[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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@@ -6,7 +6,8 @@ Please refer to [README.md](../../../README.md)
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## Run examples (Qwen2.5-Omni)
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Launch the server
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### Launch the Server
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```bash
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vllm serve Qwen/Qwen2.5-Omni-7B --omni --port 8091
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```
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@@ -16,29 +17,59 @@ If you have custom stage configs file, launch the server with command below
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vllm serve Qwen/Qwen2.5-Omni-7B --omni --port 8091 --stage-configs-path /path/to/stage_configs_file
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```
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### Send Multi-modal Request
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Get into the example folder
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```bash
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cd examples/online_serving/qwen2_5_omni
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```
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Send request via python
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#### Send request via python
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```bash
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python openai_chat_completion_client_for_multimodal_generation.py --query-type mixed_modalities
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```
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Send request via curl
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The Python client supports the following command-line arguments:
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- `--query-type` (or `-q`): Query type (default: `mixed_modalities`)
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- Options: `mixed_modalities`, `use_audio_in_video`, `multi_audios`, `text`
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- `--video-path` (or `-v`): Path to local video file or URL
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- If not provided and query-type uses video, uses default video URL
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- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
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- Example: `--video-path /path/to/video.mp4` or `--video-path https://example.com/video.mp4`
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- `--image-path` (or `-i`): Path to local image file or URL
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- If not provided and query-type uses image, uses default image URL
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- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
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- Supports common image formats: JPEG, PNG, GIF, WebP
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- Example: `--image-path /path/to/image.jpg` or `--image-path https://example.com/image.png`
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- `--audio-path` (or `-a`): Path to local audio file or URL
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- If not provided and query-type uses audio, uses default audio URL
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- Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
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- Supports common audio formats: MP3, WAV, OGG, FLAC, M4A
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- Example: `--audio-path /path/to/audio.wav` or `--audio-path https://example.com/audio.mp3`
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- `--prompt` (or `-p`): Custom text prompt/question
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- If not provided, uses default prompt for the selected query type
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- Example: `--prompt "What are the main activities shown in this video?"`
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For example, to use mixed modalities with all local files:
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```bash
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python openai_chat_completion_client_for_multimodal_generation.py \
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--query-type mixed_modalities \
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--video-path /path/to/your/video.mp4 \
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--image-path /path/to/your/image.jpg \
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--audio-path /path/to/your/audio.wav \
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--prompt "Analyze all the media content and provide a comprehensive summary."
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```
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#### Send request via curl
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```bash
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bash run_curl_multimodal_generation.sh mixed_modalities
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```
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### FAQ
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If you encounter error about backend of librosa, try to install ffmpeg with command below.
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```
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sudo apt update
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sudo apt install ffmpeg
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```
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## Run Local Web UI Demo
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This Web UI demo allows users to interact with the model through a web browser.
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@@ -53,21 +84,18 @@ python gradio_demo.py --model Qwen/Qwen2.5-Omni-7B --port 7861
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Then open `http://localhost:7861/` on your local browser to interact with the web UI.
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The gradio script supports the following arguments:
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### Options
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- `--model`: Model name
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- `--ip`: Host/IP for Gradio server (default: 127.0.0.1)
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- `--port`: Port for Gradio server (default: 7861)
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- `--stage-configs-path`: Path to custom stage configs YAML file (optional)
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- `--share`: Share the Gradio demo publicly (creates a public link)
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You can customize its basic launch parameters:
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### FAQ
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```bash
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python gradio_demo.py \
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--model Qwen/Qwen2.5-Omni-7B \
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--ip 127.0.0.1 \
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--port 7861 \
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--stage-configs-path /path/to/stage_configs.yaml
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If you encounter error about backend of librosa, try to install ffmpeg with command below.
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```
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sudo apt update
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sudo apt install ffmpeg
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```
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- `--model`: Local model checkpoint to load (default `Qwen/Qwen2.5-Omni-7B`).
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- `--ip`: Host/IP for the Gradio server (default `127.0.0.1`).
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- `--port`: Port for the Gradio server (default `7861`).
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- `--stage-configs-path`: Optional path to custom stage configs YAML.
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- `--share`: Set to expose a temporary public link via Gradio.
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+201
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@@ -1,4 +1,6 @@
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import base64
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import os
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from typing import Optional
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import requests
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from openai import OpenAI
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@@ -28,6 +30,129 @@ def encode_base64_content_from_url(content_url: str) -> str:
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return result
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def encode_base64_content_from_file(file_path: str) -> str:
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"""Encode a local file to base64 format."""
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with open(file_path, "rb") as f:
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content = f.read()
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result = base64.b64encode(content).decode("utf-8")
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return result
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def get_video_url_from_path(video_path: Optional[str]) -> str:
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"""Convert a video path (local file or URL) to a video URL format for the API.
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If video_path is None or empty, returns the default URL.
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If video_path is a local file path, encodes it to base64 data URL.
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If video_path is a URL, returns it as-is.
