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app.py

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+import gradio as gr
+import spaces
+import torch
+import numpy as np
+import os
+import random
+from ltx_video.inference import infer, InferenceConfig
+from functools import partial
+
+@spaces.GPU
+def create(
+        prompt,
+        mode="text-to-video",
+        negative_prompt="",
+        input_image_filepath=None,
+        input_video_filepath=None,
+        height_ui=512,
+        width_ui=704,
+        duration_ui=2.0,
+        ui_frames_to_use=16,
+        seed_ui=42,
+        randomize_seed=True,
+        ui_guidance_scale=3.0,
+        improve_texture_flag=True,
+        progress=gr.Progress(track_tqdm=True),
+        fps=8,   
+    ):
+    """
+    Generate videos using the LTX Video model.
+    """
+
+    # pick seed
+    used_seed = random.randint(0, 2**32 - 1) if randomize_seed else seed_ui
+
+    output_path = f"output_{mode}_{used_seed}.mp4"
+
+    config = InferenceConfig(
+        pipeline_config="configs/ltxv-13b-0.9.8-distilled.yaml",
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        height=height_ui,
+        width=width_ui,
+        num_frames=ui_frames_to_use,
+        seed=used_seed,
+        guidance_scale=ui_guidance_scale,
+        output_path=output_path,
+        improve_texture=improve_texture_flag,
+    )
+
+    # attach initial image or video if mode requires
+    if mode == "image-to-video" and input_image_filepath:
+        config.init_image = input_image_filepath
+    elif mode == "video-to-video" and input_video_filepath:
+        config.init_video = input_video_filepath
+
+    # run inference
+    infer(config)
+
+    return output_path, f"✅ Done! Seed: {used_seed}"
+
+# ---- Gradio Blocks & UI ----
+with gr.Blocks(title="AI Video Converter", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🎬 AI Video Converter")
+    gr.Markdown("Convert text, images, and videos into stunning AI-generated videos!")
+    
+    with gr.Tabs():
+        # --- Text to Video ---
+        with gr.Tab("📝 Text to Video"):
+            gr.Markdown("### Generate videos from text descriptions")
+            with gr.Row():
+                with gr.Column():
+                    text_prompt = gr.Textbox(
+                        label="Text Prompt",
+                        placeholder="Describe the video you want to create...",
+                        value="A Nigerian woman dancing on the streets of Lagos, Nigeria",
+                        lines=3
+                    )
+                    text_num_frames = gr.Slider(minimum=8, maximum=32, value=16, step=1,label="Number of Frames")
+                    text_fps = gr.Slider(minimum=4, maximum=30, value=8, step=1,label="Frames Per Second")
+                    text_generate_video_btn = gr.Button("Generate Video", variant="primary")
+                
+                with gr.Column():
+                    text_output_video = gr.Video(label="Generated Video")
+                    text_status = gr.Textbox(label="Status", interactive=False)
+        
+        # --- Image to Video ---
+        with gr.Tab("🖼️ Image to Video"):
+            gr.Markdown("### Animate images into videos")
+            with gr.Row():
+                with gr.Column():
+                    image_input = gr.Image(label="Input Image",type="filepath", sources=["upload", "webcam", "clipboard"])
+                    image_text_prompt = gr.Textbox(
+                        label="Text Prompt",
+                        placeholder="Describe the video you want to create...",
+                        value="The creature from the image starts to move",
+                        lines=3
+                    )
+                    image_num_frames = gr.Slider(minimum=8, maximum=50, value=25, step=1,label="Number of Frames")
+                    image_fps = gr.Slider(minimum=4, maximum=30, value=8, step=1,label="Frames Per Second")
+                    image_generate_video_btn = gr.Button("Generate Video", variant="primary")
+                
+                with gr.Column():
+                    image_output_video = gr.Video(label="Generated Video")
+                    image_status = gr.Textbox(label="Status", interactive=False)
+        
+        # --- Video to Video ---
+        with gr.Tab("🎥 Video to Video"):
+            gr.Markdown("### Transform videos with AI")
+            with gr.Row():
+                with gr.Column():
+                    video_input = gr.Video(label="Input Video", type="filepath", sources=["upload", "webcam", "clipboard"])
+                    video_prompt = gr.Textbox(
+                        label="Transformation Prompt",
+                        placeholder="Describe how you want to transform the video...",
+                        lines=3
+                    )
+                    video_strength = gr.Slider(minimum=0.1, maximum=1.0, value=0.8, step=0.1,label="Transformation Strength")
+                    video_generate_video_btn = gr.Button("Transform Video", variant="primary")
+                
+                with gr.Column():
+                    video_output_video = gr.Video(label="Transformed Video")
+                    video_status = gr.Textbox(label="Status", interactive=False)
+    
+    
+    # --- Inputs ---
+    tgv_inputs = {"prompt": text_prompt, "ui_frames_to_use": text_num_frames, "fps": text_fps}
+    igv_inputs = {"prompt": image_text_prompt, "input_image_filepath": image_input, "ui_frames_to_use": image_num_frames,"fps": image_fps}
+    vgv_inputs = {
+        "prompt": video_prompt,
+        "input_video_filepath": video_input,
+        "ui_guidance_scale": video_strength
+    }
+
+    # --- Outputs ---
+    tgv_outputs = {"video": text_output_video, "status": text_status}
+    igv_outputs = {"video": image_output_video, "status": image_status}
+    vgv_outputs = {"video": video_output_video, "status": video_status}
+    
+
+    # --- Button Logic ---
+    text_generate_video_btn.click(
+        fn=partial(create, mode="text-to-video"),
+        inputs=tgv_inputs,
+        outputs=tgv_outputs
+    )
+    
+    image_generate_video_btn.click(
+        fn=partial(create, mode="image-to-video"),
+        inputs=igv_inputs,
+        outputs=igv_outputs
+    )
+    
+    video_generate_video_btn.click(
+        fn=partial(create, mode="video-to-video"),
+        inputs=vgv_inputs,
+        outputs=vgv_outputs
+    )
+
+if __name__ == "__main__":
+    demo.launch(debug=True, share=False)

