docling-serve returns refs as strings today; the dict shape is
+        accepted in case the API changes."""
+
+        async def fake_chunk_api(_document):
+            return [
+                {
+                    "raw_text": "body",
+                    # A label the document does NOT carry, so the assertion
+                    # proves the dict's own label was used rather than a
+                    # lookup against the document.
+                    "doc_items": [{"self_ref": "#/texts/0", "label": "caption"}],
+                }
+            ]
+
+        chunker._call_chunk_api = fake_chunk_api  # type: ignore[method-assign]
+
+        chunks = await chunker.chunk(document)
+
+        assert len(chunks) == 1
+        assert chunks[0].metadata["doc_item_refs"] == ["#/texts/0"]
+        assert chunks[0].metadata["labels"] == ["caption"]
diff --git a/tests/test_client.py b/tests/test_client.py
index c0636e16..48de4ad5 100644
--- a/tests/test_client.py
+++ b/tests/test_client.py
@@ -1,3 +1,4 @@
+import asyncio
 import json
 import tempfile
 import threading
@@ -14,6 +15,7 @@ from haiku.rag.client.documents import (
     DocumentImport,
     _prepare_document_from_docling,
     _write_fetch_body,
+    check_source_accessible,
 )
 from haiku.rag.config import Config
 from haiku.rag.store.compression import decompress_json
@@ -298,23 +300,6 @@ async def test_client_create_document_from_source(temp_db_path):
             assert "md5" in doc2.metadata
 
 
-@pytest.mark.vcr()
-async def test_client_create_document_from_source_with_title(temp_db_path):
-    """Test creating a document from a file source with a title."""
-    async with HaikuRAG(temp_db_path, create=True) as client:
-        with tempfile.TemporaryDirectory() as temp_dir:
-            test_content = "This is test content from a file."
-            temp_path = Path(temp_dir) / "test_title.txt"
-            temp_path.write_text(test_content)
-
-            doc = await client.create_document_from_source(
-                source=temp_path, title="My Doc"
-            )
-            assert isinstance(doc, Document)
-            assert doc.id is not None
-            assert doc.title == "My Doc"
-
-
 @pytest.mark.vcr()
 async def test_client_update_title_noop_behavior(temp_db_path):
     """When content is unchanged, updating title should update document without re-chunking."""
@@ -326,6 +311,7 @@ async def test_client_update_title_noop_behavior(temp_db_path):
             doc1 = await client.create_document_from_source(temp_path, title="Title A")
             assert isinstance(doc1, Document)
             assert doc1.id is not None
+            assert doc1.title == "Title A"
 
             # Re-add with same content but new title
             doc2 = await client.create_document_from_source(temp_path, title="Title B")
@@ -646,12 +632,14 @@ async def test_client_create_update_no_op_behavior(temp_db_path):
             assert doc1.id is not None
             assert doc1.content == test_content
             original_id = doc1.id
+            original_updated_at = doc1.updated_at
 
             # Second call with same content - should return existing document (no-op)
             doc2 = await client.create_document_from_source(temp_path)
             assert isinstance(doc2, Document)
             assert doc2.id == original_id  # Same document
             assert doc2.content == test_content
+            assert doc2.updated_at == original_updated_at  # No-op leaves it untouched
 
             # Modify file content
             updated_content = "Updated content for testing."
@@ -669,28 +657,6 @@ async def test_client_create_update_no_op_behavior(temp_db_path):
             assert retrieved_doc.content == updated_content
 
 
-@pytest.mark.vcr()
-async def test_client_unchanged_file_keeps_timestamp(temp_db_path):
-    """Test that unchanged files don't update the updated_at timestamp."""
-    async with HaikuRAG(temp_db_path, create=True) as client:
-        # Create a temporary file
-        test_content = "Test content for timestamp check."
-        with tempfile.TemporaryDirectory() as temp_dir:
-            temp_path = Path(temp_dir) / "test.txt"
-            temp_path.write_text(test_content)
-
-            # First call - create document
-            doc1 = await client.create_document_from_source(temp_path)
-            assert isinstance(doc1, Document)
-            original_updated_at = doc1.updated_at
-
-            # Second call with same content - should not update timestamp
-            doc2 = await client.create_document_from_source(temp_path)
-            assert isinstance(doc2, Document)
-            assert doc2.id == doc1.id
-            assert doc2.updated_at == original_updated_at  # Timestamp should not change
-
-
 @pytest.mark.vcr()
 async def test_client_url_create_update_no_op_behavior(temp_db_path):
     """Test create/update/no-op behavior for URLs based on MD5 changes."""
@@ -2290,3 +2256,326 @@ async def test_metadata_only_update_waits_for_write_lock(temp_db_path):
             assert not task.done()
         updated = await task
         assert updated.metadata == {"k": "v"}
+
+
+@pytest.mark.parametrize(
+    "uri,expected",
+    [
+        ("https://example.com/doc.pdf", True),
+        ("s3://bucket/key", True),
+        ("mem://not-a-source", False),
+        # urlparse rejects a malformed IPv6 host; a stored URI that no longer
+        # parses must not abort the caller's rebuild sweep.
+        ("http://[::1", False),
+    ],
+    ids=["https", "s3", "unknown_scheme", "unparseable"],
+)
+def test_check_source_accessible(uri, expected):
+    assert check_source_accessible(uri) is expected
+
+
+def test_check_source_accessible_file_uri(tmp_path):
+    existing = tmp_path / "there.txt"
+    existing.write_text("x")
+
+    assert check_source_accessible(existing.as_uri()) is True
+    assert check_source_accessible((tmp_path / "gone.txt").as_uri()) is False
+
+
+def _bbox_doc(*, with_page_image: bool, pages: tuple[int, ...] = (1,)):
+    """DoclingDocument with one paragraph per page, each carrying a bbox.
+
+    ``with_page_image=False`` produces pages with no raster, so bounding boxes
+    resolve but there is nothing to draw them on.
+    """
+    from docling_core.types.doc.base import BoundingBox, Size
+    from docling_core.types.doc.document import ImageRef, ProvenanceItem
+    from PIL import Image as PilImageModule
+
+    doc = DoclingDocument(name="bbox-doc")
+    size = Size(width=612.0, height=792.0)
+    for page_no in pages:
+        image = (
+            ImageRef.from_pil(
+                PilImageModule.new("RGB", (612, 792), color="white"), dpi=72
+            )
+            if with_page_image
+            else None
+        )
+        doc.add_page(page_no=page_no, size=size, image=image)
+        doc.add_text(
+            label=DocItemLabel.PARAGRAPH,
+            text=f"Content on page {page_no}.",
+            prov=ProvenanceItem(
+                page_no=page_no,
+                bbox=BoundingBox(l=50, t=700, r=550, b=650),
+                charspan=(0, 20),
+            ),
+        )
+    return doc
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_returns_empty_without_page_rasters(temp_db_path):
+    """Boxes resolve, but a document ingested without page images has nothing
+    to render them onto."""
+    docling_doc = _bbox_doc(with_page_image=False)
+    chunks = [
+        Chunk(
+            content="Content on page 1.",
+            metadata={
+                "doc_item_refs": ["#/texts/0"],
+                "page_numbers": [1],
+                "labels": ["paragraph"],
+            },
+            order=0,
+            embedding=[0.1] * 2560,
+        )
+    ]
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.import_document(docling_doc, chunks, uri="test://no-raster")
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+
+        assert await client.visualize_chunk(stored[0]) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_skips_pages_without_a_raster(temp_db_path):
+    """A document where only some pages carry a raster renders just those."""
+    from docling_core.types.doc.base import BoundingBox, Size
+    from docling_core.types.doc.document import ImageRef, ProvenanceItem
+    from PIL import Image as PilImageModule
+
+    docling_doc = DoclingDocument(name="mixed-rasters")
+    size = Size(width=612.0, height=792.0)
+    docling_doc.add_page(
+        page_no=1,
+        size=size,
+        image=ImageRef.from_pil(
+            PilImageModule.new("RGB", (612, 792), color="white"), dpi=72
+        ),
+    )
+    docling_doc.add_page(page_no=2, size=size, image=None)
+    for page_no in (1, 2):
+        docling_doc.add_text(
+            label=DocItemLabel.PARAGRAPH,
+            text=f"Content on page {page_no}.",
+            prov=ProvenanceItem(
+                page_no=page_no,
+                bbox=BoundingBox(l=50, t=700, r=550, b=650),
+                charspan=(0, 20),
+            ),
+        )
+
+    chunks = [
+        Chunk(
+            content="Content on page 1.\nContent on page 2.",
+            metadata={
+                "doc_item_refs": ["#/texts/0", "#/texts/1"],
+                "page_numbers": [1, 2],
+                "labels": ["paragraph", "paragraph"],
+            },
+            order=0,
+            embedding=[0.1] * 2560,
+        )
+    ]
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.import_document(
+            docling_doc, chunks, uri="test://mixed-rasters"
+        )
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+
+        images = await client.visualize_chunk(stored[0])
+
+    assert len(images) == 1
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_returns_empty_when_pages_row_missing(temp_db_path):
+    docling_doc = _bbox_doc(with_page_image=True)
+    chunks = [
+        Chunk(
+            content="Content on page 1.",
+            metadata={
+                "doc_item_refs": ["#/texts/0"],
+                "page_numbers": [1],
+                "labels": ["paragraph"],
+            },
+            order=0,
+            embedding=[0.1] * 2560,
+        )
+    ]
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.import_document(docling_doc, chunks, uri="test://no-row")
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+
+        async def no_pages_row(document_id):
+            return None
+
+        client.document_repository.get_pages_data = no_pages_row  # type: ignore[method-assign]
+
+        assert await client.visualize_chunk(stored[0]) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_skips_box_on_unstored_page(temp_db_path):
+    """A bounding box referencing a page the document never registered is
+    skipped rather than raising."""
+    from docling_core.types.doc.base import BoundingBox, Size
+    from docling_core.types.doc.document import ImageRef, ProvenanceItem
+    from PIL import Image as PilImageModule
+
+    docling_doc = DoclingDocument(name="orphan-page-box")
+    docling_doc.add_page(
+        page_no=1,
+        size=Size(width=612.0, height=792.0),
+        image=ImageRef.from_pil(
+            PilImageModule.new("RGB", (612, 792), color="white"), dpi=72
+        ),
+    )
+    docling_doc.add_text(
+        label=DocItemLabel.PARAGRAPH,
+        text="Content attributed to a page with no raster.",
+        prov=ProvenanceItem(
+            page_no=3,
+            bbox=BoundingBox(l=50, t=700, r=550, b=650),
+            charspan=(0, 20),
+        ),
+    )
+
+    chunks = [
+        Chunk(
+            content="Content attributed to a page with no raster.",
+            metadata={
+                "doc_item_refs": ["#/texts/0"],
+                "page_numbers": [3],
+                "labels": ["paragraph"],
+            },
+            order=0,
+            embedding=[0.1] * 2560,
+        )
+    ]
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.import_document(
+            docling_doc, chunks, uri="test://orphan-page"
+        )
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+
+        assert await client.visualize_chunk(stored[0]) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_without_refs_falls_back_to_chunk_metadata(temp_db_path):
+    """A chunk carrying no doc_item_refs has nothing to expand from."""
+    docling_doc = _bbox_doc(with_page_image=True)
+    chunks = [
+        Chunk(
+            content="Content on page 1.",
+            metadata={"page_numbers": [1], "labels": ["paragraph"]},
+            order=0,
+            embedding=[0.1] * 2560,
+        )
+    ]
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.import_document(docling_doc, chunks, uri="test://no-refs")
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+
+        assert await client.visualize_chunk(stored[0]) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_falls_back_when_expansion_drops_refs(temp_db_path):
+    """If expansion returns results carrying no refs, the original search
+    results' refs are used instead."""
+    from haiku.rag.client import search as search_module
+
+    docling_doc = _bbox_doc(with_page_image=True)
+    chunks = [
+        Chunk(
+            content="Content on page 1.",
+            metadata={
+                "doc_item_refs": ["#/texts/0"],
+                "page_numbers": [1],
+                "labels": ["paragraph"],
+            },
+            order=0,
+            embedding=[0.1] * 2560,
+        )
+    ]
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.import_document(docling_doc, chunks, uri="test://drops-refs")
+        stored = await client.chunk_repository.get_by_document_id(doc.id)
+
+        async def expansion_without_refs(_client, results):
+            return [r.model_copy(update={"doc_item_refs": []}) for r in results]
+
+        with patch.object(search_module, "expand_context", expansion_without_refs):
+            images = await client.visualize_chunk(stored[0])
+
+    assert len(images) == 1
+
+
+@pytest.mark.vcr()
+@pytest.mark.parametrize("auto_vacuum", [True, False])
+async def test_import_documents_schedules_vacuum_per_config(temp_db_path, auto_vacuum):
+    """A batch import runs a background vacuum only when auto_vacuum is on."""
+    from haiku.rag.config import AppConfig
+
+    config = AppConfig()
+    config.storage.auto_vacuum = auto_vacuum
+
+    async with HaikuRAG(temp_db_path, config=config, create=True) as client:
+        docling_doc = await client.convert("Batch imported body.")
+        chunks = await client.chunk(docling_doc)
+
+        # Spy rather than inspecting _vacuum_tasks: the scheduling code
+        # discards each task on completion, so the set races to empty. The
+        # spy's count does not race, and draining the scheduled task keeps
+        # the assertion deterministic without pulling in the close-time pass.
+        with patch.object(client.store, "vacuum", new=AsyncMock()) as vacuum:
+            await client.import_documents(
+                [
+                    DocumentImport(
+                        docling_document=docling_doc,
+                        chunks=chunks,
+                        uri="test://batch-vacuum",
+                    )
+                ]
+            )
+            await asyncio.gather(*client._vacuum_tasks)
+
+            assert vacuum.await_count == (1 if auto_vacuum else 0)
+
+
+@pytest.mark.vcr()
+async def test_reingesting_a_source_applies_an_explicit_title(temp_db_path):
+    """Re-adding a changed source with a title updates both, in place."""
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        with tempfile.TemporaryDirectory() as temp_dir:
+            source = Path(temp_dir) / "retitled.txt"
+            source.write_text("stable content")
+
+            first = await client.create_document_from_source(source)
+            assert not isinstance(first, list)
+            source.write_text("changed content")
+
+            second = await client.create_document_from_source(
+                source, title="Explicit Title"
+            )
+
+        assert not isinstance(second, list)
+        assert second.id == first.id
+        assert second.title == "Explicit Title"
+        assert second.content == "changed content"
+
+
+async def test_update_document_rejects_unknown_id(temp_db_path):
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        with pytest.raises(ValueError, match="not found"):
+            await client.update_document("no-such-document", content="x")
diff --git a/tests/test_config.py b/tests/test_config.py
index ba659d29..3bcdef6d 100644
--- a/tests/test_config.py
+++ b/tests/test_config.py
@@ -42,17 +42,17 @@ def test_find_config_file_cwd(tmp_path, monkeypatch):
 def test_find_config_file_user_config(tmp_path, monkeypatch):
     """Test finding config in user config directory."""
     monkeypatch.delenv("HAIKU_RAG_CONFIG_PATH", raising=False)
-    monkeypatch.chdir(tmp_path)
 
