import gradio as gr
import csv
from datetime import datetime
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import os
from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader
import huggingface_hub
from huggingface_hub import Repository

DATASET_REPO_URL = os.environ.get("repo")
DATA_FILENAME = "data.csv"
DATA_FILE = os.path.join("data", DATA_FILENAME)

HF_TOKEN = os.environ.get("hf")
print("is none?", HF_TOKEN is None)

print("hfh", huggingface_hub.__version__)

repo = Repository(
    local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN, repo_type="dataset"
)

print('done cloning repo')

access = os.environ.get("access")
os.environ["OPENAI_API_KEY"] = os.environ.get("openai-1")

os.makedirs("/home/user/app/data1", exist_ok=True)
os.makedirs("/home/user/app/data2", exist_ok=True)

base_url_1 = os.environ.get("base_url_1")
visited_urls = []
counter = 0
limit = 10000

def scrape_page(url):
    global counter
    counter += 1
    try:

        response = requests.get(url)
        soup = BeautifulSoup(response.content, "html.parser")

        paragraphs = soup.find_all("p")
        print('------------------------------------------------------------------------------------------------------')
        print('counter: ', counter)
        print('reference url: ', url)
        print('text: ')
        for paragraph in paragraphs:
            print(paragraph.text)
        print('------------------------------------------------------------------------------------------------------')
        result = "reference url: " + url + "\n"
        content = "\n".join([paragraph.text for paragraph in paragraphs])
        result += content
        with open("/home/user/app/data2/base_url_1_"+str(counter)+".txt", "w") as file:
          file.write(result)

        visited_urls.append(url) 

        links = soup.find_all("a", href=True)
        for link in links:
            absolute_url = urljoin(url, link["href"])
            if absolute_url not in visited_urls and absolute_url.startswith(base_url_1) and 'tel' not in absolute_url and counter <= limit:
                content += "\n" + scrape_page(absolute_url)

        return ""
    except requests.exceptions.InvalidSchema:
        print(f"Ignoring invalid URL: {url}")
        return ""

result = scrape_page(base_url_1)

base_url_2 = os.environ.get("base_url_2")
date_urls = [base_url_2+str(year)+"/" for year in range(2023,2010,-1)]
visited_urls = []
counter = 0
limit = 10000

def scrape_page(url):
    global counter
    counter += 1
    try:

        response = requests.get(url)

        soup = BeautifulSoup(response.content, "html.parser")

        paragraphs = soup.find_all("p")
        print('------------------------------------------------------------------------------------------------------')
        print('counter: ', counter)
        print('reference url: ', url)
        print('text: ')
        for paragraph in paragraphs:
            print(paragraph.text)
        print('------------------------------------------------------------------------------------------------------')
        result = "reference url: " + url + "\n"
        content = "\n".join([paragraph.text for paragraph in paragraphs])
        result += content
        with open("/home/user/app/data2/base_url_2_"+str(counter)+".txt", "w") as file:
          file.write(result)

        visited_urls.append(url) 

        links = soup.find_all("a", href=True)
        for link in links:
            absolute_url = urljoin(url, link["href"])
            starts_with = False
            for date_url in date_urls:
              if absolute_url.startswith(date_url): starts_with = True
            if absolute_url not in visited_urls and starts_with and 'tel' not in absolute_url and counter <= limit:
                content += "\n" + scrape_page(absolute_url)

        return ""
    except requests.exceptions.InvalidSchema:
        print(f"Ignoring invalid URL: {url}")
        return ""

result = scrape_page(base_url_2)

documents = SimpleDirectoryReader("/home/user/app/data2/").load_data()
index = GPTVectorStoreIndex.from_documents(documents)

query_engine = index.as_query_engine()

def generate_text(input_text):

    output_text = 'Access is limited to specific users'
    
    words = input_text.split(" ")
    
    if words[0] == access:
        input_text = " ".join(words[1:])
        output_text = query_engine.query(input_text).response
        
    with open(DATA_FILE, mode='a', newline='') as file:
      writer = csv.writer(file)
      writer.writerow([input_text, output_text, datetime.now().strftime("%Y-%m-%d %H:%M:%S")])
        
    commit_url = repo.push_to_hub()
    
    return output_text

interface = gr.Interface(
    fn=generate_text,
    inputs=gr.inputs.Textbox(lines=10, label="Input Text"),
    outputs="text",
    title="OpenAI Test 1",
    description="By: Navid Moghaddam      -------------       Notice: This app may produce inaccurate information. All interactions are logged.",
    theme="default",
    allow_flagging = 'auto'
)

interface.launch(debug = True)