From c94ce4d85fe3db56e07fb4c7a9e64c87ce80d7e4 Mon Sep 17 00:00:00 2001
From: Zeyu Huang <11222265+fhfuih@users.noreply.github.com>
Date: Wed, 31 Dec 2025 18:34:02 +0800
Subject: [PATCH] [Doc] complete the clarification on batch image generation
 (#567)

Signed-off-by: Huang, Zeyu <11222265+fhfuih@users.noreply.github.com>
---
 .../offline_inference/text_to_image.md        | 17 +++++++++++++++++
 .../offline_inference/text_to_image/README.md | 19 +++++++++++++++++++
 2 files changed, 36 insertions(+)

diff --git a/docs/user_guide/examples/offline_inference/text_to_image.md b/docs/user_guide/examples/offline_inference/text_to_image.md
index fbc62526b..cf5cdf860 100644
--- a/docs/user_guide/examples/offline_inference/text_to_image.md
+++ b/docs/user_guide/examples/offline_inference/text_to_image.md
@@ -23,6 +23,23 @@ if __name__ == "__main__":
     images[0].save("coffee.png")
 ```
 
+Or put more than one prompt in a request, processing them sequentially.
+
+```python
+from vllm_omni.entrypoints.omni import Omni
+
+if __name__ == "__main__":
+    omni = Omni(model="Qwen/Qwen-Image")
+    prompts = [
+      "a cup of coffee on a table",
+      "a toy dinosaur on a sandy beach",
+      "a fox waking up in bed and yawning",
+    ]
+    outputs = omni.generate(prompts)
+    for i, output in enumerate(outputs):
+      image = output.request_output[0]["images"][0].save(f"{i}.jpg")
+```
+
 ## Local CLI Usage
 
 ```bash
diff --git a/examples/offline_inference/text_to_image/README.md b/examples/offline_inference/text_to_image/README.md
index 21358f333..2403c4139 100644
--- a/examples/offline_inference/text_to_image/README.md
+++ b/examples/offline_inference/text_to_image/README.md
@@ -5,6 +5,8 @@ This folder provides several entrypoints for experimenting with `Qwen/Qwen-Image
 - `text_to_image.py`: command-line script for single image generation with advanced options.
 - `web_demo.py`: lightweight Gradio UI for interactive prompt/seed/CFG exploration.
 
+Note that when you pass in multiple independent prompts, they will be processed sequentially. Batching requests is currently not supported.
+
 ## Basic Usage
 
 ```python
@@ -18,6 +20,23 @@ if __name__ == "__main__":
     images[0].save("coffee.png")
 ```
 
+Or put more than one prompt in a request, processing them sequentially.
+
+```python
+from vllm_omni.entrypoints.omni import Omni
+
+if __name__ == "__main__":
+    omni = Omni(model="Qwen/Qwen-Image")
+    prompts = [
+      "a cup of coffee on a table",
+      "a toy dinosaur on a sandy beach",
+      "a fox waking up in bed and yawning",
+    ]
+    outputs = omni.generate(prompts)
+    for i, output in enumerate(outputs):
+      image = output.request_output[0]["images"][0].save(f"{i}.jpg")
+```
+
 ## Local CLI Usage
 
 ```bash