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hao-ai-lab-FastVideo/examples/inference/basic/basic_longcat_t2v.py
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"""
LongCat Text-to-Video (T2V) Example Script
This script demonstrates LongCat T2V inference using the FastVideo Python API.
It runs both basic generation (50 steps) and distill+refine generation
(16 steps distill + 50 steps refinement to 720p).
Usage:
python examples/inference/basic/basic_longcat_t2v.py
"""
import glob
import os
from fastvideo import VideoGenerator
# Common prompts and settings matching the shell script examples
PROMPT = (
"In a realistic photography style, a white boy around seven or eight years old "
"sits on a park bench, wearing a light blue T-shirt, denim shorts, and white sneakers. "
"He holds an ice cream cone with vanilla and chocolate flavors, and beside him is a "
"medium-sized golden Labrador. Smiling, the boy offers the ice cream to the dog, "
"who eagerly licks it with its tongue. The sun is shining brightly, and the background "
"features a green lawn and several tall trees, creating a warm and loving scene."
)
NEGATIVE_PROMPT = (
"Bright tones, overexposed, static, blurred details, subtitles, style, works, "
"paintings, images, static, overall gray, worst quality, low quality, JPEG compression "
"residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, "
"deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, "
"three legs, many people in the background, walking backwards"
)
SEED = 42
def basic_generation():
"""
Run basic LongCat T2V generation (50 steps at 480p).
This uses the full 50-step denoising process for highest quality.
"""
print("=" * 60)
print("LongCat T2V: Basic Generation (50 steps, 480p)")
print("=" * 60)
generator = VideoGenerator.from_pretrained(
"FastVideo/LongCat-Video-T2V-Diffusers",
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
dit_cpu_offload=False,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
enable_bsa=False,
)
output_path = "outputs_video/longcat_t2v_basic"
generator.generate_video(
prompt=PROMPT,
negative_prompt=NEGATIVE_PROMPT,
output_path=output_path,
save_video=True,
height=480,
width=832,
num_frames=93,
num_inference_steps=50,
fps=15,
guidance_scale=4.0,
seed=SEED,
)
print(f"\nBasic generation complete! Video saved to: {output_path}")
generator.shutdown()
def distill_refine_generation():
"""
Run LongCat T2V with distill+refine pipeline (16 steps + refinement to 720p).
This uses the distilled LoRA for fast 480p generation (16 steps),
then refines to 720p using the refinement LoRA with BSA enabled.
"""
print("\n" + "=" * 60)
print("LongCat T2V: Distill + Refine Pipeline")
print("=" * 60)
# Stage 1: Distilled generation (16 steps at 480p)
print("\n[Stage 1] Distilled generation (16 steps, 480p)")
print("-" * 40)
generator = VideoGenerator.from_pretrained(
"FastVideo/LongCat-Video-T2V-Diffusers",
num_gpus=1,
use_fsdp_inference=True,
dit_cpu_offload=False,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
enable_bsa=False,
lora_path="FastVideo/LongCat-Video-T2V-Distilled-LoRA",
lora_nickname="distilled",
)
distill_output_path = "outputs_video/longcat_t2v_distill"
generator.generate_video(
prompt=PROMPT,
negative_prompt=NEGATIVE_PROMPT,
output_path=distill_output_path,
save_video=True,
height=480,
width=832,
num_frames=93,
num_inference_steps=16,
fps=15,
guidance_scale=1.0,
seed=SEED,
)
print(f"Distilled generation complete! Video saved to: {distill_output_path}")
generator.shutdown()
# Stage 2: Refinement (480p -> 720p)
print("\n[Stage 2] Refinement (480p -> 720p with BSA)")
print("-" * 40)
# Find the actual saved video file from stage 1
video_files = glob.glob(os.path.join(distill_output_path, "*.mp4"))
if not video_files:
raise FileNotFoundError(f"No video file found in {distill_output_path}")
# Use the most recently created video file
distill_video_path = max(video_files, key=os.path.getmtime)
print(f"Using stage 1 video: {distill_video_path}")
# Create a new generator with refinement LoRA and BSA enabled
refine_generator = VideoGenerator.from_pretrained(
"FastVideo/LongCat-Video-T2V-Diffusers",
num_gpus=1,
use_fsdp_inference=True,
dit_cpu_offload=True,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=False,
enable_bsa=True,
bsa_sparsity=0.875,
bsa_chunk_q=[4, 4, 8],
bsa_chunk_k=[4, 4, 8],
lora_path="FastVideo/LongCat-Video-T2V-Refinement-LoRA",
lora_nickname="refinement",
)
refine_output_path = "outputs_video/longcat_t2v_refine_720p"
refine_generator.generate_video(
prompt=PROMPT,
negative_prompt=NEGATIVE_PROMPT,
output_path=refine_output_path,
save_video=True,
refine_from=distill_video_path,
t_thresh=0.5,
spatial_refine_only=False,
num_cond_frames=0,
height=720,
width=1280,
num_inference_steps=50,
fps=30,
guidance_scale=1.0,
seed=SEED,
)
print(f"Refinement complete! Video saved to: {refine_output_path}")
refine_generator.shutdown()
def main():
"""Run both basic and distill+refine generation pipelines."""
print("\n" + "=" * 60)
print("LongCat Text-to-Video Example")
print("=" * 60 + "\n")
# Run basic generation
basic_generation()
# Run distill+refine pipeline
distill_refine_generation()
print("\n" + "=" * 60)
print("All generations complete!")
print("=" * 60)
if __name__ == "__main__":
main()