# Wan 2.2 VACE Fun A14B > VACE Fun for Wan 2.2 A14B from Alibaba-PAI ## Overview - **Endpoint**: `https://fal.run/fal-ai/wan-22-vace-fun-a14b/outpainting` - **Model ID**: `fal-ai/wan-22-vace-fun-a14b/outpainting` - **Category**: video-to-video - **Kind**: inference ## Pricing Your request will cost **$0.10** per **video second** for **720p**, **$0.075** per **video second** for **580p**, **$0.05** per **video second** for **480p**. Video seconds are calculated at 16 frames per second. For more details, see [fal.ai pricing](https://fal.ai/pricing). ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`prompt`** (`string`, _required_): The text prompt to guide video generation. - Examples: "A lone woman strides through the neon-drenched streets of Tokyo at night. Her crimson dress, a vibrant splash of color against the deep blues and blacks of the cityscape, flows slightly with each step. A tailored black jacket, crisp and elegant, contrasts sharply with the dress's rich texture. Medium shot: The city hums around her, blurred lights creating streaks of color in the background. Close-up: The fabric of her dress catches the streetlight's glow, revealing a subtle silk sheen and the intricate stitching at the hem. Her black jacket’s subtle texture is visible – a fine wool perhaps, with a matte finish. The overall mood is one of quiet confidence and mystery, a vibrant woman navigating a bustling, nocturnal landscape. High resolution 4k." - **`negative_prompt`** (`string`, _optional_): Negative prompt for video generation. Default value: `"letterboxing, borders, black bars, bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards"` - Default: `"letterboxing, borders, black bars, bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards"` - Examples: "letterboxing, borders, black bars, bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards" - **`match_input_num_frames`** (`boolean`, _optional_): If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter. - Default: `false` - Examples: false - **`num_frames`** (`integer`, _optional_): Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: `81` - Default: `81` - Range: `17` to `241` - **`match_input_frames_per_second`** (`boolean`, _optional_): If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter. - Default: `false` - Examples: false - **`frames_per_second`** (`integer`, _optional_): Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: `16` - Default: `16` - Range: `5` to `30` - **`seed`** (`integer`, _optional_): Random seed for reproducibility. If None, a random seed is chosen. - **`resolution`** (`ResolutionEnum`, _optional_): Resolution of the generated video. Default value: `"auto"` - Default: `"auto"` - Options: `"auto"`, `"240p"`, `"360p"`, `"480p"`, `"580p"`, `"720p"` - **`aspect_ratio`** (`AspectRatioEnum`, _optional_): Aspect ratio of the generated video. Default value: `"auto"` - Default: `"auto"` - Options: `"auto"`, `"16:9"`, `"1:1"`, `"9:16"` - **`num_inference_steps`** (`integer`, _optional_): Number of inference steps for sampling. Higher values give better quality but take longer. Default value: `30` - Default: `30` - Range: `2` to `50` - **`guidance_scale`** (`float`, _optional_): Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: `5` - Default: `5` - Range: `1` to `10` - Examples: 5 - **`sampler`** (`SamplerEnum`, _optional_): Sampler to use for video generation. Default value: `"unipc"` - Default: `"unipc"` - Options: `"unipc"`, `"dpm++"`, `"euler"` - Examples: "unipc" - **`shift`** (`float`, _optional_): Shift parameter for video generation. Default value: `5` - Default: `5` - Range: `1` to `15` - **`video_url`** (`string`, _required_): URL to the source video file. Required for outpainting. - Examples: "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4" - **`ref_image_urls`** (`list`, _optional_): URLs to source reference image. If provided, the model will use this image as reference. - Array of string - **`first_frame_url`** (`string`, _optional_): URL to the first frame of the video. If provided, the model will use this frame as a reference. - **`last_frame_url`** (`string`, _optional_): URL to the last frame of the video. If provided, the model will use this frame as a reference. - **`enable_safety_checker`** (`boolean`, _optional_): If set to true, the safety checker will be enabled. Disabling it requires account authorization; unauthorized requests are always checked. - Default: `false` - Examples: true - **`enable_prompt_expansion`** (`boolean`, _optional_): Whether to enable prompt expansion. - Default: `false` - Examples: false - **`acceleration`** (`Enum`, _optional_): Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: `regular` - Default: `"regular"` - Options: `"none"`, `"low"`, `"regular"` - Examples: "regular" - **`video_quality`** (`VideoQualityEnum`, _optional_): The quality of the generated video. Default value: `"high"` - Default: `"high"` - Options: `"low"`, `"medium"`, `"high"`, `"maximum"` - Examples: "high" - **`video_write_mode`** (`VideoWriteModeEnum`, _optional_): The write mode of the generated video. Default value: `"balanced"` - Default: `"balanced"` - Options: `"fast"`, `"balanced"`, `"small"` - Examples: "balanced" - **`num_interpolated_frames`** (`integer`, _optional_): Number of frames to interpolate between the original frames. A value of 0 means no interpolation. - Default: `0` - Range: `0` to `5` - Examples: 0 - **`temporal_downsample_factor`** (`integer`, _optional_): Temporal downsample factor for the video. This is an integer value that determines how many frames to skip in the video. A value of 0 means no downsampling. For each downsample factor, one upsample factor will automatically be applied. - Default: `0` - Range: `0` to `5` - Examples: 0 - **`enable_auto_downsample`** (`boolean`, _optional_): If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length. - Default: `false` - Examples: false - **`auto_downsample_min_fps`** (`float`, _optional_): The minimum frames per second to downsample the video to. This is used to help determine the auto downsample factor to try and find the lowest detail-preserving downsample factor. The default value is appropriate for most videos, if you are using a video with very fast motion, you may need to increase this value. If your video has a very low amount of motion, you could decrease this value to allow for higher downsampling and thus longer sequences. Default value: `15` - Default: `15` - Range: `1` to `60` - Examples: 15 - **`interpolator_model`** (`InterpolatorModelEnum`, _optional_): The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: `"film"` - Default: `"film"` - Options: `"rife"`, `"film"` - Examples: "film" - **`sync_mode`** (`boolean`, _optional_): If `True`, the media will be returned as a data URI and the output data won't be available in the request history. - Default: `false` - Examples: false - **`transparency_mode`** (`TransparencyModeEnum`, _optional_): The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: `"content_aware"` - Default: `"content_aware"` - Options: `"content_aware"`, `"white"`, `"black"` - Examples: "content_aware" - **`return_frames_zip`** (`boolean`, _optional_): If true, also return a ZIP file containing all generated frames. - Default: `false` - Examples: false - **`expand_left`** (`boolean`, _optional_): Whether to expand the video to the left. - Default: `false` - Examples: true - **`expand_right`** (`boolean`, _optional_): Whether to expand the video to the right. - Default: `false` - Examples: true - **`expand_top`** (`boolean`, _optional_): Whether to expand the video to the top. - Default: `false` - Examples: true - **`expand_bottom`** (`boolean`, _optional_): Whether to expand the video to the bottom. - Default: `false` - Examples: true - **`expand_ratio`** (`float`, _optional_): Amount of expansion. This is a float value between 0 and 1, where 0.25 adds 25% to the original video size on the specified sides. Default value: `0.25` - Default: `0.25` - Range: `0` to `1` - Examples: 0.25 **Required Parameters Example**: ```json { "prompt": "A lone woman strides through the neon-drenched streets of Tokyo at night. Her crimson dress, a vibrant splash of color against the deep blues and blacks of the cityscape, flows slightly with each step. A tailored black jacket, crisp and elegant, contrasts sharply with the dress's rich texture. Medium shot: The city hums around her, blurred lights creating streaks of color in the background. Close-up: The fabric of her dress catches the streetlight's glow, revealing a subtle silk sheen and the intricate stitching at the hem. Her black jacket’s subtle texture is visible – a fine wool perhaps, with a matte finish. The overall mood is one of quiet confidence and mystery, a vibrant woman navigating a bustling, nocturnal landscape. High resolution 4k.", "video_url": "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4" } ``` **Full Example**: ```json { "prompt": "A lone woman strides through the neon-drenched streets of Tokyo at night. Her crimson dress, a vibrant splash of color against the deep blues and blacks of the cityscape, flows slightly with each step. A tailored black jacket, crisp and elegant, contrasts sharply with the dress's rich texture. Medium shot: The city hums around her, blurred lights creating streaks of color in the background. Close-up: The fabric of her dress catches the streetlight's glow, revealing a subtle silk sheen and the intricate stitching at the hem. Her black jacket’s subtle texture is visible – a fine wool perhaps, with a matte finish. The overall mood is one of quiet confidence and mystery, a vibrant woman navigating a bustling, nocturnal landscape. High resolution 4k.", "negative_prompt": "letterboxing, borders, black bars, bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards", "match_input_num_frames": false, "num_frames": 