Merge pull request #243 from ggozad/chore/ty

replace pyright with ty type checker

.github/workflows/test.yml

@@ -23,7 +23,7 @@ jobs:
       - name: Lint
         run: uv run ruff check
       - name: Type check
-        run: uv run pyright
+        run: uv run ty check
 
   lint-frontend:
     runs-on: ubuntu-latest

.pre-commit-config.yaml

@@ -16,10 +16,14 @@ repos:
       # Run the formatter.
       - id: ruff-format
 
-  - repo: https://github.com/RobertCraigie/pyright-python
-    rev: v1.1.407
+  - repo: local
     hooks:
-      - id: pyright
+      - id: ty
+        name: ty check
+        entry: uvx ty check
+        language: system
+        types: [python]
+        pass_filenames: false
 
   - repo: local
     hooks:

CHANGELOG.md

@@ -1,6 +1,20 @@
 # Changelog
 ## [Unreleased]
 
+### Changed
+
+- **Type Checker**: Replaced pyright with [ty](https://github.com/astral-sh/ty), Astral's extremely fast Python type checker
+  - Added explicit `Agent[Deps, Output]` type annotations to all pydantic-ai agents for better type inference
+  - Removed ~24 unnecessary `# type: ignore` comments that ty correctly infers
+- **Dependencies**: Updated to latest versions
+  - `pydantic-ai-slim`: 1.39.0 → 1.44.0
+  - `docling`: 2.67.0 → 2.68.0
+  - `pathspec`: 0.12.1 → 1.0.3
+  - `textual`: 7.0.0 → 7.3.0
+  - `datasets`: 4.4.2 → 4.5.0
+  - `ruff`: 0.14.11 → 0.14.13
+  - `opencv-python-headless`: 4.12.0.88 → 4.13.0.90
+
 ## [0.26.6] - 2026-01-19
 
 ### Changed

app/backend/main.py

@@ -226,7 +226,7 @@ app = Starlette(
     ],
     middleware=[
         Middleware(
-            CORSMiddleware,
+            CORSMiddleware,  # type: ignore[invalid-argument-type]
             allow_origins=["http://localhost:3000", "http://frontend:3000"],
             allow_credentials=True,
             allow_methods=["*"],

evaluations/evaluations/datasets/hotpotqa.py

@@ -1,7 +1,7 @@
 from collections.abc import Mapping
 from typing import Any, cast
 
-from datasets import Dataset, DatasetDict, load_dataset
+from datasets import Dataset, load_dataset
 from pydantic_evals import Case
 
 from evaluations.config import DatasetSpec, DocumentPayload, RetrievalSample
@@ -9,8 +9,8 @@ from evaluations.evaluators import MAPEvaluator
 
 
 def load_hotpotqa_validation() -> Dataset:
-    dataset_dict = cast(DatasetDict, load_dataset("hotpotqa/hotpot_qa", "distractor"))
-    return cast(Dataset, dataset_dict["validation"])
+    dataset_dict = load_dataset("hotpotqa/hotpot_qa", "distractor")
+    return dataset_dict["validation"]
 
 
 def extract_unique_documents(dataset: Dataset) -> list[dict[str, Any]]:

evaluations/evaluations/datasets/repliqa.py

@@ -1,7 +1,7 @@
 from collections.abc import Mapping
-from typing import Any, cast
+from typing import Any
 
-from datasets import Dataset, DatasetDict, load_dataset
+from datasets import Dataset, load_dataset
 from pydantic_evals import Case
 
 from evaluations.config import DatasetSpec, DocumentPayload, RetrievalSample
@@ -9,8 +9,8 @@ from evaluations.evaluators import MRREvaluator
 
 
 def load_repliqa_corpus() -> Dataset:
-    dataset_dict = cast(DatasetDict, load_dataset("ServiceNow/repliqa"))
-    dataset = cast(Dataset, dataset_dict["repliqa_3"])
+    dataset_dict = load_dataset("ServiceNow/repliqa")
+    dataset = dataset_dict["repliqa_3"]
     return dataset.filter(lambda doc: doc["document_topic"] == "News Stories")
 
 

evaluations/evaluations/datasets/wix.py

@@ -1,8 +1,8 @@
 import json
 from collections.abc import Iterable, Mapping
-from typing import Any, cast
+from typing import Any
 
