Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 import torch
 from transformers import AutoModelForSeq2SeqLM, T5Tokenizer
+import time
 
 # Load the model and tokenizer from Hugging Face
 model_name = "ambrosfitz/history-qa-t5-base"
@@ -41,15 +42,27 @@ def generate_qa(text, max_length=512):
     else:
         return "Unable to generate a proper question and answer. Please try again with a different input."
 
-# Define the Gradio interface
-iface = gr.Interface(
-    fn=generate_qa,
-    inputs=gr.Textbox(lines=5, label="Enter historical text"),
-    outputs=gr.Textbox(label="Generated Q&A"),
-    title="History Q&A Generator",
-    description="Enter a piece of historical text, and the model will generate a related question, answer options, correct answer, and explanation."
-)
+def slow_qa(message, history):
+    full_response = generate_qa(message)
+    for i in range(len(full_response)):
+        time.sleep(0.01)  # Adjust this value to control the speed of the response
+        yield full_response[:i+1]
 
-# Launch the app
-if __name__ == "__main__":
-    iface.launch()
+# Create and launch the Gradio interface
+gr.ChatInterface(
+    slow_qa,
+    chatbot=gr.Chatbot(height=500),
+    textbox=gr.Textbox(placeholder="Enter historical text here...", container=False, scale=7),
+    title="History Q&A Generator",
+    description="Enter a piece of historical text, and the model will generate a related question, answer options, correct answer, and explanation.",
+    theme="soft",
+    examples=[
+        "The American Revolution was a colonial revolt that took place between 1765 and 1783.",
+        "World War II was a global conflict that lasted from 1939 to 1945, involving many of the world's nations.",
+        "The Renaissance was a period of cultural, artistic, political, and economic revival following the Middle Ages."
+    ],
+    cache_examples=False,
+    retry_btn="Regenerate",
+    undo_btn="Remove last",
+    clear_btn="Clear",
+).launch()