-    # Mock get_default_data_dir to return tmp_path
-    def mock_get_default_data_dir():
-        return tmp_path
+    # The data dir must differ from the cwd, or the cwd branch answers first
+    # and this never reaches the user-directory lookup.
+    cwd = tmp_path / "cwd"
+    cwd.mkdir()
+    data_dir = tmp_path / "data"
+    data_dir.mkdir()
+    monkeypatch.chdir(cwd)
+    monkeypatch.setattr("haiku.rag.utils.get_default_data_dir", lambda: data_dir)
 
-    monkeypatch.setattr(
-        "haiku.rag.utils.get_default_data_dir", mock_get_default_data_dir
-    )
-
-    config_file = tmp_path / "haiku.rag.yaml"
+    config_file = data_dir / "haiku.rag.yaml"
     config_file.write_text("environment: production")
 
     found = find_config_file()
@@ -518,3 +518,42 @@ def test_expand_env_var_plain_string_unchanged(tmp_path):
 
     config = load_yaml_config(config_file)
     assert config["environment"] == "production"
+
+
+def test_find_config_file_returns_none_when_nothing_exists(tmp_path, monkeypatch):
+    """No env var, no file in cwd, none in the data dir."""
+    monkeypatch.delenv("HAIKU_RAG_CONFIG_PATH", raising=False)
+    monkeypatch.chdir(tmp_path)
+
+    empty_data_dir = tmp_path / "data"
+    empty_data_dir.mkdir()
+    monkeypatch.setattr("haiku.rag.utils.get_default_data_dir", lambda: empty_data_dir)
+
+    assert find_config_file() is None
+
+
+def test_load_default_config_falls_back_to_builtin_defaults(monkeypatch):
+    """With no config file discoverable, the packaged defaults are used."""
+    from haiku.rag.config import _load_default_config
+
+    monkeypatch.setattr("haiku.rag.config.find_config_file", lambda _=None: None)
+
+    config = _load_default_config()
+
+    assert config.model_dump() == AppConfig().model_dump()
+
+
+def test_get_config_initialises_lazily_then_reuses(monkeypatch):
+    """get_config() builds the instance on first use and caches it.
+
+    Asserted explicitly rather than relying on some test happening to be the
+    first caller in its worker process: under xdist that depends on how cases
+    shard across workers, which varies with the core count.
+    """
+    from haiku.rag import config as config_module
+
+    monkeypatch.setattr(config_module, "_config", None)
+
+    first = config_module.get_config()
+    assert isinstance(first, AppConfig)
+    assert config_module.get_config() is first
diff --git a/tests/test_context.py b/tests/test_context.py
index ec945327..d99a70a9 100644
--- a/tests/test_context.py
+++ b/tests/test_context.py
@@ -1360,3 +1360,147 @@ class TestExpandWithItemsPictureBytes:
             e_low = by_chunk["c-low"]
             assert e_low.image_data == {"#/pictures/0": "LOWBYTES"}
             assert "HIGHBYTES" not in (e_low.image_data or {}).values()
+
+
+class TestSpanInWindow:
+    def test_zero_width_span_is_inside_when_position_is_in_window(self):
+        from haiku.rag.context import _span_in_window
+        from haiku.rag.store.models.document_item import DocumentItem
+
+        item = DocumentItem(
+            document_id="d1", position=0, self_ref="#/pictures/0", label="picture"
+        )
+        # A picture occupies no characters, so containment is by position.
+        assert _span_in_window((10, 10, item), 0, 20) is True
+        assert _span_in_window((30, 30, item), 0, 20) is False
+
+
+@pytest.mark.asyncio
+class TestExpandWithItemsWindowEdges:
+    async def test_empty_window_returns_original_results(
+        self, temp_db_path, monkeypatch
+    ):
+        """Refs resolve but the surrounding window comes back empty, so there is
+        nothing to expand from."""
+        from haiku.rag.client import HaikuRAG
+        from haiku.rag.store.models.document import Document
+
+        async with HaikuRAG(temp_db_path, create=True) as rag:
+            doc = await rag.document_repository.create(
+                Document(content="body", uri="test://window")
+            )
+            assert doc.id is not None
+            await rag.document_item_repository.create_items(
+                doc.id,
+                [
+                    DocumentItem(
+                        document_id=doc.id,
+                        position=0,
+                        self_ref="#/texts/0",
+                        label="paragraph",
+                        text="body",
+                        page_numbers=[1],
+                    )
+                ],
+            )
+
+            async def no_window(*_args, **_kwargs):
+                return []
+
+            monkeypatch.setattr(
+                rag.document_item_repository, "get_items_in_range", no_window
+            )
+
+            result = SearchResult(
+                content="original",
+                score=0.9,
+                document_id=doc.id,
+                doc_item_refs=["#/texts/0"],
+            )
+            expanded = await expand_with_items(
+                rag.document_item_repository, doc.id, [result], 5000
+            )
+
+            assert [r.content for r in expanded] == ["original"]
+
+    async def test_result_with_unmatched_refs_passes_through(self, temp_db_path):
+        """Two results share a document; the one whose refs resolve is expanded
+        and the other is returned unchanged."""
+        from haiku.rag.client import HaikuRAG
+        from haiku.rag.store.models.document import Document
+
+        async with HaikuRAG(temp_db_path, create=True) as rag:
+            doc = await rag.document_repository.create(
+                Document(content="body", uri="test://mixed")
+            )
+            assert doc.id is not None
+            await rag.document_item_repository.create_items(
+                doc.id,
+                [
+                    DocumentItem(
+                        document_id=doc.id,
+                        position=i,
+                        self_ref=f"#/texts/{i}",
+                        label="paragraph",
+                        text=f"paragraph {i}",
+                        page_numbers=[1],
+                    )
+                    for i in range(2)
+                ],
+            )
+
+            resolvable = SearchResult(
+                content="paragraph 0",
+                score=0.9,
+                document_id=doc.id,
+                doc_item_refs=["#/texts/0"],
+            )
+            unmatched = SearchResult(
+                content="untouched",
+                score=0.5,
+                document_id=doc.id,
+                doc_item_refs=["#/texts/404"],
+            )
+
+            expanded = await expand_with_items(
+                rag.document_item_repository, doc.id, [resolvable, unmatched], 5000
+            )
+
+            assert len(expanded) == 2
+            by_content = {r.content for r in expanded}
+            # The unmatched result is passed through byte-for-byte...
+            assert "untouched" in by_content
+            # ...while the resolvable one actually grew to its neighbours.
+            grew = next(c for c in by_content if c != "untouched")
+            assert "paragraph 0" in grew and "paragraph 1" in grew
+
+
+def test_build_result_skips_positions_with_no_item():
+    """A sparse position map (items removed or never stored) leaves gaps in the
+    range; those positions contribute nothing."""
+    from haiku.rag.context import _build_result
+
+    original = SearchResult(content="p0", score=0.9, document_id="d1")
+    # Positions 1 and 2 in the 0..3 range carry no item.
+    pos_to_item = {
+        0: DocumentItem(
+            document_id="d1",
+            position=0,
+            self_ref="#/texts/0",
+            label="paragraph",
+            text="first",
+            page_numbers=[1],
+        ),
+        3: DocumentItem(
+            document_id="d1",
+            position=3,
+            self_ref="#/texts/3",
+            label="paragraph",
+            text="last",
+            page_numbers=[1],
+        ),
+    }
+
+    built = _build_result(0, 3, [original], pos_to_item, False, 5000)
+
+    assert built.content == "first\n\nlast"
diff --git a/tests/test_converters.py b/tests/test_converters.py
index 74518b12..e6579281 100644
--- a/tests/test_converters.py
+++ b/tests/test_converters.py
@@ -405,6 +405,46 @@ class TestDoclingLocalConverter:
         assert isinstance(doc, DoclingDocument)
         assert doc.name == "test"
 