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"""
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if not video_path:
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# Default video URL
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return "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4"
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# Check if it's a URL (starts with http:// or https://)
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if video_path.startswith(("http://", "https://")):
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return video_path
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# Otherwise, treat it as a local file path
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if not os.path.exists(video_path):
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raise FileNotFoundError(f"Video file not found: {video_path}")
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# Detect video MIME type from file extension
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video_path_lower = video_path.lower()
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if video_path_lower.endswith(".mp4"):
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mime_type = "video/mp4"
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elif video_path_lower.endswith(".webm"):
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mime_type = "video/webm"
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elif video_path_lower.endswith(".mov"):
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mime_type = "video/quicktime"
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elif video_path_lower.endswith(".avi"):
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mime_type = "video/x-msvideo"
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elif video_path_lower.endswith(".mkv"):
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mime_type = "video/x-matroska"
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else:
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# Default to mp4 if extension is unknown
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mime_type = "video/mp4"
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video_base64 = encode_base64_content_from_file(video_path)
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return f"data:{mime_type};base64,{video_base64}"
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def get_image_url_from_path(image_path: Optional[str]) -> str:
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"""Convert an image path (local file or URL) to an image URL format for the API.
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If image_path is None or empty, returns the default URL.
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If image_path is a local file path, encodes it to base64 data URL.
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If image_path is a URL, returns it as-is.
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"""
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if not image_path:
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# Default image URL
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return "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/cherry_blossom.jpg"
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# Check if it's a URL (starts with http:// or https://)
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if image_path.startswith(("http://", "https://")):
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return image_path
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# Otherwise, treat it as a local file path
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if not os.path.exists(image_path):
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raise FileNotFoundError(f"Image file not found: {image_path}")
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# Detect image MIME type from file extension
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image_path_lower = image_path.lower()
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if image_path_lower.endswith((".jpg", ".jpeg")):
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mime_type = "image/jpeg"
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elif image_path_lower.endswith(".png"):
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mime_type = "image/png"
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elif image_path_lower.endswith(".gif"):
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mime_type = "image/gif"
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elif image_path_lower.endswith(".webp"):
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mime_type = "image/webp"
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else:
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# Default to jpeg if extension is unknown
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mime_type = "image/jpeg"
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image_base64 = encode_base64_content_from_file(image_path)
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return f"data:{mime_type};base64,{image_base64}"
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def get_audio_url_from_path(audio_path: Optional[str]) -> str:
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"""Convert an audio path (local file or URL) to an audio URL format for the API.
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If audio_path is None or empty, returns the default URL.
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If audio_path is a local file path, encodes it to base64 data URL.
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If audio_path is a URL, returns it as-is.
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"""
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if not audio_path:
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# Default audio URL
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return AudioAsset("mary_had_lamb").url
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# Check if it's a URL (starts with http:// or https://)
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if audio_path.startswith(("http://", "https://")):
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return audio_path
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# Otherwise, treat it as a local file path
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if not os.path.exists(audio_path):
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raise FileNotFoundError(f"Audio file not found: {audio_path}")
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# Detect audio MIME type from file extension
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audio_path_lower = audio_path.lower()
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if audio_path_lower.endswith((".mp3", ".mpeg")):
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mime_type = "audio/mpeg"
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elif audio_path_lower.endswith(".wav"):
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mime_type = "audio/wav"
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elif audio_path_lower.endswith(".ogg"):
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mime_type = "audio/ogg"
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elif audio_path_lower.endswith(".flac"):
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mime_type = "audio/flac"
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elif audio_path_lower.endswith(".m4a"):
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mime_type = "audio/mp4"
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else:
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# Default to wav if extension is unknown
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mime_type = "audio/wav"
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audio_base64 = encode_base64_content_from_file(audio_path)
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return f"data:{mime_type};base64,{audio_base64}"
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def get_system_prompt():
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return {
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"role": "system",
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@@ -44,8 +169,10 @@ def get_system_prompt():
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}
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def get_text_query():
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question = "Explain the system architecture for a scalable audio generation pipeline. Answer in 15 words."
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def get_text_query(custom_prompt: Optional[str] = None):
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question = (
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custom_prompt or "Explain the system architecture for a scalable audio generation pipeline. Answer in 15 words."
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)
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prompt = {
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"role": "user",
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"content": [
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@@ -58,26 +185,32 @@ def get_text_query():
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return prompt
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def get_mixed_modalities_query():
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question = "What is recited in the audio? What is the content of this image? Why is this video funny?"
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def get_mixed_modalities_query(
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video_path: Optional[str] = None,
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image_path: Optional[str] = None,
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audio_path: Optional[str] = None,
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custom_prompt: Optional[str] = None,
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):
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question = (
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custom_prompt or "What is recited in the audio? What is the content of this image? Why is this video funny?"
