Update app.py

app.py

@@ -5,6 +5,7 @@ import numpy as np
 import gradio as gr
 import os
 import gc
+import spaces
 
 
 model_id = "hunyuanvideo-community/HunyuanVideo"
@@ -15,11 +16,15 @@ transformer = HunyuanVideoTransformer3DModel.from_pretrained(
 
 pipe = HunyuanVideoPipeline.from_pretrained(model_id, transformer=transformer, torch_dtype=torch.float16)
 pipe.vae.enable_tiling()
-pipe.load_lora_weights("ovi054/ovimxVid")
-pipe.to("cuda")
-
-
-def generate(prompt, negative_prompt, width=1280, height=720, num_inference_steps=30, progress=gr.Progress(track_tqdm=True)):
+# pipe.load_lora_weights("ovi054/ovimxVid")
+# pipe.to("cuda")
+
+@spaces.GPU()
+def generate(prompt, width=832, height=832, num_inference_steps=30, lora_id=None, progress=gr.Progress(track_tqdm=True)):
+    if lora_id and lora_id.strip() != "":
+        pipe.unload_lora_weights()
+        pipe.load_lora_weights(lora_id.strip())
+    pipe.to("cuda")
     try:
         output = pipe(
             prompt=prompt,
@@ -45,10 +50,11 @@ iface = gr.Interface(
         gr.Textbox(label="Input prompt"),
     ],
     additional_inputs = [
-        gr.Textbox(label="Negative prompt", value = "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"),
+        # gr.Textbox(label="Negative prompt", value = "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"),
         gr.Slider(label="Width", minimum=480, maximum=1280, step=16, value=832),
         gr.Slider(label="Height", minimum=480, maximum=1280, step=16, value=832),
         gr.Slider(minimum=1, maximum=80, step=1, label="Inference Steps", value=30)
+        gr.Textbox(label="LoRA ID"),
     ],
     outputs=gr.Image(label="output"),
 )