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Create app.py
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app.py
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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# Load a language model (e.g., Llama) for generating alternative XPath suggestions
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tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b") # Replace with the actual model
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model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b")
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# Helper function to generate alternative XPaths
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def get_alternative_xpaths(html_structure, original_xpath):
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prompt = f"""
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Given the following HTML structure and an original XPath, generate alternative XPaths that could help locate the same element if it has changed position.
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HTML Structure:
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{html_structure}
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Original XPath: {original_xpath}
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Suggested alternative XPaths:
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"""
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# Encode and generate with the model
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(inputs['input_ids'], max_length=200, temperature=0.3)
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response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Process the response to extract XPath suggestions
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alternative_xpaths = response_text.strip().split('\n')
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return alternative_xpaths
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# Gradio interface function for self-healing XPath
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def locate_element_with_self_healing(html_structure, original_xpath):
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# Simulate the failure to find an element and ask for alternatives
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print("Original XPath failed. Attempting to heal...")
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alternative_xpaths = get_alternative_xpaths(html_structure, original_xpath)
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return {
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"original_xpath": original_xpath,
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"alternative_xpaths": alternative_xpaths
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}
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# Define Gradio interface
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interface = gr.Interface(
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fn=locate_element_with_self_healing,
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inputs=[
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gr.Textbox(label="HTML Structure", placeholder="Paste the HTML structure here..."),
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gr.Textbox(label="Original XPath", placeholder="//div[@id='submit-button']")
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],
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outputs=[
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gr.JSON(label="Healing Result")
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],
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title="Self-Healing XPath API",
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description="This tool provides alternative XPaths if the original XPath is not found in the given HTML structure."
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)
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# Launch the Gradio interface
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interface.launch()
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