import gradio as gr
import requests
from bs4 import BeautifulSoup
from gradio_client import Client
from urllib.parse import urljoin
import pandas as pd
from io import StringIO
import json
import groq
import os

google_api_key = os.getenv('google_search')
API_URL = "https://blavken-flowiseblav.hf.space/api/v1/prediction/fbc118dc-ec00-4b59-acff-600648958be3"
api_key = os.getenv('groq')
client = groq.Client(api_key=api_key)

custom_css = """
#md {
    height: 200px;  
    font-size: 30px;
    background: #121212;
    padding: 20px;
    color: white;
    border: 1 px solid white;
    font-size:10px;
}
"""

def query(payload):
    response = requests.post(API_URL, json=payload)
    return response.json()

def google_search(payloads):
    output = query({
        "question": f"{payloads}",
    })
    print(output)
    #return result_text
      
    # Formuliere die Antwort
    #search_query = f"{payloads} antworte kurz und knapp. antworte auf deutsch. du findest die antwort hier:\n {output}"
    #result = predict(search_query)
    texte=""
    for o in output:
        texte +=o
    return output

def llm(message):
    message = f"return a json object with the keys: name,email,phone,website \n the values can be found here, leave blank if value is not available:\n {message} \n return a json object only. no text, no explanaition"
    try:        
        completion = client.chat.completions.create(
            model="llama3-70b-8192",
            messages=[
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user", "content": f"{message}"}
            ],
        )       
        return completion.choices[0].message.content
    except Exception as e:
        return f"Error in response generation: {str(e)}"

def qwen(jsondata):
    client = Client("Qwen/Qwen2.5-72B-Instruct")
    result = client.predict(
		query= f"return valid json \n {jsondata}",
		history=[],
		system="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.",
		api_name="/model_chat"
    )
    return result

def list_of_clubs(ort):
    base_url = "https://vereine-in-deutschland.net"
    all_links_text = []
    initial_url = f"{base_url}/vereine/Bayern/{ort}"

    try:
        response = requests.get(initial_url)
        response.raise_for_status()
        soup = BeautifulSoup(response.content, 'html.parser')
        
        # Determine the last page
        link_element = soup.select_one('li.page-item:nth-child(8) > a:nth-child(1)')
        last_page = 10
        if link_element and 'href' in link_element.attrs:
            href = link_element['href']
            last_page = int(href.split('/')[-1])

        # Loop through all pages and collect links
        for page_number in range(1, last_page + 1):
            page_url = f"{base_url}/vereine/Bayern/{ort}/p/{page_number}"
            response = requests.get(page_url)
            response.raise_for_status()
            soup = BeautifulSoup(response.content, 'html.parser')
            target_div = soup.select_one('div.row-cols-1:nth-child(4)')

            if target_div:
                texts = [a.text for a in target_div.find_all('a', href=True)]
                all_links_text.extend(texts)
            else:
                print(f"Target div not found on page {page_number}")

    except Exception as e:
        return str(e), []

    all_links_text = all_links_text[0::2]
    return all_links_text

def process_ort(ort):
    links_text = list_of_clubs(ort)
    #return links_text
    vereine = []
    
    for verein in links_text:
        prompt=f"impressum {verein}",
        result = google_search(prompt)
        json_data = llm(result)
        vereine.append(json_data)
        
    return vereine
        
    for verein in links_text:
        client = Client("mgokg/gemini-2.0-flash-exp")
        result = client.predict(
    		prompt=f"impressum {verein}",
    		api_name="/perform_search"
        )
        #json_object = llm(result)
        """
        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=impressum {verein}"
        response = requests.get(url, headers=headers)
        soup = BeautifulSoup(response.content, 'html.parser')
        impressum_div = soup.find('body')
        contact_detailes = impressum_div.text
        json_object = llm(contact_detailes)
        """
        #vereine.append(contact_detailes)
        vereine.append(result)
        #vereine.append(json_object)
    #dicts = [json.loads(item) for item in vereine] 
    #df = pd.DataFrame(dicts)
    #return df
    return vereine

# Create the Gradio interface
with gr.Blocks(css=custom_css) as demo:
    with gr.Row():
        #details_output = gr.DataFrame(label="Ausgabe", elem_id="md")        
        details_output = gr.Textbox(label="Ausgabe")  
    with gr.Row():
        ort_input = gr.Textbox(label="Ort eingeben", placeholder="ask anything...")      
    with gr.Row():         
        button = gr.Button("Senden")    

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

# Launch the Gradio application
demo.launch()