requirements.txt

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+aiofiles==24.1.0
+annotated-types==0.7.0
+anyio==4.9.0
+audioop-lts==0.2.2
+blinker==1.9.0
+Brotli==1.1.0
+certifi==2025.7.14
+charset-normalizer==3.4.3
+click==8.2.1
+decorator==5.2.1
+diffusers==0.35.1
+einops==0.8.1
+fastapi==0.116.1
+ffmpy==0.6.1
+filelock==3.19.1
+Flask==3.1.1
+flask-cors==6.0.1
+fsspec==2025.7.0
+gradio==5.43.1
+gradio_client==1.12.1
+groovy==0.1.2
+h11==0.16.0
+hf-xet==1.1.8
+httpcore==1.0.9
+httpx==0.28.1
+httpx-ws==0.7.2
+huggingface-hub==0.34.4
+idna==3.10
+imageio==2.37.0
+imageio-ffmpeg==0.6.0
+importlib_metadata==8.7.0
+itsdangerous==2.2.0
+Jinja2==3.1.6
+lmstudio==1.4.1
+ltx-video==0.1.2
+markdown-it-py==4.0.0
+MarkupSafe==3.0.2
+mdurl==0.1.2
+moviepy==2.2.1
+mpmath==1.3.0
+msgspec==0.19.0
+networkx==3.5
+numpy==2.3.2
+orjson==3.11.2
+packaging==25.0
+pandas==2.3.1
+pillow==11.3.0
+proglog==0.1.12
+pydantic==2.11.7
+pydantic_core==2.33.2
+pydub==0.25.1
+Pygments==2.19.2
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.1
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.2
+regex==2025.7.34
+requests==2.32.5
+rich==14.1.0
+ruff==0.12.9
+safehttpx==0.1.6
+safetensors==0.6.2
+scipy==1.16.1
+semantic-version==2.10.0
+sentencepiece==0.2.1
+setuptools==80.9.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+starlette==0.47.2
+sympy==1.14.0
+timm==1.0.19
+tokenizers==0.21.4
+tomlkit==0.13.3
+torch==2.8.0
+torchvision==0.23.0
+tqdm==4.67.1
+transformers==4.51.3
+typer==0.16.1
+typing-inspection==0.4.1
+typing_extensions==4.14.1
+tzdata==2025.2
+urllib3==2.5.0
+uvicorn==0.35.0
+websockets==15.0.1
+Werkzeug==3.1.3
+wsproto==1.2.0
+zipp==3.23.0