diff --git a/vllm/core/block/naive_block.py b/vllm/core/block/naive_block.py
index dae6ead04e9c..7d9b32cd4b67 100644
--- a/vllm/core/block/naive_block.py
+++ b/vllm/core/block/naive_block.py
@@ -207,7 +207,7 @@ def get_physical_block_id(self, absolute_id: int) -> int:
 
         Args:
             absolute_id (int): The absolute block id for the block 
-            in whole allocator.
+                in whole allocator.
 
         Returns:
             int: The zero-offset block id on certain device.
diff --git a/vllm/core/block/prefix_caching_block.py b/vllm/core/block/prefix_caching_block.py
index 2913a01bf34a..a21d69323abb 100644
--- a/vllm/core/block/prefix_caching_block.py
+++ b/vllm/core/block/prefix_caching_block.py
@@ -61,7 +61,7 @@ class PrefixCachingBlockAllocator(BlockAllocator):
     Args:
         num_blocks (int): The total number of blocks to manage.
         block_size (int): The size of each block in tokens.
-        block_ids(Optional[Iterable[int]], optional): An optional iterable of
+        block_ids (Optional[Iterable[int]], optional): An optional iterable of
             block IDs. If not provided, block IDs will be assigned sequentially
             from 0 to num_blocks - 1.
     """
diff --git a/vllm/core/scheduler.py b/vllm/core/scheduler.py
index 63894e7f5dc8..c89f3f663264 100644
--- a/vllm/core/scheduler.py
+++ b/vllm/core/scheduler.py
@@ -657,7 +657,7 @@ def _schedule_running(
                 `budget.num_batched_tokens` has not enough capacity to schedule
                 all tokens.
             partial_prefill_metadata: information about the partial prefills
-            that are currently running
+                that are currently running
 
