# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project from __future__ import annotations from collections.abc import Sequence from dataclasses import dataclass from vllm.v1.core.kv_cache_utils import BlockHash from vllm.v1.request import RequestStatus @dataclass(frozen=True) class DiffusionKVContext: """An independently managed K/V context outside the primary sequence. ``context_id`` identifies the logical context within one execution sequence. ``cache_role`` binds it to a logical attention cache role exposed by the Worker. Physical cache geometry remains native ``KVCacheSpec`` / ``KVCacheConfig`` state and is deliberately absent here. """ context_id: str cache_role: str num_tokens: int block_hashes: tuple[BlockHash, ...] = () def __post_init__(self) -> None: if not self.context_id: raise ValueError("context_id must be non-empty") if not self.cache_role: raise ValueError("cache_role must be non-empty") if self.num_tokens <= 0: raise ValueError(f"num_tokens must be positive, got {self.num_tokens}") object.__setattr__(self, "block_hashes", tuple(self.block_hashes)) class DiffusionKVRequest: """Scheduler-owned KV state for one diffusion execution sequence. The primary sequence follows an ordered ``[prefix | target]`` policy, such as one Hunyuan CFG row. ``prefix_len`` is the contiguous reusable prefix; ``target_len`` is overwritten by every denoise step; ``num_tokens`` is the complete first-step allocation boundary. Independent cross/joint-attention K/V does not belong to that token axis and is described by ``kv_contexts``. This object also exposes the minimal mutable Request surface consumed by native ``KVCacheManager``. An empty ``block_hashes`` sequence means the prefix has no canonical cache identity yet. Such a request may use native request-local page allocation, but consumers must not publish it through ``KVCacheManager.cache_blocks``. Prefix publication becomes valid only after model preprocessing supplies one canonical hash for every cacheable full block. """ def __init__( self, request_id: str, *, sequence_id: int, prefix_len: int, target_len: int, seq_len: int, block_hashes: Sequence[BlockHash] = (), kv_contexts: Sequence[DiffusionKVContext] = (), ) -> None: if not request_id: raise ValueError("request_id must be non-empty") if sequence_id < 0: raise ValueError(f"sequence_id must be non-negative, got {sequence_id}") if prefix_len < 0: raise ValueError(f"prefix_len must be non-negative, got {prefix_len}") if target_len <= 0: raise ValueError(f"target_len must be positive, got {target_len}") if seq_len <= 0: raise ValueError(f"seq_len must be positive, got {seq_len}") if prefix_len + target_len > seq_len: raise ValueError( "prefix_len + target_len must not exceed seq_len: " f"prefix_len={prefix_len}, target_len={target_len}, seq_len={seq_len}" ) contexts = tuple(kv_contexts) if any(not isinstance(context, DiffusionKVContext) for context in contexts): raise TypeError("kv_contexts must contain only DiffusionKVContext values") context_ids = [context.context_id for context in contexts] if len(context_ids) != len(set(context_ids)): raise ValueError(f"kv_contexts must have unique context_id values, got {context_ids}") # Diffusion semantics consumed by the Scheduler-side facade. self.sequence_id = sequence_id self.prefix_len = prefix_len self.target_len = target_len self.kv_contexts = contexts # Native vLLM Request surface. Keep this list intentionally small and # cover it with real-KVCacheManager conformance tests. self.request_id = request_id self.num_tokens = seq_len self.num_prompt_tokens = prefix_len self.num_computed_tokens = 0 self.block_hashes = list(block_hashes) self.skip_reading_prefix_cache = not self.block_hashes self.status = RequestStatus.WAITING self.num_preemptions = 0 self.num_in_flight_tokens = 0 # vLLM 0.26 uses this optional boundary when publishing cached blocks; # zero means that no sparse-retention boundary is active. self.shared_prefix_boundary = 0 @property def seq_len(self) -> int: """Complete first-step sequence length and allocation boundary.""" return self.num_tokens