+    @pytest.mark.asyncio
+    async def test_convert_file_reads_unknown_extension_as_text(
+        self, converter, tmp_path
+    ):
+        """An extension in neither the docling nor the text set is read as text."""
+        source = tmp_path / "notes.xyz"
+        source.write_text("Plain body for an unknown extension.")
+
+        doc = await converter.convert_file(source)
+
+        assert isinstance(doc, DoclingDocument)
+        assert "Plain body for an unknown extension." in doc.export_to_markdown()
+
+    @pytest.mark.asyncio
+    async def test_convert_file_raises_for_undecodable_file(self, converter, tmp_path):
+        source = tmp_path / "binary.xyz"
+        source.write_bytes(b"\xff\xfe\x00\x01 not utf-8")
+
+        with pytest.raises(ValueError, match="Failed to parse file"):
+            await converter.convert_file(source)
+
+    @pytest.mark.asyncio
+    async def test_convert_text_wraps_conversion_failure(self, converter, monkeypatch):
+        def boom(*_args, **_kwargs):
+            raise RuntimeError("docling exploded")
+
+        monkeypatch.setattr(converter, "_sync_convert_docling_text", boom)
+
+        with pytest.raises(ValueError, match="Failed to convert text"):
+            await converter.convert_text("# Test", name="test.md")
+
+    @pytest.mark.asyncio
+    async def test_convert_text_falls_back_when_format_not_inferable(self, converter):
+        """docling raises ConversionError for an extension it has no backend
+        for; the simple-document fallback keeps the text."""
+        doc = await converter.convert_text("just some prose", name="mystery.zzz")
+
+        assert isinstance(doc, DoclingDocument)
+        assert "just some prose" in doc.export_to_markdown()
+
     @pytest.mark.asyncio
     async def test_convert_code_file(self, converter):
         """Test that code files are wrapped in code blocks."""
@@ -1522,3 +1562,136 @@ class TestDoclingServeConverterIntegration:
         assert str(sample.image.uri).startswith("data:image/"), (
             "Rehydrated picture URI should be a data: URI, not a bare artifact filename"
         )
+
+
+class TestDoclingServeZipParsing:
+    """_parse_zip_to_docling decodes the target_type=zip payload. These drive
+    its branches directly — no docling-serve instance involved."""
+
+    @pytest.fixture
+    def converter(self):
+        config = AppConfig()
+        config.processing.converter = "docling-serve"
+        conv = get_converter(config)
+        assert isinstance(conv, DoclingServeConverter)
+        return conv
+
+    @staticmethod
+    def _zip(entries: dict[str, bytes]) -> bytes:
+        import io
+        import zipfile
+
+        buf = io.BytesIO()
+        with zipfile.ZipFile(buf, mode="w") as zf:
+            for name, blob in entries.items():
+                zf.writestr(name, blob)
+        return buf.getvalue()
+
+    @staticmethod
+    def _doc_json(**extra) -> dict:
+        base = {
+            "name": "document",
+            "texts": [],
+            "tables": [],
+            "pictures": [],
+            "groups": [],
+            "body": {"self_ref": "#/body", "children": []},
+            "furniture": {"self_ref": "#/furniture", "children": []},
+        }
+        base.update(extra)
+        return base
+
+    def test_raises_without_top_level_json(self, converter):
+        blob = self._zip({"artifacts/image.png": b"png"})
+
+        with pytest.raises(ValueError, match="no top-level JSON document"):
+            converter._parse_zip_to_docling(blob, "doc.pdf")
+
+    def test_picture_without_image_is_left_alone(self, converter):
+        import json as _json
+
+        doc_json = self._doc_json(
+            pictures=[
+                {
+                    "self_ref": "#/pictures/0",
+                    "label": "picture",
+                    "image": None,
+                    "prov": [],
+                }
+            ]
+        )
+        blob = self._zip({"document.json": _json.dumps(doc_json).encode()})
+
+        doc = converter._parse_zip_to_docling(blob, "doc.pdf")
+
+        assert doc.pictures[0].image is None
+
+    def test_data_uri_image_is_passed_through(self, converter):
+        import json as _json
+
+        data_uri = "data:image/png;base64,aGVsbG8="
+        doc_json = self._doc_json(
+            pictures=[
+                {
+                    "self_ref": "#/pictures/0",
+                    "label": "picture",
+                    "image": {
+                        "mimetype": "image/png",
+                        "dpi": 72,
+                        "size": {"width": 1, "height": 1},
+                        "uri": data_uri,
+                    },
+                    "prov": [],
+                }
+            ]
+        )
+        blob = self._zip({"document.json": _json.dumps(doc_json).encode()})
+
+        doc = converter._parse_zip_to_docling(blob, "doc.pdf")
+
+        assert str(doc.pictures[0].image.uri) == data_uri
+
+    def test_non_dict_page_entry_is_skipped_while_inlining(self, converter):
+        """A page entry that isn't an object must not blow up the image-inlining
+        loop with an AttributeError; it falls through to schema validation."""
+        import json as _json
+
+        from pydantic import ValidationError
+
+        doc_json = self._doc_json(pages={"1": "not-a-page-object"})
+        blob = self._zip({"document.json": _json.dumps(doc_json).encode()})
+
+        with pytest.raises(ValidationError):
+            converter._parse_zip_to_docling(blob, "doc.pdf")
+
+    @pytest.mark.asyncio
+    async def test_convert_text_rejects_unsupported_format(self, converter):
+        with pytest.raises(ValueError, match="Unsupported format"):
+            await converter.convert_text("body", format="pdf")
+
+    @pytest.mark.asyncio
+    async def test_convert_text_plain_builds_document_locally(self, converter):
+        """format="plain" never reaches the network."""
+        converter.client.submit_and_poll_zip = AsyncMock(
+            side_effect=AssertionError("must not call docling-serve")
+        )
+
+        doc = await converter.convert_text("just text", format="plain")
+
+        assert isinstance(doc, DoclingDocument)
+        assert "just text" in doc.export_to_markdown()
+
+
+@pytest.mark.asyncio
+async def test_docling_serve_convert_file_wraps_text_read_failure(tmp_path):
+    """An undecodable text file surfaces as a ValueError naming the path."""
+    config = AppConfig()
+    config.processing.converter = "docling-serve"
+    converter = get_converter(config)
+    assert isinstance(converter, DoclingServeConverter)
+
+    source = tmp_path / "broken.txt"
+    source.write_bytes(b"\xff\xfe\x00\x01 not utf-8")
+
+    with pytest.raises(ValueError, match="Failed to read text file"):
+        await converter.convert_file(source)
diff --git a/tests/test_database_autocreate.py b/tests/test_database_autocreate.py
index d15bb950..1d14c936 100644
--- a/tests/test_database_autocreate.py
+++ b/tests/test_database_autocreate.py
@@ -43,3 +43,36 @@ async def test_operations_work_after_database_created(tmp_path):
         doc = await client.get_document_by_id(docs[0].id)
         assert doc is not None
         assert doc.content == "Test content"
+
+
+def test_default_db_path_comes_from_storage_data_dir(tmp_path):
+    """Omitting db_path places the database under the configured data dir."""
+    from haiku.rag.client import HaikuRAG
+    from haiku.rag.config import AppConfig
+
+    config = AppConfig()
+    config.storage.data_dir = tmp_path
+
+    client = HaikuRAG(config=config)
+
+    assert client._db_path == tmp_path / "haiku.rag.lancedb"
+
+
+@pytest.mark.asyncio
+async def test_vacuum_optimizes_tables_without_losing_rows(temp_db_path):
+    """The public vacuum() runs the store's optimize pass over real rows."""
+    from haiku.rag.store.models.document import Document
+    from haiku.rag.store.repositories.document import DocumentRepository
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        repo = DocumentRepository(client.store)
+        for i in range(3):
+            await repo.create(Document(content=f"body {i}", uri=f"test://doc{i}"))
+        before = len(await client.store.documents_table.list_versions())
+
+        await client.vacuum()
+
+        # Optimize compacts the per-document fragments into new versions; an
+        # unchanged count would mean nothing reached the tables.
+        assert len(await client.store.documents_table.list_versions()) > before
+        assert await client.count_documents() == 3
diff --git a/tests/test_docling_serve_client.py b/tests/test_docling_serve_client.py
index ceaf89ee..175ed53e 100644
--- a/tests/test_docling_serve_client.py
+++ b/tests/test_docling_serve_client.py
@@ -481,3 +481,29 @@ def test_from_config_wires_retry_and_breaker():
         assert client._max_attempts == 7
         assert client._breaker_config.failure_threshold == 9
         assert client._breaker_config.cooldown_s == 90.0
+
+
+@pytest.mark.asyncio
+async def test_submit_without_task_id_raises():
+    """A 200 that carries no task_id is a protocol violation, not a silent pass."""
+    import httpx
+
+    from haiku.rag.providers.docling_serve import DoclingServeClient
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(200, json={})
+
+    client = DoclingServeClient(base_urls="http://docling:5001")
+    files = {"files": ("doc.pdf", b"pdf", "application/octet-stream")}
+
+    async with httpx.AsyncClient(transport=httpx.MockTransport(handler)) as http:
+        with pytest.raises(ValueError, match="did not return a task_id"):
+            await client._submit_and_wait(
+                http,
+                "http://docling:5001",
+                "/v1/convert/source/async",
+                files,
+                {},
+                {},
+                "doc.pdf",
+            )
diff --git a/tests/test_doctor.py b/tests/test_doctor.py
index d6d0d3a2..03771327 100644
--- a/tests/test_doctor.py
+++ b/tests/test_doctor.py
@@ -1206,3 +1206,26 @@ async def test_duplicate_documents_check_reads_config(temp_db_path):
         ).severity
         is Severity.WARN
     )
+
+
+@pytest.mark.asyncio
+async def test_many_unembedded_chunks_are_sampled(temp_db_path):
+    """Beyond the sample limit the detail list ends with a count of the rest."""
+    db = await _build_db(temp_db_path)
+    chunks_tbl = await db.open_table("chunks")
+    await chunks_tbl.add(
+        [
+            ChunkRecord(
+                id=f"z{i}",
+                document_id="d1",
+                content="x",
+                metadata=json.dumps({"doc_item_refs": ["#/texts/0"]}),
+                vector=[0.0] * VECTOR_DIM,
+            )
+            for i in range(8)
+        ]
+    )
+    report = await run_doctor(_config(), temp_db_path, {})
+    details = _result(report, "unembedded_chunks").details
+    assert len(details) == 6
+    assert details[-1] == "... (+3 more)"
diff --git a/tests/test_document.py b/tests/test_document.py
index f850915c..a1c2ccb0 100644
--- a/tests/test_document.py
+++ b/tests/test_document.py
@@ -8,49 +8,33 @@ from haiku.rag.store.repositories.document_item import DocumentItemRepository
 
 
 @pytest.mark.asyncio
-async def test_document_list_excludes_content_by_default(
-    qa_corpus: list[dict[str, str]], temp_db_path
+@pytest.mark.parametrize("include_content", [False, True])
+async def test_document_list_all(
+    qa_corpus: list[dict[str, str]], temp_db_path, include_content
 ):
-    """list_all excludes content and docling_document by default."""
+    """list_all excludes content and docling_document unless include_content=True."""
     async with Store(temp_db_path, create=True) as store:
         doc_repo = DocumentRepository(store)
 
+        content = qa_corpus[0]["document_extracted"]
         doc = Document(
-            content=qa_corpus[0]["document_extracted"],
+            content=content,
             uri="https://example.com/doc.txt",
             title="Test Document",
             metadata={"key": "value"},
         )
         created = await doc_repo.create(doc)
 
-        docs = await doc_repo.list_all()
+        docs = await doc_repo.list_all(include_content=include_content)
         assert len(docs) == 1
         assert docs[0].id == created.id
         assert docs[0].title == "Test Document"
         assert docs[0].uri == "https://example.com/doc.txt"
         assert docs[0].metadata == {"key": "value"}
-        assert docs[0].content == ""
+        assert docs[0].content == (content if include_content else "")
         assert docs[0].docling_document is None
 
 
-@pytest.mark.asyncio
-async def test_document_list_includes_content_when_requested(
-    qa_corpus: list[dict[str, str]], temp_db_path
-):
-    """list_all returns content when include_content=True."""
-    async with Store(temp_db_path, create=True) as store:
-        doc_repo = DocumentRepository(store)
-
-        content = qa_corpus[0]["document_extracted"]
-        doc = Document(content=content, uri="https://example.com/doc.txt")
-        created = await doc_repo.create(doc)
-
-        docs = await doc_repo.list_all(include_content=True)
-        assert len(docs) == 1
-        assert docs[0].id == created.id
-        assert docs[0].content == content
-
-
 @pytest.mark.asyncio
 async def test_document_list_with_filter(qa_corpus: list[dict[str, str]], temp_db_path):
     """Test listing documents with filter clause."""
@@ -391,16 +375,26 @@ async def test_get_docling_data_loads_only_docling_columns(
 
 
 @pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "with_pages",
+    # Markdown documents have no page images, so their pages blob stays None.
+    [True, False],
+    ids=["with_pages", "markdown"],
+)
 async def test_get_pages_data_loads_only_pages_column(
-    qa_corpus: list[dict[str, str]], temp_db_path
+    qa_corpus: list[dict[str, str]], temp_db_path, with_pages
 ):
     """get_pages_data returns only page image data for a document."""
     import json
 
     from haiku.rag.store.compression import compress_json
 
-    pages_blob = compress_json(
-        json.dumps({"1": {"size": {"width": 612, "height": 792}, "page_no": 1}})
+    pages_blob = (
+        compress_json(
+            json.dumps({"1": {"size": {"width": 612, "height": 792}, "page_no": 1}})
+        )
+        if with_pages
+        else None
     )
 
     async with Store(temp_db_path, create=True) as store:
@@ -424,27 +418,6 @@ async def test_get_pages_data_loads_only_pages_column(
         assert await doc_repo.get_pages_data("nonexistent-id") is None
 
 
-@pytest.mark.asyncio
-async def test_get_pages_data_none_for_markdown_document(
-    qa_corpus: list[dict[str, str]], temp_db_path
-):
-    """Markdown documents have no page images — get_pages_data returns None pages."""
-    async with Store(temp_db_path, create=True) as store:
-        doc_repo = DocumentRepository(store)
-
-        doc = Document(
-            content=qa_corpus[0]["document_extracted"],
-            uri="https://example.com/doc.md",
-        )
-        created = await doc_repo.create(doc)
-        assert created.id is not None
-
-        result = await doc_repo.get_pages_data(created.id)
-        assert result is not None
-        assert result.id == created.id
-        assert result.docling_pages is None
-
-
 @pytest.mark.asyncio
 async def test_document_get_by_uri_with_special_characters(
     qa_corpus: list[dict[str, str]], temp_db_path
diff --git a/tests/test_download_models.py b/tests/test_download_models.py
index 50ad06a4..41e571c5 100644
--- a/tests/test_download_models.py
+++ b/tests/test_download_models.py
@@ -6,6 +6,7 @@ import pytest
 
 from haiku.rag.client.downloads import download_models
 from haiku.rag.config import Config
+from haiku.rag.config.models import ModelConfig
 