-from datasets import Dataset, DatasetDict, load_dataset
+from datasets import Dataset, load_dataset
 from pydantic_evals import Case
 
 from evaluations.config import DatasetSpec, DocumentPayload, RetrievalSample
@@ -10,8 +10,8 @@ from evaluations.evaluators import MAPEvaluator
 
 
 def load_wix_corpus() -> Dataset:
-    dataset_dict = cast(DatasetDict, load_dataset("Wix/WixQA", "wix_kb_corpus"))
-    return cast(Dataset, dataset_dict["train"])
+    dataset_dict = load_dataset("Wix/WixQA", "wix_kb_corpus")
+    return dataset_dict["train"]
 
 
 def map_wix_document(doc: Mapping[str, Any]) -> DocumentPayload:
@@ -35,8 +35,8 @@ def map_wix_document(doc: Mapping[str, Any]) -> DocumentPayload:
 
 
 def load_wix_qa() -> Dataset:
-    dataset_dict = cast(DatasetDict, load_dataset("Wix/WixQA", "wixqa_expertwritten"))
-    return cast(Dataset, dataset_dict["train"])
+    dataset_dict = load_dataset("Wix/WixQA", "wixqa_expertwritten")
+    return dataset_dict["train"]
 
 
 def map_wix_retrieval(doc: Mapping[str, Any]) -> RetrievalSample | None:

evaluations/evaluations/evaluators/judge.py

@@ -40,7 +40,7 @@ class LLMJudge:
         model_obj = get_model(model_config, config)
 
         # Create Pydantic AI agent
-        self._agent = Agent(
+        self._agent: Agent[None, LLMJudgeResponseSchema] = Agent(
             model=model_obj,
             output_type=LLMJudgeResponseSchema,
             system_prompt=ANSWER_EQUIVALENCE_RUBRIC,

evaluations/pyproject.toml

@@ -9,8 +9,8 @@ requires-python = ">=3.12"
 
 dependencies = [
     "haiku.rag-slim",
-    "pydantic-ai-slim[evals,logfire]>=1.39.0",
-    "datasets>=4.4.2",
+    "pydantic-ai-slim[evals,logfire]>=1.44.0",
+    "datasets>=4.5.0",
     "typer>=0.19.2,<0.20.0",
     "python-dotenv>=1.2.1",
 ]

haiku_rag_slim/haiku/rag/agents/qa/agent.py

@@ -32,7 +32,7 @@ class QuestionAnswerAgent:
         self._client = client
         model_obj = get_model(model_config, config)
 
-        self._agent = Agent(
+        self._agent: Agent[Dependencies, RawSearchAnswer] = Agent(
             model=model_obj,
             deps_type=Dependencies,
             output_type=ToolOutput(RawSearchAnswer, max_retries=3),
@@ -75,5 +75,6 @@ class QuestionAnswerAgent:
         """
         deps = Dependencies(client=self._client, search_filter=filter)
         result = await self._agent.run(question, deps=deps)
-        citations = resolve_citations(result.output.cited_chunks, deps.search_results)
-        return result.output.answer, citations
+        output = result.output
+        citations = resolve_citations(output.cited_chunks, deps.search_results)
+        return output.answer, citations

haiku_rag_slim/haiku/rag/agents/research/graph.py

@@ -105,7 +105,7 @@ async def _plan_step_logic(
         else plan_prompt
     )
 
-    plan_agent = Agent(
+    plan_agent: Agent[ResearchDependencies, ResearchPlan] = Agent(
         model=get_model(model_config, config),
         output_type=ResearchPlan,
         instructions=effective_plan_prompt,
@@ -151,7 +151,8 @@ async def _plan_step_logic(
 
     agent_deps = ResearchDependencies(client=deps.client, context=state.context)
     plan_result = await plan_agent.run(prompt, deps=agent_deps)
-    state.context.sub_questions = list(plan_result.output.sub_questions)
+    output = plan_result.output
+    state.context.sub_questions = list(output.sub_questions)
 
 
 async def _search_one_step_logic(
@@ -168,7 +169,7 @@ async def _search_one_step_logic(
         deps.semaphore = asyncio.Semaphore(state.max_concurrency)
 
     async with deps.semaphore:
-        agent = Agent(
+        agent: Agent[ResearchDependencies, RawSearchAnswer] = Agent(
             model=get_model(model_config, config),
             output_type=ToolOutput(RawSearchAnswer, max_retries=3),
             instructions=search_prompt,
@@ -289,7 +290,7 @@ def build_research_graph(
         state = ctx.state
         deps = ctx.deps
 