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)
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video_url = get_video_url_from_path(video_path)
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image_url = get_image_url_from_path(image_path)
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audio_url = get_audio_url_from_path(audio_path)
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prompt = {
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"role": "user",
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"content": [
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{
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"type": "audio_url",
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"audio_url": {"url": AudioAsset("mary_had_lamb").url},
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"audio_url": {"url": audio_url},
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},
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{
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"type": "image_url",
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"image_url": {
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"url": "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/cherry_blossom.jpg"
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},
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"image_url": {"url": image_url},
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},
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{
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"type": "video_url",
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"video_url": {
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"url": "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4"
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},
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"video_url": {"url": video_url},
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},
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{
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"type": "text",
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@@ -89,8 +222,9 @@ def get_mixed_modalities_query():
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return prompt
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def get_use_audio_in_video_query():
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question = "Describe the content of the video, then convert what the baby say into text."
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def get_use_audio_in_video_query(video_path: Optional[str] = None, custom_prompt: Optional[str] = None):
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question = custom_prompt or "Describe the content of the video, then convert what the baby say into text."
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video_url = get_video_url_from_path(video_path)
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prompt = {
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"role": "user",
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@@ -98,7 +232,7 @@ def get_use_audio_in_video_query():
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{
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"type": "video_url",
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"video_url": {
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"url": "https://huggingface.co/datasets/raushan-testing-hf/videos-test/resolve/main/sample_demo_1.mp4",
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"url": video_url,
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"num_frames": 16,
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},
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},
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@@ -112,14 +246,15 @@ def get_use_audio_in_video_query():
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return prompt
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def get_multi_audios_query():
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question = "Are these two audio clips the same?"
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def get_multi_audios_query(audio_path: Optional[str] = None, custom_prompt: Optional[str] = None):
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question = custom_prompt or "Are these two audio clips the same?"
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audio_url = get_audio_url_from_path(audio_path)
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prompt = {
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"role": "user",
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"content": [
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{
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"type": "audio_url",
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"audio_url": {"url": AudioAsset("mary_had_lamb").url},
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"audio_url": {"url": audio_url},
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},
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{
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"type": "audio_url",
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@@ -179,7 +314,27 @@ def run_multimodal_generation(args) -> None:
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code2wav_sampling_params,
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]
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prompt = query_map[args.query_type]()
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# Get paths and custom prompt from args
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video_path = getattr(args, "video_path", None)
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image_path = getattr(args, "image_path", None)
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audio_path = getattr(args, "audio_path", None)
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custom_prompt = getattr(args, "prompt", None)
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# Get the query function and call it with appropriate parameters
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query_func = query_map[args.query_type]
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if args.query_type == "mixed_modalities":
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prompt = query_func(
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video_path=video_path, image_path=image_path, audio_path=audio_path, custom_prompt=custom_prompt
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)
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elif args.query_type == "use_audio_in_video":
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prompt = query_func(video_path=video_path, custom_prompt=custom_prompt)
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elif args.query_type == "multi_audios":
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prompt = query_func(audio_path=audio_path, custom_prompt=custom_prompt)
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elif args.query_type == "text":
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prompt = query_func(custom_prompt=custom_prompt)
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else:
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prompt = query_func()
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extra_body = {
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"sampling_params_list": sampling_params_list # Optional, it has a default setting in stage_configs of the corresponding model.
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}
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@@ -219,6 +374,34 @@ def parse_args():
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choices=query_map.keys(),
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help="Query type.",
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)
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parser.add_argument(
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"--video-path",
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"-v",
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type=str,
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default=None,
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help="Path to local video file or URL. If not provided and query-type uses video, uses default video URL.",
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)
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parser.add_argument(
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"--image-path",
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"-i",
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type=str,
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default=None,
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help="Path to local image file or URL. If not provided and query-type uses image, uses default image URL.",
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)
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parser.add_argument(
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"--audio-path",
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"-a",
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type=str,
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default=None,
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help="Path to local audio file or URL. If not provided and query-type uses audio, uses default audio URL.",
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)
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parser.add_argument(
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"--prompt",
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"-p",
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type=str,
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default=None,
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help="Custom text prompt/question to use instead of the default prompt for the selected query type.",
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)
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return parser.parse_args()
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@@ -6,7 +6,8 @@ Please refer to [README.md](../../../README.md)
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## Run examples (Qwen3-Omni)
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Launch the server
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||||
### Launch the Server
|
||||
|
||||
```bash
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vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
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```
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@@ -16,21 +17,59 @@ If you have custom stage configs file, launch the server with command below
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||||
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 --stage-configs-path /path/to/stage_configs_file
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```
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### Send Multi-modal Request
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Get into the example folder
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```bash
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cd examples/online_serving/qwen3_omni
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```
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Send request via python
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||||
#### Send request via python
|
||||
|
||||
```bash
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python openai_chat_completion_client_for_multimodal_generation.py --query-type use_image
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```
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|
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Send request via curl
|
||||
The Python client supports the following command-line arguments:
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|
||||
- `--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)
|
||||
|
||||
+188
-17
@@ -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()
|
||||
|
||||
|
||||
Reference in new issue
Block a user