[Misc][WIP] Support qwen-omni online inference with local video/audio/image path (#131)

Signed-off-by: samithuang <285365963@qq.com>
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Samit authored and GitHub committed 2025-12-01 00:30:22 -08:00
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+53 -25
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@@ -6,7 +6,8 @@ Please refer to [README.md](../../../README.md)
## Run examples (Qwen2.5-Omni)
Launch the server
### Launch the Server
```bash
vllm serve Qwen/Qwen2.5-Omni-7B --omni --port 8091
```
@@ -16,29 +17,59 @@ If you have custom stage configs file, launch the server with command below
vllm serve Qwen/Qwen2.5-Omni-7B --omni --port 8091 --stage-configs-path /path/to/stage_configs_file
```
### Send Multi-modal Request
Get into the example folder
```bash
cd examples/online_serving/qwen2_5_omni
```
Send request via python
#### Send request via python
```bash
python openai_chat_completion_client_for_multimodal_generation.py --query-type mixed_modalities
```
Send request via curl
The Python client supports the following command-line arguments:
- `--query-type` (or `-q`): Query type (default: `mixed_modalities`)
- Options: `mixed_modalities`, `use_audio_in_video`, `multi_audios`, `text`
- `--video-path` (or `-v`): Path to local video file or URL
- If not provided and query-type uses video, uses default video URL
- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
- Example: `--video-path /path/to/video.mp4` or `--video-path https://example.com/video.mp4`
- `--image-path` (or `-i`): Path to local image file or URL
- If not provided and query-type uses image, uses default image URL
- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
- Supports common image formats: JPEG, PNG, GIF, WebP
- Example: `--image-path /path/to/image.jpg` or `--image-path https://example.com/image.png`
- `--audio-path` (or `-a`): Path to local audio file or URL
- If not provided and query-type uses audio, uses default audio URL
- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
- Supports common audio formats: MP3, WAV, OGG, FLAC, M4A
- Example: `--audio-path /path/to/audio.wav` or `--audio-path https://example.com/audio.mp3`
- `--prompt` (or `-p`): Custom text prompt/question
- If not provided, uses default prompt for the selected query type
- Example: `--prompt "What are the main activities shown in this video?"`
For example, to use mixed modalities with all local files:
```bash
python openai_chat_completion_client_for_multimodal_generation.py \
--query-type mixed_modalities \
--video-path /path/to/your/video.mp4 \
--image-path /path/to/your/image.jpg \
--audio-path /path/to/your/audio.wav \
--prompt "Analyze all the media content and provide a comprehensive summary."
```
#### Send request via curl
```bash
bash run_curl_multimodal_generation.sh mixed_modalities
```
### FAQ
If you encounter error about backend of librosa, try to install ffmpeg with command below.
```
sudo apt update
sudo apt install ffmpeg
```
## Run Local Web UI Demo
This Web UI demo allows users to interact with the model through a web browser.
@@ -53,21 +84,18 @@ python gradio_demo.py --model Qwen/Qwen2.5-Omni-7B --port 7861
Then open `http://localhost:7861/` on your local browser to interact with the web UI.
The gradio script supports the following arguments:
### Options
- `--model`: Model name
- `--ip`: Host/IP for Gradio server (default: 127.0.0.1)
- `--port`: Port for Gradio server (default: 7861)
- `--stage-configs-path`: Path to custom stage configs YAML file (optional)
- `--share`: Share the Gradio demo publicly (creates a public link)
You can customize its basic launch parameters:
### FAQ
```bash
python gradio_demo.py \
--model Qwen/Qwen2.5-Omni-7B \
--ip 127.0.0.1 \
--port 7861 \
--stage-configs-path /path/to/stage_configs.yaml
If you encounter error about backend of librosa, try to install ffmpeg with command below.
```
sudo apt update
sudo apt install ffmpeg
```
- `--model`: Local model checkpoint to load (default `Qwen/Qwen2.5-Omni-7B`).
- `--ip`: Host/IP for the Gradio server (default `127.0.0.1`).
- `--port`: Port for the Gradio server (default `7861`).
- `--stage-configs-path`: Optional path to custom stage configs YAML.
