Add description

app.py

@@ -4,14 +4,11 @@ import json
 
 tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
 
-demo_conversation1 = """[
+demo_conversation = """[
+    {"role": "system": "content": "You are a helpful chatbot."},
     {"role": "user", "content": "Hi there!"},
-    {"role": "assistant", "content": "Hello, human!"}
-]"""
-
-demo_conversation2 = """[
-    {"role": "system", "content": "You are a helpful chatbot."},
-    {"role": "user", "content": "Hi there!"}
+    {"role": "assistant", "content": "Hello, human!"},
+    {"role": "user", "content": "Can I ask a question?"}
 ]"""
 
 default_template = """{% for message in messages %}
@@ -21,27 +18,26 @@ default_template = """{% for message in messages %}
     {{ "<|im_start|>assistant\\n" }}
 {% endif %}"""
 
-conversations = [demo_conversation1, demo_conversation2]
+description_text = """This space is a helper app for writing [Chat Templates](https://huggingface.co/docs/transformers/main/en/chat_templating). Please see the linked
+documentation for more information! When you're happy with the outputs from your template, you can use the code block at the end to create a PR to add your template to a
+model"""
 
-def apply_chat_template(template, test_conversation1, test_conversation2, cleanup_whitespace):
+def apply_chat_template(template, test_conversation, add_generation_prompt, cleanup_whitespace):
     if cleanup_whitespace:
         template = "".join([line.strip() for line in template.split('\n')])
     tokenizer.chat_template = template
     outputs = []
-    for i, conversation_str in enumerate((test_conversation1, test_conversation2)):
-        conversation = json.loads(conversation_str)
-        outputs.append(tokenizer.apply_chat_template(conversation, tokenize=False))
-        outputs.append(tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True))
-    return tuple(outputs)
+    conversation = json.loads(test_conversation)
+    return tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=add_generation_prompt)
 
-output_names = ["Conversation 1 without generation prompt", "Conversation 1 with generation prompt", "Conversation 2 without generation prompt", "Conversation 2 with generation prompt"]
 iface = gr.Interface(
+    description=description_text,
     fn=apply_chat_template,
     inputs=[
         gr.TextArea(value=default_template, lines=10, max_lines=30, label="Chat Template"),
-        gr.TextArea(value=str(demo_conversation1), lines=5, label="Conversation 1"),
-        gr.TextArea(value=str(demo_conversation2), lines=5, label="Conversation 2"),
+        gr.TextArea(value=demo_conversation, lines=6, label="Conversation"),
+        gr.Checkbox(value=False, label="Add generation prompt"),
         gr.Checkbox(value=True, label="Cleanup template whitespace"),
     ],
-    outputs=[gr.TextArea(label=output_name) for output_name in output_names])
+    outputs=gr.TextArea(label="Formatted conversation"))
 iface.launch()