refactor: convert f-string logging to lazy %-style format (G004)

Sweep all 1676 G004 violations across 112 files, converting
`logger.<level>(f"…{x}…")` to `logger.<level>("…%s…", x)`.

Why: ruff rule G004 was added to pyproject.toml to enforce lazy
%-style logging — defers formatting until the log level is enabled
and lets structured log tooling match the unformatted template.

Conversion preserves rendered output byte-for-byte:
- `{x}` → `%s` + `x`
- `{x!r}` / `{x!s}` / `{x!a}` → `%r` / `%s` / `%a`
- Format specs (`{x:.2f}`, `{x:>10}`) → `%s` + `format(x, 'spec')`
  (printf-style specs aren't 1:1 with Python format specs, so we
  delegate to `format()` to keep identical output)
- Literal `%` → `%%`
- Concatenated f-strings (`f"a {x} " "b"`) flattened
- Trailing kwargs (`exc_info=True`) preserved

Verified:
- `uv run ruff check --select G004` → 0 violations
- `uv run ty check -- nextcloud_mcp_server` → passes
- `uv run pytest tests/unit/` → 1010 passed

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

nextcloud_mcp_server/embedding/bm25_provider.py

@@ -30,11 +30,11 @@ class BM25SparseEmbeddingProvider:
             model_name: FastEmbed BM25 model name (default: Qdrant/bm25)
         """
         self.model_name = model_name
-        logger.info(f"Initializing BM25 sparse embedding provider: {model_name}")
+        logger.info("Initializing BM25 sparse embedding provider: %s", model_name)
 
         # Initialize FastEmbed sparse embedding model
         self.model = SparseTextEmbedding(model_name=model_name)
-        logger.info(f"BM25 sparse embedding model loaded: {model_name}")
+        logger.info("BM25 sparse embedding model loaded: %s", model_name)
 
     def encode(self, text: str) -> dict[str, Any]:
         """

nextcloud_mcp_server/embedding/ollama_provider.py

@@ -33,7 +33,10 @@ class OllamaEmbeddingProvider(EmbeddingProvider):
         self.client = httpx.AsyncClient(verify=verify_ssl, timeout=timeout)
         self._dimension: int | None = None  # Will be detected dynamically
         logger.info(
-            f"Initialized Ollama provider: {base_url} (model={model}, verify_ssl={verify_ssl})"
+            "Initialized Ollama provider: %s (model=%s, verify_ssl=%s)",
+            base_url,
+            model,
+            verify_ssl,
         )
 
         self._check_model_is_loaded(autoload=True)
@@ -82,11 +85,13 @@ class OllamaEmbeddingProvider(EmbeddingProvider):
         instead of relying on hardcoded values.
         """
         if self._dimension is None:
-            logger.debug(f"Detecting embedding dimension for model {self.model}...")
+            logger.debug("Detecting embedding dimension for model %s...", self.model)
             test_embedding = await self.embed("test")
             self._dimension = len(test_embedding)
             logger.info(
-                f"Detected embedding dimension: {self._dimension} for model {self.model}"
+                "Detected embedding dimension: %s for model %s",
+                self._dimension,
+                self.model,
             )
 
     def get_dimension(self) -> int: