[Core][Frontend] Support request-level batching for diffusion pipelines (#4079)

Signed-off-by: jader <yjader@foxmail.com>
Co-authored-by: Samit <285365963@qq.com>

docs/user_guide/diffusion/request_batching.md

@@ -0,0 +1,110 @@
+# Request-Level Batching
+
+Request-level batching lets diffusion serving combine multiple compatible
+logical requests into one pipeline `forward()` call. Each prompt remains a
+separate request with its own `request_id`, sampling parameters, seed, output,
+error, and abort state. The scheduler decides which requests can run together.
+
+!!! warning "Prompt List Semantics"
+
+    Diffusion request-level batching does not support a top-level packed
+    list-prompt request. Submit multiple prompts as independent requests and let
+    the scheduler batch compatible in-flight requests. Multimodal payloads stay
+    inside a single prompt dict, for example
+    `{"prompt": "...", "multi_modal_data": {"image": image}}`.
+
+## Enablement
+
+Increase `max_num_seqs` above `1` to allow the request scheduler to keep more
+than one compatible request active:
+
+```bash
+vllm serve Qwen/Qwen-Image --omni \
+  --port 8091 \
+  --max-num-seqs 4
+```
+
+For bursty online traffic, you can also set a small admission wait window. This
+lets the engine wait briefly before the first `schedule()` of a new wave so
+nearby compatible requests can arrive and share the same fused forward pass:
+
+```bash
+vllm serve Qwen/Qwen-Image --omni \
+  --port 8091 \
+  --max-num-seqs 4 \
+  --request-batch-max-wait-ms 20
+```
+
+`--request-batch-max-wait-ms 0` is the default and disables admission waiting,
+so there is no added wait latency.
+
+For deploy YAMLs, configure the diffusion stage engine args:
+
+```yaml
+stage_args:
+  - stage_id: 0
+    stage_type: diffusion
+    engine_args:
+      max_num_seqs: 4
+      request_batch_max_wait_ms: 20
+```
+
+## Compatibility
+
+Only pipelines that declare request-batch support use the fused request-batch
+path. The engine validates that the pipeline `forward()` uses the request-batch
+contract and returns `list[DiffusionOutput]`. Pipelines that do not support this
+contract do not use fused `pipeline.forward(batch)`; scheduled requests are
+executed through per-request worker calls.
+
+The scheduler batches only compatible requests. Compatibility is based on
+shape-sensitive and guidance-sensitive sampling fields, including resolution,
+frame count, CFG settings, output count, and LoRA identity. Requests with
+different LoRA adapters or scales are kept in separate batches so the worker
+activates one adapter per batch.
+
+Request-level batching applies when `step_execution=False`. For the separate
+step-wise runtime, see [Step Execution](step_execution.md).
+
+## Tuning
+
+- `max_num_seqs` caps the number of active compatible requests in one scheduler
+  wave.
+- `request_batch_max_wait_ms` is an upper bound on extra admission wait before a
+  new wave starts. Keep it small for latency-sensitive serving; values such as
+  `10` to `50` ms are a practical starting range for bursty HTTP ingress.
+- `0` disables admission waiting and preserves the lowest first-request latency.
+- FIFO ordering is conservative: an incompatible request at the front of the
+  waiting queue can block later compatible requests from joining the current
+  batch.
+
+## Python API
+
+When constructing `Omni`, pass the same engine arguments:
+
+```python
+from vllm_omni.entrypoints.omni import Omni
+
+omni = Omni(
+    model="Qwen/Qwen-Image",
+    max_num_seqs=4,
+    request_batch_max_wait_ms=20.0,
+)
+
+outputs = omni.generate(
+    [
+        "a cup of coffee on a table",
+        "a toy dinosaur on a sandy beach",
+        "a fox waking up in bed and yawning",
+    ]
+)
+```
+
+`Omni.generate([...])` submits each list item as its own logical diffusion
+request. The runtime may batch those requests internally when their sampling
+parameters are compatible.
+
+## For Contributors
+
+For implementation details and model-author guidance, see
+[Request-Level Batching for Diffusion](../../design/feature/diffusion_request_level_batching.md).