[BugFix] Readme and example runner file for cosyvoice3 missed in refactoring (#1685)

Signed-off-by: dsinghvi <divyanshsinghvi@gmail.com>
Signed-off-by: Divyansh Singhvi <divyanshsinghvi@gmail.com>
Co-authored-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>

docs/user_guide/examples/offline_inference/cosyvoice3.md

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+# CosyVoice3
+
+Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/cosyvoice3>.
+
+
+## Setup
+
+Install dependencies:
+```
+uv pip install -e .
+```
+
+> **Note:** This includes required libraries such as `librosa`, `soundfile`,
+> `onnxruntime`, `x-transformers`, and `einops` via
+> `requirements/common.txt` and platform-specific requirements files.
+
+Download the model snapshot:
+```
+from huggingface_hub import snapshot_download
+snapshot_download('FunAudioLLM/Fun-CosyVoice3-0.5B-2512', local_dir='pretrained_models/Fun-CosyVoice3-0.5B')
+```
+
+Add `config.json` in `pretrained_models/Fun-CosyVoice3-0.5B/`:
+```json
+{
+    "model_type": "cosyvoice3",
+    "architectures": [
+        "CosyVoice3Model"
+    ]
+}
+```
+
+> **Why `config.json` is required:**
+> `AutoConfig.register("cosyvoice3", CosyVoice3Config)` only registers a class mapping.
+> The loader still needs `model_type: "cosyvoice3"` from `config.json` to select that class.
+> If no `config.json` is present, model type cannot be inferred automatically.
+> If your downloaded checkpoint already includes a valid `config.json` with
+> `model_type: "cosyvoice3"`, this manual step can be skipped.
+
+Run the offline verification script:
+```
+python examples/offline_inference/cosyvoice3/verify_e2e_cosyvoice.py \
+  --model pretrained_models/Fun-CosyVoice3-0.5B \
+  --tokenizer pretrained_models/Fun-CosyVoice3-0.5B/CosyVoice-BlankEN
+```
+
+## Implementation Overview
+
+CosyVoice3 runs as a **2-stage Omni pipeline**.
+
+- **Stage 0** (`talker`) converts text + prompt audio to speech tokens.
+- **Stage 1** (`code2wav`) converts speech tokens + prompt features to waveform via flow matching and HiFiGAN.
+
+Key components live in `vllm_omni/model_executor/models/cosyvoice3/cosyvoice3.py`.
+
+- `CosyVoice3MultiModalProcessor` builds the multimodal inputs:
+    - Tokenizes `prompt` and `prompt_text`.
+    - Extracts speech tokens and mel features from the prompt audio.
+    - Extracts a speaker embedding.
+- `CosyVoice3Model` implements both stages:
+    - Stage 0 uses `CosyVoice3LM` and outputs speech tokens + conditioning features.
+    - Stage 1 runs the flow model (DiT-based CFM) and HiFiGAN to synthesize waveform.
+
+Stage wiring is configured in `vllm_omni/model_executor/stage_configs/cosyvoice3.yaml`.
+
+- Stage 0 emits latent speech tokens.
+- Stage 1 consumes them via `custom_process_input_func` and outputs audio.
+
+## Example materials
+
+??? abstract "verify_e2e_cosyvoice.py"
+    ``````py
+    --8<-- "examples/offline_inference/cosyvoice3/verify_e2e_cosyvoice.py"
+    ``````