Add ty type checker to CI and fix type errors (fixes bug from PR #157) (#192)

* Add ty type checker to CI and fix type errors

- Add ty (Astral's fast Python type checker) to GitHub CI workflow
- Fix type annotations across all RAG apps:
  - Update load_data return types from list[str] to list[dict[str, Any]]
  - Fix base_rag_example.py to properly handle dict format from create_text_chunks
- Fix type errors in leann-core:
  - chunking_utils.py: Add explicit type annotations
  - cli.py: Fix return type annotations for PDF extraction functions
  - interactive_utils.py: Fix readline import type handling
- Fix type errors in apps:
  - wechat_history.py: Fix return type annotations
  - document_rag.py, code_rag.py: Replace **kwargs with explicit arguments
- Add ty configuration to pyproject.toml

This resolves the bug introduced in PR #157 where create_text_chunks()
changed to return list[dict] but callers were not updated.

* Fix remaining ty type errors

- Fix slack_mcp_reader.py channel parameter can be None
- Fix embedding_compute.py ContextProp type issue
- Fix searcher_base.py method override signatures
- Fix chunking_utils.py chunk_text assignment
- Fix slack_rag.py and twitter_rag.py return types
- Fix email.py and image_rag.py method overrides

* Fix multimodal benchmark scripts type errors

- Fix undefined LeannRetriever -> LeannMultiVector
- Add proper type casts for HuggingFace Dataset iteration
- Cast task config values to correct types
- Add type annotations for dataset row dicts

* Enable ty check for multimodal scripts in CI

All type errors in multimodal scripts have been fixed, so we can now
include them in the CI type checking.

* Fix all test type errors and enable ty check on tests

- Fix test_basic.py: search() takes str not list
- Fix test_cli_prompt_template.py: add type: ignore for Mock assignments
- Fix test_prompt_template_persistence.py: match BaseSearcher.search signature
- Fix test_prompt_template_e2e.py: add type narrowing asserts after skip
- Fix test_readme_examples.py: use explicit kwargs instead of **model_args
- Fix metadata_filter.py: allow Optional[MetadataFilters]
- Update CI to run ty check on tests

* Format code with ruff

* Format searcher_base.py

tests/test_prompt_template_persistence.py

@@ -581,7 +581,18 @@ class TestQueryTemplateApplicationInComputeEmbedding:
 
         # Create a concrete implementation for testing
         class TestSearcher(BaseSearcher):
-            def search(self, query_vectors, top_k, complexity, beam_width=1, **kwargs):
+            def search(
+                self,
+                query,
+                top_k,
+                complexity=64,
+                beam_width=1,
+                prune_ratio=0.0,
+                recompute_embeddings=False,
+                pruning_strategy="global",
+                zmq_port=None,
+                **kwargs,
+            ):
                 return {"labels": [], "distances": []}
 
         searcher = object.__new__(TestSearcher)
@@ -625,7 +636,18 @@ class TestQueryTemplateApplicationInComputeEmbedding:
 
         # Create a concrete implementation for testing
         class TestSearcher(BaseSearcher):
-            def search(self, query_vectors, top_k, complexity, beam_width=1, **kwargs):
+            def search(
+                self,
+                query,
+                top_k,
+                complexity=64,
+                beam_width=1,
+                prune_ratio=0.0,
+                recompute_embeddings=False,
+                pruning_strategy="global",
+                zmq_port=None,
+                **kwargs,
+            ):
                 return {"labels": [], "distances": []}
 
         searcher = object.__new__(TestSearcher)
@@ -671,7 +693,18 @@ class TestQueryTemplateApplicationInComputeEmbedding:
         from leann.searcher_base import BaseSearcher
 
         class TestSearcher(BaseSearcher):
-            def search(self, query_vectors, top_k, complexity, beam_width=1, **kwargs):
+            def search(
+                self,
+                query,
+                top_k,
+                complexity=64,
+                beam_width=1,
+                prune_ratio=0.0,
+                recompute_embeddings=False,
+                pruning_strategy="global",
+                zmq_port=None,
+                **kwargs,
+            ):
                 return {"labels": [], "distances": []}
 
         searcher = object.__new__(TestSearcher)
@@ -710,7 +743,18 @@ class TestQueryTemplateApplicationInComputeEmbedding:
         from leann.searcher_base import BaseSearcher
 
         class TestSearcher(BaseSearcher):
-            def search(self, query_vectors, top_k, complexity, beam_width=1, **kwargs):
+            def search(
+                self,
+                query,
+                top_k,
+                complexity=64,
+                beam_width=1,
+                prune_ratio=0.0,
+                recompute_embeddings=False,
+                pruning_strategy="global",
+                zmq_port=None,
+                **kwargs,
+            ):
                 return {"labels": [], "distances": []}
 
         searcher = object.__new__(TestSearcher)
@@ -774,7 +818,18 @@ class TestQueryTemplateApplicationInComputeEmbedding:
         from leann.searcher_base import BaseSearcher
 
         class TestSearcher(BaseSearcher):
-            def search(self, query_vectors, top_k, complexity, beam_width=1, **kwargs):
+            def search(
+                self,
+                query,
+                top_k,
+                complexity=64,
+                beam_width=1,
+                prune_ratio=0.0,
+                recompute_embeddings=False,
+                pruning_strategy="global",
+                zmq_port=None,
+                **kwargs,
+            ):
                 return {"labels": [], "distances": []}
 
         searcher = object.__new__(TestSearcher)