- `--share`: Set to expose a temporary public link via Gradio.
@@ -1,4 +1,6 @@
import base64
import os
from typing import Optional
import requests
from openai import OpenAI
@@ -28,6 +30,129 @@ def encode_base64_content_from_url(content_url: str) -> str:
return result
def encode_base64_content_from_file(file_path: str) -> str:
"""Encode a local file to base64 format."""
with open(file_path, "rb") as f:
content = f.read()
result = base64.b64encode(content).decode("utf-8")
return result
def get_video_url_from_path(video_path: Optional[str]) -> str:
"""Convert a video path (local file or URL) to a video URL format for the API.
If video_path is None or empty, returns the default URL.
If video_path is a local file path, encodes it to base64 data URL.
If video_path is a URL, returns it as-is.
"""
if not video_path:
# Default video URL
return "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4"
# Check if it's a URL (starts with http:// or https://)
if video_path.startswith(("http://", "https://")):
return video_path
# Otherwise, treat it as a local file path
if not os.path.exists(video_path):
raise FileNotFoundError(f"Video file not found: {video_path}")
# Detect video MIME type from file extension
video_path_lower = video_path.lower()
if video_path_lower.endswith(".mp4"):
mime_type = "video/mp4"
elif video_path_lower.endswith(".webm"):
mime_type = "video/webm"
elif video_path_lower.endswith(".mov"):
mime_type = "video/quicktime"
elif video_path_lower.endswith(".avi"):
mime_type = "video/x-msvideo"
elif video_path_lower.endswith(".mkv"):
mime_type = "video/x-matroska"
else:
# Default to mp4 if extension is unknown
mime_type = "video/mp4"
video_base64 = encode_base64_content_from_file(video_path)
return f"data:{mime_type};base64,{video_base64}"
def get_image_url_from_path(image_path: Optional[str]) -> str:
"""Convert an image path (local file or URL) to an image URL format for the API.
If image_path is None or empty, returns the default URL.
If image_path is a local file path, encodes it to base64 data URL.
If image_path is a URL, returns it as-is.
"""
if not image_path:
# Default image URL
return "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/cherry_blossom.jpg"
# Check if it's a URL (starts with http:// or https://)
if image_path.startswith(("http://", "https://")):
return image_path
# Otherwise, treat it as a local file path
if not os.path.exists(image_path):
raise FileNotFoundError(f"Image file not found: {image_path}")
# Detect image MIME type from file extension
image_path_lower = image_path.lower()
if image_path_lower.endswith((".jpg", ".jpeg")):
mime_type = "image/jpeg"
elif image_path_lower.endswith(".png"):
mime_type = "image/png"
elif image_path_lower.endswith(".gif"):
mime_type = "image/gif"
elif image_path_lower.endswith(".webp"):
mime_type = "image/webp"
else:
# Default to jpeg if extension is unknown
mime_type = "image/jpeg"
image_base64 = encode_base64_content_from_file(image_path)
return f"data:{mime_type};base64,{image_base64}"
def get_audio_url_from_path(audio_path: Optional[str]) -> str:
"""Convert an audio path (local file or URL) to an audio URL format for the API.
If audio_path is None or empty, returns the default URL.
If audio_path is a local file path, encodes it to base64 data URL.
If audio_path is a URL, returns it as-is.
"""
if not audio_path:
# Default audio URL
return AudioAsset("mary_had_lamb").url
# Check if it's a URL (starts with http:// or https://)
if audio_path.startswith(("http://", "https://")):
return audio_path
# Otherwise, treat it as a local file path
if not os.path.exists(audio_path):
raise FileNotFoundError(f"Audio file not found: {audio_path}")
# Detect audio MIME type from file extension
audio_path_lower = audio_path.lower()
if audio_path_lower.endswith((".mp3", ".mpeg")):
mime_type = "audio/mpeg"
elif audio_path_lower.endswith(".wav"):
mime_type = "audio/wav"
elif audio_path_lower.endswith(".ogg"):
mime_type = "audio/ogg"
elif audio_path_lower.endswith(".flac"):
mime_type = "audio/flac"
elif audio_path_lower.endswith(".m4a"):
mime_type = "audio/mp4"
else:
# Default to wav if extension is unknown
mime_type = "audio/wav"
audio_base64 = encode_base64_content_from_file(audio_path)
return f"data:{mime_type};base64,{audio_base64}"
def get_system_prompt():
return {
"role": "system",
@@ -44,8 +169,10 @@ def get_system_prompt():
}
def get_text_query():
question = "Explain the system architecture for a scalable audio generation pipeline. Answer in 15 words."
