fal-ai/ltx23-trainer-v2/t2v
About
T2V
1. Calling the API#
Install the client#
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientMigrate to @fal-ai/client
The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Please check the migration guide for more information.
Setup your API Key#
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"Submit a request#
The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.
import { fal } from "@fal-ai/client";
const result = await fal.subscribe("fal-ai/ltx23-trainer-v2/t2v", {
input: {
training_data_url: ""
},
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);2. Authentication#
The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
API Key#
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_KEY"
});Protect your API Key
When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.
3. Queue#
Submit a request#
The client API provides a convenient way to submit requests to the model.
import { fal } from "@fal-ai/client";
const { request_id } = await fal.queue.submit("fal-ai/ltx23-trainer-v2/t2v", {
input: {
training_data_url: ""
},
webhookUrl: "https://optional.webhook.url/for/results",
});Fetch request status#
You can fetch the status of a request to check if it is completed or still in progress.
import { fal } from "@fal-ai/client";
const status = await fal.queue.status("fal-ai/ltx23-trainer-v2/t2v", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});Get the result#
Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.
import { fal } from "@fal-ai/client";
const result = await fal.queue.result("fal-ai/ltx23-trainer-v2/t2v", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);4. Files#
Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.
Data URI (base64)#
You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.
Hosted files (URL)#
You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.
Uploading files#
We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.
import { fal } from "@fal-ai/client";
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);Auto uploads
The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).
Read more about file handling in our file upload guide.
5. Schema#
Input#
training_data_url string* requiredURL to a .zip archive of your training data. The exact file layout depends on the training mode — see this endpoint's documentation for the required structure. You can include a .txt caption alongside each media file (same base name).
rank RankEnumThe rank of the LoRA adaptation. Higher values increase capacity but use more memory. Default value: "32"
Possible enum values: 8, 16, 32, 64, 128
number_of_steps integerThe number of training steps. Default value: 2000
learning_rate floatLearning rate for optimization. Default value: 0.0002
number_of_frames integerNumber of frames per training sample. Must satisfy frames % 8 == 1 (e.g., 1, 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97). Default value: 89
frame_rate integerTarget frames per second for the training video (LTX-2.3 native is 24). Default value: 24
resolution ResolutionEnumResolution to use for training. Higher resolutions require more memory. Default value: "medium"
Possible enum values: low, medium, high
aspect_ratio AspectRatioEnumAspect ratio to use for training. Default value: "1:1"
Possible enum values: 16:9, 1:1, 9:16
trigger_phrase stringA phrase that will trigger the LoRA style. Will be prepended to captions during training. Default value: ""
auto_scale_input booleanIf true, videos will be automatically scaled to the target frame count and fps. This option has no effect on image datasets.
split_input_into_scenes booleanIf true, videos above a certain duration threshold will be split into scenes. Default value: true
split_input_duration_threshold floatThe duration threshold in seconds. If a video is longer than this, it will be split into scenes. Default value: 30
debug_dataset booleanWhen enabled, the trainer returns a downloadable archive of your preprocessed training data for manual inspection. Use this to verify that your videos, images, and captions were processed correctly before committing to a full training run.
with_audio booleanEnable joint audio-video training. If None (default), auto-detects whether input videos have audio. Set True to force audio training, or False to disable.
audio_normalize booleanPeak-normalize audio for consistent levels across the dataset. Default value: true
audio_preserve_pitch booleanPreserve pitch when fitting audio to video duration (vs trimming/padding). Default value: true
A list of validation prompts to use during training.
validation_negative_prompt stringA negative prompt to use for validation. Note: validation previews are single-stage approximations of the production two-stage (distilled) inference, so preview quality and guidance differ from final inference. Default value: "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
validation_number_of_frames integerThe number of frames in validation videos. Default value: 89
validation_frame_rate integerTarget frames per second for validation videos (LTX-2.3 native is 24). Default value: 24
validation_resolution ValidationResolutionEnumThe resolution to use for validation. Default value: "high"
Possible enum values: low, medium, high
validation_aspect_ratio ValidationAspectRatioEnumThe aspect ratio to use for validation. Default value: "1:1"
Possible enum values: 16:9, 1:1, 9:16
stg_scale floatSTG (Spatio-Temporal Guidance) scale. 0.0 disables STG. Recommended value is 1.0. Default value: 1
{
"training_data_url": "",
"rank": 32,
"number_of_steps": 2000,
"learning_rate": 0.0002,
"number_of_frames": 89,
"frame_rate": 24,
"resolution": "medium",
"aspect_ratio": "1:1",
"trigger_phrase": "",
"auto_scale_input": false,
"split_input_into_scenes": true,
"split_input_duration_threshold": 30,
"audio_normalize": true,
"audio_preserve_pitch": true,
"validation": [],
"validation_negative_prompt": "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts.",
"validation_number_of_frames": 89,
"validation_frame_rate": 24,
"validation_resolution": "high",
"validation_aspect_ratio": "1:1",
"stg_scale": 1
}Output#
Combined validation video preview (video-producing endpoints), if any.
