[P/D]Mooncake Layerwise Connector supports hybrid attention manager with multiple kvcache groups (#7022)

### What this PR does / why we need it?
Mooncake Layerwise Connector supports hybrid attention manager with
multiple kvcache groups.

### Does this PR introduce _any_ user-facing change?
Yes.

### How was this patch tested?
By CI.

- vLLM version: v0.16.0
- vLLM main:
15d76f74e2

---------

Signed-off-by: nwpu-zxr <zhouxuerong2@huawei.com>

vllm_ascend/core/recompute_scheduler.py

@@ -91,6 +91,11 @@ class RecomputeScheduler(Scheduler):
             and self.vllm_config.kv_transfer_config
             and self.vllm_config.kv_transfer_config.is_kv_consumer
         )
+        self.is_kv_producer = self.vllm_config.kv_transfer_config and self.vllm_config.kv_transfer_config.is_kv_producer
+        self.is_hybrid_model = (
+            "qwen3_next" in self.vllm_config.model_config.model_type
+            or "qwen3_5" in self.vllm_config.model_config.model_type
+        )
 
     def add_request(self, request: Request) -> None:
         existing = self.requests.get(request.request_id)
@@ -111,6 +116,10 @@ class RecomputeScheduler(Scheduler):
                 request.streaming_queue = deque()
             # Fill in placeholder tokens to enable full graph compatibility. Without
             # placeholders, graph matching may fail, forcing eager mode execution.
+            if self.is_kv_producer and self.is_hybrid_model and request.num_tokens > 1:
+                request.prompt_token_ids.pop()
+                request._all_token_ids.pop()
+                request.num_prompt_tokens -= 1
             if self.is_mtp_kv_consumer:
                 request.spec_token_ids = [PLACEHOLDER_TOKEN_ID] * self.num_spec_tokens
             self.waiting.add_request(request)
@@ -118,6 +127,55 @@ class RecomputeScheduler(Scheduler):
             if self.log_stats:
                 request.record_event(EngineCoreEventType.QUEUED)
 
+    def _update_waiting_for_remote_kv(self, request: Request) -> bool:
+        """
+        KV Connector: check if the request_id is finished_recving.
+
+        The finished_recving_kv_req_ids list is populated
+        on the previous steps()'s update_from_output based
+        on the worker side connector.
+
+        When the kv transfer is ready, we cache the blocks
+        and the request state will be moved back to WAITING from
+        WAITING_FOR_REMOTE_KV.
+        """
+        assert self.connector is not None
+        if request.request_id not in self.finished_recving_kv_req_ids:
+            return False
+
+        if request.request_id in self.failed_recving_kv_req_ids:
+            # Request had KV load failures; num_computed_tokens was already
+            # updated in _update_requests_with_invalid_blocks
+            if request.num_computed_tokens:
+                # Cache any valid computed tokens.
+                self.kv_cache_manager.cache_blocks(request, request.num_computed_tokens)
+            else:
+                # No valid computed tokens, release allocated blocks.
+                # There may be a local cache hit on retry.
+                self.kv_cache_manager.free(request)
+
+            self.failed_recving_kv_req_ids.remove(request.request_id)
+        else:
+            # Now that the blocks are ready, actually cache them.
+            block_ids = self.kv_cache_manager.get_block_ids(request.request_id)
+            if len(block_ids) == 1:
+                num_computed_tokens = len(block_ids[0]) * self.block_size
+                # Handle the case where num request tokens less than one block.
+                num_computed_tokens = min(num_computed_tokens, request.num_tokens)
+            else:
+                num_computed_tokens = request.num_tokens
+            if num_computed_tokens == request.num_tokens:
+                num_computed_tokens -= 1
+            # This will cache the blocks iff caching is enabled.
+            self.kv_cache_manager.cache_blocks(request, num_computed_tokens)
+
+            # Update the request state for scheduling.
+            request.num_computed_tokens = num_computed_tokens
+
+        # Return that we are ready.
+        self.finished_recving_kv_req_ids.remove(request.request_id)
+        return True
+
     def schedule(self) -> RecomputeSchedulerOutput:
         # NOTE(woosuk) on the scheduling algorithm:
         # There's no "decoding phase" nor "prefill phase" in the scheduler.