Remove unecessary tests, add no coverage pragmas where appropriate

haiku_rag_slim/haiku/rag/embeddings/lm_studio.py

@@ -5,7 +5,7 @@ from openai import AsyncOpenAI
 from haiku.rag.embeddings.base import EmbedderBase
 
 
-class Embedder(EmbedderBase):
+class Embedder(EmbedderBase):  # pragma: no cover
     @overload
     async def embed(self, text: str) -> list[float]: ...
 

haiku_rag_slim/haiku/rag/embeddings/vllm.py

@@ -5,7 +5,7 @@ from openai import AsyncOpenAI
 from haiku.rag.embeddings.base import EmbedderBase
 
 
-class Embedder(EmbedderBase):
+class Embedder(EmbedderBase):  # pragma: no cover
     @overload
     async def embed(self, text: str) -> list[float]: ...
 

haiku_rag_slim/haiku/rag/graph/agui/server.py

@@ -151,7 +151,9 @@ def format_sse_event(event: AGUIEvent) -> str:
     return f"data: {event_json}\n\n"
 
 
-def create_agui_server(config: "AppConfig", db_path: Path | None = None) -> Starlette:
+def create_agui_server(  # pragma: no cover
+    config: "AppConfig", db_path: Path | None = None
+) -> Starlette:
     """Create AG-UI server with both research and deep ask endpoints.
 
     Args:

haiku_rag_slim/haiku/rag/inspector/app.py

@@ -24,7 +24,7 @@ except ImportError:
     App = object  # type: ignore
 
 
-class InspectorApp(App):  # type: ignore[misc]
+class InspectorApp(App):  # type: ignore[misc]  # pragma: no cover
     """Textual TUI for inspecting LanceDB data."""
 
     TITLE = "haiku.rag DB Inspector"
@@ -193,7 +193,7 @@ class InspectorApp(App):  # type: ignore[misc]
         await self.push_screen(VisualGroundingModal(chunk=chunk, client=self.client))
 
 
-def run_inspector(db_path: Path | None = None) -> None:
+def run_inspector(db_path: Path | None = None) -> None:  # pragma: no cover
     """Run the inspector TUI.
 
     Args:

haiku_rag_slim/haiku/rag/inspector/widgets/chunk_list.py

@@ -8,7 +8,7 @@ from haiku.rag.client import HaikuRAG
 from haiku.rag.store.models import Chunk
 
 
-class ChunkList(VerticalScroll):
+class ChunkList(VerticalScroll):  # pragma: no cover
     """Widget for displaying and browsing chunks."""
 
     can_focus = False

haiku_rag_slim/haiku/rag/inspector/widgets/detail_view.py

@@ -16,7 +16,7 @@ class ProvenanceData(Protocol):
     doc_item_refs: list[str]
 
 
-class DetailView(VerticalScroll):
+class DetailView(VerticalScroll):  # pragma: no cover
     """Widget for displaying detailed content of documents or chunks."""
 
     can_focus = True

haiku_rag_slim/haiku/rag/inspector/widgets/document_list.py

@@ -8,7 +8,7 @@ from haiku.rag.client import HaikuRAG
 from haiku.rag.store.models import Document
 
 
-class DocumentList(VerticalScroll):
+class DocumentList(VerticalScroll):  # pragma: no cover
     """Widget for displaying and browsing documents."""
 
     can_focus = False

haiku_rag_slim/haiku/rag/inspector/widgets/search_modal.py

@@ -11,7 +11,7 @@ from haiku.rag.inspector.widgets.detail_view import DetailView
 from haiku.rag.store.models import Chunk, SearchResult
 
 
-class SearchModal(Screen):
+class SearchModal(Screen):  # pragma: no cover
     """Screen for searching chunks."""
 
     BINDINGS = [

haiku_rag_slim/haiku/rag/inspector/widgets/visual_modal.py

@@ -15,7 +15,7 @@ if TYPE_CHECKING:
     from haiku.rag.store.models import Chunk
 
 
-class VisualGroundingModal(Screen):
+class VisualGroundingModal(Screen):  # pragma: no cover
     """Modal screen for displaying visual grounding with bounding boxes."""
 
