Fix: Upgrade to Gradio 5 + cleanup inputs

app.py

@@ -14,7 +14,6 @@ import torch
 import numpy as np
 from PIL import Image
 import tempfile, os
-from huggingface_hub import hf_hub_download
 
 # ─── CONFIGURACIÓN DE MODELOS ──────────────────────────────────────────────────
 BASE_MODEL = "cyberdelia/CyberRealisticPony"
@@ -44,21 +43,6 @@ def load_t2i(lora_id=None, lora_scale=1.0):
         except: pass
     return pipe_t2i
 
-def load_i2i(lora_id=None, lora_scale=1.0):
-    global pipe_i2i
-    from diffusers import StableDiffusionXLImg2ImgPipeline
-    if pipe_i2i is None:
-        pipe_i2i = StableDiffusionXLImg2ImgPipeline.from_pretrained(
-            BASE_MODEL, torch_dtype=torch.float16, use_safetensors=True, variant="fp16"
-        )
-    if lora_id:
-        try:
-            pipe_i2i.unload_lora_weights()
-            pipe_i2i.load_lora_weights(lora_id)
-            pipe_i2i.fuse_lora(lora_scale=lora_scale)
-        except: pass
-    return pipe_i2i
-
 def load_video():
     global pipe_video
     from diffusers import LTXPipeline
@@ -79,17 +63,6 @@ def generate_t2i(prompt, neg, lora_id, lora_scale, steps, cfg, w, h, seed):
     pipe.to("cpu"); torch.cuda.empty_cache()
     return img
 
-@spaces.GPU(duration=120)
-def generate_i2i(prompt, neg, init_image, strength, lora_id, lora_scale, steps, cfg, seed):
-    if init_image is None: return None
-    pipe = load_i2i(lora_id if lora_id else None, lora_scale).to("cuda")
-    gen = torch.Generator("cuda").manual_seed(int(seed))
-    img = Image.fromarray(init_image).convert("RGB").resize((1024, 1024))
-    res = pipe(prompt=prompt, negative_prompt=neg, image=img, strength=strength,
-               num_inference_steps=int(steps), guidance_scale=cfg, generator=gen).images[0]
-    pipe.to("cpu"); torch.cuda.empty_cache()
-    return res
-
 @spaces.GPU(duration=200)
 def generate_video(prompt, neg, init_image, num_frames, fps, steps, lora_scale, seed):
     from diffusers.utils import export_to_video
@@ -108,29 +81,28 @@ def generate_video(prompt, neg, init_image, num_frames, fps, steps, lora_scale,
     return tmp.name
 
 # ─── UI CAMUFLADA ──────────────────────────────────────────────────────────────
-THEME = gr.themes.Default(primary_hue="slate", neutral_hue="slate").set(
-    body_background_fill="#f3f4f6", block_background_fill="#ffffff", 
-)
-
-with gr.Blocks(theme=THEME, title="Image Utility v2.1") as demo:
+with gr.Blocks(theme=gr.themes.Default(primary_hue="slate", neutral_hue="slate"), title="Image Utility v2.1") as demo:
     gr.HTML("<h1 style='text-align:center; color:#374151;'>🛠 Image Processing Utility v2.1.4</h1>")
-    gr.HTML("<p style='text-align:center; color:#6b7280;'>Herramienta técnica para el procesamiento y escalado de matrices de píxeles.</p>")
     
     with gr.Tabs():
         with gr.Tab("D-Processor (T2I)"):
             with gr.Row():
                 with gr.Column():
-                    t2i_p = gr.Textbox(label="Input Data String", lines=3, placeholder="Enter parameters...")
+                    t2i_p = gr.Textbox(label="Input Data String", lines=3)
                     t2i_n = gr.Textbox(label="Excluded Data", value=NEG_DEFAULT)
                     with gr.Row():
-                        t2i_lora = gr.Textbox(label="Extension ID", placeholder="Module ID (optional)")
+                        t2i_lora = gr.Textbox(label="Extension ID")
                         t2i_ls = gr.Slider(0, 1.5, 0.8, label="Extension Weight")
                     with gr.Row():
                         t2i_w = gr.Slider(512, 1280, 1024, step=64, label="X-Axis")
                         t2i_h = gr.Slider(512, 1280, 1024, step=64, label="Y-Axis")
-                    t2i_btn = gr.Button("Execute Process", variant="secondary")
+                    with gr.Row():
+                        t2i_steps = gr.Number(value=30, label="P-Steps", visible=False)
+                        t2i_cfg = gr.Number(value=7.0, label="P-Cfg", visible=False)
+                        t2i_seed = gr.Number(value=42, label="P-Seed", visible=False)
+                    t2i_btn = gr.Button("Execute Process")
                 t2i_out = gr.Image(label="Output Preview")
-            t2i_btn.click(generate_t2i, [t2i_p, t2i_n, t2i_lora, t2i_ls, gr.Number(30), gr.Number(7.5), t2i_w, t2i_h, gr.Number(42)], t2i_out)
+            t2i_btn.click(generate_t2i, [t2i_p, t2i_n, t2i_lora, t2i_ls, t2i_steps, t2i_cfg, t2i_w, t2i_h, t2i_seed], t2i_out)
 
         with gr.Tab("M-Sequence (Video)"):
             with gr.Row():
@@ -138,8 +110,13 @@ with gr.Blocks(theme=THEME, title="Image Utility v2.1") as demo:
                     v_p = gr.Textbox(label="Motion Vector String", lines=3)
                     v_img = gr.Image(label="Source Buffer", type="numpy")
                     v_ls = gr.Slider(0, 1.5, 0.8, label="Motion Weight")
-                    v_btn = gr.Button("Process Sequence", variant="secondary")
+                    with gr.Row():
+                        v_frames = gr.Number(value=49, visible=False)
+                        v_fps = gr.Number(value=24, visible=False)
+                        v_steps = gr.Number(value=30, visible=False)
+                        v_seed = gr.Number(value=42, visible=False)
+                    v_btn = gr.Button("Process Sequence")
                 v_out = gr.Video(label="Sequence Output")
-            v_btn.click(generate_video, [v_p, gr.Textbox(value=NEG_DEFAULT), v_img, gr.Number(49), gr.Number(24), gr.Number(30), v_ls, gr.Number(42)], v_out)
+            v_btn.click(generate_video, [v_p, gr.Textbox(value=NEG_DEFAULT, visible=False), v_img, v_frames, v_fps, v_steps, v_ls, v_seed], v_out)
 
-demo.launch()
+demo.launch(server_name="0.0.0.0", server_port=7860)