Delete app.py

app.py

@@ -1,104 +0,0 @@
-import gradio as gr
-import torch
-from diffusers import AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler
-from diffusers.utils import export_to_video
-from huggingface_hub import hf_hub_download
-from safetensors.torch import load_file
-import spaces
-import os
-
-# 1. Load the Model Components
-print("Loading AnimateDiff-Lightning... this will be fast.")
-
-# STEP A: Load the standard adapter first (the "skeleton")
-adapter = MotionAdapter.from_pretrained(
-    "guoyww/animatediff-motion-adapter-v1-5-2",
-    torch_dtype=torch.float16
-)
-
-# STEP B: Download the "Lightning" speed update
-print("Downloading Lightning weights...")
-file_path = hf_hub_download(
-    repo_id="ByteDance/AnimateDiff-Lightning",
-    filename="animatediff_lightning_4step_diffusers.safetensors"
-)
-
-# STEP C: Apply the Lightning update to the adapter
-print("Applying Lightning weights...")
-adapter.load_state_dict(
-    load_file(file_path)
-)
-
-# STEP D: Load the base model (Realism) with the lightning adapter
-pipe = AnimateDiffPipeline.from_pretrained(
-    "emilianJR/epiCRealism",
-    motion_adapter=adapter,
-    torch_dtype=torch.float16
-)
-
-# Set up the scheduler specifically for Lightning (4-step generation)
-pipe.scheduler = EulerDiscreteScheduler.from_config(
-    pipe.scheduler.config, 
-    timestep_spacing="trailing", 
-    beta_schedule="linear"
-)
-
-# Move to GPU immediately
-device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe.to(device)
-
-# 2. Define the Generation Function
-# NOTE: If you are on the CPU Free Tier, DELETE the line below starting with @spaces
-@spaces.GPU(duration=60)
-def generate_video(prompt, negative_prompt):
-    print(f"Generating video for: {prompt}")
-    
-    # Generate the video frames
-    output = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        num_inference_steps=4,  # Lightning needs only 4 steps!
-        guidance_scale=1.5,     # Keep guidance low for Lightning
-        num_frames=16,          # Standard length for AnimateDiff
-    )
-    
-    frames = output.frames[0]
-    
-    # Save to MP4
-    output_path = "output.mp4"
-    export_to_video(frames, output_path)
-    
-    return output_path
-
-# 3. Build the User Interface
-with gr.Blocks(theme="soft") as demo:
-    gr.Markdown("# ⚡ AnimateDiff Lightning (Free & Fast)")
-    gr.Markdown("A truly free, open-source video generator.")
-    
-    with gr.Row():
-        with gr.Column():
-            prompt_input = gr.Textbox(
-                label="Prompt", 
-                placeholder="Close up portrait of a cyberpunk woman, neon city background, rainfall, 8k, realistic",
-                lines=3
-            )
-            neg_prompt_input = gr.Textbox(
-                label="Negative Prompt", 
-                value="bad quality, worst quality, deformed, distorted, watermark",
-                lines=2
-            )
-            generate_btn = gr.Button("⚡ Generate Video", variant="primary")
-        
-        with gr.Column():
-            video_output = gr.Video(label="Generated Result")
-
-    generate_btn.click(
-        fn=generate_video,
-        inputs=[prompt_input, neg_prompt_input],
-        outputs=video_output
-    )
-
-# Launch
-demo.launch()
-
-