def get_text_query(custom_prompt: Optional[str] = None):
question = (
custom_prompt or "Explain the system architecture for a scalable audio generation pipeline. Answer in 15 words."
)
prompt = {
"role": "user",
"content": [
@@ -58,26 +185,32 @@ def get_text_query():
return prompt
def get_mixed_modalities_query():
question = "What is recited in the audio? What is the content of this image? Why is this video funny?"
def get_mixed_modalities_query(
video_path: Optional[str] = None,
image_path: Optional[str] = None,
audio_path: Optional[str] = None,
custom_prompt: Optional[str] = None,
):
question = (
custom_prompt or "What is recited in the audio? What is the content of this image? Why is this video funny?"
)
video_url = get_video_url_from_path(video_path)
image_url = get_image_url_from_path(image_path)
audio_url = get_audio_url_from_path(audio_path)
prompt = {
"role": "user",
"content": [
{
"type": "audio_url",
"audio_url": {"url": AudioAsset("mary_had_lamb").url},
"audio_url": {"url": audio_url},
},
{
"type": "image_url",
"image_url": {
"url": "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/cherry_blossom.jpg"
},
"image_url": {"url": image_url},
},
{
"type": "video_url",
"video_url": {
"url": "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4"
},
"video_url": {"url": video_url},
},
{
"type": "text",
@@ -89,8 +222,9 @@ def get_mixed_modalities_query():
return prompt
def get_use_audio_in_video_query():
question = "Describe the content of the video, then convert what the baby say into text."
def get_use_audio_in_video_query(video_path: Optional[str] = None, custom_prompt: Optional[str] = None):
question = custom_prompt or "Describe the content of the video, then convert what the baby say into text."
video_url = get_video_url_from_path(video_path)
prompt = {
"role": "user",
@@ -98,7 +232,7 @@ def get_use_audio_in_video_query():
{
"type": "video_url",
"video_url": {
"url": "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4",
"url": video_url,
"num_frames": 16,
},
},
@@ -112,14 +246,15 @@ def get_use_audio_in_video_query():
return prompt
def get_multi_audios_query():
question = "Are these two audio clips the same?"
def get_multi_audios_query(audio_path: Optional[str] = None, custom_prompt: Optional[str] = None):
question = custom_prompt or "Are these two audio clips the same?"
audio_url = get_audio_url_from_path(audio_path)
prompt = {
"role": "user",
"content": [
{
"type": "audio_url",
"audio_url": {"url": AudioAsset("mary_had_lamb").url},
"audio_url": {"url": audio_url},
},
{
"type": "audio_url",
@@ -179,7 +314,27 @@ def run_multimodal_generation(args) -> None:
code2wav_sampling_params,
]
prompt = query_map[args.query_type]()
# Get paths and custom prompt from args
video_path = getattr(args, "video_path", None)
image_path = getattr(args, "image_path", None)
audio_path = getattr(args, "audio_path", None)
custom_prompt = getattr(args, "prompt", None)
# Get the query function and call it with appropriate parameters
query_func = query_map[args.query_type]
if args.query_type == "mixed_modalities":
prompt = query_func(
video_path=video_path, image_path=image_path, audio_path=audio_path, custom_prompt=custom_prompt
)
elif args.query_type == "use_audio_in_video":
prompt = query_func(video_path=video_path, custom_prompt=custom_prompt)
elif args.query_type == "multi_audios":
prompt = query_func(audio_path=audio_path, custom_prompt=custom_prompt)
elif args.query_type == "text":
prompt = query_func(custom_prompt=custom_prompt)
else:
prompt = query_func()
extra_body = {
"sampling_params_list": sampling_params_list # Optional, it has a default setting in stage_configs of the corresponding model.
