[Docs] Remove stale stage config references (#6270)

Signed-off-by: zwhzzz0821 <2831474076@qq.com>

docs/user_guide/diffusion/execution_modes.md

@@ -207,18 +207,16 @@ outputs = omni.generate(
 )
 ```
 
-## Stage Configuration
+## Deploy Configuration
 
 Use the equivalent engine arguments in a deployment YAML:
 
 ```yaml
-stage_args:
+stages:
   - stage_id: 0
-    stage_type: diffusion
-    engine_args:
-      step_execution: false
-      max_num_seqs: 4
-      request_batch_max_wait_ms: 20
+    step_execution: false
+    max_num_seqs: 4
+    request_batch_max_wait_ms: 20
 ```
 
 For step execution, set `step_execution: true` and remove

docs/user_guide/diffusion/regional_compilation.md

@@ -24,7 +24,7 @@ stages:
 
 For an experimental whole-transformer compile scope, set
 `--diffusion-compile-granularity full` or use
-`diffusion_compile_granularity: full` in the stage configuration. Full scope may
+`diffusion_compile_granularity: full` in the deploy configuration. Full scope may
 still contain graph breaks; it does not force one graph. It is rejected when
 HSDP, sequence parallelism, CPU offload, or layerwise offload is enabled. Use
 regional scope with those features.

docs/user_guide/examples/offline_inference/mimo_audio.md

@@ -22,7 +22,7 @@ MiMo-Audio provides multiple task variants for audio understanding and generatio
 
 ## Setup
 
-Please refer to the [stage configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) to configure memory allocation appropriately for your hardware setup.
+See the [pipeline and deploy configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) to configure memory allocation for your hardware.
 
 ### Environment Variables
 
@@ -188,7 +188,7 @@ Note: This task uses hardcoded message lists in the script.
 
 ### Other
 
-- If the model or stage config fails to load, check [stage configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) for memory and GPU settings.
+- If the model or deploy config fails to load, check the [pipeline and deploy configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) for memory and GPU settings.
 - For errors when reading/writing WAV (e.g. unsupported format), ensure input files are standard WAV/MP3 and that `soundfile` is linked to a working libsndfile (see above).
 
 ## Notes

docs/user_guide/examples/offline_inference/qwen2_5_omni.md

@@ -4,7 +4,7 @@ Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inf
 
 
 ## Setup
-Please refer to the [stage configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) to configure memory allocation appropriately for your hardware setup.
+See the [pipeline and deploy configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) to configure memory allocation for your hardware.
 
 ## Run examples
 

docs/user_guide/examples/offline_inference/qwen3_omni.md

@@ -4,7 +4,8 @@ Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inf
 
 
 ## Setup
-Please refer to the [stage configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/) to configure memory allocation appropriately for your hardware setup.
+Use `--deploy-config` for deployment overrides such as stage memory allocation.
+See the [pipeline and deploy configuration documentation](https://docs.vllm.ai/projects/vllm-omni/en/latest/configuration/stage_configs/).
 
 ## Run examples
 
@@ -73,8 +74,8 @@ For true stage-level concurrency -- where downstream stages (Talker, Code2Wav)
 start **before** the upstream stage (Thinker) finishes -- use the async_chunk
 example. This requires:
 
-1. A stage config YAML with ``async_chunk: true`` (e.g.
-   ``qwen3_omni_moe_async_chunk.yaml``).
+1. A deploy YAML with ``async_chunk: true`` (for example, an overlay based on
+   ``vllm_omni/deploy/qwen3_omni_moe.yaml``).
 2. Hardware that matches the config (e.g. 2x H100 for the default 3-stage
    config).
 
@@ -100,11 +101,11 @@ bash run_multiple_prompts_async_chunk.sh --max-in-flight 4
 python end2end_async_chunk.py --query-type text --modalities text
 ```
 
-#### Custom stage config
+#### Custom deploy config
 ```bash
 python end2end_async_chunk.py \
     --query-type use_audio \
-    --stage-configs-path /path/to/your_async_chunk.yaml
+    --deploy-config /path/to/your_async_chunk.yaml
 ```
 
 > **Note**: The synchronous ``end2end.py`` (using ``Omni``) is still the

docs/user_guide/examples/offline_inference/text_to_speech.md

@@ -69,7 +69,7 @@ python examples/offline_inference/text_to_speech/voxcpm2/end2end.py \
 
 ### Notes
 - Output: 48 kHz mono WAV.
-- Stage config: `vllm_omni/model_executor/stage_configs/voxcpm2.yaml` (default).
+- Deploy config: `vllm_omni/deploy/voxcpm2.yaml` (default).
 
 ---
 
@@ -152,7 +152,7 @@ python examples/offline_inference/text_to_speech/fish_speech/end2end.py \
     --text "Hello, this is a streaming test." \
     --streaming
 ```
-Streaming requires `async_chunk: true` in the stage config.
+Streaming requires `async_chunk: true` in the deploy config.
 
 ### Notes
 - Output: 44.1 kHz mono WAV.
@@ -274,7 +274,7 @@ python examples/offline_inference/text_to_speech/qwen3_tts/end2end.py \
     --streaming \
     --output-dir /tmp/out_stream
 ```
-Streaming requires `async_chunk: true` in the stage config.
+Streaming requires `async_chunk: true` in the deploy config.
 