     BINDINGS = [

haiku_rag_slim/haiku/rag/reranking/cohere.py

@@ -9,7 +9,7 @@ except ImportError as e:
     ) from e
 
 
-class CohereReranker(RerankerBase):
+class CohereReranker(RerankerBase):  # pragma: no cover
     def __init__(self):
         # Cohere SDK reads CO_API_KEY from environment by default
         self._client = cohere.ClientV2()

haiku_rag_slim/haiku/rag/reranking/vllm.py

@@ -5,7 +5,7 @@ from haiku.rag.reranking.base import RerankerBase
 from haiku.rag.store.models.chunk import Chunk
 
 
-class VLLMReranker(RerankerBase):
+class VLLMReranker(RerankerBase):  # pragma: no cover
     def __init__(self, model: str):
         self._model = model
         self._base_url = Config.providers.vllm.rerank_base_url

haiku_rag_slim/haiku/rag/reranking/zeroentropy.py

@@ -4,7 +4,7 @@ from haiku.rag.reranking.base import RerankerBase
 from haiku.rag.store.models.chunk import Chunk
 
 
-class ZeroEntropyReranker(RerankerBase):
+class ZeroEntropyReranker(RerankerBase):  # pragma: no cover
     """Zero Entropy reranker implementation using the zerank-1 model."""
 
     def __init__(self, model: str = "zerank-1"):

haiku_rag_slim/haiku/rag/store/upgrades/v0_10_1.py

@@ -7,7 +7,7 @@ from haiku.rag.store.engine import Store
 from haiku.rag.store.upgrades import Upgrade
 
 
-def _apply_add_document_title(store: Store) -> None:
+def _apply_add_document_title(store: Store) -> None:  # pragma: no cover
     """Add a nullable 'title' column to the documents table."""
 
     # Read existing rows using Arrow for schema-agnostic access

haiku_rag_slim/haiku/rag/store/upgrades/v0_19_6.py

@@ -7,7 +7,7 @@ from haiku.rag.store.upgrades import Upgrade
 logger = logging.getLogger(__name__)
 
 
-def _apply_embeddings_model_config(store: Store) -> None:
+def _apply_embeddings_model_config(store: Store) -> None:  # pragma: no cover
     """Migrate embeddings config from flat to nested EmbeddingModelConfig structure."""
     results = list(
         store.settings_table.search()

haiku_rag_slim/haiku/rag/store/upgrades/v0_20_0.py

@@ -7,7 +7,7 @@ from haiku.rag.store.engine import Store
 from haiku.rag.store.upgrades import Upgrade
 
 
-def _apply_add_docling_document_columns(store: Store) -> None:
+def _apply_add_docling_document_columns(store: Store) -> None:  # pragma: no cover
     """Add 'docling_document_json' and 'docling_version' columns to documents table."""
 
     # Read existing rows using Arrow for schema-agnostic access

haiku_rag_slim/haiku/rag/store/upgrades/v0_9_3.py

@@ -7,7 +7,7 @@ from haiku.rag.store.engine import Store
 from haiku.rag.store.upgrades import Upgrade
 
 
-def _infer_vector_dim(store: Store) -> int:
+def _infer_vector_dim(store: Store) -> int:  # pragma: no cover
     """Infer vector dimension from existing data; fallback to embedder config."""
     try:
         arrow = store.chunks_table.search().limit(1).to_arrow()
@@ -22,7 +22,7 @@ def _infer_vector_dim(store: Store) -> int:
     return getattr(store.embedder, "_vector_dim", 1024)
 
 
-def _apply_chunk_order(store: Store) -> None:
+def _apply_chunk_order(store: Store) -> None:  # pragma: no cover
     """Add integer 'order' column to chunks and backfill from metadata."""
 