         Returns:
             SchedulerRunningOutputs.
diff --git a/vllm/v1/attention/backends/cpu_attn.py b/vllm/v1/attention/backends/cpu_attn.py
index 973979fdf7df..ced8234a7b43 100644
--- a/vllm/v1/attention/backends/cpu_attn.py
+++ b/vllm/v1/attention/backends/cpu_attn.py
@@ -491,7 +491,8 @@ def forward(
             query: shape = [num_tokens, num_heads * head_size]
             key: shape = [num_tokens, num_kv_heads * head_size]
             value: shape = [num_tokens, num_kv_heads * head_size]
-            kv_cache = [2, num_blocks, block_size * num_kv_heads * head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size * num_kv_heads * head_size]
                 NOTE: kv_cache will be an empty tensor with shape [0]
                 for profiling run.
             attn_metadata: Metadata for attention.
diff --git a/vllm/v1/attention/backends/flash_attn.py b/vllm/v1/attention/backends/flash_attn.py
index 6e7096de924c..dd2b956d4fa3 100755
--- a/vllm/v1/attention/backends/flash_attn.py
+++ b/vllm/v1/attention/backends/flash_attn.py
@@ -438,7 +438,8 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache = [2, num_blocks, block_size, num_kv_heads, head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size, num_kv_heads, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/attention/backends/flashinfer.py b/vllm/v1/attention/backends/flashinfer.py
index 1115fc606b05..70d3471a4725 100755
--- a/vllm/v1/attention/backends/flashinfer.py
+++ b/vllm/v1/attention/backends/flashinfer.py
@@ -637,11 +637,9 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache: shape -
-            # NHD: [num_blocks, 2, block_size, num_kv_heads, head_size]
-            # HND: [num_blocks, 2,  num_kv_heads, block_size, head_size]
-
-
+            kv_cache: KV cache tensor with different possible shapes:
+                - NHD: [num_blocks, 2, block_size, num_kv_heads, head_size]
+                - HND: [num_blocks, 2, num_kv_heads, block_size, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/attention/backends/flex_attention.py b/vllm/v1/attention/backends/flex_attention.py
index 458562ebc8d2..a596f6b2b32a 100644
--- a/vllm/v1/attention/backends/flex_attention.py
+++ b/vllm/v1/attention/backends/flex_attention.py
@@ -689,7 +689,8 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache = [2, num_blocks, block_size, num_kv_heads, head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size, num_kv_heads, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/attention/backends/pallas.py b/vllm/v1/attention/backends/pallas.py
index fd97db0abb84..26f9abf13d0e 100644
--- a/vllm/v1/attention/backends/pallas.py
+++ b/vllm/v1/attention/backends/pallas.py
@@ -235,7 +235,8 @@ def forward(
             query: shape = [num_tokens, num_heads * head_size]
             key: shape = [num_tokens, num_kv_heads * head_size]
             value: shape = [num_tokens, num_kv_heads * head_size]
-            kv_cache = [num_blocks, block_size, num_kv_heads * 2, head_size]
+            kv_cache: shape =
+                [num_blocks, block_size, num_kv_heads * 2, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
@@ -329,7 +330,7 @@ def write_to_kv_cache(
     Args:
         key: shape = [num_tokens, num_kv_heads, head_size]
         value: shape = [num_tokens, num_kv_heads, head_size]
-        kv_cache = [num_blocks, block_size, num_kv_heads * 2, head_size]
+        kv_cache: shape = [num_blocks, block_size, num_kv_heads * 2, head_size]
         num_slices_per_kv_cache_update_block: int
     """
     _, page_size, num_combined_kv_heads, head_size = kv_cache.shape
diff --git a/vllm/v1/attention/backends/rocm_aiter_fa.py b/vllm/v1/attention/backends/rocm_aiter_fa.py
index 403ad8e88a95..173a0a255e49 100644
--- a/vllm/v1/attention/backends/rocm_aiter_fa.py
+++ b/vllm/v1/attention/backends/rocm_aiter_fa.py
@@ -429,7 +429,8 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache = [2, num_blocks, block_size, num_kv_heads, head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size, num_kv_heads, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/attention/backends/tree_attn.py b/vllm/v1/attention/backends/tree_attn.py
index c93223a34083..b96d957a150b 100644
--- a/vllm/v1/attention/backends/tree_attn.py
+++ b/vllm/v1/attention/backends/tree_attn.py
@@ -362,7 +362,8 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache = [2, num_blocks, block_size, num_kv_heads, head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size, num_kv_heads, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/attention/backends/triton_attn.py b/vllm/v1/attention/backends/triton_attn.py
index b12036c59979..a37a7f6811ef 100644
--- a/vllm/v1/attention/backends/triton_attn.py
+++ b/vllm/v1/attention/backends/triton_attn.py
@@ -285,7 +285,8 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache = [2, num_blocks, block_size, num_kv_heads, head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size, num_kv_heads, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/attention/backends/xformers.py b/vllm/v1/attention/backends/xformers.py
index e0eb7d8be974..7f888c113574 100644
--- a/vllm/v1/attention/backends/xformers.py
+++ b/vllm/v1/attention/backends/xformers.py
@@ -330,7 +330,8 @@ def forward(
             query: shape = [num_tokens, num_heads, head_size]
             key: shape = [num_tokens, num_kv_heads, head_size]
             value: shape = [num_tokens, num_kv_heads, head_size]
-            kv_cache = [2, num_blocks, block_size, num_kv_heads, head_size]
+            kv_cache: shape =
+                [2, num_blocks, block_size, num_kv_heads, head_size]
             attn_metadata: Metadata for attention.
         Returns:
             shape = [num_tokens, num_heads * head_size]
diff --git a/vllm/v1/core/encoder_cache_manager.py b/vllm/v1/core/encoder_cache_manager.py
index c9d18033a198..bd2ec036834b 100644
--- a/vllm/v1/core/encoder_cache_manager.py
+++ b/vllm/v1/core/encoder_cache_manager.py
@@ -255,9 +255,9 @@ def compute_encoder_budget(
 
