Update app.py

app.py

@@ -4,9 +4,10 @@ import json
 import os
 from huggingface_hub import login
 
-HUGGINGFACEHUB_API_TOKEN = os.environ.get("HF_TOKEN")
+# Fetch HF Token
+HUGGINGFACEHUB_API_TOKEN = os.environ.get("HF_TOKEN", "")
 
-default_model="meta-llama/Meta-Llama-3-8B-Instruct"
+default_model = "meta-llama/Meta-Llama-3-8B-Instruct"
 
 demo_conversation = """[
     {"role": "system", "content": "You are a helpful chatbot."},
@@ -19,9 +20,19 @@ description_text = """# Chat Template Viewer
 ### This space is a helper to learn more about [Chat Templates](https://huggingface.co/docs/transformers/main/en/chat_templating).
 """
 
-default_tools = [{"type": "function", "function": {"name":"get_current_weather", "description": "Get▁the▁current▁weather", "parameters": {"type": "object", "properties": {"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}, "format": {"type": "string", "enum": ["celsius", "fahrenheit"], "description": "The temperature unit to use. Infer this from the users location."}},"required":["location","format"]}}}]
+default_tools = [{"type": "function", "function": {"name": "get_current_weather",
+                "description": "Get the current weather",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"},
+                        "format": {"type": "string", "enum": ["celsius", "fahrenheit"],
+                                   "description": "The temperature unit to use. Infer this from the user's location."}
+                    },
+                    "required": ["location", "format"]
+                }
+            }}]
 
-# render the tool use prompt as a string:
 def get_template_names(model_name):
     try:
         tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -35,38 +46,55 @@ def get_template_names(model_name):
 def update_template_dropdown(model_name):
     template_names = get_template_names(model_name)
     if template_names:
-        return gr.update(choices=template_names, value=None)
+        return gr.Dropdown.update(choices=template_names, value=template_names[0])
+    return gr.Dropdown.update(choices=[], value=None)
 
 def apply_chat_template(model_name, test_conversation, add_generation_prompt, cleanup_whitespace, template_name, hf_token, kwargs):
     try:
-        login(token=hf_token)
+        if hf_token:
+            login(token=hf_token)  # Ensure login is successful
+
         tokenizer = AutoTokenizer.from_pretrained(model_name)
-    except:
-        return f"model {model_name} could not be loaded or invalid HF token"
+    except Exception as e:
+        return f"Error: Could not load model {model_name} or invalid HF token. {str(e)}"
+
     try:
-        outputs = []
         conversation = json.loads(test_conversation)
         
-        template = tokenizer.chat_template.get(template_name) if template_name else None
-        print(kwargs)
-        formatted = tokenizer.apply_chat_template(conversation, chat_template=template, tokenize=False, add_generation_prompt=add_generation_prompt, tools=default_tools)
+        if template_name and tokenizer.chat_template:
+            template = tokenizer.chat_template.get(template_name, None)
+        else:
+            template = None
+
+        formatted = tokenizer.apply_chat_template(
+            conversation,
+            chat_template=template,
+            tokenize=False,
+            add_generation_prompt=add_generation_prompt,
+            tools=default_tools
+        )
         return formatted
     except Exception as e:
-        return str(e)
+        return f"Error: {str(e)}"
 
 with gr.Blocks() as demo:
+    gr.Markdown(description_text)
+
     model_name_input = gr.Textbox(label="Model Name", placeholder="Enter model name", value=default_model)
     template_dropdown = gr.Dropdown(label="Template Name", choices=[], interactive=True)
     conversation_input = gr.TextArea(value=demo_conversation, lines=6, label="Conversation")
     add_generation_prompt_checkbox = gr.Checkbox(value=False, label="Add generation prompt")
     cleanup_whitespace_checkbox = gr.Checkbox(value=True, label="Cleanup template whitespace")
-    hf_token_input = gr.Textbox(label="Hugging Face Token (optional)", placeholder="Enter your HF token")
-    kwargs_input = gr.JSON(label="Additional kwargs", value=default_tools, render=False)
-    output = gr.TextArea(label="Formatted conversation")
+    hf_token_input = gr.Textbox(label="Hugging Face Token (optional)", placeholder="Enter your HF token", type="password")
+    kwargs_input = gr.JSON(label="Additional kwargs", value=default_tools, visible=False)
+    output = gr.TextArea(label="Formatted conversation", interactive=False)
+
+    update_button = gr.Button("Update Template List")
+    format_button = gr.Button("Format Conversation")
+
+    update_button.click(fn=update_template_dropdown, inputs=model_name_input, outputs=template_dropdown)
 
-    model_name_input.change(fn=update_template_dropdown, inputs=model_name_input, outputs=template_dropdown)
-    gr.Interface(
-        description=description_text,
+    format_button.click(
         fn=apply_chat_template,
         inputs=[
             model_name_input,
@@ -80,4 +108,4 @@ with gr.Blocks() as demo:
         outputs=output
     )
 
-demo.launch()
+demo.launch()