Signed-off-by: Ian Eaves <ian.k.eaves@gmail.com> Signed-off-by: Samit <285365963@qq.com> Co-authored-by: Samit <285365963@qq.com> Co-authored-by: Gao Han <gaohan19@huawei.com>
202 lines
6.4 KiB
Markdown
202 lines
6.4 KiB
Markdown
# Text-To-Video
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This example demonstrates how to deploy the Wan2.2 text-to-video model for online video generation using vLLM-Omni.
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## Start Server
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### Basic Start
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```bash
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vllm serve Wan-AI/Wan2.2-T2V-A14B-Diffusers --omni --port 8091
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```
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### Start with Parameters
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Or use the startup script:
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```bash
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bash run_server.sh
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```
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The script allows overriding:
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- `MODEL` (default: `Wan-AI/Wan2.2-T2V-A14B-Diffusers`)
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- `PORT` (default: `8091`)
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- `BOUNDARY_RATIO` (default: `0.875`)
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- `FLOW_SHIFT` (default: `5.0`)
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- `CACHE_BACKEND` (default: `none`)
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- `ENABLE_CACHE_DIT_SUMMARY` (default: `0`)
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## Async Job Behavior
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`POST /v1/videos` is asynchronous. It creates a video job and immediately
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returns metadata like the job ID and initial `queued` status. To get the final
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artifact, poll the job status and then download the completed file from the
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content endpoint.
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The main endpoints are:
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- `POST /v1/videos`: create a video generation job
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- `GET /v1/videos/{video_id}`: retrieve the current job status and metadata
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- `GET /v1/videos`: list stored video jobs
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- `GET /v1/videos/{video_id}/content`: download the generated video file
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- `DELETE /v1/videos/{video_id}`: delete the job and any stored output
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## Storage
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Generated video files are stored on local disk by the async video API.
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Local file storage behavior can be controlled via the following environment variables:
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- `VLLM_OMNI_STORAGE_PATH`: directory used for generated files (default: `/tmp/storage`)
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- `VLLM_OMNI_STORAGE_MAX_CONCURRENCY`: max concurrent save/delete operations (default: `4`)
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Example:
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```bash
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export VLLM_OMNI_STORAGE_PATH=/var/tmp/vllm-omni-videos
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export VLLM_OMNI_STORAGE_MAX_CONCURRENCY=8
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```
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## API Calls
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### Method 1: Using curl
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```bash
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# Basic text-to-video generation
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bash run_curl_text_to_video.sh
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# Or execute directly (OpenAI-style multipart)
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create_response=$(curl -s http://localhost:8091/v1/videos \
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-H "Accept: application/json" \
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-F "prompt=Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage." \
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-F "width=832" \
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-F "height=480" \
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-F "num_frames=33" \
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-F "negative_prompt=色调艳丽 ,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走" \
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-F "fps=16" \
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-F "num_inference_steps=40" \
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-F "guidance_scale=4.0" \
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-F "guidance_scale_2=4.0" \
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-F "boundary_ratio=0.875" \
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-F "flow_shift=5.0" \
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-F "seed=42")
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video_id=$(echo "$create_response" | jq -r '.id')
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while true; do
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status=$(curl -s "http://localhost:8091/v1/videos/${video_id}" | jq -r '.status')
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if [ "$status" = "completed" ]; then
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break
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fi
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if [ "$status" = "failed" ]; then
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echo "Video generation failed"
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exit 1
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fi
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sleep 2
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done
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curl -s "http://localhost:8091/v1/videos/${video_id}" | jq .
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curl -L "http://localhost:8091/v1/videos/${video_id}/content" -o wan22_output.mp4
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```
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## Request Format
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### Simple Text-to-Video Generation
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```bash
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curl -X POST http://localhost:8091/v1/videos \
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-F "prompt=A cinematic view of a futuristic city at sunset"
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```
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### Generation with Parameters
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```bash
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curl -X POST http://localhost:8091/v1/videos \
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-F "prompt=A cinematic view of a futuristic city at sunset" \
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-F "width=832" \
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-F "height=480" \
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-F "num_frames=33" \
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-F "negative_prompt=low quality, blurry, static" \
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-F "fps=16" \
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-F "num_inference_steps=40" \
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-F "guidance_scale=4.0" \
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-F "guidance_scale_2=4.0" \
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-F "boundary_ratio=0.875" \
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-F "flow_shift=5.0" \
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-F "seed=42"
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```
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## Generation Parameters
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| Parameter | Type | Default | Description |
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| --------------------- | ------ | ------- | ------------------------------------------------ |
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| `prompt` | str | - | Text description of the desired video |
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| `seconds` | str | None | Clip duration in seconds |
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| `size` | str | None | Output size in `WIDTHxHEIGHT` format |
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| `negative_prompt` | str | None | Negative prompt |
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| `width` | int | None | Video width in pixels |
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| `height` | int | None | Video height in pixels |
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| `num_frames` | int | None | Number of frames to generate |
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| `fps` | int | None | Frames per second for output video |
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| `num_inference_steps` | int | None | Number of denoising steps |
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| `guidance_scale` | float | None | CFG guidance scale (low-noise stage) |
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| `guidance_scale_2` | float | None | CFG guidance scale (high-noise stage, Wan2.2) |
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| `boundary_ratio` | float | None | Boundary split ratio for low/high DiT (Wan2.2) |
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| `flow_shift` | float | None | Scheduler flow shift (Wan2.2) |
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| `seed` | int | None | Random seed (reproducible) |
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| `lora` | object | None | LoRA configuration |
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## Create Response Format
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`POST /v1/videos` returns a job record, not inline base64 video data.
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```json
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{
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"id": "video_gen_123",
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"object": "video",
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"status": "queued",
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"model": "Wan-AI/Wan2.2-T2V-A14B-Diffusers",
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"prompt": "A cinematic view of a futuristic city at sunset",
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"created_at": 1234567890
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}
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```
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## Retrieve, List, Download, and Delete
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### Retrieve a job
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```bash
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curl -s http://localhost:8091/v1/videos/${video_id} | jq .
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```
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### List jobs
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```bash
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curl -s http://localhost:8091/v1/videos | jq .
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```
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### Download the completed video
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```bash
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curl -L http://localhost:8091/v1/videos/${video_id}/content -o wan22_output.mp4
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```
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### Delete a job and its stored file
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```bash
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curl -X DELETE http://localhost:8091/v1/videos/${video_id} | jq .
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```
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## Poll Until Complete
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```bash
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while true; do
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status=$(curl -s http://localhost:8091/v1/videos/${video_id} | jq -r '.status')
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if [ "$status" = "completed" ]; then
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break
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fi
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if [ "$status" = "failed" ]; then
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echo "Video generation failed"
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exit 1
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fi
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sleep 2
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done
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```
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