import gradio as gr
from selenium import webdriver
from selenium.common.exceptions import WebDriverException
from selenium.webdriver.common.by import By
from gradio_client import Client
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.chrome.options import Options

def selenium(message):
    options = webdriver.ChromeOptions()
    options.add_argument('--headless')
    wd = webdriver.Chrome(options=options)
    text_input = WebDriverWait(driver, 15).until(
        EC.presence_of_element_located((By.XPATH, '/html/body/main/div/div/div[2]/div[1]/div/div[3]/div/div/div[2]/div[2]/div/div/span/div/div/div/div[1]/textarea'))
    )
    text_input.send_keys(prompt)
    button_send = driver.find_element(By.XPATH, '/html/body/main/div/div/div[2]/div[1]/div/div[3]/div/div/div[2]/div[2]/div/div/span/div/div/div/div[3]/button').click()
    time.sleep(5)

    txtelements = driver.find_elements(By.XPATH, '/html/body/main/div/div/div[2]/div[1]/div/div[3]/div/div[1]/div/div[2]/div/div[1]/div[2]/div[2]/div[2]')
    #text_el =  txtelements.text
    time.sleep(5)
    txtcode = ""
    #with open("datei.txt", "w") as f:
        #f.write(code)
    #response_code = {"result": code}
    #json.dump(response_code, open('code.json', 'w'), indent=4, sort_keys=True)
    for e in txtelements:
        txtcode += e.text
    #response_txt = {"result": txtcode}
    #print(code)
    print(txtcode)
    
    #json.dump(response_txt, open('text.json', 'w'), indent=4, sort_keys=True)
    #json.dump(response_code, open('code.json', 'w'), indent=4, sort_keys=True)
    return txtcode
    wd.quit()
    #erg ="\n".join(results)
    #return erg
    #erg=results[0]
    #return "\n".join(results)
    client = Client("Qwen/Qwen2.5-72B-Instruct")
  
    result = client.predict(
        query=f"erstelle ein json objekt für die vereine: \n{''.join(results)}",
        #query="wie hoch ist der kölner dom",
        history=[],
        system="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.",
    api_name="/model_chat"
    )
    result = result[1]
    result = result[0][1]
    result=gr.Markdown(result)
    return result

iface = gr.Interface(
    fn=take_screenshots,
    inputs=[
        gr.Textbox(label="Ort", value=""),
    ],
    outputs=gr.Textbox(),
    title="perplexity.ai",
    description="get answer from perplexity"
)

iface.launch()