correct using get_model with data_only=False in semantic tokens and formatting

Author: d-biehl

robotcode/language_server/robotframework/parts/formatting.py

@@ -87,7 +87,7 @@ async def format_robot_tidy(
         from robotidy.api import RobotidyAPI
 
         try:
-            model = await self.parent.documents_cache.get_model(document)
+            model = await self.parent.documents_cache.get_model(document, False)
 
             robot_tidy = RobotidyAPI(document.uri.to_path(), None)
 
@@ -144,7 +144,7 @@ async def format_internal(
             SeparatorNormalizer,
         )
 
-        model = cast(File, await self.parent.documents_cache.get_model(document))
+        model = cast(File, await self.parent.documents_cache.get_model(document, False))
 
         Cleaner().visit(model)
         NewlineNormalizer(self.line_separator, self.short_test_name_length).visit(model)

robotcode/language_server/robotframework/parts/semantic_tokens.py

@@ -726,7 +726,11 @@ async def get_tokens() -> AsyncGenerator[Tuple[Token, ast.AST], None]:
             lambda t: range is None or token_in_range(t[0], range),
             async_dropwhile(
                 lambda t: range is not None and not token_in_range(t[0], range),
-                ((t, n) async for t, n in get_tokens()),
+                (
+                    (t, n)
+                    async for t, n in get_tokens()
+                    if t.type not in [RobotToken.SEPARATOR, RobotToken.EOL, RobotToken.EOS]
+                ),
             ),
         ):
             async for token in self.generate_sem_tokens(
@@ -766,7 +770,7 @@ async def collect_threading(
         self, document: TextDocument, range: Optional[Range]
     ) -> Union[SemanticTokens, SemanticTokensPartialResult, None]:
 
-        model = await self.parent.documents_cache.get_model(document, True)
+        model = await self.parent.documents_cache.get_model(document, False)
         namespace = await self.parent.documents_cache.get_namespace(document)
 
         builtin_library_doc = next(