     vector_dim = _infer_vector_dim(store)
@@ -95,7 +95,7 @@ upgrade_order = Upgrade(
 )
 
 
-def _apply_fts_phrase_support(store: Store) -> None:
+def _apply_fts_phrase_support(store: Store) -> None:  # pragma: no cover
     """Recreate FTS index with phrase query support and no stop-word removal."""
     try:
         store.chunks_table.create_fts_index(

tests/test_document.py

@@ -1,102 +1,11 @@
 import pytest
 from datasets import Dataset
 
-from haiku.rag.client import HaikuRAG
-from haiku.rag.config import Config
 from haiku.rag.store.engine import Store
 from haiku.rag.store.models.document import Document
 from haiku.rag.store.repositories.document import DocumentRepository
 
 
-@pytest.mark.asyncio
-async def test_create_document_with_chunks(qa_corpus: Dataset, temp_db_path):
-    """Test creating a document with chunks from the qa_corpus using repository."""
-    # Create client
-    client = HaikuRAG(db_path=temp_db_path, config=Config, create=True)
-
-    # Get the first document from the corpus
-    first_doc = qa_corpus[0]
-    document_text = first_doc["document_extracted"]
-
-    # Create the document with chunks in the database
-    created_document = await client.create_document(
-        content=document_text,
-        metadata={"source": "qa_corpus", "topic": first_doc.get("document_topic", "")},
-    )
-
-    # Verify the document was created
-    assert created_document.id is not None
-    assert created_document.content == document_text
-
-    # Check that chunks were created using repository
-    chunks = await client.chunk_repository.get_by_document_id(created_document.id)
-
-    assert len(chunks) > 0
-
-    # Verify chunk order is set correctly
-    for i, chunk in enumerate(chunks):
-        assert chunk.order == i
-
-    client.close()
-
-
-@pytest.mark.asyncio
-async def test_document_repository_crud(qa_corpus: Dataset, temp_db_path):
-    """Test CRUD operations in DocumentRepository."""
-    # Create a store and repository
-    store = Store(temp_db_path, create=True)
-    doc_repo = DocumentRepository(store)
-
-    # Get the first document from the corpus
-    first_doc = qa_corpus[0]
-    document_text = first_doc["document_extracted"]
-
-    # Create a document with URI
-    test_uri = "file:///path/to/test.txt"
-    document = Document(
-        content=document_text, uri=test_uri, metadata={"source": "test"}
-    )
-    created_document = await doc_repo.create(document)
-
-    # Test get_by_id
-    assert created_document.id is not None
-    retrieved_document = await doc_repo.get_by_id(created_document.id)
-    assert retrieved_document is not None
-    assert retrieved_document.content == document_text
-    assert retrieved_document.uri == test_uri
-
-    # Test get_by_uri
-    retrieved_by_uri = await doc_repo.get_by_uri(test_uri)
-    assert retrieved_by_uri is not None
-    assert retrieved_by_uri.id == created_document.id
-    assert retrieved_by_uri.content == document_text
-    assert retrieved_by_uri.uri == test_uri
-
-    # Test get_by_uri with non-existent URI
-    non_existent = await doc_repo.get_by_uri("file:///non/existent.txt")
-    assert non_existent is None
-
-    # Test update (should regenerate chunks)
-    retrieved_document.content = "Updated content for testing"
-    updated_document = await doc_repo.update(retrieved_document)
-    assert updated_document.content == "Updated content for testing"
-
-    # Test list_all
-    all_documents = await doc_repo.list_all()
-    assert len(all_documents) == 1
-    assert all_documents[0].id == created_document.id
-
-    # Test delete
-    deleted = await doc_repo.delete(created_document.id)
-    assert deleted is True
-
-    # Verify document is gone
-    retrieved_document = await doc_repo.get_by_id(created_document.id)
-    assert retrieved_document is None
-
-    store.close()
-
-
 @pytest.mark.asyncio
 async def test_document_list_with_filter(qa_corpus: Dataset, temp_db_path):
     """Test listing documents with filter clause."""