-        agent = Agent(
+        agent: Agent[ResearchDependencies, EvaluationResult] = Agent(
             model=get_model(model_config, config),
             output_type=EvaluationResult,
             instructions=decision_prompt,
@@ -350,7 +351,7 @@ def build_research_graph(
         state = ctx.state
         deps = ctx.deps
 
-        agent = Agent(
+        agent: Agent[ResearchDependencies, ResearchReport] = Agent(
             model=get_model(model_config, config),
             output_type=ResearchReport,
             instructions=synthesis_prompt,
@@ -488,7 +489,7 @@ def build_conversational_graph(
         state = ctx.state
         deps = ctx.deps
 
-        agent = Agent(
+        agent: Agent[ResearchDependencies, ConversationalAnswer] = Agent(
             model=get_model(config.research.model, config),
             output_type=ConversationalAnswer,
             instructions=conversational_prompt,

haiku_rag_slim/haiku/rag/app.py

@@ -494,7 +494,7 @@ class HaikuRAGApp:
 
             # Confidence (from last evaluation)
             if state.last_eval:
-                conf = state.last_eval.confidence_score  # type: ignore[attr-defined]
+                conf = state.last_eval.confidence_score
                 self.console.print(f"[bold cyan]Confidence:[/bold cyan] {conf:.1%}")
                 self.console.print()
 

haiku_rag_slim/haiku/rag/chat/app.py

@@ -51,7 +51,7 @@ except ImportError:
     App = object  # type: ignore
 
 
-class ChatApp(App):  # type: ignore[misc]
+class ChatApp(App):
     """Textual TUI for conversational RAG."""
 
     TITLE = "haiku.rag Chat"

haiku_rag_slim/haiku/rag/inspector/app.py

@@ -26,7 +26,7 @@ except ImportError:
     App = object  # type: ignore
 
 
-class InspectorApp(App):  # type: ignore[misc]  # pragma: no cover
+class InspectorApp(App):  # pragma: no cover
     """Textual TUI for inspecting LanceDB data."""
 
     TITLE = "haiku.rag DB Inspector"

haiku_rag_slim/haiku/rag/monitor.py

@@ -4,7 +4,6 @@ from pathlib import Path
 from typing import TYPE_CHECKING
 
 import pathspec
-from pathspec.patterns.gitwildmatch import GitWildMatchPattern
 from watchfiles import Change, DefaultFilter, awatch
 
 from haiku.rag.client import HaikuRAG
@@ -37,12 +36,12 @@ class FileFilter(DefaultFilter):
 
         self.extensions = tuple(supported_extensions)
         self.ignore_spec = (
-            pathspec.PathSpec.from_lines(GitWildMatchPattern, ignore_patterns)
+            pathspec.PathSpec.from_lines("gitwildmatch", ignore_patterns)
             if ignore_patterns
             else None
         )
         self.include_spec = (
-            pathspec.PathSpec.from_lines(GitWildMatchPattern, include_patterns)
+            pathspec.PathSpec.from_lines("gitwildmatch", include_patterns)
             if include_patterns
             else None
         )

haiku_rag_slim/haiku/rag/store/engine.py

@@ -258,7 +258,7 @@ class Store:
         }
 
         # Documents table stats
-        doc_stats: dict = self.documents_table.stats()  # type: ignore[assignment]
+        doc_stats: dict = self.documents_table.stats()
         stats_dict["documents"] = {
             "exists": True,
             "num_rows": doc_stats.get("num_rows", 0),
@@ -266,7 +266,7 @@ class Store:
         }
 
         # Chunks table stats
-        chunk_stats: dict = self.chunks_table.stats()  # type: ignore[assignment]
+        chunk_stats: dict = self.chunks_table.stats()
         stats_dict["chunks"] = {
             "exists": True,
             "num_rows": chunk_stats.get("num_rows", 0),

haiku_rag_slim/haiku/rag/utils.py

@@ -177,6 +177,10 @@ def get_model(
         return OpenAIChatModel(model_name=model, settings=openai_settings)
 
     elif provider == "anthropic":
+        from anthropic.types.beta import (
+            BetaThinkingConfigDisabledParam,
+            BetaThinkingConfigEnabledParam,
+        )
         from pydantic_ai.models.anthropic import AnthropicModel, AnthropicModelSettings
 