}
@@ -219,6 +374,34 @@ def parse_args():
choices=query_map.keys(),
help="Query type.",
)
parser.add_argument(
"--video-path",
"-v",
type=str,
default=None,
help="Path to local video file or URL. If not provided and query-type uses video, uses default video URL.",
)
parser.add_argument(
"--image-path",
"-i",
type=str,
default=None,
help="Path to local image file or URL. If not provided and query-type uses image, uses default image URL.",
)
parser.add_argument(
"--audio-path",
"-a",
type=str,
default=None,
help="Path to local audio file or URL. If not provided and query-type uses audio, uses default audio URL.",
)
parser.add_argument(
"--prompt",
"-p",
type=str,
default=None,
help="Custom text prompt/question to use instead of the default prompt for the selected query type.",
)
return parser.parse_args()
+43 -18
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@@ -6,7 +6,8 @@ Please refer to [README.md](../../../README.md)
## Run examples (Qwen3-Omni)
Launch the server
### Launch the Server
```bash
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
```
@@ -16,21 +17,59 @@ If you have custom stage configs file, launch the server with command below
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 --stage-configs-path /path/to/stage_configs_file
```
### Send Multi-modal Request
Get into the example folder
```bash
cd examples/online_serving/qwen3_omni
```
Send request via python
#### Send request via python
```bash
python openai_chat_completion_client_for_multimodal_generation.py --query-type use_image
```
Send request via curl
The Python client supports the following command-line arguments:
- `--query-type` (or `-q`): Query type (default: `use_video`)
- Options: `text`, `use_audio`, `use_image`, `use_video`
- `--model` (or `-m`): Model name/path (default: `Qwen/Qwen3-Omni-30B-A3B-Instruct`)
- `--video-path` (or `-v`): Path to local video file or URL
- If not provided and query-type is `use_video`, uses default video URL
- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
- Example: `--video-path /path/to/video.mp4` or `--video-path https://example.com/video.mp4`
- `--image-path` (or `-i`): Path to local image file or URL
- If not provided and query-type is `use_image`, uses default image URL
- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
- Supports common image formats: JPEG, PNG, GIF, WebP
- Example: `--image-path /path/to/image.jpg` or `--image-path https://example.com/image.png`
- `--audio-path` (or `-a`): Path to local audio file or URL
- If not provided and query-type is `use_audio`, uses default audio URL
- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
- Supports common audio formats: MP3, WAV, OGG, FLAC, M4A
- Example: `--audio-path /path/to/audio.wav` or `--audio-path https://example.com/audio.mp3`
- `--prompt` (or `-p`): Custom text prompt/question
- If not provided, uses default prompt for the selected query type
- Example: `--prompt "What are the main activities shown in this video?"`
For example, to use a local video file with custom prompt:
```bash
python openai_chat_completion_client_for_multimodal_generation.py \
--query-type use_video \
--video-path /path/to/your/video.mp4 \
--prompt "What are the main activities shown in this video?"
```
#### Send request via curl
```bash
bash run_curl_multimodal_generation.sh use_image
```
### FAQ
If you encounter error about backend of librosa, try to install ffmpeg with command below.
@@ -54,23 +93,9 @@ python gradio_demo.py --model Qwen/Qwen3-Omni-30B-A3B-Instruct --port 7861
Then open `http://localhost:7861/` on your local browser to interact with the web UI.
### Options
The gradio demo also supports running with an existing API server and can be customized with the following arguments.
```bash
python gradio_demo.py \
--model Qwen/Qwen3-Omni-30B-A3B-Instruct \
--use-api-server \
--api-base http://localhost:8091/v1 \
--ip 127.0.0.1 \
--port 7861
```
The gradio script supports the following arguments:
- `--model`: Model name
- `--use-api-server`: If set, connect to an existing vLLM HTTP API server instead of running AsyncOmni locally.
