Update app.py

app.py

@@ -1,7 +1,45 @@
 import gradio as gr
+from transformers import AutoTokenizer
 
-def greet(name):
-    return "Hello " + name + "!!"
+def load_tokenizer(repo_path):
+    try:
+        # Load the tokenizer from the provided repository path
+        tokenizer = AutoTokenizer.from_pretrained(repo_path, trust_remote_code=True)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+        messages = [
+            {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
+            {"role": "user", "content": "Who are you?"},
+        ]
+
+        input_ids = tokenizer.apply_chat_template(
+            messages,
+            add_generation_prompt=True,
+            tokenize=False,
+        )
+        
+        # Extract relevant details about the tokenizer and chat template
+        details = {
+            "Tokenizer Name": tokenizer.name_or_path,
+            "Vocabulary Size": tokenizer.vocab_size,
+            "Model Max Length": tokenizer.model_max_length,
+            "Special Tokens": tokenizer.all_special_tokens,
+            "Chat Template": input_ids,
+        }
+        
+        # Convert details to a formatted string for display
+        details_str = "\n".join([f"{key}: {value}" for key, value in details.items()])
+        return details_str
+    except Exception as e:
+        return str(e)
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=load_tokenizer,
+    inputs=gr.Textbox(label="Hugging Face Repository Path (e.g., user/repo)"),
+    outputs=gr.Textbox(label="Tokenizer Details"),
+    title="Hugging Face Tokenizer Loader",
+    description="Enter the Hugging Face repository path to load the tokenizer and view its details."
+)
+
+# Launch the app
+iface.launch()