     Returns:
         - Compute budget for encoder execution, measured in number of tokens
-          from the input sequence.
+            from the input sequence.
         - Space budget for encoder cache size, measured in number of tokens
-          from the input sequence.
+            from the input sequence.
     """
     if mm_registry.supports_multimodal_inputs(model_config):
         max_tokens_by_modality = mm_registry \
@@ -303,9 +303,9 @@ def compute_mm_encoder_budget(
 
     Returns:
         - Compute budget for encoder execution, measured in number of tokens
-          from the input sequence.
+            from the input sequence.
         - Space budget for encoder cache size, measured in number of tokens
-          from the input sequence.
+            from the input sequence.
     """
 
     if not max_tokens_by_modality:
diff --git a/vllm/v1/core/kv_cache_coordinator.py b/vllm/v1/core/kv_cache_coordinator.py
index f082ad00f2e3..9421341f990c 100644
--- a/vllm/v1/core/kv_cache_coordinator.py
+++ b/vllm/v1/core/kv_cache_coordinator.py
@@ -119,7 +119,8 @@ def cache_blocks(self, request: Request, num_computed_tokens: int) -> None:
 
         Args:
             request: The request.
-            num_tokens: The total number of tokens that need to be cached 
+            num_computed_tokens: The total number of tokens
+                that need to be cached
                 (including tokens that are already cached).
         """
         for manager in self.single_type_managers:
diff --git a/vllm/v1/core/kv_cache_manager.py b/vllm/v1/core/kv_cache_manager.py
index b427a9c497fe..87a11fe58a04 100644
--- a/vllm/v1/core/kv_cache_manager.py
+++ b/vllm/v1/core/kv_cache_manager.py
@@ -54,14 +54,15 @@ def get_block_ids(
     def get_block_ids(
         self,
         allow_none: bool = False,
-    ):
+    ) -> Optional[tuple[list[int], ...]]:
         """
         Converts the KVCacheBlocks instance to block_ids.
-        
+
         Returns:
-            tuple[list[int], ...]: A tuple of lists where
-            * the outer tuple corresponds to KV cache groups
-            * each inner list contains the block_ids of the blocks in that group
+            tuple[list[int], ...]: A tuple of lists where:
+                - the outer tuple corresponds to KV cache groups
+                - each inner list contains the block_ids of the blocks in that
+                  group
         """
         if allow_none and all(len(group) == 0 for group in self.blocks):
             return None
diff --git a/vllm/v1/executor/ray_distributed_executor.py b/vllm/v1/executor/ray_distributed_executor.py
index c05ad1966d61..8394ae788ab0 100644
--- a/vllm/v1/executor/ray_distributed_executor.py
+++ b/vllm/v1/executor/ray_distributed_executor.py
@@ -8,6 +8,7 @@
 from vllm.executor.ray_distributed_executor import (  # noqa
     RayDistributedExecutor as RayDistributedExecutorV0)
 from vllm.logger import init_logger
+from vllm.v1.core.sched.output import SchedulerOutput
 from vllm.v1.engine import ReconfigureDistributedRequest, ReconfigureRankType
 from vllm.v1.executor.abstract import Executor
 from vllm.v1.outputs import ModelRunnerOutput
@@ -64,7 +65,7 @@ def max_concurrent_batches(self) -> int:
 
     def execute_model(
         self,
-        scheduler_output,
+        scheduler_output: SchedulerOutput,
     ) -> Union[ModelRunnerOutput, Future[ModelRunnerOutput]]:
         """Execute the model on the Ray workers.
 
diff --git a/vllm/v1/metrics/prometheus.py b/vllm/v1/metrics/prometheus.py
index 61ba5d66cb31..a43cf9ce255e 100644
--- a/vllm/v1/metrics/prometheus.py
+++ b/vllm/v1/metrics/prometheus.py
@@ -36,7 +36,7 @@ def setup_multiprocess_prometheus():
                        "and vLLM will properly handle cleanup.")
 