         anthropic_settings: Any = None
@@ -184,12 +188,19 @@ def get_model(
         # Apply thinking control
         if model_config.enable_thinking is not None:
             if model_config.enable_thinking:
+                thinking_config: BetaThinkingConfigEnabledParam = {
+                    "type": "enabled",
+                    "budget_tokens": 4096,
+                }
                 anthropic_settings = AnthropicModelSettings(
-                    anthropic_thinking={"type": "enabled", "budget_tokens": 4096}
+                    anthropic_thinking=thinking_config
                 )
             else:
+                thinking_disabled: BetaThinkingConfigDisabledParam = {
+                    "type": "disabled"
+                }
                 anthropic_settings = AnthropicModelSettings(
-                    anthropic_thinking={"type": "disabled"}
+                    anthropic_thinking=thinking_disabled
                 )
 
         anthropic_settings = apply_common_settings(

haiku_rag_slim/pyproject.toml

@@ -25,9 +25,9 @@ dependencies = [
     "docling-core==2.59.0",
     "httpx>=0.28.1",
     "lancedb==0.26.1",
-    "pathspec>=0.12.1",
+    "pathspec>=1.0.3",
     "pydantic>=2.12.5",
-    "pydantic-ai-slim[openai,fastmcp,logfire,ag-ui]>=1.39.0",
+    "pydantic-ai-slim[openai,fastmcp,logfire,ag-ui]>=1.44.0",
     "python-dotenv>=1.2.1",
     "pyyaml>=6.0.3",
     "rich>=14.2.0",
@@ -37,7 +37,7 @@ dependencies = [
 
 [project.optional-dependencies]
 # Document processing
-docling = ["docling==2.67.0", "opencv-python-headless>=4.12.0.88"]
+docling = ["docling==2.68.0", "opencv-python-headless>=4.13.0.90"]
 # Embedding providers
 voyageai = ["voyageai>=0.3.7"]
 # Rerankers
@@ -45,7 +45,7 @@ mxbai = ["mxbai-rerank>=0.1.6"]
 cohere = ["cohere>=5.20.1"]
 zeroentropy = ["zeroentropy>=0.1.0a7"]
 # TUI (chat and inspect commands)
-tui = ["textual>=7.0.0", "textual-image>=0.8.5"]
+tui = ["textual>=7.3.0", "textual-image>=0.8.5"]
 # Model providers (delegated to pydantic-ai-slim)
 anthropic = ["pydantic-ai-slim[anthropic]"]
 groq = ["pydantic-ai-slim[groq]"]

pyproject.toml

@@ -67,7 +67,7 @@ members = ["haiku_rag_slim", "evaluations"]
 [dependency-groups]
 dev = [
     "haiku.rag-evals",
-    "datasets>=4.4.2",
+    "datasets>=4.5.0",
     "mkdocs>=1.6.1",
     "mkdocs-material>=9.7.1",
     "pre-commit>=4.5.1",
@@ -75,12 +75,12 @@ dev = [
     "pydantic-ai-slim[bedrock]",
     "pydantic-ai-slim[google]",
     "pydantic-ai-slim[groq]",
-    "pyright>=1.1.408",
+    "ty>=0.0.12",
     "pytest>=9.0.2",
     "pytest-asyncio>=1.3.0",
     "pytest-cov>=7.0.0",
     "pytest-recording>=0.13.4",
-    "ruff>=0.14.11",
+    "ruff>=0.14.13",
 ]
 
 [tool.ruff]
@@ -110,10 +110,12 @@ indent-style = "space"
 skip-magic-trailing-comma = false
 line-ending = "auto"
 
-[tool.pyright]
-venvPath = "."
-venv = ".venv"
-pythonVersion = "3.12"
+[tool.ty.src]
+exclude = ["examples/**"]
+
+[tool.ty.environment]
+python-version = "3.12"
+python = ".venv"
 
 [tool.pytest.ini_options]
 asyncio_default_fixture_loop_scope = "session"

tests/agents/chat/test_chat_agent.py

@@ -81,9 +81,10 @@ def test_chat_agent_has_dynamic_system_prompt():
     agent = create_chat_agent(Config)
     # The agent should have at least one system prompt function registered
     # (the add_background_context function)
-    assert len(agent._system_prompt_functions) >= 1
+    system_prompt_functions = getattr(agent, "_system_prompt_functions")
+    assert len(system_prompt_functions) >= 1
     # Verify it's the add_background_context function
-    func_names = [r.function.__name__ for r in agent._system_prompt_functions]
+    func_names = [r.function.__name__ for r in system_prompt_functions]
     assert "add_background_context" in func_names
 