 
 @pytest.fixture
@@ -108,3 +109,73 @@ async def test_download_models_no_ollama_models(mock_to_thread):
     models = {e.model for e in events}
     assert "qwen3-embedding:4b" not in models
     assert "gpt-oss" not in models
+
+
+@pytest.mark.parametrize(
+    "configure,expected_model",
+    [
+        (
+            lambda c: setattr(
+                c.reranking,
+                "model",
+                ModelConfig(provider="ollama", name="rerank-model"),
+            ),
+            "rerank-model",
+        ),
+        (
+            lambda c: (
+                setattr(c.processing, "pictures", "description"),
+                setattr(
+                    c.processing.conversion_options.picture_description.model,
+                    "provider",
+                    "ollama",
+                ),
+                setattr(
+                    c.processing.conversion_options.picture_description.model,
+                    "name",
+                    "vision-model",
+                ),
+            ),
+            "vision-model",
+        ),
+        (
+            lambda c: (
+                setattr(c.processing, "auto_title", True),
+                setattr(c.processing.title_model, "provider", "ollama"),
+                setattr(c.processing.title_model, "name", "title-model"),
+            ),
+            "title-model",
+        ),
+    ],
+    ids=["reranker", "picture_description", "auto_title"],
+)
+async def test_ollama_models_from_every_config_slot_are_pulled(
+    mock_to_thread, configure, expected_model
+):
+    """Each config slot that can name an ollama model contributes to the pull set."""
+    from haiku.rag.config import AppConfig
+
+    config = AppConfig()
+    configure(config)
+
+    @asynccontextmanager
+    async def mock_stream(method, url, **kwargs):
+        mock_resp = AsyncMock()
+
+        async def aiter_lines():
+            yield '{"status": "success"}'
+
+        mock_resp.aiter_lines = aiter_lines
+        yield mock_resp
+
+    with patch(
+        "haiku.rag.client.downloads.httpx.AsyncClient",
+        return_value=_mock_httpx_client(mock_stream),
+    ):
+        pulled = {
+            progress.model
+            async for progress in download_models(config)
+            if progress.status == "pulling"
+        }
+
+    assert expected_model in pulled
diff --git a/tests/test_embedder_config.py b/tests/test_embedder_config.py
index a8a37fde..8d21257b 100644
--- a/tests/test_embedder_config.py
+++ b/tests/test_embedder_config.py
@@ -148,3 +148,50 @@ def test_vllm_embedder_does_not_double_append_v1():
     base_url = embedder._base_url.rstrip("/")  # type: ignore[attr-defined]  # ty: ignore[unresolved-attribute]
     assert base_url.endswith("/v1")
     assert not base_url.endswith("/v1/v1")
+
+
+def test_vector_dim_property_reports_configured_dimension():
+    from haiku.rag.embeddings import EmbedderWrapper
+
+    assert EmbedderWrapper(embedder=None, vector_dim=512).vector_dim == 512
+
+
+@pytest.mark.parametrize(
+    "provider,env_var",
+    [("voyageai", "VOYAGE_API_KEY"), ("cohere", "CO_API_KEY")],
+)
+def test_saas_providers_are_wired_without_a_request(monkeypatch, provider, env_var):
+    """Construction wires the SDK and reports the configured dimension."""
+    monkeypatch.setenv(env_var, "test-key")
+    config = AppConfig(
+        embeddings=EmbeddingsConfig(
+            model=EmbeddingModelConfig(
+                provider=provider, name="some-model", vector_dim=1024
+            ),
+        ),
+    )
+
+    embedder = get_embedder(config)
+
+    assert embedder.vector_dim == 1024
+    assert embedder.supports_images is False
+    # The provider and model reach the underlying pydantic-ai embedder.
+    assert embedder._embedder._model == f"{provider}:some-model"  # ty: ignore[unresolved-attribute]
+
+
+def test_cohere_floats_rejects_missing_embeddings():
+    from types import SimpleNamespace
+
+    from haiku.rag.embeddings.cohere import _floats
+
+    result = SimpleNamespace(embeddings=SimpleNamespace(float_=None))
+
+    with pytest.raises(ValueError, match="no float embeddings"):
+        _floats(result)
+
+
+def test_voyageai_to_pil_rejects_unsupported_type():
+    from haiku.rag.embeddings.voyageai import _to_pil
+
+    with pytest.raises(TypeError, match="Unsupported image type"):
+        _to_pil("not an image")  # ty: ignore[invalid-argument-type]
diff --git a/tests/test_lancedb_connection.py b/tests/test_lancedb_connection.py
index 1d283557..8e624250 100644
--- a/tests/test_lancedb_connection.py
+++ b/tests/test_lancedb_connection.py
@@ -310,3 +310,91 @@ class TestInitFailureCleanup:
                 pass
 
         assert close_calls, "Store.close() was not called when _initialize raised"
+
+
+class TestVectorIndexCreation:
+    """_ensure_vector_index needs 256 rows of training data before it builds."""
+
+    @staticmethod
+    async def _seed_chunks(store, count: int) -> None:
+        import random
+
+        records = [
+            store.ChunkRecord(
+                document_id="doc-1",
+                content=f"row {i}",
+                content_fts=f"row {i}",
+                metadata="{}",
+                order=i,
+                vector=[random.random() for _ in range(store.embedder.vector_dim)],
+            )
+            for i in range(count)
+        ]
+        await store.chunks_table.add(records)
+
+    @pytest.mark.asyncio
+    async def test_builds_index_once_enough_rows_exist(self, temp_db_path):
+        async with Store(temp_db_path, create=True) as store:
+            await self._seed_chunks(store, 256)
+
+            await store._ensure_vector_index()
+
+            indexes = await store.chunks_table.list_indices()
+            assert any("vector" in idx.columns for idx in indexes)
+
+    @pytest.mark.asyncio
+    async def test_index_failure_is_warned_not_raised(self, temp_db_path):
+        import logging
+
+        from haiku.rag.store import engine as engine_module
+        from tests.conftest import capture_logs
+
+        async with Store(temp_db_path, create=True) as store:
+            await self._seed_chunks(store, 256)
+
+            async def boom(*_args, **_kwargs):
+                raise RuntimeError("index build failed")
+
+            with patch.object(store.chunks_table, "create_index", boom):
+                with capture_logs(engine_module.logger, logging.WARNING) as records:
+                    await store._ensure_vector_index()
+
+            assert any("index build failed" in r.getMessage() for r in records)
+            indexes = await store.chunks_table.list_indices()
+            assert not any("vector" in idx.columns for idx in indexes)
+
+
+class TestStoreMiscellany:
+    @pytest.mark.asyncio
+    async def test_create_makes_missing_parent_directories(self, tmp_path):
+        nested = tmp_path / "a" / "b" / "db.lancedb"
+
+        async with Store(nested, create=True) as store:
+            assert store._is_new_db is True
+
+        assert nested.exists()
+
+    @pytest.mark.asyncio
+    async def test_stored_vector_dim_is_none_for_corrupt_settings(self, temp_db_path):
+        async with Store(temp_db_path, create=True) as store:
+            await store.settings_table.update(
+                {"settings": "not json at all"}, where="id = 'settings'"
+            )
+
+            assert await store._get_stored_vector_dim() is None
+
+    @pytest.mark.asyncio
+    async def test_vacuum_skips_when_already_running(self, temp_db_path):
+        import asyncio
+
+        async with Store(temp_db_path, create=True) as store:
+            async with store._vacuum_lock:
+                # Bounded: a regression here blocks on the held lock, and the
+                # timeout turns that deadlock into a clean failure.
+                await asyncio.wait_for(store.vacuum(), timeout=5)
+
+    @pytest.mark.asyncio
+    async def test_history_rejects_unknown_table(self, temp_db_path):
+        async with Store(temp_db_path, create=True) as store:
+            with pytest.raises(ValueError, match="Unknown table"):
+                await store.list_table_versions("not_a_table")
diff --git a/tests/test_mcp.py b/tests/test_mcp.py
index eda2e2e2..f0c36474 100644
--- a/tests/test_mcp.py
+++ b/tests/test_mcp.py
@@ -332,3 +332,152 @@ class TestMCPImageInput:
         result = await ask(question="q")
         assert result == "answer"
         assert captured["images"] is None
+
+
+class TestMCPFileAndUrlIngestion:
+    @pytest.mark.asyncio
+    async def test_add_document_from_file(self, temp_db_path, tmp_path):
+        async with HaikuRAG(temp_db_path, create=True):
+            pass
+        source = tmp_path / "note.txt"
+        source.write_text("Ingested from a file path.")
+
+        mcp = create_mcp_server(temp_db_path, read_only=False)
+        add_file = await _get_tool(mcp, "add_document_from_file")
+
+        doc_id = await add_file(file_path=str(source), title="File Doc")
+        assert doc_id is not None
+
+        get_doc = await _get_tool(mcp, "get_document")
+        doc = await get_doc(document_id=doc_id)
+        assert doc.title == "File Doc"
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "tool_name,kwargs",
+        [
+            ("add_document_from_file", {"file_path": "/tmp/x.txt"}),
+            ("add_document_from_url", {"url": "https://example.com/x.txt"}),
+        ],
+    )
+    @pytest.mark.parametrize(
+        "results,expected",
+        [
+            (
+                [Document(id="first", content="a"), Document(id="second", content="b")],
+                "first",
+            ),
+            ([], None),
+        ],
+        ids=["directory_reports_first_id", "empty_directory_reports_none"],
+    )
+    async def test_add_tools_handle_multi_document_sources(
+        self, mcp_db, monkeypatch, tool_name, kwargs, results, expected
+    ):
+        """A source resolving to several documents reports the first id."""
+
+        async def fake_from_source(self, source, title=None, metadata=None, **kw):
+            return results
+
+        monkeypatch.setattr(HaikuRAG, "create_document_from_source", fake_from_source)
+        mcp = create_mcp_server(mcp_db, read_only=False)
+        add = await _get_tool(mcp, tool_name)
+
+        assert await add(**kwargs) == expected
+
+    @pytest.mark.asyncio
+    async def test_add_document_from_url(self, mcp_db, monkeypatch):
+        async def fake_from_source(self, source, title=None, metadata=None, **kwargs):
+            assert source == "https://example.com/doc.txt"
+            return Document(id="url-doc", content="fetched")
+
+        monkeypatch.setattr(HaikuRAG, "create_document_from_source", fake_from_source)
+        mcp = create_mcp_server(mcp_db, read_only=False)
+        add_url = await _get_tool(mcp, "add_document_from_url")
+
+        assert await add_url(url="https://example.com/doc.txt") == "url-doc"
+
+
+class TestMCPToolsDegradeOnError:
+    """Every tool swallows client failures and returns its empty value rather
+    than propagating an exception to the MCP transport."""
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "client_method,tool_name,kwargs,expected",
+        [
+            (
+                "create_document_from_source",
+                "add_document_from_file",
+                {"file_path": "/tmp/x.txt"},
+                None,
+            ),
+            (
+                "create_document_from_source",
+                "add_document_from_url",
+                {"url": "https://example.com/x"},
+                None,
+            ),
+            ("create_document", "add_document_from_text", {"content": "x"}, None),
+            ("delete_document", "delete_document", {"document_id": "x"}, False),
+            ("search", "search_documents", {"query": "x"}, []),
+            ("get_document_by_id", "get_document", {"document_id": "x"}, None),
+            ("list_documents", "list_documents", {}, []),
+        ],
+    )
+    async def test_tool_returns_empty_value_when_client_raises(
+        self, mcp_db, monkeypatch, client_method, tool_name, kwargs, expected
+    ):
+        async def boom(self, *args, **kw):
+            raise RuntimeError("client exploded")
+
+        monkeypatch.setattr(HaikuRAG, client_method, boom)
+        mcp = create_mcp_server(mcp_db, read_only=False)
+        tool = await _get_tool(mcp, tool_name)
+
+        assert await tool(**kwargs) == expected
+
+    @pytest.mark.asyncio
+    async def test_list_documents_returns_empty_for_invalid_filter(self, mcp_db):
+        mcp = create_mcp_server(mcp_db, read_only=True)
+        list_docs = await _get_tool(mcp, "list_documents")
+
+        assert await list_docs(filter="no_such_column = 1") == []
+
+    @pytest.mark.asyncio
+    async def test_analyze_reports_the_error(self, mcp_db, monkeypatch):
+        async def boom(self, question, filter=None, images=None):
+            raise RuntimeError("sandbox exploded")
+
+        monkeypatch.setattr(HaikuRAG, "analyze", boom)
+        mcp = create_mcp_server(mcp_db, read_only=True)
+        analyze = await _get_tool(mcp, "analyze")
+
+        assert "sandbox exploded" in await analyze(question="q")
+
+    @pytest.mark.asyncio
+    async def test_ask_question_appends_citations_when_requested(
+        self, mcp_db, monkeypatch
+    ):
+        from haiku.rag.store.models.citation import Citation
+
+        citation = Citation(
+            chunk_id="c1",
+            document_id="d1",
+            content="cited text",
+            document_uri="test://ai-overview",
+            document_title="AI Overview",
+        )
+
+        async def fake_ask(self, question, filter=None, images=None):
+            return ("the answer", [citation])
+
+        monkeypatch.setattr(HaikuRAG, "ask", fake_ask)
+        mcp = create_mcp_server(mcp_db, read_only=True)
+        ask = await _get_tool(mcp, "ask_question")
+
+        with_cite = await ask(question="q", cite=True)
+        assert with_cite.startswith("the answer")
+        assert "AI Overview" in with_cite
+
+        assert await ask(question="q", cite=False) == "the answer"
diff --git a/tests/test_pdf_split.py b/tests/test_pdf_split.py
index 09b3f274..af5abaf9 100644
--- a/tests/test_pdf_split.py
+++ b/tests/test_pdf_split.py
@@ -243,3 +243,14 @@ def test_concatenate_shifts_page_nos_and_unique_self_refs():
     assert page_nos == [1, 2], f"expected b's page 1 to shift to page 2, got {page_nos}"
 
     assert sorted(merged.pages.keys()) == [1, 2]
+
+
+def test_iter_pdf_slices_rejects_unopenable_pdf(tmp_path):
+    """pdfium refuses non-PDF bytes; the caller sees UnsupportedSourceError."""
+    from haiku.rag.client.exceptions import UnsupportedSourceError
+
+    junk = tmp_path / "not-really.pdf"
+    junk.write_bytes(b"this is not a pdf at all")
+
+    with pytest.raises(UnsupportedSourceError, match="cannot open PDF"):
+        list(iter_pdf_slices(junk, slice_size=1))
diff --git a/tests/test_picture_in_context.py b/tests/test_picture_in_context.py
index 770c7f57..55f2f368 100644
--- a/tests/test_picture_in_context.py
+++ b/tests/test_picture_in_context.py
@@ -1011,3 +1011,32 @@ async def test_rag_capability_attaches_images_for_vision_model(temp_db_path):
     assert isinstance(result, ToolReturn)
     assert result.content is not None
     assert any(isinstance(part, BinaryContent) for part in result.content)
+
+
+def test_build_picture_chunks_records_provenance_pages():
+    """A picture with provenance contributes its page numbers to the chunk."""
+    from docling_core.types.doc.base import BoundingBox
+    from docling_core.types.doc.document import ProvenanceItem
+
+    from haiku.rag.client.processing import build_picture_chunks
+    from tests.store.test_document_items import _docling_doc_with_picture
+
+    doc = _docling_doc_with_picture()
+    picture = doc.pictures[0]
+    picture.prov = [
+        ProvenanceItem(
+            page_no=3,
+            bbox=BoundingBox(l=0, t=10, r=10, b=0),
+            charspan=(0, 0),
+        ),
+        # A repeat of the same page must not be counted twice.
+        ProvenanceItem(
+            page_no=3,
+            bbox=BoundingBox(l=0, t=20, r=10, b=10),
+            charspan=(0, 0),
+        ),
+    ]
+
+    chunks = build_picture_chunks(doc, document_id="doc-1")
+
+    assert chunks[0].metadata["page_numbers"] == [3]
diff --git a/tests/test_processing.py b/tests/test_processing.py
index 8e7133d2..29ec8fdc 100644
--- a/tests/test_processing.py
+++ b/tests/test_processing.py
@@ -7,6 +7,7 @@ import pytest
 
 from haiku.rag.client.processing import _warn_if_descriptions_missing, convert
 from haiku.rag.config import AppConfig
+from tests.conftest import capture_logs
 
 
 def _doc_with_pictures(*, with_descriptions: bool):
@@ -44,24 +45,12 @@ def _doc_without_pictures():
 
