from gradio_client import Client, file, handle_file client = Client("http://sd.demo.polygraf.ai:7890/") generated_text = client.predict( input_role="Student", topic="Low Resource Language Models", keywords="", article_length=400, format="Article", writing_style="Formal", tone="Professional", user_category="General Public", depth_of_content="Moderate analysis", structure="Introduction, Body, Conclusion", references="News outlets", num_examples="1-2", conclusion_type="Call to Action", # ai_model="OpenAI GPT 4o Mini", ai_model="LLaMA 3", google_search_check=True, year_from="2000", month_from="January", day_from="01", year_to="2024", month_to="August", day_to="08", domains_to_include=["com", "org", "net", "int", "edu", "gov", "mil"], include_sites="", exclude_sites="", pdf_file_input=[handle_file("/home/eljan/article_writer/Abstract.pdf")], api_name="/generate_and_format", ) client.predict(text="Polygraf AI (Advanced Model)", api_name="/highlight_visible_1") detect_generated = client.predict( text=generated_text, option="Polygraf AI (Advanced Model)", api_name="/ai_check", ) humanized_text = client.predict( text=generated_text, model="XL Model", temperature=1.2, repetition_penalty=1, top_k=50, length_penalty=1, api_name="/humanize", ) client.predict(text="Polygraf AI (Advanced Model)", api_name="/highlight_visible_1") detect_humanized = client.predict( text=humanized_text, option="Polygraf AI (Advanced Model)", api_name="/ai_check", ) print(detect_generated) print(detect_humanized)