 

tests/conftest.py

@@ -2,7 +2,7 @@ import logging
 import os
 import tempfile
 from pathlib import Path
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, cast
 
 # Prevent tests from loading user's local haiku.rag.yaml by setting env var
 # to a test config file BEFORE any haiku.rag imports.
@@ -26,7 +26,7 @@ from datasets import Dataset, load_dataset, load_from_disk  # noqa: E402
 if TYPE_CHECKING:
     from vcr import VCR
 
-pydantic_ai.models.ALLOW_MODEL_REQUESTS = False
+setattr(pydantic_ai.models, "ALLOW_MODEL_REQUESTS", False)
 logging.getLogger("vcr.cassette").setLevel(logging.WARNING)
 
 
@@ -35,10 +35,9 @@ def qa_corpus() -> Dataset:
     ds_path = Path(__file__).parent / "data" / "dataset"
     ds_path.mkdir(parents=True, exist_ok=True)
     try:
-        ds: Dataset = load_from_disk(ds_path)  # type: ignore
-        return ds
+        return cast(Dataset, load_from_disk(ds_path))
     except FileNotFoundError:
-        ds: Dataset = load_dataset("ServiceNow/repliqa")["repliqa_3"]  # type: ignore
+        ds: Dataset = load_dataset("ServiceNow/repliqa")["repliqa_3"]
         corpus = ds.filter(lambda doc: doc["document_topic"] == "News Stories")
         corpus.save_to_disk(ds_path)
         return corpus

tests/test_client.py

@@ -58,7 +58,7 @@ async def test_client_document_crud(qa_corpus: Dataset, temp_db_path):
 
         # Test update_document
         updated_doc = await client.update_document(
-            document_id=retrieved_doc.id,  # type: ignore[arg-type]
+            document_id=retrieved_doc.id,
             content="Updated content",
         )
         assert updated_doc.content == "Updated content"

tests/test_mcp.py

@@ -30,8 +30,7 @@ async def test_mcp_add_document_from_file():
                 t for t in tools.values() if t.name == "add_document_from_file"
             )
 
-            result = await add_file_tool.fn(file_path="/test.txt")  # type: ignore[attr-defined]
-
+            result = await add_file_tool.fn(file_path="/test.txt")
             assert result == "doc123"
             mock_rag.create_document_from_source.assert_called_once()
 
@@ -52,9 +51,7 @@ async def test_mcp_ask_question():
             tools = await mcp.get_tools()
             ask_tool = next(t for t in tools.values() if t.name == "ask_question")
 
-            result = await ask_tool.fn(  # type: ignore[attr-defined]
-                question="What is this?", cite=False, deep=False
-            )
+            result = await ask_tool.fn(question="What is this?", cite=False, deep=False)
 
             assert result == "This is the answer"
             mock_rag.ask.assert_called_once_with("What is this?")
@@ -81,8 +78,7 @@ async def test_mcp_add_document_from_url():
                 t for t in tools.values() if t.name == "add_document_from_url"
             )
 
-            result = await add_url_tool.fn(url="https://example.com")  # type: ignore[attr-defined]
-
+            result = await add_url_tool.fn(url="https://example.com")
             assert result == "doc456"
             mock_rag.create_document_from_source.assert_called_once()
 
@@ -108,9 +104,7 @@ async def test_mcp_add_document_from_text():
                 t for t in tools.values() if t.name == "add_document_from_text"
             )
 
-            result = await add_text_tool.fn(  # type: ignore[attr-defined]
-                content="test content", uri="text://test"
-            )
+            result = await add_text_tool.fn(content="test content", uri="text://test")
 
             assert result == "doc789"
             mock_rag.create_document.assert_called_once()
@@ -141,8 +135,7 @@ async def test_mcp_search_documents():
                 t for t in tools.values() if t.name == "search_documents"
             )
 
