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import openai | |
import os | |
from bs4 import BeautifulSoup | |
from bs4.element import Comment | |
from selenium import webdriver | |
from selenium.webdriver.chrome.service import Service | |
import re | |
openai.api_key = os.getenv('OPENAI_API_KEY') | |
url = "https://www.greatschools.org/california/san-jose/5442-Joaquin-Miller-Middle-School" | |
questions = [ | |
"where is the location of school? ", | |
"how many students this school has?", | |
"what percentage of the students are asian?" | |
] | |
tags = ["p_div"] | |
question_str = " ".join(questions) | |
chrome_driver_path = "<path_to_chromium>" | |
options = webdriver.ChromeOptions() | |
options.add_argument('--headless') | |
driver = webdriver.Chrome(service=Service(chrome_driver_path), options=options) | |
driver.get(url) | |
driver.implicitly_wait(5) # Let the JavaScript load | |
html = driver.page_source | |
soup = BeautifulSoup(html, "html.parser") # Get the page source and parse it | |
driver.close() # Close the driver | |
def tag_visible(element): | |
if element.parent.name in ['style', 'script', 'head', 'title', 'meta', '[document]']: | |
return False | |
if isinstance(element, Comment): | |
return False | |
return True | |
def text_from_html(html): | |
texts = soup.findAll(text=True) | |
visible_texts = filter(tag_visible, texts) | |
return u" ".join(t.strip() for t in visible_texts) | |
def get_completion(prompt, model="gpt-3.5-turbo"): #This is a more one turn conversation | |
messages = [{"role": "user", "content": prompt}] | |
response = openai.ChatCompletion.create( | |
model=model, | |
messages=messages, | |
temperature=0, # this is the degree of randomness of the model's output | |
) | |
return response.choices[0].message["content"] | |
target_text = text_from_html(html) | |
prompt = f""" | |
The output from webscrap and subsequent regex processing is delimited in triple quotes. | |
Answer the following questions: {question_str} | |
### {target_text} ###. | |
""" | |
response = get_completion(prompt) | |
print(response) |
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