- `--api-base`: Base URL for vllm serve (only used when `use-api-server` is set, default: http://localhost:8091/v1)
- `--ip`: Host/IP for Gradio server (default: 127.0.0.1)
- `--port`: Port for Gradio server (default: 7861)
- `--stage-configs-path`: Path to custom stage configs YAML file (optional)
@@ -1,5 +1,6 @@
import base64
from typing import NamedTuple
import os
from typing import NamedTuple, Optional
import requests
from openai import OpenAI
@@ -34,6 +35,129 @@ def encode_base64_content_from_url(content_url: str) -> str:
return result
def encode_base64_content_from_file(file_path: str) -> str:
"""Encode a local file to base64 format."""
with open(file_path, "rb") as f:
content = f.read()
result = base64.b64encode(content).decode("utf-8")
return result
def get_video_url_from_path(video_path: Optional[str]) -> str:
"""Convert a video path (local file or URL) to a video URL format for the API.
If video_path is None or empty, returns the default URL.
If video_path is a local file path, encodes it to base64 data URL.
If video_path is a URL, returns it as-is.
"""
if not video_path:
# Default video URL
return "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4"
# Check if it's a URL (starts with http:// or https://)
if video_path.startswith(("http://", "https://")):
return video_path
# Otherwise, treat it as a local file path
if not os.path.exists(video_path):
raise FileNotFoundError(f"Video file not found: {video_path}")
# Detect video MIME type from file extension
video_path_lower = video_path.lower()
if video_path_lower.endswith(".mp4"):
mime_type = "video/mp4"
elif video_path_lower.endswith(".webm"):
mime_type = "video/webm"
elif video_path_lower.endswith(".mov"):
mime_type = "video/quicktime"
elif video_path_lower.endswith(".avi"):
mime_type = "video/x-msvideo"
elif video_path_lower.endswith(".mkv"):
mime_type = "video/x-matroska"
else:
# Default to mp4 if extension is unknown
mime_type = "video/mp4"
video_base64 = encode_base64_content_from_file(video_path)
return f"data:{mime_type};base64,{video_base64}"
def get_image_url_from_path(image_path: Optional[str]) -> str:
"""Convert an image path (local file or URL) to an image URL format for the API.
If image_path is None or empty, returns the default URL.
If image_path is a local file path, encodes it to base64 data URL.
If image_path is a URL, returns it as-is.
"""
if not image_path:
# Default image URL
return "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/cherry_blossom.jpg"
# Check if it's a URL (starts with http:// or https://)
if image_path.startswith(("http://", "https://")):
return image_path
# Otherwise, treat it as a local file path
if not os.path.exists(image_path):
raise FileNotFoundError(f"Image file not found: {image_path}")
# Detect image MIME type from file extension
image_path_lower = image_path.lower()
if image_path_lower.endswith((".jpg", ".jpeg")):
mime_type = "image/jpeg"
elif image_path_lower.endswith(".png"):
mime_type = "image/png"
elif image_path_lower.endswith(".gif"):
mime_type = "image/gif"
elif image_path_lower.endswith(".webp"):
mime_type = "image/webp"
else:
# Default to jpeg if extension is unknown
mime_type = "image/jpeg"
image_base64 = encode_base64_content_from_file(image_path)
return f"data:{mime_type};base64,{image_base64}"
def get_audio_url_from_path(audio_path: Optional[str]) -> str:
"""Convert an audio path (local file or URL) to an audio URL format for the API.
If audio_path is None or empty, returns the default URL.
If audio_path is a local file path, encodes it to base64 data URL.
If audio_path is a URL, returns it as-is.
"""
if not audio_path:
# Default audio URL
return AudioAsset("mary_had_lamb").url
# Check if it's a URL (starts with http:// or https://)
if audio_path.startswith(("http://", "https://")):
return audio_path
# Otherwise, treat it as a local file path
if not os.path.exists(audio_path):
raise FileNotFoundError(f"Audio file not found: {audio_path}")
# Detect audio MIME type from file extension
audio_path_lower = audio_path.lower()
if audio_path_lower.endswith((".mp3", ".mpeg")):
mime_type = "audio/mpeg"
elif audio_path_lower.endswith(".wav"):
mime_type = "audio/wav"
elif audio_path_lower.endswith(".ogg"):
mime_type = "audio/ogg"
elif audio_path_lower.endswith(".flac"):
mime_type = "audio/flac"
elif audio_path_lower.endswith(".m4a"):
mime_type = "audio/mp4"
else:
# Default to wav if extension is unknown
mime_type = "audio/wav"
audio_base64 = encode_base64_content_from_file(audio_path)
return f"data:{mime_type};base64,{audio_base64}"
def get_system_prompt():
return {
"role": "system",
@@ -50,8 +174,10 @@ def get_system_prompt():
}
def get_text_query():
question = "Explain the system architecture for a scalable audio generation pipeline. Answer in 15 words."
