Delete app.py

app.py

@@ -1,57 +0,0 @@
-import os
-import subprocess
-import gradio as gr
-from caption import generate_caption  # Your BLIP-2 captioning script
-
-# ===== 1. Install Kohya_SS Manually =====
-if not os.path.exists("kohya_ss"):
-    print("⬇️ Cloning Kohya_SS...")
-    os.system("git clone https://github.com/bmaltais/kohya_ss")
-    os.chdir("kohya_ss")
-    os.system("pip install -r requirements.txt")
-    os.system("pip install .")  # Editable install
-    os.chdir("..")
-
-# ===== 2. Training Function =====
-def train_lora(images, trigger_word, model_choice="Flux"):
-    # Save images
-    os.makedirs("train", exist_ok=True)
-    for i, img in enumerate(images):
-        img_path = f"train/img_{i}.jpg"
-        img.save(img_path)
-        # Auto-caption (from caption.py)
-        caption = generate_caption(img_path, trigger_word)
-        with open(f"train/img_{i}.txt", "w") as f:
-            f.write(caption)
-
-    # Train LoRA (simplified Kohya_SS command)
-    cmd = f"""
-    python kohya_ss/train_network.py \
-        --pretrained_model_name_or_path="{model_choice}" \
-        --train_data_dir="train" \
-        --output_dir="output" \
-        --resolution=512 \
-        --network_dim=64 \
-        --lr=1e-4 \
-        --max_train_steps=1000
-    """
-    subprocess.run(cmd, shell=True)
-    return "output/lora.safetensors"
-
-# ===== 3. Gradio UI =====
-with gr.Blocks() as demo:
-    gr.Markdown("## 🎨 1-Click LoRA Trainer")
-    with gr.Row():
-        images = gr.Files(label="Upload 30 Images", file_types=["image"])
-        trigger = gr.Textbox(label="Trigger Word (e.g., 'my_char')")
-    train_btn = gr.Button("🚀 Train LoRA")
-    output = gr.File(label="Download LoRA")
-    
-    train_btn.click(
-        train_lora,
-        inputs=[images, trigger],
-        outputs=output
-    )
-
-if __name__ == "__main__":
-    demo.launch()