Combined validation audio preview for the audio-only-output endpoints (/v2a, /a2a, /t2a, /audio-extend-prefix, /audio-extend-suffix, /audio-inpaint), if any.
URL to the trained LoRA weights (.safetensors).
Configuration used for setting up inference endpoints.
Downloadable archive of the preprocessed training data, when debug_dataset is enabled.
{
"lora_file": {
"url": "",
"content_type": "image/png",
"file_name": "z9RV14K95DvU.png",
"file_size": 4404019
},
"config_file": {
"url": "",
"content_type": "image/png",
"file_name": "z9RV14K95DvU.png",
"file_size": 4404019
}
}Other types#
OutpaintValidation#
prompt string* requiredThe prompt to use for validation.
video_url string* requiredURL to the full-canvas video whose surround should be outpainted.
AV2AVValidation#
prompt string* requiredThe prompt to use for validation.
reference_video_url string* requiredURL to the reference video (its audio track is also used as the audio reference) that conditions the generated audio+video.
reference_audio_url stringOptional URL to a separate reference audio. If omitted, the audio is taken from reference_video_url's own track.
A2AValidation#
prompt string* requiredThe prompt to use for validation.
reference_audio_url string* requiredURL to the reference audio that conditions the generated audio.
T2VValidation#
prompt string* requiredThe prompt to use for validation.
V2VMaskedValidation#
prompt string* requiredThe prompt to use for validation.
video_url string* requiredURL to the source video. Its UNMASKED region is kept pixel-faithful and the masked region is regenerated.
mask_url string* requiredURL to the mask (image or video). Standard convention: WHITE marks the region to regenerate/edit, BLACK is kept unchanged.
reference_video_url string* requiredURL to the reference (control) video that guides the regenerated region.
A2VValidation#
prompt string* requiredThe prompt to use for validation.
image_url string* requiredURL to the start image used as the first frame (a2v is image+audio -> video, so the model conditions on this frame and the audio rather than generating the first frame).
audio_url string* requiredURL to the conditioning audio track that drives the generated video.
V2VValidation#
prompt string* requiredThe prompt to use for validation.
reference_video_url string* requiredURL to reference video for IC-LoRA validation. This is the input video that will be transformed.
InterpolateValidation#
prompt string* requiredThe prompt to use for validation.
start_image_url string* requiredURL to the first-frame keyframe image.
end_image_url string* requiredURL to the last-frame keyframe image.
middle_image_url stringOptional URL to a middle keyframe image; required when the run sets include_middle_keyframe=true (first+middle+last interpolation).
File#
url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.
AV2AVMaskedValidation#
prompt string* requiredThe prompt to use for validation.
video_url string* requiredURL to the source video. Its UNMASKED region is kept pixel-faithful and the masked region is regenerated.
mask_url string* requiredURL to the mask (image or video). WHITE marks the region to regenerate, BLACK is kept unchanged.
reference_video_url string* requiredURL to the reference video (its audio track is also used as the audio reference) guiding the regenerated audio+video.
reference_audio_url stringOptional URL to a separate reference audio. If omitted, the audio is taken from reference_video_url's own track.
ExtendValidation#
prompt string* requiredThe prompt to use for validation.
video_url string* requiredURL to the video the model should temporally extend.
T2AValidation#
prompt string* requiredThe prompt to use for validation.
AudioInpaintValidation#
prompt string* requiredThe prompt to use for validation.
audio_url string* requiredURL to the audio clip to inpaint.
Time ranges (in seconds, [start, end]) to REGENERATE/inpaint; the rest of the audio is kept. e.g. [[1.0, 2.0]].
I2VValidation#
prompt string* requiredThe prompt to use for validation.
image_url string* requiredAn image to use as the first frame for image-to-video validation.
InpaintValidation#
prompt string* requiredThe prompt to use for validation.
video_url string* requiredURL to the source video to inpaint.
mask_url string* requiredURL to the inpainting mask (image or video). Standard convention: WHITE marks the region to regenerate/edit, BLACK is kept unchanged. Resolution need not match the video; it is resized automatically.
V2AValidation#
prompt string* requiredThe prompt to use for validation.
video_url string* requiredURL to the silent video the model should generate audio for.
AudioExtendValidation#
prompt string* requiredThe prompt to use for validation.
audio_url string* requiredURL to the audio clip the model should temporally extend.