-            result = await search_tool.fn(query="test query", limit=5)  # type: ignore[attr-defined]
-
+            result = await search_tool.fn(query="test query", limit=5)
             assert len(result) == 2
             assert result[0].document_id == "doc1"
             assert result[0].content == "Result 1"
@@ -174,8 +167,7 @@ async def test_mcp_get_document():
             tools = await mcp.get_tools()
             get_tool = next(t for t in tools.values() if t.name == "get_document")
 
-            result = await get_tool.fn(document_id="doc123")  # type: ignore[attr-defined]
-
+            result = await get_tool.fn(document_id="doc123")
             assert result is not None
             assert result.id == "doc123"
             assert result.content == "test"
@@ -211,8 +203,7 @@ async def test_mcp_list_documents():
             tools = await mcp.get_tools()
             list_tool = next(t for t in tools.values() if t.name == "list_documents")
 
-            result = await list_tool.fn(limit=10, offset=0)  # type: ignore[attr-defined]
-
+            result = await list_tool.fn(limit=10, offset=0)
             assert len(result) == 2
             assert result[0].id == "doc1"
             assert result[1].id == "doc2"
@@ -235,8 +226,7 @@ async def test_mcp_delete_document():
             tools = await mcp.get_tools()
             delete_tool = next(t for t in tools.values() if t.name == "delete_document")
 
-            result = await delete_tool.fn(document_id="doc123")  # type: ignore[attr-defined]
-
+            result = await delete_tool.fn(document_id="doc123")
             assert result is True
             mock_rag.delete_document.assert_called_once_with("doc123")
 
@@ -268,9 +258,7 @@ async def test_mcp_ask_question_deep():
             ask_tool = next(t for t in tools.values() if t.name == "ask_question")
 
             # cite=False to avoid citation formatting in output
-            result = await ask_tool.fn(  # type: ignore[attr-defined]
-                question="Deep question?", cite=False, deep=True
-            )
+            result = await ask_tool.fn(question="Deep question?", cite=False, deep=True)
 
             assert result == "Deep answer from research"
             mock_graph.run.assert_called_once()
@@ -311,7 +299,7 @@ async def test_mcp_research_question():
                 t for t in tools.values() if t.name == "research_question"
             )
 
-            result = await research_tool.fn(  # type: ignore[attr-defined]
+            result = await research_tool.fn(
                 question="Research question?",
             )
 

tests/test_rebuild.py

@@ -1,9 +1,20 @@
+from typing import TypedDict
+
 import pytest
 from datasets import Dataset
 
 from haiku.rag.client import HaikuRAG, RebuildMode
 
 
+class ChunkData(TypedDict):
+    id: str
+    document_id: str
+    content: str
+    content_fts: str
+    metadata: str
+    order: int
+
+
 @pytest.mark.vcr()
 async def test_rebuild_full(qa_corpus: Dataset, temp_db_path):
     """Test full rebuild: converts, chunks, and embeds all documents."""
@@ -132,15 +143,15 @@ async def test_rebuild_embed_only_with_changed_vector_dim(
 
         chunks_before = await client.chunk_repository.get_by_document_id(doc.id)
         assert len(chunks_before) > 0
-        chunk_data = [
-            {
-                "id": c.id,
-                "document_id": c.document_id,
-                "content": c.content,
-                "content_fts": c.content,
-                "metadata": json.dumps(c.metadata),
-                "order": c.order,
-            }
+        chunk_data: list[ChunkData] = [
+            ChunkData(
+                id=c.id or "",
+                document_id=c.document_id or "",
+                content=c.content,
+                content_fts=c.content,
+                metadata=json.dumps(c.metadata),
+                order=c.order,
+            )
             for c in chunks_before
         ]
 

tests/test_search.py

@@ -19,8 +19,8 @@ async def test_search_qa_corpus(qa_corpus: Dataset, temp_db_path):
     for doc_data in qa_corpus:
         if len(seen_documents) >= 10:
             break
-        document_text = doc_data["document_extracted"]  # type: ignore
-        document_id = doc_data.get("document_id", "")  # type: ignore
+        document_text = doc_data["document_extracted"]
+        document_id = doc_data.get("document_id", "")
 
         if document_id in seen_documents:
             continue

tests/test_versioning.py

@@ -14,7 +14,7 @@ async def test_version_rollback_on_create_failure(temp_db_path):
             await orig_create(chunks)
             raise RuntimeError("boom")
 
-        client.chunk_repository.create = succeed_then_fail  # type: ignore[method-assign]
+        client.chunk_repository.create = succeed_then_fail
 