 
 @pytest.fixture
-def caplog_warnings(caplog):
+def caplog_warnings():
     """Capture WARNING-level records from the processing logger."""
-    caplog.set_level(logging.WARNING, logger="haiku.rag.client.processing")
-    # The haiku.rag parent logger sets propagate=False after get_logger() runs,
-    # which can break caplog under xdist when other tests have already
-    # configured logging. Attach directly to the module logger.
     from haiku.rag.client.processing import logger as proc_logger
 
-    records: list[logging.LogRecord] = []
-
-    class _Capture(logging.Handler):
-        def emit(self, record: logging.LogRecord) -> None:
-            records.append(record)
-
-    handler = _Capture(level=logging.WARNING)
-    proc_logger.addHandler(handler)
-    yield records
-    proc_logger.removeHandler(handler)
+    with capture_logs(proc_logger, logging.WARNING) as records:
+        yield records
 
 
 def test_no_warning_when_picture_description_disabled(caplog_warnings):
@@ -222,3 +211,56 @@ def test_merge_picture_chunks_no_pictures_returns_text_chunks():
 
     assert result is text_chunks
     assert [c.order for c in result] == [0, 1]
+
+
+@pytest.mark.asyncio
+async def test_convert_dispatches_large_pdfs_through_split_and_merge(
+    tmp_path, monkeypatch
+):
+    """With split_pages configured, PDF conversion routes through the
+    split-and-merge helper rather than the converter directly."""
+    from docling_core.types.doc.document import DoclingDocument
+
+    config = AppConfig()
+    config.processing.split_pages = 2
+
+    pdf = tmp_path / "big.pdf"
+    pdf.write_bytes(b"%PDF-1.4 stub")
+    called: dict = {}
+
+    async def fake_split(converter, path, uri, slice_size):
+        called["slice_size"] = slice_size
+        called["path"] = path
+        return DoclingDocument(name="merged")
+
+    monkeypatch.setattr(
+        "haiku.rag.converters.pdf_split.convert_pdf_with_splitting", fake_split
+    )
+
+    doc = await convert(config, pdf)
+
+    assert doc.name == "merged"
+    assert called["slice_size"] == 2
+    assert called["path"] == pdf
+
+
+def _write_unsupported(directory):
+    target = directory / "thing.sqlite3"
+    target.write_bytes(b"binary")
+    return target.as_uri()
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "make_source,match",
+    [
+        (lambda d: (d / "missing.md").as_uri(), "File does not exist"),
+        (_write_unsupported, "Unsupported file extension"),
+    ],
+    ids=["missing_file", "unsupported_extension"],
+)
+async def test_convert_rejects_bad_file_uris(tmp_path, make_source, match):
+    from haiku.rag.client.exceptions import UnsupportedSourceError
+
+    with pytest.raises(UnsupportedSourceError, match=match):
+        await convert(AppConfig(), make_source(tmp_path))
diff --git a/tests/test_rebuild.py b/tests/test_rebuild.py
index c371bae2..f76c5592 100644
--- a/tests/test_rebuild.py
+++ b/tests/test_rebuild.py
@@ -7,6 +7,7 @@ import pytest
 
 from haiku.rag.client import HaikuRAG, RebuildMode
 from haiku.rag.config import Config
+from tests.conftest import capture_logs
 
 
 class ChunkData(TypedDict):
@@ -615,25 +616,11 @@ async def test_rebuild_full_source_failure_is_logged_and_skipped(
 
             monkeypatch.setattr(client, "create_document_from_source", failing_create)
 
-            # Attach directly to the rebuild module's logger rather than
-            # relying on caplog — `haiku.rag.logging.get_logger()` (invoked
-            # by other tests) sets `propagate=False` on the `haiku.rag`
-            # logger, which breaks caplog under xdist ordering.
-            records: list[logging.LogRecord] = []
-
-            class _ListHandler(logging.Handler):
-                def emit(self, record: logging.LogRecord) -> None:
-                    records.append(record)
-
-            handler = _ListHandler(level=logging.ERROR)
-            rebuild_module.logger.addHandler(handler)
-            try:
+            with capture_logs(rebuild_module.logger, logging.ERROR) as records:
                 processed_ids = [
                     doc_id
                     async for doc_id in client.rebuild_database(mode=RebuildMode.FULL)
                 ]
-            finally:
-                rebuild_module.logger.removeHandler(handler)
 
             assert processed_ids == []
             assert any(
@@ -843,7 +830,7 @@ async def test_patch_picture_descriptions_returns_zero_for_doc_without_pictures(
 
 
 @pytest.mark.asyncio
-async def test_patch_picture_descriptions_warns_on_missing_bytes(temp_db_path, caplog):
+async def test_patch_picture_descriptions_warns_on_missing_bytes(temp_db_path):
     """When the docling blob has pictures but document_items.picture_data is
     empty (e.g. legacy DB ingested before A2b), the helper logs a warning
     and returns 0 instead of trying to drive the VLM with no input."""
@@ -872,23 +859,10 @@ async def test_patch_picture_descriptions_warns_on_missing_bytes(temp_db_path, c
             where=f"document_id = '{created.id}' AND label = 'picture'",
         )
 
-        # Capture warnings directly off the rebuild module logger — the
-        # haiku.rag parent logger is configured non-propagating elsewhere
-        # in the suite so caplog can miss records.
         from haiku.rag.client import rebuild as rebuild_module
 
-        records: list[logging.LogRecord] = []
-
-        class _ListHandler(logging.Handler):
-            def emit(self, record: logging.LogRecord) -> None:
-                records.append(record)
-
-        handler = _ListHandler(level=logging.WARNING)
-        rebuild_module.logger.addHandler(handler)
-        try:
+        with capture_logs(rebuild_module.logger, logging.WARNING) as records:
             n = await _patch_picture_descriptions(rag, created)
-        finally:
-            rebuild_module.logger.removeHandler(handler)
 