def get_text_query(custom_prompt: Optional[str] = None):
question = (
custom_prompt or "Explain the system architecture for a scalable audio generation pipeline. Answer in 15 words."
)
prompt = {
"role": "user",
"content": [
@@ -71,16 +197,15 @@ default_system = (
)
def get_video_query() -> QueryResult:
question = "Why is this video funny?"
def get_video_query(video_path: Optional[str] = None, custom_prompt: Optional[str] = None):
question = custom_prompt or "Why is this video funny?"
video_url = get_video_url_from_path(video_path)
prompt = {
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4"
},
"video_url": {"url": video_url},
},
{
"type": "text",
@@ -91,16 +216,15 @@ def get_video_query() -> QueryResult:
return prompt
def get_image_query() -> QueryResult:
question = "What is the content of this image?"
def get_image_query(image_path: Optional[str] = None, custom_prompt: Optional[str] = None):
question = custom_prompt or "What is the content of this image?"
image_url = get_image_url_from_path(image_path)
prompt = {
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/cherry_blossom.jpg"
},
"image_url": {"url": image_url},
},
{
"type": "text",
@@ -111,14 +235,15 @@ def get_image_query() -> QueryResult:
return prompt
def get_audio_query() -> QueryResult:
question = "What is the content of this audio?"
def get_audio_query(audio_path: Optional[str] = None, custom_prompt: Optional[str] = None):
question = custom_prompt or "What is the content of this audio?"
audio_url = get_audio_url_from_path(audio_path)
prompt = {
"role": "user",
"content": [
{
"type": "audio_url",
"audio_url": {"url": AudioAsset("mary_had_lamb").url},
"audio_url": {"url": audio_url},
},
{
"type": "text",
@@ -178,7 +303,25 @@ def run_multimodal_generation(args) -> None:
code2wav_sampling_params,
]
prompt = query_map[args.query_type]()
# Get paths and custom prompt from args
video_path = getattr(args, "video_path", None)
image_path = getattr(args, "image_path", None)
audio_path = getattr(args, "audio_path", None)
custom_prompt = getattr(args, "prompt", None)
# Get the query function and call it with appropriate parameters
query_func = query_map[args.query_type]
if args.query_type == "use_video":
prompt = query_func(video_path=video_path, custom_prompt=custom_prompt)
elif args.query_type == "use_image":
prompt = query_func(image_path=image_path, custom_prompt=custom_prompt)
elif args.query_type == "use_audio":
prompt = query_func(audio_path=audio_path, custom_prompt=custom_prompt)
elif args.query_type == "text":
prompt = query_func(custom_prompt=custom_prompt)
else:
prompt = query_func()
extra_body = {
"sampling_params_list": sampling_params_list # Optional, it has a default setting in stage_configs of the corresponding model.
}
@@ -225,6 +368,34 @@ def parse_args():
default="Qwen/Qwen3-Omni-30B-A3B-Instruct",
help="Model Name / Path",
)
parser.add_argument(
"--video-path",
"-v",
type=str,
default=None,
help="Path to local video file or URL. If not provided and query-type is 'use_video', uses default video URL.",
)
parser.add_argument(
"--image-path",
"-i",
type=str,
default=None,
help="Path to local image file or URL. If not provided and query-type is 'use_image', uses default image URL.",
)
parser.add_argument(
"--audio-path",
"-a",
type=str,
default=None,
help="Path to local audio file or URL. If not provided and query-type is 'use_audio', uses default audio URL.",
)
parser.add_argument(
"--prompt",
"-p",
type=str,
default=None,
help="Custom text prompt/question to use instead of the default prompt for the selected query type.",
)
return parser.parse_args()