 
-def get_prometheus_registry():
+def get_prometheus_registry() -> CollectorRegistry:
     """Get the appropriate prometheus registry based on multiprocessing 
     configuration.
     
diff --git a/vllm/v1/sample/logits_processor/interface.py b/vllm/v1/sample/logits_processor/interface.py
index 12b4db24bff8..c9c649705dfd 100644
--- a/vllm/v1/sample/logits_processor/interface.py
+++ b/vllm/v1/sample/logits_processor/interface.py
@@ -80,7 +80,7 @@ def update_state(
         to each forward pass.
 
         Args:
-            batch_update is non-None iff there have been
-            changes to the batch makeup.
+            batch_update: Non-None iff there have been changes
+                to the batch makeup.
         """
         raise NotImplementedError
diff --git a/vllm/v1/sample/rejection_sampler.py b/vllm/v1/sample/rejection_sampler.py
index b2354c53302a..2d9ce3101b6c 100644
--- a/vllm/v1/sample/rejection_sampler.py
+++ b/vllm/v1/sample/rejection_sampler.py
@@ -68,7 +68,7 @@ def forward(
                 different requests are flattened into a single tensor because
                 this is the shape of the output logits.
                 NOTE: `target_logits` can be updated in place to save memory.
-            bonus_token_ids_tensor (torch.Tensor):
+            bonus_token_ids (torch.Tensor):
                 A tensor containing bonus tokens. Shape is [batch_size, 1].
                 Bonus tokens are added to the end of the sequence if all
                 proposed tokens are accepted. We generate the bonus tokens
diff --git a/vllm/v1/sample/tpu/sampler.py b/vllm/v1/sample/tpu/sampler.py
index 04545d587e4a..e84136e3a6d0 100644
--- a/vllm/v1/sample/tpu/sampler.py
+++ b/vllm/v1/sample/tpu/sampler.py
@@ -89,7 +89,7 @@ def gather_logprobs(
         Gather logprobs for topk and sampled/prompt token.
 
         Args:
-          logits: (num tokens) x (vocab) tensor
+          logprobs: (num tokens) x (vocab) tensor
           num_logprobs: minimum number of logprobs to
                         retain per token
           token_ids: prompt tokens (if prompt logprobs)
diff --git a/vllm/v1/structured_output/backend_types.py b/vllm/v1/structured_output/backend_types.py
index d500783aa4b3..9a53aa7a1ad1 100644
--- a/vllm/v1/structured_output/backend_types.py
+++ b/vllm/v1/structured_output/backend_types.py
@@ -110,7 +110,7 @@ def compile_grammar(self, request_type: StructuredOutputOptions,
 
         Args:
             request_type (StructuredOutputOptions): The type of structured
-              output request.
+                output request.
             grammar_spec (str): The grammar specification to compile.
 
         Returns:
@@ -124,7 +124,7 @@ def allocate_token_bitmask(self, max_num_seqs: int) -> torch.Tensor:
 
         Args:
             max_num_seqs (int): The maximum number of sequences for which
-              to allocate the bitmask.
+                to allocate the bitmask.
         """
 
     @abstractmethod
diff --git a/vllm/v1/worker/gpu_input_batch.py b/vllm/v1/worker/gpu_input_batch.py
index 284af6bfedce..f4c2f45df595 100644
--- a/vllm/v1/worker/gpu_input_batch.py
+++ b/vllm/v1/worker/gpu_input_batch.py
@@ -525,9 +525,6 @@ def condense(self) -> None:
         Any consecutive empty indices at the very end of the list are not
         filled.
 