         assert n == 0
         assert any("no stored picture bytes" in r.getMessage() for r in records)
@@ -1095,3 +1069,458 @@ async def test_rebuild_blocks_tag_operations(temp_db_path, monkeypatch):
         assert not client.store._rebuild_lock.locked()
         await client.store.create_tag("post-rebuild")
         assert set(await client.store.list_tags()) == {"post-rebuild"}
+
+
+def _count_flushes(monkeypatch, rebuild_module) -> list[int]:
+    """Record the size of every batch handed to _flush_rebuild_batch."""
+    real = rebuild_module._flush_rebuild_batch
+    sizes: list[int] = []
+
+    async def spy(client, documents, chunks):
+        sizes.append(len(documents))
+        return await real(client, documents, chunks)
+
+    monkeypatch.setattr(rebuild_module, "_flush_rebuild_batch", spy)
+    return sizes
+
+
+# --- unit-level rebuild helpers (no embedder involved) ---
+
+
+@pytest.mark.vcr()
+async def test_flush_rebuild_batch_is_a_noop_without_documents(temp_db_path):
+    from haiku.rag.client.rebuild import _flush_rebuild_batch
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        # A populated table makes "unchanged" distinguishable from "wiped".
+        existing = await client.create_document(content="keep me")
+        before = await client.store.documents_table.count_rows()
+        assert before == 1
+
+        await _flush_rebuild_batch(client, [], [])
+
+        assert await client.store.documents_table.count_rows() == before
+        after = await client.get_document_by_id(existing.id)
+        assert after is not None
+        assert after.updated_at == existing.updated_at
+
+
+async def test_mark_phase1_complete_is_idempotent(temp_db_path):
+    from haiku.rag.client.rebuild import (
+        _STAGING_MARKER_TABLE_NAME,
+        _mark_phase1_complete,
+    )
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        await _mark_phase1_complete(client)
+        await _mark_phase1_complete(client)
+
+        tables = (await client.store.db.list_tables()).tables
+        assert _STAGING_MARKER_TABLE_NAME in tables
+
+
+async def test_populate_staging_returns_early_without_chunks_table(temp_db_path):
+    from haiku.rag.client.rebuild import _STAGING_TABLE_NAME, _populate_staging_table
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        await client.store.db.drop_table("chunks")
+
+        await _populate_staging_table(client)
+
+        staging = await client.store.db.open_table(_STAGING_TABLE_NAME)
+        assert await staging.count_rows() == 0
+
+
+async def test_hydrate_skips_documents_deleted_mid_rebuild(temp_db_path):
+    """A document removed between listing and hydration is skipped."""
+    from haiku.rag.client.rebuild import _hydrate
+    from haiku.rag.store.models.document import Document
+    from haiku.rag.store.repositories.document import DocumentRepository
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        stored = await DocumentRepository(client.store).create(
+            Document(content="body", uri="test://gone")
+        )
+
+        async def vanished(_document_id):
+            return None
+
+        client.get_document_by_id = vanished  # type: ignore[method-assign]
+
+        assert [doc async for doc in _hydrate(client, [stored])] == []
+
+
+@pytest.mark.parametrize(
+    "description,expected_text",
+    [("", None), ("a red square", "a red square")],
+    ids=["empty_skipped", "populated_applied"],
+)
+async def test_apply_descriptions_writes_only_non_empty_text(
+    description, expected_text
+):
+    """An empty generated description leaves the picture untouched; a real one
+    is written through to the picture meta."""
+    from haiku.rag.client.rebuild import _apply_descriptions_sync
+    from haiku.rag.store.models.document import Document
+    from tests.store.test_document_items import _docling_doc_with_picture
+
+    docling_doc = _docling_doc_with_picture()
+    ref = docling_doc.pictures[0].self_ref
+    document = Document(content="x", uri="test://doc")
+
+    _apply_descriptions_sync(docling_doc, document, {ref: description})
+
+    meta = docling_doc.pictures[0].meta
+    actual = getattr(getattr(meta, "description", None), "text", None) if meta else None
+    assert actual == expected_text
+    # The blob is re-compressed either way; page rasters must survive it.
+    assert document.docling_document is not None
+
+
+@pytest.mark.asyncio
+async def test_patch_picture_descriptions_returns_zero_without_descriptions(
+    temp_db_path, monkeypatch
+):
+    """When the VLM returns nothing, no blob rewrite is attempted."""
+    from haiku.rag.client.documents import _store_document_with_chunks
+    from haiku.rag.client.rebuild import _patch_picture_descriptions
+    from haiku.rag.config import AppConfig
+    from haiku.rag.store.models.document import Document
+    from tests.store.test_document_items import _docling_doc_with_picture
+
+    docling_doc = _docling_doc_with_picture()
+    config = AppConfig()
+    config.processing.pictures = "description"
+
+    async def no_descriptions(_bytes_by_ref, config=None):
+        return {}
+
+    monkeypatch.setattr(
+        "haiku.rag.providers.picture_description.describe_pictures",
+        no_descriptions,
+    )
+
+    async with HaikuRAG(temp_db_path, config=config, create=True) as rag:
+        document = Document(content="x", uri="test://doc")
+        document.set_docling(docling_doc)
+        created = await _store_document_with_chunks(rag, document, [], docling_doc)
+
+        assert await _patch_picture_descriptions(rag, created) == 0
+
+
+@pytest.mark.vcr()
+async def test_rebuild_warns_when_post_rebuild_vacuum_fails(temp_db_path, monkeypatch):
+    """A failing post-rebuild vacuum is logged, not raised — the rebuild itself
+    already succeeded."""
+    import logging
+
+    from haiku.rag.client import rebuild as rebuild_module
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.create_document(content="vacuum failure doc")
+        assert doc.id is not None
+        client._config.storage.auto_vacuum = True
+
+        async def failing_vacuum():
+            raise RuntimeError("vacuum exploded")
+
+        monkeypatch.setattr(client.store, "vacuum", failing_vacuum)
+
+        with capture_logs(rebuild_module.logger, logging.WARNING) as records:
+            processed = [
+                doc_id
+                async for doc_id in client.rebuild_database(mode=RebuildMode.RECHUNK)
+            ]
+
+        assert doc.id in processed
+        assert any("vacuum failed" in r.getMessage() for r in records)
+
+
+@pytest.mark.vcr()
+async def test_rebuild_embed_only_yields_documents_without_chunks(temp_db_path):
+    """A document whose chunks were all removed is still reported as processed."""
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.create_document(content="doc that loses its chunks")
+        assert doc.id is not None
+        await client.chunk_repository.delete_by_document_id(doc.id)
+
+        processed = [
+            doc_id
+            async for doc_id in client.rebuild_database(mode=RebuildMode.EMBED_ONLY)
+        ]
+
+        assert processed == [doc.id]
+
+
+@pytest.mark.vcr()
+async def test_rebuild_embed_only_flushes_in_batches(temp_db_path, monkeypatch):
+    """Forces a tiny batch size so the mid-loop flush in phase 2 runs."""
+    from haiku.rag.client import rebuild as rebuild_module
+
+    monkeypatch.setattr(rebuild_module, "_REBUILD_BATCH_SIZE", 2)
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        ids = []
+        for i in range(3):
+            doc = await client.create_document(content=f"embed only batch doc {i}")
+            assert doc.id is not None
+            ids.append(doc.id)
+
+        # Phase 2 writes straight to the chunks table rather than going
+        # through _flush_rebuild_batch, so count the adds it makes. Patch at
+        # class level: embed-only recreates the table, discarding any patch
+        # applied to the instance that exists now.
+        import lancedb
+
+        real_add = lancedb.AsyncTable.add
+        adds: list[int] = []
+
+        async def counting_add(self, records, *args, **kwargs):
+            if self.name == "chunks":
+                adds.append(len(records))
+            return await real_add(self, records, *args, **kwargs)
+
+        monkeypatch.setattr(lancedb.AsyncTable, "add", counting_add)
+
+        processed = [
+            doc_id
+            async for doc_id in client.rebuild_database(mode=RebuildMode.EMBED_ONLY)
+        ]
+
+        assert sorted(processed) == sorted(ids)
+        for doc_id in ids:
+            assert await client.chunk_repository.get_by_document_id(doc_id)
+
+        # 3 docs at batch size 2: one mid-loop write plus the trailing one.
+        assert len(adds) == 2
+
+
+@pytest.mark.vcr()
+async def test_rechunk_raises_when_docling_blob_is_missing(temp_db_path):
+    """RECHUNK needs the stored docling document; without it the user is told
+    to run a full rebuild."""
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.create_document(content="doc with a cleared blob")
+        assert doc.id is not None
+
+        await client.store.documents_table.update(
+            {"docling_document": None}, where=f"id = '{doc.id}'"
+        )
+
+        with pytest.raises(ValueError, match="has no stored docling document"):
+            async for _ in client.rebuild_database(mode=RebuildMode.RECHUNK):
+                pass
+
+
+@pytest.mark.vcr()
+async def test_rebuild_full_flushes_in_batches(temp_db_path, monkeypatch):
+    from haiku.rag.client import rebuild as rebuild_module
+
+    monkeypatch.setattr(rebuild_module, "_REBUILD_BATCH_SIZE", 2)
+    flushes = _count_flushes(monkeypatch, rebuild_module)
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        ids = []
+        for i in range(3):
+            doc = await client.create_document(content=f"full batch doc {i}")
+            assert doc.id is not None
+            ids.append(doc.id)
+
+        processed = [
+            doc_id async for doc_id in client.rebuild_database(mode=RebuildMode.FULL)
+        ]
+
+        assert sorted(processed) == sorted(ids)
+
+    assert len(flushes) == 2
+
+
+@pytest.mark.vcr()
+async def test_rebuild_full_warns_when_source_is_missing(temp_db_path):
+    """A document whose file source is gone is re-embedded from stored content."""
+    import logging
+
+    from haiku.rag.client import rebuild as rebuild_module
+
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.create_document(
+            content="content whose source vanished",
+            uri="file:///definitely/not/here.txt",
+        )
+        assert doc.id is not None
+
+        with capture_logs(rebuild_module.logger, logging.WARNING) as records:
+            processed = [
+                doc_id
+                async for doc_id in client.rebuild_database(mode=RebuildMode.FULL)
+            ]
+
+        assert doc.id in processed
+        assert any("Source missing" in r.getMessage() for r in records)
+
+
+@pytest.mark.vcr()
+async def test_rebuild_full_flushes_pending_before_source_rebuild(temp_db_path):
+    """A live source is re-ingested, which creates a new document, so any
+    documents pending from the content path must be flushed first."""
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        content_doc = await client.create_document(content="plain content doc")
+        assert content_doc.id is not None
+
+        with tempfile.TemporaryDirectory() as temp_dir:
+            source = Path(temp_dir) / "live.txt"
+            source.write_text("content from a source that still exists")
+            source_doc = await client.create_document_from_source(source)
+            assert not isinstance(source_doc, list)
+
+            processed = [
+                doc_id
+                async for doc_id in client.rebuild_database(mode=RebuildMode.FULL)
+            ]
+
+            # The content-path document keeps its id and must survive the
+            # flush that precedes the source re-ingest; the source document
+            # is replaced by a freshly ingested one with a new id.
+            assert content_doc.id in processed
+            assert source_doc.id not in processed
+            assert len(processed) == 2
+            assert await client.store.documents_table.count_rows() == 2
+
+
+@pytest.mark.vcr()
+async def test_rebuild_descriptions_flushes_in_batches(temp_db_path, monkeypatch):
+    """Two picture documents with a batch size of one exercise the mid-loop
+    flush in the descriptions path."""
+    from haiku.rag.client import rebuild as rebuild_module
+    from haiku.rag.client.documents import _store_document_with_chunks
+    from haiku.rag.config import AppConfig
+    from haiku.rag.store.models.document import Document
+    from tests.store.test_document_items import _docling_doc_with_picture
+
+    config = AppConfig()
+    config.processing.pictures = "description"
+
+    monkeypatch.setattr(rebuild_module, "_REBUILD_BATCH_SIZE", 1)
+    flushes = _count_flushes(monkeypatch, rebuild_module)
+
+    async def fake_describe(image_bytes_by_ref, *, config):
+        return {ref: "A red square (mocked)." for ref in image_bytes_by_ref}
+
+    monkeypatch.setattr(
+        "haiku.rag.providers.picture_description.describe_pictures", fake_describe
+    )
+
+    async with HaikuRAG(temp_db_path, config=config, create=True) as rag:
+        ids = []
+        for i in range(2):
+            docling_doc = _docling_doc_with_picture()
+            document = Document(content=f"picture doc {i}", uri=f"test://doc-{i}")
+            document.set_docling(docling_doc)
+            created = await _store_document_with_chunks(rag, document, [], docling_doc)
+            assert created.id is not None
+            ids.append(created.id)
+
+        processed = [
+            doc_id
+            async for doc_id in rag.rebuild_database(mode=RebuildMode.DESCRIPTIONS)
+        ]
+
+        assert sorted(processed) == sorted(ids)
+
+    # 2 docs at batch size 1: one flush each, none left for the trailing pass.
+    assert len(flushes) == 2
+
+
+@pytest.mark.vcr()
+async def test_rebuild_full_skips_document_deleted_mid_rebuild(temp_db_path):
+    """A document removed between listing and the content-path reload is skipped."""
+    async with HaikuRAG(temp_db_path, create=True) as client:
+        doc = await client.create_document(content="doc that disappears")
+        assert doc.id is not None
+
+        async def vanished(_document_id):
+            return None
+
+        client.get_document_by_id = vanished  # type: ignore[method-assign]
+
+        processed = [
+            doc_id async for doc_id in client.rebuild_database(mode=RebuildMode.FULL)
+        ]
+
+        assert processed == []
+
+
+@pytest.mark.vcr()
+@pytest.mark.parametrize("wipe_bytes", [True, False], ids=["wiped", "recoverable"])
+async def test_rebuild_embed_only_recovers_picture_bytes(
+    temp_db_path, monkeypatch, wipe_bytes
+):
+    """Embed-only re-attaches picture bytes from document_items. When they are
+    gone the chunk falls back to embedding its caption as text rather than
+    failing the rebuild."""
+    import logging
+
+    from haiku.rag.client import rebuild as rebuild_module
+    from haiku.rag.client.documents import _store_document_with_chunks
+    from haiku.rag.store.models.chunk import Chunk
+    from haiku.rag.store.models.document import Document
+    from tests.store.test_document_items import _docling_doc_with_picture
+
+    docling_doc = _docling_doc_with_picture()
+    ref = docling_doc.pictures[0].self_ref
+
+    async with HaikuRAG(temp_db_path, create=True) as rag:
+        # The configured ollama embedder is text-only; stand in for a
+        # multimodal one so the picture-bytes recovery branch runs.
+        embedded_images: list[bytes] = []
+
+        async def fake_embed_image(image):
+            embedded_images.append(image)
+            return [0.2] * rag.embedder.vector_dim
+
+        monkeypatch.setattr(rag.embedder, "supports_images", True)
+        monkeypatch.setattr(rag.embedder, "embed_image", fake_embed_image)
+
+        document = Document(content="picture doc", uri="test://pic")
+        document.set_docling(docling_doc)
+        picture_chunk = Chunk(
+            content="Figure caption",
+            metadata={"doc_item_refs": [ref], "labels": ["picture"]},
+            order=0,
+            embedding=[0.1] * rag.embedder.vector_dim,
+        )
+        # A sibling text chunk exercises the non-picture skip in the same loop.
+        text_chunk = Chunk(
+            content="Surrounding prose",
+            metadata={"doc_item_refs": ["#/texts/0"], "labels": ["text"]},
+            order=1,
+            embedding=[0.1] * rag.embedder.vector_dim,
+        )
+        created = await _store_document_with_chunks(
+            rag, document, [picture_chunk, text_chunk], docling_doc
+        )
+        assert created.id is not None
+
+        if wipe_bytes:
+            await rag.store.document_items_table.update(
+                {"picture_data": None},
+                where=f"document_id = '{created.id}' AND label = 'picture'",
+            )
+
+        with capture_logs(rebuild_module.logger, logging.WARNING) as records:
+            processed = [
+                doc_id
+                async for doc_id in rag.rebuild_database(mode=RebuildMode.EMBED_ONLY)
+            ]
+
+        assert created.id in processed
+        warned = any("no recoverable bytes" in r.getMessage() for r in records)
+        assert warned is wipe_bytes
+
+        if wipe_bytes:
+            # Nothing to recover, so the caption is text-embedded instead.
+            assert embedded_images == []
+        else:
+            # The stored PNG was re-attached and routed through embed_image.
+            assert len(embedded_images) == 1
+            assert embedded_images[0].startswith(b"\x89PNG")
diff --git a/tests/test_reranker.py b/tests/test_reranker.py
index 0f8c77bf..635fe5fc 100644
--- a/tests/test_reranker.py
+++ b/tests/test_reranker.py
@@ -479,3 +479,30 @@ async def test_cross_encoder_reranker():
         assert "0" in top_ids or "2" in top_ids
     except ImportError:
         pytest.skip("sentence-transformers not installed")
+
+
+@pytest.mark.asyncio
+async def test_cross_encoder_reranks_via_model_ranking(monkeypatch):
+    """The rank() results map back onto the input chunks by corpus_id."""
+    from haiku.rag.reranking import cross_encoder as ce_module
+
+    class _StubCrossEncoder:
+        def __init__(self, model):
+            self.model = model
+
+        def rank(self, query, documents, top_k=10):
+            # Reverse order so the mapping back to chunks is observable.
+            return [
+                {"corpus_id": i, "score": 1.0 - (i / 10)}
+                for i in reversed(range(len(documents)))
+            ][:top_k]
+
+    monkeypatch.setattr(ce_module, "CrossEncoder", _StubCrossEncoder)
+
+    reranker = ce_module.CrossEncoderReranker("stub/model")
+    reranked = await reranker.rerank("query", chunks, top_n=2)
+
+    assert len(reranked) == 2
+    last_index = len(chunks) - 1
+    assert reranked[0][0] is chunks[last_index]
+    assert reranked[0][1] == pytest.approx(1.0 - last_index / 10)
diff --git a/tests/test_search.py b/tests/test_search.py
index e1eccf66..6a6e429f 100644
--- a/tests/test_search.py
+++ b/tests/test_search.py
@@ -275,72 +275,35 @@ async def test_fts_search_targets_content_fts_column(temp_db_path):
         )
 
 
-def test_search_result_primary_label_prioritizes_structural_types():
-    """Test _get_primary_label prioritizes structural labels correctly."""
-    # Table should be prioritized
-    result = SearchResult(
-        content="test",
-        score=0.5,
-        chunk_id="c1",
-        document_id="d1",
-        labels=["paragraph", "table", "text"],
-    )
-    assert result._get_primary_label() == "table"
-
-    # Code should be prioritized over paragraph
-    result = SearchResult(
-        content="test",
-        score=0.5,
-        chunk_id="c2",
-        document_id="d2",
-        labels=["paragraph", "code"],
-    )
-    assert result._get_primary_label() == "code"
-
-    # list_item should be prioritized
-    result = SearchResult(
-        content="test",
-        score=0.5,
-        chunk_id="c3",
-        document_id="d3",
-        labels=["text", "list_item"],
-    )
-    assert result._get_primary_label() == "list_item"
-
-    # Returns first label when no priority match
-    result = SearchResult(
-        content="test",
-        score=0.5,
-        chunk_id="c4",
-        document_id="d4",
-        labels=["paragraph", "text"],
-    )
-    assert result._get_primary_label() == "paragraph"
-
-    # Returns None for empty labels
-    result = SearchResult(
-        content="test",
-        score=0.5,
-        chunk_id="c5",
-        document_id="d5",
-        labels=[],
-    )
-    assert result._get_primary_label() is None
-
-
 # Image queries (bytes / PIL.Image)
 