         # Attempt to create document; expect failure and rollback
         content = "Hello, rollback!"
@@ -43,20 +43,20 @@ async def test_version_rollback_on_update_failure(temp_db_path):
             await orig_create(chunks)
             raise RuntimeError("update fail")
 
-        client.chunk_repository.create = succeed_then_fail  # type: ignore[method-assign]
+        client.chunk_repository.create = succeed_then_fail
 
         # Attempt update
         with pytest.raises(RuntimeError):
             await client.update_document(
-                document_id=created.id,  # type: ignore[arg-type]
+                document_id=created.id,
                 content="Updated content",
             )
 
         # Content and chunks should remain the original
-        persisted = await client.get_document_by_id(created.id)  # type: ignore[arg-type]
+        persisted = await client.get_document_by_id(created.id)
         assert persisted is not None
         assert persisted.content == base_content
-        original_chunks = await client.chunk_repository.get_by_document_id(created.id)  # type: ignore[arg-type]
+        original_chunks = await client.chunk_repository.get_by_document_id(created.id)
         assert len(original_chunks) > 0
 
 

uv.lock

@@ -659,7 +659,7 @@ wheels = [
 
 [[package]]
 name = "datasets"
-version = "4.4.2"
+version = "4.5.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "dill" },
@@ -677,9 +677,9 @@ dependencies = [
     { name = "tqdm" },
     { name = "xxhash" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/55/bf/bb927bde63d649296c83e883171ae77074717c1b80fe2868b328bd0dbcbb/datasets-4.5.0.tar.gz", hash = "sha256:00c698ce1c2452e646cc5fad47fef39d3fe78dd650a8a6eb205bb45eb63cd500", size = 588384, upload-time = "2026-01-14T18:27:54.297Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/fc/d5/0d563ea3c205eee226dc8053cf7682a8ac588db8acecd0eda2b587987a0b/datasets-4.5.0-py3-none-any.whl", hash = "sha256:b5d7e08096ffa407dd69e58b1c0271c9b2506140839b8d99af07375ad31b6726", size = 515196, upload-time = "2026-01-14T18:27:52.419Z" },
 ]
 
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@@ -741,7 +741,7 @@ wheels = [
 
 [[package]]
 name = "docling"
-version = "2.67.0"
+version = "2.68.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "accelerate" },
@@ -773,9 +773,9 @@ dependencies = [
     { name = "tqdm" },
     { name = "typer" },
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+sdist = { url = "https://files.pythonhosted.org/packages/f4/cb/5dcda48a739e18c3d087de55be064d1fe9dfa802132aba274d55466ced01/docling-2.68.0.tar.gz", hash = "sha256:fabadc7aa807b96ac9bf85cc78f4fe343b5df658857386bc23541a9a6c116132", size = 265952, upload-time = "2026-01-13T10:47:35.925Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/d5/a5/08716dcbf93e350f0595b58ece138b3b78606ef2f6a5a5058b1642cfe142/docling-2.68.0-py3-none-any.whl", hash = "sha256:97b2a4957e221973c69f1706da326fda8e973707d041778df12c01a5279e3e7e", size = 282854, upload-time = "2026-01-13T10:47:34.325Z" },
 ]
 
 [[package]]
@@ -1304,12 +1304,12 @@ dev = [
     { name = "mkdocs-material" },
     { name = "pre-commit" },
     { name = "pydantic-ai-slim", extra = ["anthropic", "bedrock", "google", "groq"] },
-    { name = "pyright" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-cov" },
     { name = "pytest-recording" },
     { name = "ruff" },
+    { name = "ty" },
 ]
 
 [package.metadata]
@@ -1321,7 +1321,7 @@ provides-extras = ["tui"]
 
 [package.metadata.requires-dev]
 dev = [
-    { name = "datasets", specifier = ">=4.4.2" },
+    { name = "datasets", specifier = ">=4.5.0" },
     { name = "haiku-rag-evals", editable = "evaluations" },
     { name = "mkdocs", specifier = ">=1.6.1" },
     { name = "mkdocs-material", specifier = ">=9.7.1" },
@@ -1330,12 +1330,12 @@ dev = [
     { name = "pydantic-ai-slim", extras = ["bedrock"] },
     { name = "pydantic-ai-slim", extras = ["google"] },
     { name = "pydantic-ai-slim", extras = ["groq"] },
-    { name = "pyright", specifier = ">=1.1.408" },
     { name = "pytest", specifier = ">=9.0.2" },
     { name = "pytest-asyncio", specifier = ">=1.3.0" },
     { name = "pytest-cov", specifier = ">=7.0.0" },
     { name = "pytest-recording", specifier = ">=0.13.4" },
-    { name = "ruff", specifier = ">=0.14.11" },
+    { name = "ruff", specifier = ">=0.14.13" },
+    { name = "ty", specifier = ">=0.0.12" },
 ]
 