81, "match_input_frames_per_second": false, "frames_per_second": 16, "resolution": "auto", "aspect_ratio": "auto", "num_inference_steps": 30, "guidance_scale": 5, "sampler": "unipc", "shift": 5, "video_url": "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4", "enable_safety_checker": true, "enable_prompt_expansion": false, "acceleration": "regular", "video_quality": "high", "video_write_mode": "balanced", "num_interpolated_frames": 0, "temporal_downsample_factor": 0, "enable_auto_downsample": false, "auto_downsample_min_fps": 15, "interpolator_model": "film", "sync_mode": false, "transparency_mode": "content_aware", "return_frames_zip": false, "expand_left": true, "expand_right": true, "expand_top": true, "expand_bottom": true, "expand_ratio": 0.25 } ``` ### Output Schema The API returns the following output format: - **`video`** (`VideoFile`, _required_): The generated outpainting video file. - Examples: {"url":"https://storage.googleapis.com/falserverless/example_outputs/wan-vace-outpainting-output.mp4"} - **`prompt`** (`string`, _required_): The prompt used for generation. - **`seed`** (`integer`, _required_): The seed used for generation. - **`frames_zip`** (`File`, _optional_): ZIP archive of all video frames if requested. **Example Response**: ```json { "video": { "url": "https://storage.googleapis.com/falserverless/example_outputs/wan-vace-outpainting-output.mp4" }, "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/wan-22-vace-fun-a14b/outpainting \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "A lone woman strides through the neon-drenched streets of Tokyo at night. Her crimson dress, a vibrant splash of color against the deep blues and blacks of the cityscape, flows slightly with each step. A tailored black jacket, crisp and elegant, contrasts sharply with the dress's rich texture. Medium shot: The city hums around her, blurred lights creating streaks of color in the background. Close-up: The fabric of her dress catches the streetlight's glow, revealing a subtle silk sheen and the intricate stitching at the hem. Her black jacket’s subtle texture is visible – a fine wool perhaps, with a matte finish. The overall mood is one of quiet confidence and mystery, a vibrant woman navigating a bustling, nocturnal landscape. High resolution 4k.", "video_url": "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4" }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/wan-22-vace-fun-a14b/outpainting", arguments={ "prompt": "A lone woman strides through the neon-drenched streets of Tokyo at night. Her crimson dress, a vibrant splash of color against the deep blues and blacks of the cityscape, flows slightly with each step. A tailored black jacket, crisp and elegant, contrasts sharply with the dress's rich texture. Medium shot: The city hums around her, blurred lights creating streaks of color in the background. Close-up: The fabric of her dress catches the streetlight's glow, revealing a subtle silk sheen and the intricate stitching at the hem. Her black jacket’s subtle texture is visible – a fine wool perhaps, with a matte finish. The overall mood is one of quiet confidence and mystery, a vibrant woman navigating a bustling, nocturnal landscape. High resolution 4k.", "video_url": "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/wan-22-vace-fun-a14b/outpainting", { input: { prompt: "A lone woman strides through the neon-drenched streets of Tokyo at night. Her crimson dress, a vibrant splash of color against the deep blues and blacks of the cityscape, flows slightly with each step. A tailored black jacket, crisp and elegant, contrasts sharply with the dress's rich texture. Medium shot: The city hums around her, blurred lights creating streaks of color in the background. Close-up: The fabric of her dress catches the streetlight's glow, revealing a subtle silk sheen and the intricate stitching at the hem. Her black jacket’s subtle texture is visible – a fine wool perhaps, with a matte finish. The overall mood is one of quiet confidence and mystery, a vibrant woman navigating a bustling, nocturnal landscape. High resolution 4k.", video_url: "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/wan-22-vace-fun-a14b/outpainting) - [API Documentation](https://fal.ai/models/fal-ai/wan-22-vace-fun-a14b/outpainting/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/wan-22-vace-fun-a14b/outpainting) ### fal.ai Platform - [Platform Documentation](https://fal.ai/docs/documentation) - [Python Client](https://fal.ai/docs/api-reference/client-libraries/python) - [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript) ### Other agent-readable surfaces This file covers one model. To find anything else: - [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs - [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page - [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined - Any other model: `https://fal.ai/models//llms.txt`