Update app.py

app.py

@@ -1,26 +1,23 @@
-import os
 import torch
 import gradio as gr
 from diffusers import AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler
-from huggingface_hub import login
-
-# HuggingFace auth (Space secret)
-login(token=os.environ["HF_TOKEN"])
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 dtype = torch.float16 if device == "cuda" else torch.float32
 
 print("Running on:", device)
 
+# Load motion adapter (video motion)
 adapter = MotionAdapter.from_pretrained(
     "guoyww/animatediff-motion-adapter-v1-5-2",
     torch_dtype=dtype
 )
 
+# Load base Stable Diffusion model
 pipe = AnimateDiffPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-schnell",
+    "runwayml/stable-diffusion-v1-5",
     motion_adapter=adapter,
-    torch_dtype=dtype,
+    torch_dtype=dtype
 )
 
 pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
@@ -30,12 +27,13 @@ pipe.enable_vae_slicing()
 pipe.enable_attention_slicing()
 
 def generate(prompt, steps, guidance, frames, fps, seed):
-    generator = torch.Generator(device).manual_seed(int(seed))
+    generator = torch.Generator(device=device).manual_seed(int(seed))
+
     video = pipe(
-        prompt,
-        num_inference_steps=steps,
-        guidance_scale=guidance,
-        num_frames=frames,
+        prompt=prompt,
+        num_inference_steps=int(steps),
+        guidance_scale=float(guidance),
+        num_frames=int(frames),
         generator=generator
     ).frames[0]
 
@@ -45,14 +43,15 @@ demo = gr.Interface(
     fn=generate,
     inputs=[
         gr.Textbox(label="Prompt"),
-        gr.Slider(5, 30, value=15, label="Steps"),
-        gr.Slider(1, 10, value=7.5, label="Guidance"),
-        gr.Slider(8, 32, value=16, label="Frames"),
-        gr.Slider(4, 24, value=8, label="FPS"),
+        gr.Slider(10, 40, value=20, step=1, label="Steps"),
+        gr.Slider(1, 12, value=7.5, step=0.5, label="Guidance"),
+        gr.Slider(8, 32, value=16, step=1, label="Frames"),
+        gr.Slider(4, 24, value=8, step=1, label="FPS"),
         gr.Number(value=42, label="Seed"),
     ],
     outputs=gr.Video(),
-    title="FLUX AnimateDiff – ZeroGPU Video Generator"
+    title="AnimateDiff Video Generator",
+    description="Text to Video using Stable Diffusion + AnimateDiff"
 )
 
 demo.launch()