app_mm.py

import gradio as gr
import torch
import gc
import json
from pipeline_tabs.text_tab import text_tab
from pipeline_tabs.diffusion_tab import diffusion_tab

model_cache = {}

def unload_all_models():
    model_cache.clear()
    gc.collect()
    if torch.cuda.is_available():
        torch.cuda.empty_cache()

with gr.Blocks() as demo:
    with gr.Tabs():
        text_tab(model_cache, unload_all_models)
        diffusion_tab(model_cache, unload_all_models)
    # Shared state display
    def pretty_json():
        return json.dumps(list(model_cache.keys()), indent=2, ensure_ascii=False)
    state_box = gr.Textbox(label="Loaded Models", lines=4, interactive=False, value=pretty_json())
    # Update state_box whenever a model is loaded/unloaded
    demo.load(fn=pretty_json, inputs=None, outputs=state_box)

    # Optionally, you can add a button to refresh the state display
    refresh_btn = gr.Button("Refresh Model State")
    refresh_btn.click(fn=pretty_json, inputs=None, outputs=state_box)

demo.launch()