First draft of basic layout + model loading.

app.py

@@ -1,7 +1,57 @@
+# app.py
 import gradio as gr
+from transformers import AutoModel, AutoImageProcessor
+from PIL import Image
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Global state to store loaded model + processor
+state = {
+    "model": None,
+    "processor": None,
+    "repo_id": None,
+}
+
+def load_model(repo_id: str, revision: str = None):
+    """
+    Load a Hugging Face model and processor from a repo ID.
+    """
+    try:
+        model = AutoModel.from_pretrained(repo_id, revision=revision, trust_remote_code=False)
+        processor = AutoImageProcessor.from_pretrained(repo_id, revision=revision, trust_remote_code=False)
+        # Move model to CPU/GPU if needed
+        if torch.cuda.is_available():
+            model.to("cuda")
+        else:
+            model.to("cpu")
+        # Store in global state
+        state["model"] = model
+        state["processor"] = processor
+        state["repo_id"] = repo_id
+        return f"Successfully loaded model '{repo_id}'"
+    except Exception as e:
+        return f"Error loading model: {e}"
+
+def display_image(image: Image):
+    """
+    Simply returns the uploaded image (you can process it later).
+    """
+    return image
+
+# Build the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Dynamic ViT Loader Template")
+    
+    with gr.Row():
+        repo_input = gr.Textbox(label="Hugging Face model repo ID", placeholder="e.g. google/vit-base-patch16-224")
+        revision_input = gr.Textbox(label="Revision (optional)", placeholder="branch, tag, or commit hash")
+        load_btn = gr.Button("Load Model")
+    load_status = gr.Textbox(label="Model Status", interactive=False)
+    
+    image_input = gr.Image(type="pil", label="Upload Image")
+    image_output = gr.Image(label="Displayed Image")
+
+    # Button clicks / image upload handlers
+    load_btn.click(fn=load_model, inputs=[repo_input, revision_input], outputs=load_status)
+    image_input.change(fn=display_image, inputs=image_input, outputs=image_output)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()