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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
# Load a publicly accessible model
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-neo-2.7B")
def get_alternative_xpaths(html_structure, original_xpath):
prompt = f"""
Given the following HTML structure and an original XPath, generate alternative XPaths that could help locate the same element if it has changed position.
HTML Structure:
{html_structure}
Original XPath: {original_xpath}
Suggested alternative XPaths:
"""
# Generate response
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(inputs['input_ids'], max_length=200, temperature=0.3)
response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
alternative_xpaths = response_text.strip().split('\n')
return alternative_xpaths
def locate_element_with_self_healing(html_structure, original_xpath):
print("Original XPath failed. Attempting to heal...")
alternative_xpaths = get_alternative_xpaths(html_structure, original_xpath)
return {
"original_xpath": original_xpath,
"alternative_xpaths": alternative_xpaths
}
interface = gr.Interface(
fn=locate_element_with_self_healing,
inputs=[
gr.Textbox(label="HTML Structure", placeholder="Paste the HTML structure here..."),
gr.Textbox(label="Original XPath", placeholder="//div[@id='submit-button']")
],
outputs=[
gr.JSON(label="Healing Result")
],
title="Self-Healing XPath API",
description="This tool provides alternative XPaths if the original XPath is not found in the given HTML structure."
)
interface.launch()
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