Update app.py

app.py

@@ -1,10 +1,11 @@
+import gradio as gr
 import time
 from transformers import pipeline
 
 # Load the speed reading model from Hugging Face Spaces
 speed_reading = pipeline("text-classification", model="sberbank-ai/rugpt3small_based_on_gpt2")
 
-def speed_reading_test(text):
+def perform_speed_reading(text):
     # Split the text into individual sentences
     sentences = text.split(".")
     
@@ -30,13 +31,15 @@ def speed_reading_test(text):
     # Calculate reading speed in words per minute (WPM)
     wpm = (words_read / time_taken) * 60
     
-    print("Words Read:", words_read)
-    print("Time Taken (seconds):", time_taken)
-    print("Reading Speed (WPM):", wpm)
+    return words_read, time_taken, wpm
 
-# Example text for testing
-text = """
-This is an example speed reading test. It is designed to measure your reading speed using a machine learning model. You will be presented with a series of sentences. Your task is to read each sentence as quickly as possible while maintaining comprehension. At the end of the test, your reading speed will be calculated in words per minute.
-"""
+# Interface
+def speed_reading_interface(text):
+    words_read, time_taken, wpm = perform_speed_reading(text)
+    return f"Words Read: {words_read}, Time Taken (seconds): {time_taken}, Reading Speed (WPM): {wpm}"
 
-speed_reading_test(text)
+gr.Interface(
+    fn=speed_reading_interface,
+    inputs=gr.inputs.Textbox(lines=10, label="Enter text here"),
+    outputs="text"
+).launch()