[Docs] Add recipe for Helios (#3114)

Signed-off-by: JasonJ2021 <jasonj@zju.edu.cn>

recipes/Helios/Helios.md

@@ -0,0 +1,109 @@
+# Helios for video generation
+
+## Summary
+
+- Vendor: Helios
+- Model: `BestWishYsh/Helios-Base`, `BestWishYsh/Helios-Mid`, `BestWishYsh/Helios-Distilled`
+- Task: Text-to-video, image-to-video, and video-to-video generation
+- Mode: Offline inference with the bundled Helios example
+- Maintainer: Community
+
+## When to use this recipe
+
+Use this recipe when you want a known-good starting point for running Helios
+video generation with vLLM-Omni. The concrete command below focuses on
+`BestWishYsh/Helios-Base` text-to-video generation on one NVIDIA H20 GPU. The
+same example script also supports Helios-Mid, Helios-Distilled, image-to-video,
+and video-to-video; see the linked example docs for those model-specific flags.
+
+## References
+
+- Upstream repository: <https://github.com/PKU-YuanGroup/Helios>
+- Model weights:
+  <https://huggingface.co/BestWishYsh/Helios-Base>
+- Upstream or canonical docs:
+  [`docs/user_guide/examples/offline_inference/helios.md`](../../docs/user_guide/examples/offline_inference/helios.md)
+- Related example under `examples/`:
+  [`examples/offline_inference/helios/README.md`](../../examples/offline_inference/helios/README.md)
+
+## Hardware Support
+
+## GPU
+
+### 1x NVIDIA H20
+
+#### Environment
+
+- OS: Ubuntu Linux x86_64
+- Python: 3.12.12
+- Driver / runtime: NVIDIA driver `580.126.20`, CUDA `13.0`
+- Hardware: 1x NVIDIA H20 GPU from an 8x H20 host
+- vLLM version: `0.19.0`
+- vLLM-Omni version or commit: `a3903810`
+
+#### Command
+
+Run the baseline Helios-Base text-to-video example from the repository root:
+
+```bash
+cd examples/offline_inference/helios
+
+python end2end.py \
+  --model BestWishYsh/Helios-Base \
+  --sample-type t2v \
+  --prompt "A dynamic time-lapse video showing the rapidly moving scenery from the window of a speeding train." \
+  --guidance-scale 5.0 \
+  --output helios_t2v_base.mp4
+```
+
+To use cache-dit acceleration, run on a vLLM-Omni checkout that includes Helios cache-dit support and enable the cache backend:
+
+```bash
+cd examples/offline_inference/helios
+
+python end2end.py \
+  --cache-backend cache_dit \
+  --enable-cache-dit-summary \
+  --model BestWishYsh/Helios-Base \
+  --sample-type t2v \
+  --prompt "A dynamic time-lapse video showing the rapidly moving scenery from the window of a speeding train." \
+  --guidance-scale 5.0 \
+  --output helios_t2v_base.mp4
+```
+
+#### Verification
+
+The script should print the resolved generation configuration, total generation
+time, and output path. A successful run ends with output similar to:
+
+```text
+Total generation time: <seconds> seconds (<milliseconds> ms)
+Saved generated video to helios_t2v_base.mp4
+```
+
+#### Important flags and stage configs
+
+- `--model BestWishYsh/Helios-Base` selects the base Helios checkpoint used by
+  this recipe.
+- `--sample-type t2v` selects text-to-video generation. Use `i2v` with
+  `--image-path` for image-to-video, or `v2v` with `--video-path` for
+  video-to-video.
+- `--guidance-scale 5.0` matches the Helios-Base recommendation. Use
+  `--guidance-scale 1.0` for Helios-Distilled.
+- `--cache-backend cache_dit` enables the cache-dit acceleration path.
+- `--enable-cache-dit-summary` prints cache-dit summary information after
+  diffusion forward passes.
+- No separate stage config is required for this offline recipe; the bundled
+  Helios example configures the pipeline through `end2end.py` arguments.
+- For Helios-Mid, add `--is-enable-stage2`,
+  `--pyramid-num-inference-steps-list 20 20 20`, `--use-cfg-zero-star`,
+  `--use-zero-init`, and `--zero-steps 1`.
+- For Helios-Distilled, add `--is-enable-stage2`,
+  `--pyramid-num-inference-steps-list 2 2 2`, and
+  `--is-amplify-first-chunk`.
+
+#### Known limitations
+
+- Helios generates video in 33-frame chunks. For best performance, set
+  `--num-frames` to a multiple of `33`; non-multiple values are rounded up to
+  the nearest multiple of `33`.

recipes/README.md

@@ -30,6 +30,7 @@ recipes/
 | [`audiox/AudioX.md`](./audiox/AudioX.md) | Offline + online unified text/video→audio diffusion | 1x L4 24GB |
 | [`Baidu/ERNIE-Image.md`](./Baidu/ERNIE-Image.md) | Text-to-image online serving (ERNIE-Image 8B) | 1x or 2x RTX 4090 24GB |
 | [`fishaudio/Fish-Speech-S2-Pro.md`](./fishaudio/Fish-Speech-S2-Pro.md) | Online serving for TTS | 1x A800 80GB |
+| [`Helios/Helios.md`](./Helios/Helios.md) | Text-to-video, image-to-video, and video-to-video generation | 1x NVIDIA H20 |
 | [`inclusionAI/Ming-flash-omni-2.0.md`](./inclusionAI/Ming-flash-omni-2.0.md) | Online serving for multimodal chat + standalone TTS | 4x H100 / 1x H100 80GB |
 | [`LTX/LTX-2.md`](./LTX/LTX-2.md) | Text-to-video and image-to-video serving | 1x H200 141GB |
 | [`LTX/LTX-2.3.md`](./LTX/LTX-2.3.md) | Text-to-video with audio generation (22B) | 1x GPU (96GB VRAM) |
@@ -44,9 +45,7 @@ recipes/
 | [`Wan-AI/Wan2.2-I2V.md`](./Wan-AI/Wan2.2-I2V.md) | Image-to-video serving (Wan2.2 14B) | 8x Ascend NPU (A2/A3) |
 | [`Wan-AI/Wan2.2-S2V.md`](./Wan-AI/Wan2.2-S2V.md) | Speech-to-video serving (Wan2.2 14B) | 2x A100/H100 80GB |
 | [`zai-org/GLM-TTS.md`](./zai-org/GLM-TTS.md) | Online serving for Chinese/English zero-shot voice-cloned TTS | 1x A40 48GB |
-
-- [`GLM/GLM-Image.md`](./GLM/GLM-Image.md):online serving recipe for
-  image generation on `1x A800 80GB` and `2x A800 80GB`
+| [`GLM/GLM-Image.md`](./GLM/GLM-Image.md) | Online serving for image generation | 1x A800 80GB / 2x A800 80GB |
 
 Within a single recipe file, include different hardware support sections such
 as `GPU`, `ROCm`, and `NPU`, and add concrete tested configurations like