| from transformers import pipeline | |
| from bs4 import BeautifulSoup | |
| import requests | |
| import gradio as gr | |
| def extract_text_from_url(url): | |
| response = requests.get(url) | |
| soup = BeautifulSoup(response.text, 'html.parser') | |
| return soup.get_text() | |
| def answer_question(context, question): | |
| qa_pipeline = pipeline("question-answering") | |
| answer = qa_pipeline({ | |
| 'context': context, | |
| 'question': question | |
| }) | |
| return answer['answer'] | |
| def app(url, question): | |
| webpage_text = extract_text_from_url(url) | |
| answer = answer_question(webpage_text, question) | |
| return answer | |
| iface = gr.Interface(fn=app, inputs=["text", "text"], outputs="text") | |
| iface.launch() | |