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84f2f65 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | from playwright.sync_api import sync_playwright
import time
def test_app():
with sync_playwright() as p:
print("Launching browser...")
browser = p.chromium.launch(headless=True)
page = browser.new_page()
url = "http://localhost:8000/static/index.html"
print(f"Navigating to {url}...")
page.goto(url)
# We'll just use the default text already in the textarea:
# "In this project I want to use the attention vectors of a llm to bold the most important words in an input text to improve reading comprehension."
print("Clicking the 'Analyze Text' button...")
page.click("#analyze-btn")
print("Waiting for the analysis to finish (this might take a few seconds)...")
# Wait for the loading text to disappear and spans to appear
page.wait_for_selector(".token", timeout=60000)
# Get all tokens and their classes
tokens = page.query_selector_all(".token")
print("\n--- Results ---")
highlighted_words = []
full_text = []
for token in tokens:
text = token.inner_text()
classes = token.get_attribute("class")
# Format output
if "highlighted" in classes:
full_text.append(f"**{text}**")
highlighted_words.append(text)
else:
full_text.append(text)
print("Full output with bolded words (marked by **):")
# Simple join (there might be spaces in the tokens themselves based on Gemma's tokenizer)
print("".join(full_text))
print("\nWords that crossed the attention threshold:")
print(highlighted_words)
print("\nSaving screenshot to result.png...")
page.screenshot(path="result.png", full_page=True)
browser.close()
print("Done!")
if __name__ == "__main__":
test_app() |