LocalAI/docs/content/features/video-generation.md

+++ disableToc = false title = "Video Generation" weight = 51 url = "/features/video-generation/" aliases = ["/features/longcat-video/"] +++

LocalAI can generate videos from text prompts and optional image or audio conditioning via the /video endpoint. Supported backends include diffusers, stablediffusion, vllm-omni, and the dedicated longcat-video backend.

API

• Method: POST
• Endpoint: /video

Request

The request body is JSON with the following fields:

Parameter	Type	Required	Default	Description
model	string	Yes		Model name to use
prompt	string	Yes		Text description of the video to generate
negative_prompt	string	No		What to exclude from the generated video
start_image	string	No		Starting image as base64 string or URL
end_image	string	No		Ending image for guided generation
audio	string	No		Audio conditioning as base64, a data URI, or URL
width	int	No	512	Video width in pixels
height	int	No	512	Video height in pixels
num_frames	int	No		Number of frames
fps	int	No		Frames per second
seconds	string	No		Duration in seconds
size	string	No		Size specification (alternative to width/height)
input_reference	string	No		Input reference for the generation
seed	int	No		Random seed for reproducibility
cfg_scale	float	No		Classifier-free guidance scale
step	int	No		Number of inference steps
response_format	string	No	url	url to return a file URL, b64_json for base64 output
params	object	No		Backend-specific string parameters

Response

Returns an OpenAI-compatible JSON response:

Field	Type	Description
created	int	Unix timestamp of generation
id	string	Unique identifier (UUID)
data	array	Array of generated video items
data[].url	string	URL path to video file (if response_format is url)
data[].b64_json	string	Base64-encoded video (if response_format is b64_json)

Usage

First install a video-generation model from the gallery (the examples below use longcat-video):

local-ai run longcat-video

Generate a video from a text prompt

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d '{
    "model": "longcat-video",
    "prompt": "A cat playing in a garden on a sunny day",
    "width": 512,
    "height": 512,
    "num_frames": 16,
    "fps": 8
  }'

Example response

{
  "created": 1709900000,
  "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "data": [
    {
      "url": "/generated-videos/abc123.mp4"
    }
  ]
}

Generate with a starting image

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d '{
    "model": "longcat-video",
    "prompt": "A timelapse of flowers blooming",
    "start_image": "https://example.com/flowers.jpg",
    "num_frames": 24,
    "fps": 12,
    "seed": 42,
    "cfg_scale": 7.5,
    "step": 30
  }'

Get base64-encoded output

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d '{
    "model": "longcat-video",
    "prompt": "Ocean waves on a beach",
    "response_format": "b64_json"
  }'

LongCat-Video and Avatar 1.5

LocalAI's longcat-video backend serves Meituan's official LongCat video-generation models through the /video API and the Studio Video page.

Gallery model	Upstream checkpoint	Inputs	Output
longcat-video	meituan-longcat/LongCat-Video	text, optional start image	video
longcat-video-avatar-1.5	meituan-longcat/LongCat-Video-Avatar-1.5	text, audio, optional portrait	video with the source audio

The base checkpoint supports text-to-video and image-to-video. Avatar 1.5 adds audio-driven character animation, optional portrait conditioning, and continuation segments for longer speech.

{{% notice warning %}} LongCat is a large, CUDA-only model family. LocalAI publishes this backend for Linux with NVIDIA CUDA 12 or CUDA 13 on x86_64 and CUDA 13 on ARM64. CPU, ROCm, and macOS images are not available. Avatar 1.5 also loads components from the base checkpoint, so reserve substantial disk and GPU or unified memory. {{% /notice %}}

Install from the Model Gallery

Install one or both recipes from Models in the web UI, or use the CLI:

local-ai models install longcat-video
local-ai models install longcat-video-avatar-1.5

You can also import either official Hugging Face URL. The importer recognizes the two repositories and writes a longcat-video model config with the appropriate use case and input/output modalities.

The required OCI backend is installed automatically when LocalAI first loads the model. The hardware detector selects the CUDA 12, CUDA 13, or CUDA 13 ARM64 variant.

DGX Spark and NVIDIA ARM64

Use a LocalAI CUDA 13 ARM64 image as described in [GPU acceleration]({{%relref "features/GPU-acceleration" %}}). The backend defaults to PyTorch SDPA, avoiding the FlashAttention dependency that is commonly unavailable on Blackwell ARM64 systems.

For unified-memory systems, start with BF16 (use_int8:false, the default). INT8 lowers steady-state DiT memory but can have a higher load-time peak because the full model is materialized before the quantized weights are applied.

