import gradio as gr
import requests
import os
import json
import google.generativeai as genai
from bs4 import BeautifulSoup

# Load environment variables
genai.configure(api_key=os.environ["geminiapikey"])
read_key = os.environ.get('HF_TOKEN', None)

custom_css = """
#md {
    height: 400px;  
    font-size: 30px;
    background: #202020;
    padding: 20px;
    color: white;
    border: 1 px solid white;
}
"""

def predict(prompt):
    generation_config = {
      "temperature": 0.4,
      "top_p": 0.95,
      "top_k": 40,
      "max_output_tokens": 8192,
      "response_mime_type": "text/plain",
    }

    model = genai.GenerativeModel(
      model_name="gemini-2.0-flash-exp",
      generation_config=generation_config,
    )

    chat_session = model.start_chat(
      history=[]
    )
      
    response = chat_session.send_message(f"{prompt}\n antworte immer auf deutsch")
    #response_data = json.loads(response)
    # Extrahiere den Textwert
    response_value = response.candidates[0].content.parts[0].text
    # Entferne die Markdown-Formatierung (optional)
    #text_value = response_value.strip('```json\n').strip('```')
    #response_value = gr.Markdown(response_value)
    return response_value
    return response
    
def websearch(search_term):
    
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
    }
    url = f"https://www.google.com/search?q={search_term}"
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.content, 'html.parser')
    response_text = soup.find('body')
    #result = predict(response_text.text)
    #first_div = soup.find('div', class_='MjjYud')
    return response_text.text

# Create the Gradio interface
with gr.Blocks(css=custom_css) as demo:
    with gr.Row():
        details_output = gr.Markdown(label="answer", elem_id="md")        
        #details_output = gr.Textbox(label="Ausgabe", value = f"\n\n\n\n")  
    with gr.Row():
        ort_input = gr.Textbox(label="prompt", placeholder="ask anything...")      
    with gr.Row():         
        button = gr.Button("Senden")    

    # Connect the button to the function
    button.click(fn=websearch, inputs=ort_input, outputs=details_output)   

# Launch the Gradio application
demo.launch()