Update app.py

app.py

@@ -1,25 +1,36 @@
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from selenium import webdriver
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.common.by import By
 
-model_name = "gpt-3.5-turbo"
+def scrape_website(url):
+    # Create a new instance of the Chrome driver
+    driver = webdriver.Chrome()
+    
+    # Navigate to the provided URL
+    driver.get(url)
+    
+    # Wait until all processes are complete
+    wait = WebDriverWait(driver, 10)  # Maximum wait time in seconds
+    wait.until(EC.presence_of_element_located((By.TAG_NAME, 'body')))
+    
+    # Extract the page title
+    title = driver.title
+    
+    # Close the browser
+    driver.quit()
+    
+    return title
 
-# Load the model and tokenizer
-model = AutoModelForCausalLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=scrape_website,
+    inputs="text",
+    outputs="text",
+    title="Web Scraping Application",
+    description="Enter a URL to extract the page title."
+)
 
-# Generate a response
-def generate_response(prompt):
-    inputs = tokenizer.encode(prompt, return_tensors="pt")
-    response = model.generate(inputs, max_length=100, num_return_sequences=1)
-    return tokenizer.decode(response[0], skip_special_tokens=True)
-
-# Gradio interface
-def chatbot_interface(prompt):
-    response = generate_response(prompt)
-    return response
-
-# Create a Gradio interface
-iface = gr.Interface(fn=chatbot_interface, inputs="text", outputs="text")
-
-# Launch the interface
-iface.launch()
+# Run the Gradio app
+interface.launch()