Update app_demo.py

app_demo.py

@@ -1,4 +1,76 @@
-#!/usr/bin/env python
+import gradio as gr
+from huggingface_hub import HfApi, snapshot_download
+from concurrent.futures import ThreadPoolExecutor
+import asyncio
+import ast
+import os
+
+api = HfApi()
+executor = ThreadPoolExecutor()
+model_cache = {}
+
+def validate_and_list_models(hfuser):
+    try:
+        models = api.list_models(author=hfuser)
+        return [model.modelId for model in models if model.pipeline_tag == "text-to-image"]
+    except Exception:
+        return []
+
+def parse_user_model_dict(user_model_dict_str):
+    try:
+        data = ast.literal_eval(user_model_dict_str)
+        if isinstance(data, dict) and all(isinstance(v, list) for v in data.values()):
+            return data
+        return {}
+    except Exception:
+        return {}
+
+def load_model(model_id):
+    if model_id in model_cache:
+        return f"{model_id} loaded from cache"
+    try:
+        path = snapshot_download(repo_id=model_id, cache_dir="model_cache", token=os.getenv("HF_TOKEN"))
+        model_cache[model_id] = path
+        return f"{model_id} loaded successfully"
+    except Exception as e:
+        return f"{model_id} failed to load: {str(e)}"
+
+def run_models(models, parallel):
+    if parallel:
+        futures = [executor.submit(load_model, m) for m in models]
+        return [f.result() for f in futures]
+    else:
+        return [load_model(m) for m in models]
+
+with gr.Blocks() as demo:
+    hfuser_input = gr.Textbox(label="Hugging Face Username")
+    hfuser_models = gr.Dropdown(label="Models from User", choices=[], multiselect=True)
+    
+    user_model_dict = gr.Textbox(label="Dict Input (e.g., {'username': ['model1', 'model2']})")
+
+    parallel_toggle = gr.Checkbox(label="Load in Parallel", value=True)
+    output = gr.Textbox(label="Output", lines=10)
+
+    def update_models(hfuser):
+        return gr.update(choices=validate_and_list_models(hfuser))
+
+    def update_from_dict(dict_str):
+        parsed = parse_user_model_dict(dict_str)
+        if not parsed:
+            return gr.update(), gr.update()
+        hfuser = next(iter(parsed))
+        return gr.update(value=hfuser), gr.update(choices=parsed[hfuser], value=parsed[hfuser])
+
+    hfuser_input.change(update_models, hfuser_input, hfuser_models)
+    user_model_dict.change(update_from_dict, user_model_dict, [hfuser_input, hfuser_models])
+
+    run_btn = gr.Button("Load Models")
+    run_btn.click(run_models, [hfuser_models, parallel_toggle], output)
+
+demo.launch()
+
+
+'''#!/usr/bin/env python
 from __future__ import annotations
 import os
 import random
@@ -13,7 +85,7 @@ import uuid
 
 model_id = "Lykon/dreamshaper-xl-v2-turbo"
 DESCRIPTION = '''# Fast Stable Diffusion CPU with Latent Consistency Model
-Distilled from [Dreamshaper v7](https://huggingface.co/Lykon/dreamshaper-7) fine‑tune of SD v1-5.
+#Distilled from [Dreamshaper v7](https://huggingface.co/Lykon/dreamshaper-7) fine‑tune of SD v1-5.
 '''
 if not torch.cuda.is_available():
     DESCRIPTION += "\n<p>running on CPU.</p>"
@@ -114,8 +186,8 @@ with gr.Blocks(css="style.css") as demo:
         gallery = gr.Gallery(
             label="Generated images",
             show_label=False,
-            elem_id="gallery",
-            grid=[2]
+            elem_id="gallery"
+           
         )
 
     with gr.Accordion("Advanced options", open=False):
@@ -139,3 +211,4 @@ with gr.Blocks(css="style.css") as demo:
 
     demo.queue()
     demo.launch()
+'''