 [[package]]
@@ -1352,9 +1352,9 @@ dependencies = [
 
 [package.metadata]
 requires-dist = [
-    { name = "datasets", specifier = ">=4.4.2" },
+    { name = "datasets", specifier = ">=4.5.0" },
     { name = "haiku-rag-slim", editable = "haiku_rag_slim" },
-    { name = "pydantic-ai-slim", extras = ["evals", "logfire"], specifier = ">=1.39.0" },
+    { name = "pydantic-ai-slim", extras = ["evals", "logfire"], specifier = ">=1.44.0" },
     { name = "python-dotenv", specifier = ">=1.2.1" },
     { name = "typer", specifier = ">=0.19.2,<0.20.0" },
 ]
@@ -1420,25 +1420,25 @@ zeroentropy = [
 [package.metadata]
 requires-dist = [
     { name = "cohere", marker = "extra == 'cohere'", specifier = ">=5.20.1" },
-    { name = "docling", marker = "extra == 'docling'", specifier = "==2.67.0" },
+    { name = "docling", marker = "extra == 'docling'", specifier = "==2.68.0" },
     { name = "docling-core", specifier = "==2.59.0" },
     { name = "httpx", specifier = ">=0.28.1" },
     { name = "lancedb", specifier = "==0.26.1" },
     { name = "mxbai-rerank", marker = "extra == 'mxbai'", specifier = ">=0.1.6" },
-    { name = "opencv-python-headless", marker = "extra == 'docling'", specifier = ">=4.12.0.88" },
-    { name = "pathspec", specifier = ">=0.12.1" },
+    { name = "opencv-python-headless", marker = "extra == 'docling'", specifier = ">=4.13.0.90" },
+    { name = "pathspec", specifier = ">=1.0.3" },
     { name = "pydantic", specifier = ">=2.12.5" },
     { name = "pydantic-ai-slim", extras = ["anthropic"], marker = "extra == 'anthropic'" },
     { name = "pydantic-ai-slim", extras = ["bedrock"], marker = "extra == 'bedrock'" },
     { name = "pydantic-ai-slim", extras = ["google"], marker = "extra == 'google'" },
     { name = "pydantic-ai-slim", extras = ["groq"], marker = "extra == 'groq'" },
     { name = "pydantic-ai-slim", extras = ["mistral"], marker = "extra == 'mistral'" },
-    { name = "pydantic-ai-slim", extras = ["openai", "fastmcp", "logfire", "ag-ui"], specifier = ">=1.39.0" },
+    { name = "pydantic-ai-slim", extras = ["openai", "fastmcp", "logfire", "ag-ui"], specifier = ">=1.44.0" },
     { name = "pydantic-ai-slim", extras = ["vertexai"], marker = "extra == 'vertexai'" },
     { name = "python-dotenv", specifier = ">=1.2.1" },
     { name = "pyyaml", specifier = ">=6.0.3" },
     { name = "rich", specifier = ">=14.2.0" },
-    { name = "textual", marker = "extra == 'tui'", specifier = ">=7.0.0" },
+    { name = "textual", marker = "extra == 'tui'", specifier = ">=7.3.0" },
     { name = "textual-image", marker = "extra == 'tui'", specifier = ">=0.8.5" },
     { name = "typer", specifier = ">=0.19.2,<0.20.0" },
     { name = "voyageai", marker = "extra == 'voyageai'", specifier = ">=0.3.7" },
@@ -2773,19 +2773,20 @@ wheels = [
 
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+version = "4.13.0.90"
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@@ -3496,7 +3497,7 @@ email = [
 
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+version = "1.44.0"
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@@ -3507,9 +3508,9 @@ dependencies = [
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 [package.optional-dependencies]
@@ -3623,7 +3624,7 @@ wheels = [
 
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+version = "1.44.0"
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@@ -3633,14 +3634,14 @@ dependencies = [
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