 
+def _png_bytes_query() -> bytes:
+    return b"\x89PNG\r\n\x1a\n"
+
+
+def _pil_image_query():
+    from PIL import Image as PILImageModule
+
+    return PILImageModule.new("RGB", (8, 8), "red")
+
+
 @pytest.mark.asyncio
-async def test_search_with_bytes_query_uses_multimodal_embedder(
-    temp_db_path, monkeypatch
+@pytest.mark.parametrize(
+    "make_query",
+    [_png_bytes_query, _pil_image_query],
+    ids=["bytes", "pil"],
+)
+async def test_search_with_image_query_uses_multimodal_embedder(
+    temp_db_path, monkeypatch, make_query
 ):
-    """``client.search(bytes)`` embeds via ``embed_image`` and dispatches
+    """``client.search(image)`` embeds via ``embed_image`` and dispatches
     to vector-only chunk search (skipping FTS and reranker)."""
     from haiku.rag.embeddings import EmbedderWrapper
     from haiku.rag.store.models.chunk import Chunk
 
-    image_calls: list[bytes] = []
+    query = make_query()
+    image_calls: list = []
 
     class StubMultimodal(EmbedderWrapper):
         supports_images = True
@@ -383,12 +346,12 @@ async def test_search_with_bytes_query_uses_multimodal_embedder(
 
     async with HaikuRAG(temp_db_path, create=True) as rag:
         rag.chunk_repository.search = fake_chunk_search  # type: ignore[method-assign]
-        results = await rag.search(b"\x89PNG\r\n\x1a\n", limit=3, include_images=False)
+        results = await rag.search(query, limit=3, include_images=False)
 
     assert len(results) == 1
     assert results[0].score == 0.91
-    # The bytes were sent through the image embedder once.
-    assert image_calls == [b"\x89PNG\r\n\x1a\n"]
+    # The image was passed through to the image embedder untouched.
+    assert image_calls == [query]
     # The chunk repo received a pre-computed vector and an empty text query.
     assert received_kwargs["query_vector"] == [0.5, 0.5, 0.5, 0.5]
     assert received_kwargs["query"] == ""
@@ -493,42 +456,6 @@ async def test_search_attaches_picture_bytes_for_multimodal_reranker(
         assert reranked_picture._picture_data is None
 
 
-@pytest.mark.asyncio
-async def test_search_with_pil_image_works_like_bytes(temp_db_path, monkeypatch):
-    from PIL import Image as PILImageModule
-
-    from haiku.rag.embeddings import EmbedderWrapper
-    from haiku.rag.store.models.chunk import Chunk
-
-    seen_types: list[type] = []
-
-    class StubMultimodal(EmbedderWrapper):
-        supports_images = True
-
-        def __init__(self):
-            super().__init__(embedder=None, vector_dim=4)
-
-        async def embed_image(self, image):
-            seen_types.append(type(image))
-            return [0.1] * 4
-
-    monkeypatch.setattr(
-        "haiku.rag.store.engine.get_embedder",
-        lambda *a, **kw: StubMultimodal(),
-    )
-
-    async def fake_chunk_search(**kwargs):
-        return [(Chunk(content="x", metadata={}), 1.0)]
-
-    async with HaikuRAG(temp_db_path, create=True) as rag:
-        rag.chunk_repository.search = fake_chunk_search  # type: ignore[method-assign]
-        img = PILImageModule.new("RGB", (8, 8), "red")
-        results = await rag.search(img, include_images=False)
-
-    assert len(results) == 1
-    assert seen_types == [PILImageModule.Image]
-
-
 @pytest.mark.asyncio
 async def test_search_with_bytes_query_raises_for_text_only_embedder(
     temp_db_path,
@@ -553,20 +480,26 @@ def _picture_only_result(
     )
 
 
-def test_dedup_keeps_higher_scoring_picture_chunk():
+@pytest.mark.parametrize(
+    "first_score,second_score",
+    # Whichever duplicate scores higher wins, regardless of arrival order.
+    [(0.7, 0.9), (0.9, 0.7)],
+    ids=["later_wins", "earlier_wins"],
+)
+def test_dedup_keeps_higher_scoring_picture_chunk(first_score, second_score):
     """Two results referencing the same single picture self_ref collapse
     to the one with the higher score."""
     from haiku.rag.client.search import _dedup_picture_chunks
 
-    text_chunk = _picture_only_result("#/pictures/0", score=0.7)
-    pic_chunk = _picture_only_result("#/pictures/0", score=0.9)
+    text_chunk = _picture_only_result("#/pictures/0", score=first_score)
+    pic_chunk = _picture_only_result("#/pictures/0", score=second_score)
     other = _picture_only_result("#/pictures/1", score=0.6)
 
     deduped = _dedup_picture_chunks([text_chunk, pic_chunk, other])
 
     assert len(deduped) == 2
     chosen = next(r for r in deduped if r.doc_item_refs == ["#/pictures/0"])
-    assert chosen.score == 0.9
+    assert chosen.score == max(first_score, second_score)
     assert any(r.doc_item_refs == ["#/pictures/1"] for r in deduped)
 
 
@@ -598,3 +531,56 @@ def test_dedup_does_not_collapse_across_documents():
 
     deduped = _dedup_picture_chunks([a, b])
     assert len(deduped) == 2
+
+
+# visualize_chunk short-circuits
+
+
+@pytest.mark.asyncio
+async def test_expand_context_passes_through_results_without_document(temp_db_path):
+    """A result with no document_id can't be expanded; it is returned as-is."""
+    from haiku.rag.client.search import expand_context
+
+    async with HaikuRAG(temp_db_path, create=True) as rag:
+        orphan = SearchResult(content="loose text", score=0.5, chunk_id="c1")
+        assert await expand_context(rag, [orphan]) == [orphan]
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_returns_empty_for_no_chunks(temp_db_path):
+    async with HaikuRAG(temp_db_path, create=True) as rag:
+        assert await rag.visualize_chunk([]) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_returns_empty_without_document_id(temp_db_path):
+    from haiku.rag.store.models.chunk import Chunk
+
+    async with HaikuRAG(temp_db_path, create=True) as rag:
+        assert await rag.visualize_chunk(Chunk(content="x", metadata={})) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_returns_empty_when_document_missing(temp_db_path):
+    from haiku.rag.store.models.chunk import Chunk
+
+    async with HaikuRAG(temp_db_path, create=True) as rag:
+        chunk = Chunk(content="x", document_id="does-not-exist", metadata={})
+        assert await rag.visualize_chunk(chunk) == []
+
+
+@pytest.mark.asyncio
+async def test_visualize_chunk_returns_empty_when_docling_blob_absent(temp_db_path):
+    """A markdown-ingested document has no docling structure to resolve boxes in."""
+    from haiku.rag.store.models.chunk import Chunk
+    from haiku.rag.store.models.document import Document
+    from haiku.rag.store.repositories.document import DocumentRepository
+
+    async with HaikuRAG(temp_db_path, create=True) as rag:
+        doc = await DocumentRepository(rag.store).create(
+            Document(content="plain body", uri="test://plain")
+        )
+        assert doc.id is not None
+        chunk = Chunk(content="plain body", document_id=doc.id, metadata={})
+
+        assert await rag.visualize_chunk(chunk) == []
diff --git a/tests/test_settings.py b/tests/test_settings.py
index b4e1f478..f30e2756 100644
--- a/tests/test_settings.py
+++ b/tests/test_settings.py
@@ -44,6 +44,31 @@ async def test_settings_save_and_retrieve(temp_db_path):
         Config.processing.chunk_size = original_chunk_size
 
 
+@pytest.mark.asyncio
+async def test_set_haiku_version_recreates_row_from_store_config(temp_db_path):
+    """Recreating a missing settings row stamps the store's own config, not the
+    process-global one."""
+    from haiku.rag.store.engine import Store
+    from haiku.rag.store.repositories.settings import SettingsRepository
+
+    config = AppConfig()
+    config.processing.chunk_size = Config.processing.chunk_size + 512
+
+    async with Store(temp_db_path, config=config, create=True) as store:
+        settings_repo = SettingsRepository(store)
+
+        await store.settings_table.delete("id = 'settings'")
+        assert await settings_repo.get_current_settings() == {}
+        assert await store.get_haiku_version() == "0.0.0"
+
+        await store.set_haiku_version("1.2.3")
+
+        recreated = await settings_repo.get_current_settings()
+        assert recreated["version"] == "1.2.3"
+        assert recreated["processing"]["chunk_size"] == config.processing.chunk_size
+        assert await store.get_haiku_version() == "1.2.3"
+
+
 class TestValidateConfigCompatibility:
     """Tests for validate_config_compatibility method."""
 
@@ -238,3 +263,23 @@ class TestValidateConfigCompatibility:
                 await settings_repo.validate_config_compatibility()
 
             assert "9999" in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_save_current_settings_recreates_a_deleted_row(temp_db_path):
+    from haiku.rag.store.engine import Store
+    from haiku.rag.store.repositories.settings import SettingsRepository
+
+    async with Store(temp_db_path, create=True, skip_validation=True) as store:
+        settings_repo = SettingsRepository(store)
+
+        await store.settings_table.delete("id = 'settings'")
+        assert await settings_repo.get_current_settings() == {}
+
+        await settings_repo.save_current_settings()
+
+        recreated = await settings_repo.get_current_settings()
+        assert (
+            recreated["embeddings"]
+            == store._config.model_dump(mode="json")["embeddings"]
+        )
diff --git a/tests/test_title_generation.py b/tests/test_title_generation.py
index c13f736b..a88802c5 100644
--- a/tests/test_title_generation.py
+++ b/tests/test_title_generation.py
@@ -371,3 +371,40 @@ class TestRebuildTitleOnly:
 
             # Only the second doc should have been processed
             assert len(processed_ids) == 1
+
+
+@pytest.mark.asyncio
+async def test_generate_title_with_llm_returns_model_output(monkeypatch):
+    """The agent's output is stripped and returned."""
+    from pydantic_ai.messages import ModelMessage, ModelResponse, TextPart
+    from pydantic_ai.models.function import AgentInfo, FunctionModel
+
+    from haiku.rag.client.titles import generate_title_with_llm
+    from haiku.rag.config import AppConfig
+
+    def respond(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
+        return ModelResponse(parts=[TextPart("  A Generated Title  ")])
+
+    monkeypatch.setattr(
+        "haiku.rag.utils.get_model", lambda *a, **kw: FunctionModel(respond)
+    )
+
+    assert await generate_title_with_llm(AppConfig(), "body") == "A Generated Title"
+
+
+@pytest.mark.asyncio
+async def test_generate_title_with_llm_returns_none_for_blank_output(monkeypatch):
+    from pydantic_ai.messages import ModelMessage, ModelResponse, TextPart
+    from pydantic_ai.models.function import AgentInfo, FunctionModel
+
+    from haiku.rag.client.titles import generate_title_with_llm
+    from haiku.rag.config import AppConfig
+
+    def respond(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
+        return ModelResponse(parts=[TextPart("   ")])
+
+    monkeypatch.setattr(
+        "haiku.rag.utils.get_model", lambda *a, **kw: FunctionModel(respond)
+    )
+
+    assert await generate_title_with_llm(AppConfig(), "body") is None
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 01809e2b..7616c653 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -139,27 +139,70 @@ Emoji test: 🚀 ✅ 📝"""
     assert "🚀" in result_markdown
 
 
-def test_get_model_ollama():
-    """Test get_model returns OpenAIChatModel for Ollama."""
-    model_config = ModelConfig(provider="ollama", name="llama3")
-    result = get_model(model_config)
-    assert isinstance(result, OpenAIChatModel)
-
-
-def test_get_model_ollama_without_thinking():
-    """Test get_model configures thinking for gpt-oss on Ollama."""
-    model_config = ModelConfig(provider="ollama", name="gpt-oss", enable_thinking=False)
-    result = get_model(model_config)
-    assert isinstance(result, OpenAIChatModel)
-
-
-def test_get_model_ollama_with_settings():
-    """Test get_model applies temperature and max_tokens for Ollama."""
-    model_config = ModelConfig(
-        provider="ollama", name="llama3", temperature=0.5, max_tokens=100
-    )
-    result = get_model(model_config)
+@pytest.mark.parametrize(
+    "kwargs,expected_settings",
+    [
+        ({"provider": "ollama", "name": "llama3"}, None),
+        (
+            {"provider": "ollama", "name": "gpt-oss", "enable_thinking": False},
+            {"openai_reasoning_effort": "low"},
+        ),
+        (
+            {"provider": "ollama", "name": "gpt-oss", "enable_thinking": True},
+            {"openai_reasoning_effort": "high"},
+        ),
+        (
+            {
+                "provider": "ollama",
+                "name": "llama3",
+                "temperature": 0.5,
+                "max_tokens": 100,
+            },
+            {"temperature": 0.5, "max_tokens": 100},
+        ),
+        ({"provider": "openai", "name": "gpt-4o"}, None),
+        (
+            {"provider": "openai", "name": "o1", "enable_thinking": True},
+            {"openai_reasoning_effort": "high"},
+        ),
+        (
+            {"provider": "openai", "name": "o1", "enable_thinking": False},
+            {"openai_reasoning_effort": "low"},
+        ),
+        (
+            {
+                "provider": "openai",
+                "name": "gpt-4o",
+                "enable_thinking": False,
+                "temperature": 0.7,
+                "max_tokens": 500,
+            },
+            # gpt-4o is not a reasoning model, so only the common settings land.
+            {"temperature": 0.7, "max_tokens": 500},
+        ),
+    ],
+    ids=[
+        "ollama",
+        "ollama_thinking_off",
+        "ollama_thinking_on",
+        "ollama_with_settings",
+        "openai",
+        "openai_reasoning_thinking_on",
+        "openai_reasoning_thinking_off",
+        "openai_all_settings",
+    ],
+)
+def test_get_model_openai_chat_settings(kwargs, expected_settings):
+    """Each ollama/openai configuration maps onto the expected model settings."""
+    result = get_model(ModelConfig(**kwargs))
+
     assert isinstance(result, OpenAIChatModel)
+    if expected_settings is None:
+        assert result.settings is None
+        return
+    assert result.settings is not None
+    for key, value in expected_settings.items():
+        assert result.settings.get(key) == value
 
 
 def test_get_model_ollama_appends_v1_to_per_model_base_url():
@@ -183,20 +226,6 @@ def test_get_model_ollama_does_not_double_append_v1():
     assert not url.endswith("/v1/v1")
 