Generate in Studio

1. Open Studio, then choose Video.
2. Select longcat-video or longcat-video-avatar-1.5.
3. Enter a prompt and choose 832x480 or 1280x720.
4. Expand Reference media to upload a start image. For Avatar 1.5, upload or record the speech under Avatar audio.
5. Select Generate.

The base model can run without a reference image for text-to-video. Avatar 1.5 requires audio; the portrait is optional.

LongCat API examples

Text-to-video

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d '{
    "model": "longcat-video",
    "prompt": "A cinematic tracking shot through a misty redwood forest",
    "width": 832,
    "height": 480,
    "num_frames": 93,
    "fps": 15
  }'

Image-to-video

start_image accepts raw base64, a browser-style data URI, or a public HTTP(S) URL:

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"longcat-video\",
    \"prompt\": \"The subject turns toward the camera as leaves move in the breeze\",
    \"start_image\": \"$(base64 --wrap=0 portrait.png)\",
    \"params\": {
      \"resolution\": \"480p\"
    }
  }"

Avatar from speech and a portrait

audio accepts raw base64, a data URI, or a public HTTP(S) URL. Each staged image or audio input is limited to 128 MiB.

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"longcat-video-avatar-1.5\",
    \"prompt\": \"A friendly presenter speaking naturally to camera\",
    \"start_image\": \"$(base64 --wrap=0 portrait.png)\",
    \"audio\": \"$(base64 --wrap=0 speech.wav)\",
    \"width\": 832,
    \"height\": 480,
    \"params\": {
      \"offload_kv_cache\": \"true\"
    }
  }"

Avatar output is generated at 25 FPS and is muxed with the submitted audio. When neither num_frames nor params.num_segments is provided, LocalAI derives the continuation count from the audio duration, up to the model's max_segments setting.

LongCat model configuration

The gallery and importer make each model self-describing. A manual Avatar 1.5 config looks like this:

name: longcat-video-avatar-1.5
backend: longcat-video
known_usecases:
  - video
known_input_modalities:
  - text
  - image
  - audio
known_output_modalities:
  - video
options:
  - attention_backend:sdpa
  - use_distill:true
  - max_segments:8
parameters:
  model: meituan-longcat/LongCat-Video-Avatar-1.5

The explicit modality declarations are used by GET /v1/models/capabilities and attachment-aware clients. They avoid inferring model behavior from backend or checkpoint names.

Load options

Model load options use key:value entries in options:

Option	Default	Description
attention_backend	sdpa	sdpa, auto, flash2, flash3, or xformers; packaged images guarantee sdpa
use_distill	Avatar: true; base: false	Use the checkpoint's accelerated distillation path
use_int8	false	Use Avatar 1.5's INT8 DiT; unsupported by the base model
base_model	meituan-longcat/LongCat-Video	Base tokenizer, text encoder, and VAE used by Avatar 1.5
max_segments	8	Maximum continuation segments accepted for one request
resolution	480p	Default image-conditioned resolution: 480p or 720p

The initial backend supports one GPU per process. Tensor or context parallel sizes above one are rejected.

Per-request parameters

The /video request's params object accepts string values:

Parameter	Description
num_segments	Explicit number of Avatar continuation segments
audio_guidance_scale	Audio classifier-free guidance when distillation is disabled
offload_kv_cache	Offload continuation KV cache (true or false)
ref_img_index	Reference-frame index used during continuation
mask_frame_range	Number of frames blended around continuation boundaries
resolution	Per-request image-conditioned resolution (480p or 720p)

With distillation enabled, Avatar uses eight inference steps and fixed text/audio guidance of 1.0. Disable use_distill in the model config before tuning step, cfg_scale, or audio_guidance_scale.

LongCat troubleshooting

• HTTP 400, audio is required: Avatar 1.5 was selected without audio.
• HTTP 400, request needs too many segments: trim the audio or raise max_segments in the model options.
• HTTP 412: the installed LocalAI runtime cannot select a compatible NVIDIA backend image.
• Out of memory while loading: use BF16 on unified-memory hardware, close other GPU workloads, or reduce model concurrency. INT8 is not guaranteed to reduce peak load memory.
• Slow first request: the backend and checkpoints are downloaded and loaded on demand; subsequent requests reuse the loaded pipeline.

Error Responses

Status Code	Description
400	Missing or invalid model or request parameters
412	The selected backend cannot run on the available hardware
500	Backend error during video generation