-        Args:
-          empty_req_indices: empty indices which may be filled.
-
         Returns:
           swaps: list of (from,to) swap tuples for moved requests
           empty_req_indices: indices not filled by condensation
diff --git a/vllm/v1/worker/gpu_model_runner.py b/vllm/v1/worker/gpu_model_runner.py
index d93460d618e7..ed2a54eebc98 100644
--- a/vllm/v1/worker/gpu_model_runner.py
+++ b/vllm/v1/worker/gpu_model_runner.py
@@ -2953,7 +2953,7 @@ def _reshape_kv_cache_tensors(
         Args:
             kv_cache_config: The KV cache config
             kv_cache_raw_tensors: The KV cache buffer of each layer, with
-            correct size but uninitialized shape.
+                correct size but uninitialized shape.
         Returns:
             Dict[str, torch.Tensor]: A map between layer names to their
             corresponding memory buffer for KV cache.
diff --git a/vllm/v1/worker/tpu_model_runner.py b/vllm/v1/worker/tpu_model_runner.py
index d36423660427..70ffde39ca33 100644
--- a/vllm/v1/worker/tpu_model_runner.py
+++ b/vllm/v1/worker/tpu_model_runner.py
@@ -552,7 +552,7 @@ def get_kv_cache_spec(self) -> dict[str, KVCacheSpec]:
         return kv_cache_spec
 
     def _get_slot_mapping_metadata(self, num_reqs,
-                                   num_scheduled_tokens_per_req):
+                                   num_scheduled_tokens_per_req) -> np.ndarray:
         """
         Computes metadata for mapping slots to blocks in the key-value (KV)
         cache for a batch of requests.
@@ -565,15 +565,15 @@ def _get_slot_mapping_metadata(self, num_reqs,
         Args:
             num_reqs (int): Number of requests in the current batch.
             num_scheduled_tokens_per_req (int or np.ndarray): Number of tokens
-            to be scheduled for each request.
+                to be scheduled for each request.
 
         Returns:
             np.ndarray: A 2D array of shape (total_block_len, 3), where each row
-            contains:
+                contains:
                 - kv_cache_start_index (int): The starting index in the KV cache
-                    for the corresponding slice.
+                  for the corresponding slice.
                 - new_kv_start_index (int): The starting index in the new KV
-                    cache for the corresponding slice.
+                  cache for the corresponding slice.
                 - slice_len (int): The length of the slice.
         """
         slices_start = self.input_batch.num_computed_tokens_cpu[:num_reqs]
diff --git a/vllm/v1/worker/utils.py b/vllm/v1/worker/utils.py
index f40753468766..a519336e4161 100644
--- a/vllm/v1/worker/utils.py
+++ b/vllm/v1/worker/utils.py
@@ -172,10 +172,10 @@ def scatter_mm_placeholders(
 
     Args:
         embeds: The multimodal embeddings.
-          Shape: `(num_embeds, embed_dim)`
+            Shape: `(num_embeds, embed_dim)`
         is_embed: A boolean mask indicating which positions in the placeholder
-          tokens need to be filled with multimodal embeddings.
-          Shape: `(num_placeholders, num_embeds)`
+            tokens need to be filled with multimodal embeddings.
+            Shape: `(num_placeholders, num_embeds)`
     """
     if is_embed is None:
         return embeds
@@ -278,7 +278,7 @@ def bind_kv_cache(
     Args:
         kv_caches: The allocated kv_caches with layer names as keys.
         forward_context: The global forward context containing all Attention
-        layers with layer names as keys.
+            layers with layer names as keys.
         runner_kv_caches: The kv_cache declared by ModelRunner.
     """
     # Bind kv_caches to ModelRunner
diff --git a/vllm/v1/worker/worker_base.py b/vllm/v1/worker/worker_base.py
index 9c93754f93f8..038ce4b54f96 100644
--- a/vllm/v1/worker/worker_base.py
+++ b/vllm/v1/worker/worker_base.py
@@ -36,8 +36,8 @@ def __init__(
             local_rank: Local device index
             rank: Global rank in distributed setup
             distributed_init_method: Distributed initialization method
-            is_driver_worker: Whether this worker handles driver 
-            responsibilities
+            is_driver_worker: Whether this worker handles driver
+                responsibilities
         """
         # Configuration storage
         super().__init__(vllm_config=vllm_config)