 ### Batched decoding
 The Code2Wav stage supports batched decoding through the SpeechTokenizer. Configure both stages with `max_num_seqs > 1` via `--stage-overrides` and pass multiple prompts via `--txt-prompts`:

docs/user_guide/examples/online_serving/qwen3_omni.md

@@ -271,7 +271,7 @@ The script supports the following arguments:
 vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
 ```
 
-If you have custom stage configs file:
+If you have a custom deploy config file:
 ```bash
 vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 --deploy-config /path/to/deploy_config_file
 ```

docs/user_guide/examples/online_serving/text_to_speech.md

@@ -419,7 +419,7 @@ curl -X POST http://localhost:8091/v1/audio/speech \
         "response_format": "pcm"
     }' --no-buffer | play -t raw -r 24000 -e signed -b 16 -c 1 -
 ```
-Raw PCM streaming requires `stream_format="audio"`, `response_format="pcm"`, and `async_chunk: true` on the stage config (default in `qwen3_tts.yaml`). `speed` is not supported when streaming.
+Raw PCM streaming requires `stream_format="audio"`, `response_format="pcm"`, and `async_chunk: true` in the deploy config (default in `qwen3_tts.yaml`). `speed` is not supported when streaming.
 
 ### Streaming WebSocket
 The `/v1/audio/speech/stream` endpoint accepts text incrementally and synthesizes the buffered text as one continuous request on `input.done`:

docs/user_guide/quantization/fp8.md

@@ -92,7 +92,7 @@ warmup_quack_fp8([(14040, 2048, 6144), (14040, 2048, 2048)])
 | FLUX.1 | `black-forest-labs/FLUX.1-dev`, `black-forest-labs/FLUX.1-schnell` | Yes | Yes | All layers | None | |
 | FLUX.2-dev | `black-forest-labs/FLUX.2-dev` | Yes | Not validated | All layers | None | ✅︎ |
 | FLUX.2-klein | `black-forest-labs/FLUX.2-klein-4B` | Yes | Yes | All layers | None | |
-| HunyuanImage-3.0 | `tencent/HunyuanImage-3.0`, `tencent/HunyuanImage-3.0-Instruct` | Yes | Yes | All layers; use the Hunyuan stage config for multi-stage runs | None | |
+| HunyuanImage-3.0 | `tencent/HunyuanImage-3.0`, `tencent/HunyuanImage-3.0-Instruct` | Yes | Yes | All layers; use the Hunyuan deploy config for multi-stage runs | None | |
 | HunyuanVideo-1.5 | `hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_t2v`, `720p_t2v`, `480p_i2v` | Yes | Yes | All layers | None | |
 | Cosmos3 | `nvidia/Cosmos3-Nano`, `nvidia/Cosmos3-Super` | Yes | Not validated | All layers | None | |
 | MiniMax-H3 | `MiniMaxAI/MiniMax-H3` (`FL2VA` / `Ref2VA`) | Yes | Not validated | `quantization="fp8"` quantizes eligible DiT and text-encoder linears; mixed-precision input/output heads stay FP32 | None | ✅︎ |

docs/user_guide/quantization/msmodelslim.md

@@ -92,4 +92,4 @@ For HunyuanImage-3.0, use the Hunyuan-specific adaptation linked above.
 2. The `ascend` quantization method expects weights produced by the Ascend
    tooling; it is not a load-time CUDA quantizer.
 3. Keep the quantized checkpoint aligned with the same model architecture and
-   stage config used for BF16 inference.
+   pipeline and deploy config used for BF16 inference.

docs/user_guide/quantization/quantized_kvcache.md

@@ -83,23 +83,23 @@ Online serving:
 vllm serve <your-model> --omni --diffusion-kv-cache-dtype fp8
 ```
 
-Stage config:
+Deploy config:
 
 ```yaml
-stage_args:
+stages:
   - stage_id: 0
-    stage_type: diffusion
-    engine_args:
-      model_stage: dit
-      diffusion_kv_cache_dtype: "fp8"
-      diffusion_kv_cache_skip_steps: "0,1"
-      diffusion_kv_cache_skip_layers: "0-2"
+    diffusion_kv_cache_dtype: "fp8"
+    diffusion_kv_cache_skip_steps: "0,1"
+    diffusion_kv_cache_skip_layers: "0-2"
 ```
 
-Legacy YAML keys `kv_cache_dtype`, `kv_cache_skip_steps`, and
-`kv_cache_skip_layers` are still accepted when constructing
-`OmniDiffusionConfig` (for example via `from_kwargs`); prefer the `diffusion_*`
-names for new configs.
+The `model_stage` and diffusion execution type belong to the registered
+`PipelineConfig`; the deploy YAML only carries runtime overrides.
+
+The legacy keyword aliases `kv_cache_dtype`, `kv_cache_skip_steps`, and
+`kv_cache_skip_layers` remain accepted when constructing
+`OmniDiffusionConfig` directly. They are not deploy YAML fields; prefer the
+`diffusion_*` names for new code.
 
 ## Parameters