 
-def test_get_model_openai():
-    """Test get_model returns OpenAIChatModel for OpenAI."""
-    model_config = ModelConfig(provider="openai", name="gpt-4o")
-    result = get_model(model_config)
-    assert isinstance(result, OpenAIChatModel)
-
-
-def test_get_model_openai_with_thinking():
-    """Test get_model configures thinking for OpenAI reasoning models."""
-    model_config = ModelConfig(provider="openai", name="o1", enable_thinking=True)
-    result = get_model(model_config)
-    assert isinstance(result, OpenAIChatModel)
-
-
 def test_get_model_openai_non_reasoning_model_ignores_thinking():
     """Test that non-reasoning OpenAI models don't get reasoning_effort setting."""
     model_config = ModelConfig(
@@ -299,17 +328,27 @@ def test_get_model_anthropic():
 
 
 @pytest.mark.skipif(not HAS_ANTHROPIC, reason="Anthropic not installed")
-def test_get_model_anthropic_with_thinking():
+@pytest.mark.parametrize(
+    "enable_thinking,expected_thinking",
+    [
+        (True, {"type": "enabled", "budget_tokens": 4096}),
+        (False, {"type": "disabled"}),
+    ],
+)
+def test_get_model_anthropic_with_thinking(enable_thinking, expected_thinking):
     """Test get_model configures thinking for Anthropic."""
     from pydantic_ai.models.anthropic import AnthropicModel
 
     model_config = ModelConfig(
         provider="anthropic",
         name="claude-3-5-sonnet-20241022",
-        enable_thinking=True,
+        enable_thinking=enable_thinking,
     )
     result = get_model(model_config)
+
     assert isinstance(result, AnthropicModel)
+    assert result.settings is not None
+    assert result.settings.get("anthropic_thinking") == expected_thinking
 
 
 @pytest.mark.skipif(not HAS_GOOGLE, reason="Google not installed")
@@ -345,15 +384,23 @@ def test_get_model_groq():
 
 
 @pytest.mark.skipif(not HAS_GROQ, reason="Groq not installed")
-def test_get_model_groq_with_thinking():
+@pytest.mark.parametrize(
+    "enable_thinking,expected_format", [(True, "parsed"), (False, "hidden")]
+)
+def test_get_model_groq_with_thinking(enable_thinking, expected_format):
     """Test get_model configures thinking format for Groq."""
     from pydantic_ai.models.groq import GroqModel
 
     model_config = ModelConfig(
-        provider="groq", name="llama-3.3-70b-versatile", enable_thinking=False
+        provider="groq",
+        name="llama-3.3-70b-versatile",
+        enable_thinking=enable_thinking,
     )
     result = get_model(model_config)
+
     assert isinstance(result, GroqModel)
+    assert result.settings is not None
+    assert result.settings.get("groq_reasoning_format") == expected_format
 
 
 @pytest.mark.skipif(not HAS_BEDROCK, reason="Bedrock not installed")
@@ -369,17 +416,58 @@ def test_get_model_bedrock():
 
 
 @pytest.mark.skipif(not HAS_BEDROCK, reason="Bedrock not installed")
-def test_get_model_bedrock_with_thinking():
-    """Test get_model configures thinking for Bedrock Claude models."""
+@pytest.mark.parametrize(
+    "name,enable_thinking,expected_fields",
+    [
+        (
+            "anthropic.claude-3-5-sonnet-20241022-v2:0",
+            True,
+            {"thinking": {"type": "enabled", "budget_tokens": 4096}},
+        ),
+        (
+            "anthropic.claude-3-5-sonnet-20241022-v2:0",
+            False,
+            {"thinking": {"type": "disabled"}},
+        ),
+        ("openai.o3-mini-v1:0", True, {"reasoning_effort": "high"}),
+        ("openai.o3-mini-v1:0", False, {"reasoning_effort": "low"}),
+        ("qwen.qwen3-32b-v1:0", True, {"reasoning_config": "high"}),
+        ("qwen.qwen3-32b-v1:0", False, {"reasoning_config": "low"}),
+        # A family with no reasoning mapping leaves the request fields untouched.
+        ("meta.llama3-70b-instruct-v1:0", True, None),
+        ("meta.llama3-70b-instruct-v1:0", False, None),
+    ],
+    ids=[
+        "claude_on",
+        "claude_off",
+        "o_series_on",
+        "o_series_off",
+        "qwen_on",
+        "qwen_off",
+        "unmapped_on",
+        "unmapped_off",
+    ],
+)
+def test_get_model_bedrock_with_thinking(name, enable_thinking, expected_fields):
+    """Each Bedrock model family maps thinking onto its own request field."""
     from pydantic_ai.models.bedrock import BedrockConverseModel
 
     model_config = ModelConfig(
         provider="bedrock",
-        name="anthropic.claude-3-5-sonnet-20241022-v2:0",
-        enable_thinking=True,
+        name=name,
+        enable_thinking=enable_thinking,
     )
     result = get_model(model_config)
+
     assert isinstance(result, BedrockConverseModel)
+    if expected_fields is None:
+        assert result.settings is None
+        return
+    assert result.settings is not None
+    assert (
+        result.settings.get("bedrock_additional_model_requests_fields")
+        == expected_fields
+    )
 
 
 def test_get_model_unknown_provider():
@@ -390,19 +478,6 @@ def test_get_model_unknown_provider():
     assert result == "mistral:mistral-large-latest"
 
 
-def test_get_model_with_all_settings():
-    """Test get_model applies all settings together."""
-    model_config = ModelConfig(
-        provider="openai",
-        name="gpt-4o",
-        enable_thinking=False,
-        temperature=0.7,
-        max_tokens=500,
-    )
-    result = get_model(model_config)
-    assert isinstance(result, OpenAIChatModel)
-
-
 def test_get_package_versions():
     """Test get_package_versions returns expected keys."""
     from haiku.rag.utils import get_package_versions
@@ -526,20 +601,7 @@ def test_format_citations_multiple_pages():
     result = format_citations([citation])
     assert "[1] test://doc" in result
     assert "pp. 1-3" in result
-
-
-def test_format_citations_no_title():
-    from haiku.rag.store.models.citation import Citation
-    from haiku.rag.utils import format_citations
-
-    citation = Citation(
-        document_id="doc1",
-        chunk_id="chunk1",
-        document_uri="test://doc",
-        content="Content",
-    )
-    result = format_citations([citation])
-    assert "[1] test://doc" in result
+    # No title: the URI stands in, and the document id never leaks.
     assert "doc1" not in result
 
 
@@ -758,3 +820,90 @@ def test_parse_model_option():
     for bad in ["just-a-name", ":model", "provider:"]:
         with pytest.raises(ValueError, match="Invalid model format"):
             parse_model_option(bad)
+
+
+def test_cosine_similarity_identical_vectors():
+    from haiku.rag.utils import cosine_similarity
+
+    assert cosine_similarity([1.0, 0.0], [1.0, 0.0]) == pytest.approx(1.0)
+    assert cosine_similarity([1.0, 0.0], [0.0, 1.0]) == pytest.approx(0.0)
+
+
+async def test_format_citations_rich_separates_multiple_citations():
+    from haiku.rag.store.models.citation import Citation
+    from haiku.rag.utils import format_citations_rich
+
+    citations = [
+        Citation(
+            document_id=f"doc{i}",
+            chunk_id=f"chunk{i}",
+            document_uri=f"test://doc{i}",
+            document_title=f"Doc {i}",
+            content=f"Body {i}",
+        )
+        for i in (1, 2)
+    ]
+
+    output = _render_rich(await format_citations_rich(citations))
+
+    assert "[1] Doc 1 (test://doc1)" in output
+    assert "[2] Doc 2 (test://doc2)" in output
+
+
+@pytest.mark.parametrize(
+    "stored,renders",
+    [
+        (None, False),
+        (b"not a real image", False),
+        ("png", True),
+    ],
+    ids=["no_bytes", "undecodable_bytes", "valid_png"],
+)
+async def test_render_picture_handles_stored_bytes(stored, renders):
+    from unittest.mock import AsyncMock
+
+    from haiku.rag.utils import _render_picture
+
+    if stored == "png":
+        from io import BytesIO
+
+        from PIL import Image as PILImage
+
+        buf = BytesIO()
+        PILImage.new("RGB", (4, 4), "red").save(buf, format="PNG")
+        stored = buf.getvalue()
+
+    client = AsyncMock()
+    client.document_item_repository.get_picture_bytes = AsyncMock(return_value=stored)
+
+    result = await _render_picture(client, "doc1", "#/pictures/0")
+
+    if renders:
+        from textual_image.renderable import Image as RichImage
+
+        assert isinstance(result, RichImage)
+    else:
+        assert result is None
+
+
+async def test_render_picture_without_client_returns_none():
+    from haiku.rag.utils import _render_picture
+
+    assert await _render_picture(None, "doc1", "#/pictures/0") is None
+
+
+def test_get_package_versions_reports_missing_docling(monkeypatch):
+    from importlib import metadata as importlib_metadata
+
+    from haiku.rag.utils import get_package_versions
+
+    real_version = importlib_metadata.version
+
+    def fake_version(name):
+        if name == "docling":
+            raise importlib_metadata.PackageNotFoundError(name)
+        return real_version(name)
+
+    monkeypatch.setattr(importlib_metadata, "version", fake_version)
+
+    assert get_package_versions()["docling"] == "not installed"
diff --git a/tests/tools/test_document.py b/tests/tools/test_document.py
index 432dc86b..ab935cf4 100644
--- a/tests/tools/test_document.py
+++ b/tests/tools/test_document.py
@@ -187,6 +187,33 @@ class TestSummarizeDocumentTool:
 
         assert "Document not found" in result
 
+    @pytest.mark.vcr()
+    @pytest.mark.asyncio
+    async def test_summarize_document_returns_model_summary(
+        self, doc_client, doc_config, monkeypatch
+    ):
+        """A resolvable document is summarised and labelled with its title."""
+        from pydantic_ai.messages import ModelMessage, ModelResponse, TextPart
+        from pydantic_ai.models.function import AgentInfo, FunctionModel
+
+        def respond(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
+            return ModelResponse(parts=[TextPart("A concise summary.")])
+
+        monkeypatch.setattr(
+            "haiku.rag.tools.document.get_model",
+            lambda *a, **kw: FunctionModel(respond),
+        )
+
+        docs = await doc_client.list_documents()
+        assert docs and docs[0].uri
+
+        toolset = create_document_toolset(doc_config)
+        summarize_tool = toolset.tools["summarize_document"]
+        result = await summarize_tool.function(make_ctx(doc_client), docs[0].uri)
+
+        assert "A concise summary." in result
+        assert "Summary of" in result
+
 
 @pytest.fixture
 async def doc_client(temp_db_path):
diff --git a/tests/tools/test_search.py b/tests/tools/test_search.py
index 3fedd61c..2cd8499e 100644
--- a/tests/tools/test_search.py
+++ b/tests/tools/test_search.py
@@ -214,3 +214,49 @@ def search_config():
     from haiku.rag.config import Config
 
     return Config
+
+
+class TestBuildBinaryPartsFromResults:
+    """Picture bytes are attached once per (document, self_ref) pair."""
+
+    def test_results_without_image_data_contribute_nothing(self):
+        from haiku.rag.tools.search import build_binary_parts_from_results
+
+        results = [
+            SearchResult(content="text only", score=0.5, chunk_id="c1", image_data=None)
+        ]
+
+        assert build_binary_parts_from_results(results) == []
+
+    def test_duplicate_document_and_ref_is_attached_once(self):
+        import base64
+        from io import BytesIO
+
+        from PIL import Image as PILImage
+
+        from haiku.rag.tools.search import build_binary_parts_from_results
+
+        buf = BytesIO()
+        PILImage.new("RGB", (4, 4), "red").save(buf, format="PNG")
+        png = base64.b64encode(buf.getvalue()).decode()
+        shared = {"#/pictures/0": png}
+        results = [
+            SearchResult(
+                content="a",
+                score=0.9,
+                chunk_id="c1",
+                document_id="doc-1",
+                image_data=shared,
+            ),
+            SearchResult(
+                content="b",
+                score=0.8,
+                chunk_id="c2",
+                document_id="doc-1",
+                image_data=shared,
+            ),
+        ]
+
+        parts = build_binary_parts_from_results(results)
+
+        assert len(parts) == 1